The development of massively parallel sequencing (MPS) technology has enabled the discovery of several new types of forensic markers where microhaplotypes are one of these promising novel genetic markers. Microhaplotypes are, commonly, less than 300 nucleotides in length and consist of two or more closely linked single-nucleotide polymorphisms (SNPs). In this study, we have examined a custom-made QIAseq Microhaplotype panel (Qiagen), including 45 different microhaplotype loci. DNA libraries were prepared according to the GeneRead DNAseq Targeted Panels V2 library preparation workflow (Qiagen) and sequenced on a MiSeq FGx instrument (Verogen). We evaluated the performance of the panel based on 75 samples of Swedish origin and haplotype frequencies were established. We performed sensitivity studies and could detect haplotypes at input amounts down to 0.8 ng. We also studied mixture samples with two contributors for which haplotypes, for the minor contributor, were detectable down to the level of 1:100. Furthermore, we executed kinship simulations to evaluate the usefulness of this panel in kinship analysis. The results showed that both paternity and full sibling cases can clearly be solved. When simulating a half sibling versus unrelated case scenario, there were, however, some overlap of the likelihood ratio distributions potentially resulting in inconclusiveness. To conclude, the results of this initial study are promising for further implementation of this microhaplotype assay into the forensic field, although we noticed some primer design issues that could be optimized, which possibly would increase the power of the assay.

One of the major challenges in forensic genetics is being able to detect very small amounts of DNA. Massively parallel sequencing (MPS) enables sensitive detection; however, genotype errors may exist and could interfere with the interpretation. Common errors in MPS-based analysis are often induced during PCR or sequencing. Unique molecular indices (UMIs) are short random nucleotide sequences ligated to each template molecule prior to amplification. Applying UMIs can improve the limit of detection by enabling accurate counting of initial template molecules and removal of erroneous data. In this study, we applied the FORCE panel, which includes similar to 5500 SNPs, with a QIAseq Targeted DNA Custom Panel (Qiagen), including UMIs. Our main objective was to investigate whether UMIs can enhance the sensitivity and accuracy of forensic genotyping and to evaluate the overall assay performance. We analyzed the data both with and without the UMI information, and the results showed that both genotype accuracy and sensitivity were improved when applying UMIs. The results showed very high genotype accuracies (>99%) for both reference DNA and challenging samples, down to 125 pg. To conclude, we show successful assay performance for several forensic applications and improvements in forensic genotyping when applying UMIs.

A recently presented chemical vapor deposition (CVD) method involves using plasma electrons as reducing agents for deposition of metals. The plasma electrons are attracted to the substrate surface by a positive substrate bias. Here, we present how a standard quartz crystal microbalance (QCM) system can be modified to allow applying a DC bias to the QCM sensor to attract plasma electrons to it and thereby also enable in situ growth monitoring during the electron-assisted CVD method. We show initial results from mass gain evolution over time during deposition of iron films using the biased QCM and how the biased QCM can be used for process development and provide insight into the surface chemistry by time-resolving the CVD method. Post-deposition analyses of the QCM crystals by cross-section electron microscopy and high-resolution x-ray photoelectron spectroscopy show that the QCM crystals are coated by an iron-containing film and thus function as substrates in the CVD process. A comparison of the areal mass density given by the QCM crystal and the areal mass density from elastic recoil detection analysis and Rutherford backscattering spectrometry was done to verify the function of the QCM setup. Time-resolved CVD experiments show that this biased QCM method holds great promise as one of the tools for understanding the surface chemistry of the newly developed CVD method.

Recently, a novel approach of depositing metallic films with chemical vapor deposition (CVD), using plasma electrons as reducing agents, has been presented and is herein referred to as e-CVD. By applying a positive substrate bias to the substrate holder, plasma electrons are drawn to the surface of the substrate, where the film growth occurs. In this work, we have characterized the electron flux at the substrate position in terms of energy and number density as well as the plasma potential and floating potential when maintaining an unbiased and a positively biased substrate. The measurements were performed using a modified radio frequency Sobolewski probe to overcome issues due to the coating of conventional electrostatic probes. The plasma was generated using a DC hollow cathode plasma discharge at various discharge powers and operated with and without precursor gas. The results show that the electron density is typically around 10(16) m(-3) and increases with plasma power. With a precursor, an increase in the substrate bias shows a trend of increasing electron density. The electron temperature does not change much without precursor gas and is found in the range of 0.3-1.1 eV. Introducing a precursor gas to the vacuum chamber shows an increase in the electron temperature to a range of 1-5 eV and with a trend of decreasing electron temperature as a function of discharge power. From the values of the plasma potential and the substrate bias potential, we were able to calculate the potential difference between the plasma and the substrate, giving us insight into what charge carriers are expected at the substrate under different process conditions.

Ferrocene [Fe(C5H5)(2) or FeCp2] is a well-known precursor molecule for iron in vapor deposition of iron containing films by, e.g., chemical vapor deposition (CVD) processes. CVD processes often use the energy in plasma discharges to decompose precursor molecules, which allows lowering the substrate temperature for deposition on sensitive materials. Herein, we studied the plasma decomposition of ferrocene in a plasma CVD reactor using in situ optical emission spectroscopy and quadrupole mass spectrometry, coupled with in silico quantum chemical modeling. We suggest a plasma chemical decomposition model under medium vacuum conditions where FeCp2 is likely to undergo neutral decomposition, detaching both Cp ligands from the iron center, followed by fragmentation via C2H2- and C3H3 to C-2, CH, H-2, and H.

We studied deposition of copper films by a pulsed electron chemical vapor deposition process using free electrons from a plasma discharge as reducing agents, with copper beta-diketonates, Cu(hfac)(2), and Cu(acac)(2) as the copper source. The mass gain per deposition cycle, as monitored by a quartz crystal microbalance sensor, suggests that pulsing allows us to access a process window with a self-limiting deposition process. X-ray photoelectron spectroscopy shows that the films are not metallic copper and that they are contaminated by carbon, oxygen, and when Cu(hfac)(2) was used, also fluorine. We speculate that the surface chemistry involves electron stimulated desorption reactions. Optical emission spectroscopy suggests redeposition of precursor fragments from plasma volume decomposition of precursor molecules desorbing during the plasma step. This redeposition limits the control of the surface chemistry during the plasma step of the deposition cycle.a

This paper explores the digitalization of business-to-business (B2B) customer journeys, which is recognized as a top research priority, but one that has not yet received substantial academic attention. Due to their complexity, customer journeys are particularly relevant in B2B settings, and this is further emphasized through the increasing use of digital technologies. This paper identifies three key dimensions of B2B customer journeys that are influenced by digitalization. These are the digitalization of touchpoints (i.e., adding digital touchpoints and transforming or facilitating touchpoints), the change of roles in digitalized journeys (i.e., introducing new roles, activating customers, and emphasizing collectivity), and the digitalization of the overall process (i.e., extending, enhancing, and supporting the process). The research is based on an in-depth case study of a B2B firm and four customers. Insights from the research add to the customer journey literature through the exploration of digita-lized B2B customer journeys, providing guidance for academics and practitioners.

Business-to-business (B2B) suppliers need to develop specific capabilities to successfully manage digitalized touchpoints in B2B customer journeys. As digitalization leads to shifts in touchpoints, new demands arise regarding a supplier's ability to manage these touchpoints. Developing capabilities for managing digitalized touchpoints is becoming a key aspect for suppliers in designing and managing attractive B2B customer journeys. Although extant research has highlighted the importance of managing touchpoints in the form of capabilities, this area has received surprisingly little research attention. Similarly, the B2B context in customer journeys remains under-researched. The present study investigates supplier capabilities for the management of digitalized touchpoints in B2B customer journeys. Through an exploratory in-depth case study, this research identifies seven key supplier capabilities for the management of digitalized touchpoints in B2B customer journeys: preparing customer resources, integrating customer resources, enabling collective actions, supporting customer actions, balancing activation levels, hybridizing environments, and merging digital environments. These capabilities are structured around a theoretically derived conceptualization of touchpoints as consisting of resources, actions, and environments. From a capability perspective, this study also demonstrates the key role of touchpoint control, as well as approaching touchpoints as sequences to ensure consistency across, and seamlessness between transitions of, touchpoints.

Digital offerings have grown to be a significant segment in business-to-business markets. Suppliers of digital offerings are faced with unique circumstances in managing customers, requiring specific strategies to increase customer engagement. We argue that suppliers may adopt different strategies to increase engagement depending on how the engagement is influenced (i.e., directly or indirectly) and their focus on the engagement process (i.e., dispositions or activities). This study explores customer engagement strategies for digital offerings. Specifically, based on a field study of suppliers providing digital offerings, we introduce four customer engagement strategies: initiating early awareness, role-centric activation, collective alignment, and scaling supplier-initiated activities. By exploring digital offerings as a new type of engagement object, we add to existing customer engagement literature. For practitioners, we also offer guidance for how the identified strategies can be combined to increase customer engagement based on firm-related and contextual factors impacting the choice of strategy.

Background The four cannulation techniques, rope ladder (RL), area puncture (AP), buttonhole with blunt needles (BHb), and buttonhole with sharp needles (BHs), affects the arteriovenous fistula (AVF) in different ways. The aim of this study was to describe the relationship between the different cannulation techniques and the occurrence of AVF complications. Methods The study was performed as a national registry-based cohort study using data from the Swedish Renal Registry (SRR). Data were collected from January 2014 to October 2019. Seventy of Swedens dialysis units participate in the registry. We analyzed a total of 1328 AVFs in this study. The risk of complications was compared between the four different cannulation techniques. The risk of AVF complications was measured by the incidence and incidence rate ratio (IRR). We compared the IRRs of complications between different cannulation techniques. Results BHs is the most common cannulation technique in Sweden. It has been used in 55% of the AVFs at some point during their functional patency. BHb (29%), RL (13%), and AP (3%) has been used less. BHb had the lowest risk of complications compared to the other techniques, and a significantly lower risk of stenosis, infiltration, cannulation difficulties, compared to RL and BHs. Cannulation difficulties were significantly more common using AP compared to BHs, and BHb. Infections were not significantly increased using the buttonhole technique. Conclusions BHb had the lowest risk of complications. Infections were not significantly increased using the buttonhole technique. Dialysis units with a low infection rate may continue to use the buttonhole technique, as the risk of complications is lower.

Aims and objectives The aim of this study was to describe the basis for choosing a cannulation technique for arteriovenous fistula. Background Four cannulation techniques are relevant to cannulating an arteriovenous fistula: rope ladder, area puncture and buttonhole using blunt or sharp needles. The chosen technique may affect both the patency and number of complications. Design The study used a convergent mixed methods design and inductive approach. Methods A questionnaire and an inquiry of local guidelines were sent to nurses in all dialysis units in Sweden. Questionnaires were answered by nurses from 37 units, and 29 units included their local guidelines. The questionnaires were analysed using descriptive statistics and qualitative content analysis, and the guidelines were analysed using qualitative content analysis. The different analyses were combined in a final result. The study is based on GRAMMS guidelines. Results Local guidelines, patients and nurses own judgement, and consultation with colleagues were found to greatly influence the choice of cannulation technique. Buttonhole was the most preferred cannulation technique in the participating units and was favoured by nurses when choosing a cannulation technique. The process of choosing a cannulation technique was found to be influenced by the dedication to good cannulation technique and healthy arteriovenous fistulas, whether the technique is perceived as being easy to use and is expected to prevent complications and based on the experienced-based knowledge of each dialysis unit. Conclusions Choosing a cannulation technique is a process based on the nurse, local guidelines and the patient. Most dialysis nurses and units in Sweden consider buttonhole to be a good cannulation technique and use it as their standard technique. Relevance to clinical practice The results provide insight into why cannulation techniques are chosen differently in different units. The results also show the importance of evidence in making decisions on cannulation technique.

Background: Nurses have a great responsibility in the daily care of arteriovenous fistulae, which entails the potential to affect patency. However, good cannulation technique involves more than placing a needle in the vessel and relies on different skills to facilitate needling. Objectives: To describe the preconditions for cannulation in arteriovenous fistulas. Design: Descriptive statistics and qualitative content analysis were used in a mixed-methods design. Participants: Haemodialysis units in Sweden. Measurements: Local guidelines regarding arteriovenous fistula cannulation were analysed in parallel with responses to a questionnaire that contained open-ended and closed-ended questions on cannulation technique. Results: Preconditions that facilitate cannulation fall into five stages, each with relevant factors in relation to the cannulation, as follows: planning cannulation-maturation and planning the cannulation, patient record, education and experience, and patient information; precannulation-physical examination, hygiene routines, arm position, tourniquet, choosing the cannulation site, and preventing pain; during cannulation-how to needle, type of needle, angle during cannulation, fixation, and adjusting; evaluating cannulation-blood flow rate and arterial and venous pressure; and postcannulation-needle withdrawal and haemostasis. The majority of dialysis units identified implementation of most of these preconditions, but the units handle several practical aspects differently. Conclusions: Tracing the chain of cannulation led to identification of necessary preconditions for facilitating good cannulation technique. The findings also show the need for a better understanding of how different preconditions affect arteriovenous fistula and patency.

BackgroundA patient's normal skin flora is most often the origin of arteriovenous fistula (AVF) infections. When the buttonhole cannulation technique is used, the risk of these types of infections increases. The most effective disinfectant should be used to prevent AVF infections, but evidence on which to choose is lacking. The present study assessed whether chlorhexidine is more effective than ethanol in patients treated with haemodialysis via AVF.MethodsIn this randomized, cross-over, clinical trial, we compared 5 mg/mL chlorhexidine in 70% ethanol to 70% ethanol alone with and without arm washing using serial sampling of normal skin flora directly before disinfection, immediately after the disinfectant effect time, and 2 and 4 h after disinfection during four different dialysis treatments. Scabs from the buttonhole tracks were collected and the type of bacteria in the scabs compared to the patient's normal skin flora. All participants were sampled during all four interventions. The CFU/mL and types of bacteria were compared between intervention groups.ResultsCompared to ethanol, chlorhexidine resulted in fewer positive haematin plates directly after disinfection (1.4% vs. 10.8% p = 0.032). After 2 and 4 h, ethanol in combination with arm washing showed an increased regrowth of bacteria compared to chlorhexidine without arm washing (60 vs. 170 CFU/mL, p = 0.046 and 160 vs. 338 CFU/mL, p = 0.022). Scabs from the buttonhole track contained normal skin flora (Cohen's kappa = 0.97).ConclusionDisinfection with chlorhexidine is more effective than ethanol when the buttonhole cannulation technique is used for AVF.Trial registrationThe study was registered June 12, 2023 in Clinical Trials Information System (CTIS) identification number: 2023-505935-11-00.

Introduction

Differentiation between self-produced tactile stimuli and touch by others is necessary for social interactions and for a coherent concept of “self”. In attention-deficit-hyperactivity-disorder (ADHD), tactile hypersensitivity and social cognition problems are part of the symptomatology, but pathophysiological mechanisms are largely unknown. Differentiation of self- and non-self- generated sensations might be key to understand and develop novel strategies for managing hypersensitivity. Here, we compared the neural signatures of affective self- and other-touch between adults with ADHD and neurotypical controls (NC).

Methods

Twenty-eight adult ADHD participants and 30 age- and gender-matched NC performed a self-other-touch-task during functional magnetic resonance imaging: they stroked their own arm, an object, or were stroked by the experimenter. In addition, tactile detection thresholds and rubber hand illusion (RHI) were measured.

Results

ADHD participants had more autistic traits than NC and reported to engage less in interpersonal touch. They also reported to be more sensitive to tactile stimuli. Compared to NC, ADHD participants showed enhanced responses to both the self- and other-touch conditions: stronger deactivation during self-touch in the anterior and posterior insula, and increased activation during other-touch in primary somatosensory cortex. ADHD participants had intact tactile detection thresholds, but were less susceptible to the RHI.

Conclusions

Unaltered detection thresholds suggest that peripheral processing is intact, and that hypersensitivity might be driven by central mechanisms. This has clinical implications for managing somatosensory hypersensitivity in ADHD. The more pronounced differentiation between self- and other-touch might indicate a clearer self-other-distinction. This is of interest regarding body ownership perception in both NC and ADHD, and possibly other psychiatric conditions with altered self-experiences, like schizophrenia. A sharper boundary of the own body might relate to deficits in social cognition and tactile hypersensitivity.

BackgroundTactile sensitivity and sensory overload in ADHD are well-documented in clinical-, self-, and parent- reports, but empirical evidence is scarce and ambiguous and focuses primarily on children. Here, we compare both empirical and self-report tactile sensitivity and ADHD symptomatology in adults with ADHD and neurotypical controls. We evaluate whether tactile sensitivity and integration is more prevalent in ADHD and whether it is related to ADHD symptom severity.MethodsSomatosensory evoked potential (SEP) amplitudes were measured in 27 adults with ADHD and 24 controls during four conditions (rest, stroking of the own arm, stroking of the arm by a researcher, and stroking of an object). Participants also filled out questionnaires on tactile sensitivity and ADHD symptoms and performed a Qb-test as an objective measure of ADHD symptom severity.ResultsParticipants with ADHD self-reported greater tactile sensitivity and ADHD symptom severity than controls and received higher scores on the Qb-test. These values correlated with one another. ADHD participants showed lower tolerable threshold for electrical radial nerve stimulus, and greater reduction in cortical SEP amplitudes during additional tactile stimuli which was correlated with ADHD symptoms.ConclusionsWe find that ADHD symptomatology and touch sensitivity are directly linked, using both self-reports and experimental measures. We also find evidence of tactile sensory overload in ADHD, and an indication that this is linked to inattention specifically. Tactile sensitivity and sensory overload impact the functioning and life quality of many people with ADHD, and clinicians should consider this when treating their patients.

Introduction: The tactile sense plays a crucial role in the development and maintenance of a functional bodily self. The ability to differentiate between self-and nonself-generated touch contributes to the perception of the bodies boundaries and more generally to self-other-distinction, both of which are thought be altered in anorexia nervosa (AN) and autism spectrum condition (AS). While it has been suggested that AN and AS are characterized by overlapping symptomatology, they might differ regarding body perception and self-other-distinction. Methods: Participants with a diagnosis of AN (n = 25), AS (n = 29), and a comparison group without diagnoses (n = 57) performed a self-other-touch task during functional brain imaging. In the experimental conditions, they stroked their own arm or were stroked on the arm by an experimenter. Results: As shown previously, the CG group showed lower activation or deactivation in response to self-touch compared to social touch from someone else. A main group effect was found in areas including somatosensory cortex, frontal and temporal gyri, insula, and subcortical regions. This was driven by increased activations in participants with AN, while participants in the AS group showed mostly comparable activations to the com-parison group. Conclusions: AN diagnosis was associated with an increased neural activity in response to both self-touch and social touch. Failure to attenuate self-touch might relate to altered predictions regarding the own body and reduced perception of bodily boundaries. Participants with an AS diagnosis were mostly comparable to the comparison group, potentially indicating unaltered tactile self-other-distinction.

Background and aim Children growing up in vulnerable circumstances have a higher risk of caries experience. Tracking the development of caries in relation to socioeconomic variables over time is essential for fair resource distribution to groups with higher caries risk and to even out inequalities in oral health. The aim was therefore to analyse the association between 6-year-olds<acute accent> caries prevalence and socioeconomic variables at family and residential area levels in 2010 and 2019 as well as potential differences in the association between 2010 and 2019. Methods The study design is an epidemiological registry-based, repeated cross-sectional study based on caries data (grouped as 0, 1-3 and > 3 dmft) for the population of 6-year-olds in 2010 (n = 4,408, 95% coverage) and 2019 (n = 5,199, 94% coverage) in a Swedish region. Multiple socioeconomic variables for the children's families and residential areas were retrieved from official registries. Multinomial logistic regression was performed at both levels to produce models for each level and studied year. Results The variables that explained most of the association between caries and socioeconomic variables were mainly the same over the years at both levels. At the family level, these were: maternal age when having their first child (explained most of the association in both years, at 30 and 35%, respectively); maternal age when having the child in the study group; parental employment; parental and child's migration background; maternal educational level; form of housing; and financial assistance (only 2010). At the residential area level, these were: migration background (explained most of the association both years; 82 and 52%, respectively), educational level and number of persons per household. The association between socioeconomic variables and caries was consistently stronger for severe caries (dmft > 3) than moderate (dmft 1-3). Multiple socioeconomic risk variables meant an even greater likelihood of caries. Conclusion Over the studied years, variables related to socioeconomic vulnerability continued to be associated with caries in young children growing up under socially disadvantaged circumstances. Effective efforts for families living in socially vulnerable contexts are needed to achieve good and equal oral health, as is continued follow-up to evaluate whether the goal is reached.

Background: Early childhood caries (ECC) has been found to be up to five times more common among children living in areas of low socio-economic status (SES) than among children in areas of higher SES. Aim: To evaluate an ECC prevention programme from pregnancy to 3 and 6 years of age. Design: A prospective, controlled, intervention cohort study was initiated in 2013 in a low-SES area in Sweden. The intervention group received an individual interdisciplinary ECC prevention programme starting pre-birth, consisting of supportive oral health-promoting talks using motivational interviewing techniques and individual ECC preventive actions. A control group, consisting of pregnant women living in a comparable area, received ordinary routines. Results: Of the 336 pregnant women, 64 mothers (with 64 children) completed the programme, and 394 children were born in the control group. At the sixth year examination, the proportion of children with no caries was similar between the groups (53% resp. 52%, p = .976), whereas the proportion with decayed, missed, filled primary teeth (dmft = 1-5) was slightly lower (23% resp. 36%, p = .063), and the proportion with severe caries disease (dmft > 5) was higher (p = .013) in the intervention group (25%) than in the control group (12%). Conclusion: No preventive effect regarding caries can be demonstrated at sixth year of age. Maternal behavioural change in dental care was not sufficient to even out inequalities in oral health in children, eventually due to difficulties in reaching the target group and the lack of effects among the families reached.

Background To achieve good and equal oral health in children, interdisciplinary preventive oral health actions, directed toward disadvantaged areas, can be an important means. Staff play a crucial role in the implementation of these actions. The aim of the present study was to analyze circumstances of importance for conducting an interdisciplinary public preventive oral health project for children, directed toward parents in areas with low socioeconomic status from the interdisciplinary perspective of the involved staff. Method The present study consisted of a qualitative content analysis with an inductive approach, based on interviews with interdisciplinary staff who had participated in a public preventive oral health project directed toward parents in areas with low socioeconomic status. The interviews were analyzed using text-driven analysis. Results The main category concerned the staff members prerequisites and understanding necessary to perform their tasks in interdisciplinary public preventive oral health project. To have the right prerequisites and understanding regarding the oral health project enabled staff to be committed, able and willing to perform in it. Important aspects of this are to have knowledge, motivation and to experience a supportive professional context, to have good leadership and for certain resources to fulfilled. A crucial aspect was to reach the targeted mothers. Conclusions For interdisciplinary cooperation in preventive oral health care to be achieved, it is essential for the involved disciplines and professions to embrace a common view on the projects aim, their duties, and oral health, from the leadership to the individual level. Staff require competent leadership but also allocated time and adapted method support to be successful in this context. When allocating preventive health actions directed at low SES areas, it is important to acknowledge the risk of stigmatization and for staff to understand that families might be facing social challenges that prevent them from taking part in health-promoting actions. An important conclusion is that to be able to reach people, it is important for both those who design preventive programs for oral health and the staff who administer them to have sufficient knowledge about the target group.

Existing datasets for autonomous driving (AD) often lack diversity and long-range capabilities, focusing instead on 360° perception and temporal reasoning. To address this gap, we introduce Zenseact Open Dataset (ZOD), a large- scale and diverse multimodal dataset collected over two years in various European countries, covering an area 9×that of existing datasets. ZOD boasts the highest range and resolution sensors among comparable datasets, coupled with detailed keyframe annotations for 2D and 3D objects (up to 245m), road instance/semantic segmentation, traffic sign recognition, and road classification. We believe that this unique combination will facilitate breakthroughs in long-range perception and multi-task learning. The dataset is composed of Frames, Sequences, and Drives, designed to encompass both data diversity and support for spatio-temporal learning, sensor fusion, localization, and mapping. Frames consist of 100k curated camera images with two seconds of other supporting sensor data, while the 1473 Sequences and 29 Drives include the entire sensor suite for 20 seconds and a few minutes, respectively. ZOD is the only large-scale AD dataset released under a permissive license, allowing for both research and commercial use. More information, and an extensive devkit, can be found at zod.zenseact.com.

Images fed to a deep neural network have in general undergone several handcrafted image signal processing (ISP) operations, all of which have been optimized to produce visually pleasing images. In this work, we investigate the hypothesis that the intermediate representation of visually pleasing images is sub-optimal for downstream computer vision tasks compared to the RAW image representation. We suggest that the operations of the ISP instead should be optimized towards the end task, by learning the parameters of the operations jointly during training. We extend previous works on this topic and propose a new learnable operation that enables an object detector to achieve superior performance when compared to both previous works and traditional RGB images. In experiments on the open PASCALRAW dataset, we empirically confirm our hypothesis.

Self-supervised pre-training based on next-token prediction has enabled large language models to capture the underlying structure of text, and has led to unprecedented performance on a large array of tasks when applied at scale. Similarly, autonomous driving generates vast amounts of spatiotemporal data, alluding to the possibility of harnessing scale to learn the underlying geometric and semantic structure of the environment and its evolution over time. In this direction, we propose a geometric and semantic self-supervised pre-training method, GASP, that learns a unified representation by predicting, at any queried future point in spacetime, (1) general occupancy, capturing the evolving structure of the 3D scene; (2) ego occupancy, modeling the ego vehicle path through the environment; and (3) distilled high-level features from a vision foundation model. By modeling geometric and semantic 4D occupancy fields instead of raw sensor measurements, the model learns a structured, generalizable representation of the environment and its evolution through time. We validate GASP on multiple autonomous driving benchmarks, demonstrating significant improvements in semantic occupancy forecasting, online mapping, and ego trajectory prediction. Our results demonstrate that continuous 4D geometric and semantic occupancy prediction provides a scalable and effective pre-training paradigm for autonomous driving. For code and additional visualizations, see https://research.zenseact.com/publications/gasp/

We present a versatile NeRF-based simulator for testing autonomous driving (AD) software systems, designed with a focus on sensor-realistic closed-loop evaluation and the creation of safety-critical scenarios. The simulator learns from sequences of real-world driving sensor data and enables reconfigurations and renderings of new, unseen scenarios. In this work, we use our simulator to test the responses of AD models to safety-critical scenarios inspired by the European New Car Assessment Programme (Euro NCAP). Our evaluation reveals that, while state-of-the-art end-to-end planners excel in nominal driving scenarios in an open-loop setting, they exhibit critical flaws when navigating our safety-critical scenarios in a closed-loop setting. This highlights the need for advancements in the safety and real-world usability of end-to-end planners. By publicly releasing our simulator and scenarios as an easy-to-run evaluation suite, we invite the research community to explore, refine, and validate their AD models in controlled, yet highly configurable and challenging sensor-realistic environments.

Validating autonomous driving (AD) systems requires diverse and safety-critical testing, making photorealistic virtual environments essential. Traditional simulation platforms, while controllable, are resource-intensive to scale and often suffer from a domain gap with real-world data. In contrast, neural reconstruction methods like 3D Gaussian Splatting (3DGS) offer a scalable solution for creating photorealistic digital twins of real-world driving scenes. However, they struggle with dynamic object manipulation and reusability as their per-scene optimization-based methodology tends to result in incomplete object models with integrated illumination effects. This paper introduces R3D2, a lightweight, one-step diffusion model designed to overcome these limitations and enable realistic insertion of complete 3D assets into existing scenes by generating plausible rendering effects-such as shadows and consistent lighting-in real time. This is achieved by training R3D2 on a novel dataset: 3DGS object assets are generated from in-the-wild AD data using an image-conditioned 3D generative model, and then synthetically placed into neural rendering-based virtual environments, allowing R3D2 to learn realistic integration. Quantitative and qualitative evaluations demonstrate that R3D2 significantly enhances the realism of inserted assets, enabling use-cases like text-to-3D asset insertion and cross-scene/dataset object transfer, allowing for true scalability in AD validation. To promote further research in scalable and realistic AD simulation, we will release our dataset and code, see https://research.zenseact.com/publications/R3D2/

This article targets the advancement of a market orientation in Swedish social work, with a specific focus on motivational work and the construction of the motivated client. Informed by a governmentality approach, the article analyses the formation of the ideal client in a market-oriented social work setting in Sweden. The empirical focus is front-line social workers and their work. The analysis is directed at the ways in which front-line social workers conceptualise the ideal client and how such a formation is made possible. The analysis contributes to problematising motivational work as something inherently good and progressive in neoliberal times, in social work practice as well as research. The main conclusions concerning the fabrication of motivated clients as part of a broader neoliberal agenda and challenges for social work are further reflected upon.

In recent decades, market reforms have paved the way for new forms to govern social work practice by means of procurement, cost efficiency, measurement, and freedom of choice. In this article, we draw attention to how clients are constructed in terms of motivation, in a context where social work is shaped by a procurement arrangement. Empirically, the article is based on interviews with social workers providing social services in a procurement setting, with a focus on how they describe their work in relation to presumptive clients, and specifically their work upon the motivation of clients. The analysis is informed by a constructionist approach to governing and the construction of clients. The results illustrate how the ideal client is constructed as motivated to choose a provider of social services matching their specific needs and interests as well as displaying a will to change and take part in the services offered. The social work appearing as desirable is based on a therapeutic rationality, with dialogue as the primary means of working upon the motivation of clients. The results further illustrate how different technologies (of the self and power) operate and intertwine in the work upon motivation of clients.

Social service for sale. On social work in times of procurement Market reforms within the Swedish welfare sector have paved the way for models based on buying and selling welfare services. Public procurement constitutes a hub for commissioning and providing social services. The aim of this article is to explore how social work is shaped within a procurement context. Attention is directed to how social workers providing procured services describe their work. The empirical material consists of interviews with 16 providers of social services within different areas of a procured social work. The results show how procurement shapes the provision of social work, in terms of specifications of time and quantity, a quantification of the work performed with clients and how the framework of procurement shapes the client as a commission and a case. It is further shown how providers compensate for and deal with the framework of procured social work to meet the clients needs. The results raise questions about the possibilities for procured social work regarding the services demarcation, specialisation, and time frame.

In search of more efficient hydraulic systems, new system architectures are explored. These system architectures are often electrically driven and include energy recuperation. This requires hydraulic machines to function both as pumps, converting mechanical power into hydraulic power, and as motors, converting hydraulic power back into mechanical power. However, the availability of machines that can operate in all desired modes is limited. This indicates that operation in multiple modes comes with performance penalties. This paper highlights the challenges for multi-quadrant operation of hydraulic piston pump/motors, with a particular focus on commutation, i.e., the transition between high- and low-pressure level for each chamber. Various commutation strategies for piston machines are examined. Furthermore, other important aspects for pump/motor operation such as hydrostatic compensation ratios, design of inlet channels, low-speed capability, and flow control through speed or displacement control are discussed. The article shows that the design of multi-quadrant machines is challenging, and this has to be considered when choosing the system architecture.

Conventionally, variable axial piston machines vary displacement by adjusting the length of the piston stroke, which can be done by adjusting the angle of the swash plate in swash plate machines or the angle of the cylinder block in bent axis machines. Another possibility to achieve variable displacement is to rotate the valve plate and thus adjust the effective use of the piston stroke. An advantage of this method is that it only requires small forces and is easier to control in comparison to conventional displacement adjustment.

This idea is not new, and the concept was studied decades ago, but unfortunately, cavitation and high pressure peaks in the bridge between the kidneys hindered a successful implementation of valve plate rotation.

Using a double pump with opposing pistons offers the potential to overcome these obstacles, as the displacement can be adjusted by joint rotation of both valve plates, and the effective bridge angles can be adjusted by relative rotation of the valve plates. This paper presents a methodology to optimise valve plate kidney angles for a double pump with rotating valve plates. Optimisation results for exemplary sets of operating points are presented. At high setting ratios, power losses and flow pulsations can be reduced. The risk of cavitation and high pressure peaks can be eliminated, but at the expense of cross-porting and increased losses at low setting ratios and high speeds.

Noise is a critical parameter for electrified mobile machinery. Both electric and hydraulic machines generate periodic forces that excite the surrounding structures and generate noise. This paper discusses harmonic orders and their origin in hydraulic pumps and permanent magnet synchronous motors (PMSMs). By combining the pump and motor, the harmonics of both machines interact, and the noise experience changes. This must be taken into account when designing electrically driven pumps. The effect of the combination of the design parameters; number of pistons, number of slots, and number of poles on the system harmonics is discussed. Traditionally, hydraulic pumps use odd piston numbers to reduce noise. However, if identical numbers of poles and pistons are chosen, the pump and motor harmonics coincide and can interact constructively or destructively. This paper shows, using torque ripple as an example, that selecting odd piston numbers is not straightforward when combining pumps with a PMSM.

This paper explores the transition towards the electrification of hydraulic systems in material moving machines, highlighting both environmental benefits and the noise challenges posed by such technological change. With a focus on noise, the study examines the perceptual impact of replacing diesel engines with electric motors, which alters the noise profile of these machines. A survey assesses human responses to different hydraulic pump configurations in electrified setups, revealing significant variations in noise perception based on the specific design and the familiarity of the respondents with hydraulic sounds. The findings underscore the need for a nuanced approach to noise management in electric hydraulic systems, advocating for designs that consider both decibel levels and sound quality to enhance operator comfort and public acceptance.

COVID-19 primarily spreads through close contact between humans and has affected retailing industries extremely hard. To manage the situation retailers have turned to service innovation to change their operations to make consumers feel safe while shopping. This research focuses on the role of service innovativeness in retailing firms during the COVID-19 pandemic through an empirical study of almost 6000 consumers of 28 retailing firms. The results suggested that retailers with high service innovativeness performed COVID-19 imposed innovations better to improve their relative attractiveness. For retailers with physical stores, changes to the servicescape and the offering were found to be the key antecedents of service innovativeness. The findings on COVID-19 imposed service innovations demonstrate the importance of service innovativeness in successfully changing retailing services to adjust to the restrictions from governments and safety needs of customers.

The growing importance of service has brought greater opportunities for service innovations to influence the market and improve both customers’ and firms’ situations. Despite efforts by firms to develop service innovations, they often fail to introduce new services on the market. Ultimately, customers are the ones to assess, buy, and use a new service. That is why the Swedish Innovation Index was introduced as a customer-centric perspective on service innovation, which measures firms based on customers’ perceptions of their innovations. This allows firms to predict the future adoption of new services and the relative attractiveness of the firms. The Swedish Innovation Index provides a new perspective that is independent of the firm-centric view of innovation. It opens avenues for both managers and academics to observe, predict, and better utilize the potential of service innovations.

Aluminum nitride (AlN) is a semiconductor with a very wide band gap and a potential dielectric material. Deposition of thin AlN films is routinely done by several techniques, including atomic layer deposition (ALD). In this study, we deposited AlN using ALD with trimethylaluminum (TMA) as the Al precursor and ammonia (NH3) with and without plasma activation as the N precursor in the temperature range from 100 to 400 degrees C while monitoring the surface reactions using mass spectrometry. Our results, combined with recent quantum chemical modelling, suggest that the surface chemistry of the deposition process is chemisorption of TMA followed by reductive elimination of the methyl groups to render mono methyl aluminum species. The NH3 chemisorption is done by ligand exchange to form CH4 and an -NH2 terminated surface.

Dialkylamido compounds, such as tris-dimethylamido aluminum (TDMAA, Al(NMe2)3) and tetrakis-dimethylamido titanium (TDMAT, Ti(NMe2)4) are interesting precursors for depositing nitrides using atomic layer deposition (ALD) due to their high volatility and reactivity at low temperatures. In this study, we explored surface chemistry using mass spectrometry and discovered that the surface mechanisms involved beta-hydride elimination and ligand decomposition, as well as transamination and hydrogenation reactions which facilitate ligand exchange. This is mainly based on the -N(Me)2 and HN(Me)2 detected during both TDMAA and NH3 pulses, and CH4 signals detected during the NH3 pulse stage. The expected reductive elimination of the two dimethylamido ligands, via a direct nitrogen-nitrogen coupling reaction was not observed, suggesting that it is less thermodynamically favorable compared to reduction by NH3. Arrhenius analysis between 150 and 300 degrees C found activation energies (Ea) = 27-30 kJ mol-1 and pre-exponential factors (A) = 3-5 s-1 for the reaction between TDMAA and NH3.

Different approaches are used in tailoring properties of thin films to meet the requirements of specific applications. This study comprises work done on atomic layer deposition of Al (x) Ti1-x N employing the co-evaporation approach using tris-dimethylamido aluminum [Al(NMe2)(3)], tetrakis(dimethylamido)titanium (IV) [Ti(NMe2)(4)], and ammonia (NH3) plasma. High Al-content, low impurity (O and C, both <5 at. %) films with uniform grain size distribution and dense morphology were deposited. The as-deposited films were x-ray amorphous, but mixed crystallographic phases were observed when the films were annealed at 700 degrees C. The deposited aluminum-rich Al (x) Ti1-x N films show an alternative way for ternary material depositions.

Aluminum titanium nitride (AlxTi1-xN, 0 < x < 1) is a critical hard coating material for cutting tools due to its exceptional hardness, thermal stability, wear resistance, and oxidation resistance, all of which are influenced by its Al content. A common method to swiftly estimate the Al content in production of such coatings is by the size of the AlxTi1-xN unit cell – determined by standard θ-2θ X-ray diffraction – and the equilibrium cell size of the binary constituents AlN and TiN in the framework of Vegard's law. However, in most cases, the measured unit cell size does not merely depend on Al content as AlxTi1-xN is a metastable phase that may exhibit crystalline defects, non-ideal mixing of the binaries, differences in bonding characteristics, strain relaxation, and phase separation. We seek to investigate the resulting uncertainty in Vegard's-law-based estimation by comparing estimated Al content with elemental composition of AlxTi1-xN coatings – grown industrially by chemical vapor deposition on cemented tungsten carbide substrates – using energy-dispersive X-ray spectroscopy, hard X-ray photoelectron spectroscopy, time-of-flight elastic recoil detection analysis, and Rutherford backscattering spectrometry. Our results demonstrate that the uncertainties in Al content estimated by Vegard's law are relatively small, rendering this method a good first-order approach for compositional analysis of the metal sub-lattices in AlxTi1-xN. Moreover, our data indicate that a multimethod strategy is required for precise composition determination that includes both the metal and the non-metal sublattices and impurity level.

Background: Urinary retention is a common complication associated with hip surgery. There are easily available, evidence-based clinical practice guidelines pre-scribing how to prevent both urinary retention and other voiding issues, by means of bladder monitoring and risk assessments. A detected lack of adherence to such guidelines increases risks for unnecessary suffering among patients but a greater understanding of patients experiences can benefit tailored interventions to address quality and safety gaps in orthopaedic nursing and rehabilitation.Purpose: The aim was to describe patients experiences of urinary retention, bladder issues, and bladder care in orthopaedic care due to hip surgery.Method: This was a qualitative study with a descriptive design: content analysis with an inductive approach was applied to interviews (n = 32) and survey free-text responses (n = 122) across 17 orthopaedic units in Sweden.Results: The patients had received no or limited details for the recurrent bladder care interventions (such as bladder scans and prompted voiding) while at the hospital. They relied on the staff for safe procedures but were left to themselves to manage and comprehend prevailing bladder issues. Despite the patients ex-periences of bladder issues or the risk of urinary retention postoperatively, the link to hip surgery remained unknown to the patients, leaving them searching for self -management strategies and further care.Conclusions: Patients perspectives on bladder care, urinary retention and bladder issues can serve as a means for increased understanding of procedures and issues, reinforcing improved implementation of guidelines, including person-centred information. Safer bladder procedures imply further patient engagement, highlighted in guidelines.

Urinary retention is a healthcare complication putting patients at risk of unnecessary suffering and harm. Orthopaedic patients are known to face an increased such risk, calling for evidence-based preoperative assessment and corresponding measures to prevent bladder problems. The aim of this study was to evaluate healthcare professionals' adherence to risk assessment guidelines for urinary retention in hip surgery patients. This was an observational study from January 2021 to April 2021 with a descriptive and comparative design, triangulating three data sources: (I) Medical records for 1382 hip surgery patients across 17 hospitals in Sweden were reviewed for preoperative risk assessments for urinary retention and voiding-related variables at discharge; (II) The patients completed a survey regarding postoperative lower urinary tract symptoms, and; (III) data were extracted from a national quality registry regarding type of surgery, preoperative physical status, and perioperative urinary complications. Group differences were analysed with Chi-square/Fisher's exact test, t-test, Wilcoxon rank-sum test, or Mann-Whitney U-test. Logistic regression was used to analyse variables associated with completed risk assessments for urinary retention. Of all study participants, 23.4% (n = 323) had a preoperative documented risk assessment of urinary retention. Whether a risk assessment was performed was significantly associated with acute surgery [odds ratio (OR) 3.56, 95% confidence interval (CI) 2.48-5.12] and undergoing surgery at an academic hospital (OR 4.59, 95% CI 2.68-7.85). Acute patients were more often affected by urinary retention and had bladder issues and/or an indwelling catheter at discharge. More than every tenth patient (11. 9%, n = 53) completing the survey experienced intensified bladder problems after their hip surgery. The study shows a lack of adherence to risk assessment for urinary retention according to evidence-based guidelines, which negatively affects quality of care and patient safety.

AimTo better understand what enables evidence-based practice, this study investigated contextual factors influencing evidence-based practice in general, and in relation to the implementation of bladder-monitoring guidelines in orthopaedic care.DesignConvergent parallel mixed method.MethodsThis study was part of a hybrid research project across 17 Swedish orthopaedic sites. The data collection (2021-2023) included interviews with orthopaedic staff and patients post-hip surgery, patient survey free-text responses, and a staff survey on organisational context. Data were analysed with deductive content analysis and descriptive statistics, later integrated using a mixed methods approach.ResultsEvidence-based practice was supported by context factors such as staff collaboration and multiprofessional engagement. Staff addressed patient safety and equality by using evidence-based guidelines, but rarely involved the patients. Orthopaedic fast-track procedures positioned patients as passive recipients, while staff voiced a call for a more person-centred context. Positive attitudes, leadership engagement, use of champions, and adequate staffing enabled evidence-based practice, though a shortage in evaluation and high staff turnover hindered its implementation.ConclusionOrthopaedic context is characterised by several enabling organisational context factors for evidence-based practice, although patients lacking recognition of their needs and queries justify greater focus on person-centredness and mutual information exchange. Audit and feedback are crucial for improvements, but were lacking in the orthopaedic care context.Implications for the Profession and/or Patient CareAssessments of efforts made to implement evidence-based practice and its outcomes should incorporate nursing care. Slimmed care processes require attention to ensure patient participation.ImpactThe orthopaedic care context is enabling for evidence-based practice, although staff are challenged by fast-track procedures with extensive information exchange and insufficient person-centredness.Reporting MethodThe Mixed Methods Reporting in Rehabilitation & Health Sciences checklist.Patient or Public InvolvementNo patient or public contribution.Trial RegistrationIdentifier: NCT 04700969

Aviation accounts for approximately five percent of global greenhouse gas emissions through the combustion of fossil fuels. This paper analyses the opportunities and challenges of mitigation measures in limiting travel volume, energy and emission intensity to reduce the climate impact of aviation in Sweden. Several measures are in place that aim to reduce the climate impact of the aviation industry, ranging from regulations to technology alternatives to fossil-based jet fuel. These measures face several crosscutting challenges, many of which are of a socio-economic and political nature, and these aspects are often neglected in favour of focusing on technological solutions. The market creation for alternatives to fossil-based jet fuel is a major challenge, as most consumers today have a limited awareness of and willingness to pay for these innovations. Policy measures in place are proven ineffective in incentivising change. An understanding of the industry as a socio-technical system is required. The value of this review is its broader consideration of the pathways to reduce aviations climate impact, offering new perspectives and pointing to areas for further research considering all components, their interactions and interdependence.

This article analyses the political discourse about governing the future of the aviation industry in Sweden and how a polarized and entrenched discursive path dependency around aviation makes it difficult to invest into aviations possible futures as a sustainable transport. We find three different politically merged frames in the political discussion about governing the road to sustainable aviation: (1) Neoliberal sustainable aviation, (2) Green Keynesian sustainable aviation and (3) National environmentalists aviation. We can see a discrepancy between two merged frames that believe sustainable aviation will be possible with more or less government support and steering (Neoliberal sustainable aviation and Green Keynesian sustainable aviation) whereas the third merged frame (National environmentalists aviation) argues that aviation is bound to be environmentally inferior to trains and, therefore, all focus should go to the later. We can see that there is not just a path dependency in the merged frame of National environmentalists aviation that discounts the possibility that both the role of aviation or its sustainability can change as the technology changes. There is here a static perceived view of technology as being forever clean or dirty. Another path dependency is the linkage of aviation transport with particular political parties where the green party, for instance, oppose aviation while the conservative party wants to support aviation and innovation in aviation. This polarization is actually the largest and most important aspect of the discursive lock-in as this undermines any compromises or large-scale future investments in sustainable aviation.

Sweden aims for carbon neutrality by 2045, including a fossil-free transport sector. Radical innovations like civilian drones and eVTOLs offer potential for sustainable, electrified, and integrated transport, but integration is challenged by infrastructure, connectivity, regulation, and public concerns. This paper explores discursive policy leadership in governing drone innovation for sustainable transition, focusing on Sweden. Using a multi-level perspective and narrative discourse analysis, we conducted 18 expert interviews with national, regional, local, and private actors. We examine how drones are narrated within sustainable transport and how accounts reveal the presence or absence of niche leadership. Findings highlight four insights: (1) lack of public-sector leadership risks reinforcing division between private actors and regime lock-in; (2) ideological tensions frame drones as disruptive or conflictual; (3) fragmented responsibilities hindering policy coordination; and (4) new discursive models are needed to reflect complexity. We argue for active discursive policy leadership and inclusive governance to unlock drones' transformative potential.

Background Previous studies indicate a low incidence of appendicitis in third-trimester pregnancy, suggesting a protecting effect of pregnancy. This large population-based cohort study analyzes the association of appendicitis with pregnancy in more detail. The aim of the study was to investigate the incidence of appendicitis and negative appendectomy before, during and after pregnancy. Methods Cross-linking between two Swedish health registries provided data on appendectomy for all women in Sweden giving birth between 1973 and 2013. We analyzed the incidence rates (IR) of perforated and non-perforated appendicitis and negative appendectomy before, during and after pregnancy, and secular trends during the study period. Standardized incidence ratios (SIR) were estimated using age-, sex- and period-specific IR from the background population in Sweden. Results Some 3,888,452 pregnancies resulted in birth during the study period. An appendectomy was registered for 27,575 women in the interval starting one year before and ending two years after pregnancy. The incidence of appendicitis varied substantially during and after pregnancy. SIR for perforated appendicitis was 0.47 (95% CI 0.38-0.59) in the third trimester, 3.89 (2.92-5.18) peripartum, 2.20 (1.89-2.55) in the puerperium and 1.27 (1.19-1.36) in the year postpartum. The pattern was similar for non-perforated appendicitis. Negative appendectomy decreased postpartum. Incidence rate of non-perforated appendicitis and negative appendectomy decreased for both pregnant and non-pregnant women during the study period. Conclusions The findings in this study suggest a protecting effect of pregnancy on the development of appendicitis, which is followed by a rebound effect after birth.

ObjectivesAppendicitis poses diagnostic challenges. A correct diagnosis is important during pregnancy to avoid unnecessary surgery on the one hand and delayed surgery on the other hand, as both may negatively affect pregnancy outcomes. Clinical scores for risk-stratified management of suspected appendicitis are well established in adults but have not been validated during pregnancy. This nested case-control study evaluated the diagnostic accuracy of the Appendicitis Inflammatory Response (AIR) score and imaging during pregnancy.MethodsBy cross-linking national Swedish health registries from a defined geographical area, we identified a cohort of 154 women who underwent appendectomy for suspected appendicitis during pregnancy and a matched cohort of 232 pregnant women admitted for acute abdominal pain and suspected appendicitis but with a discharge diagnosis of nonspecific abdominal pain (NSAP). All variables were extracted from medical records. The diagnostic value of AIR score and imaging was estimated for patients with a final diagnosis of appendicitis compared with patients with negative appendectomy and NSAP patients.ResultsThe final diagnoses for the operated patients were uncomplicated and complicated appendicitis in 49.4% and 26.6%, respectively, and negative appendectomy in 24.0%. Nearly half of all the patients underwent diagnostic imaging (41%), mainly by ultrasonography. The sensitivity and specificity of diagnostic imaging were 44.9% (95% CI 32.9%-57.4%) and 42.2% (95% CI 31.9%-53.1%), respectively. The area under the receiver operating characteristic curve of AIR score was 0.88 (95% CI 0.84-0.92) for all appendicitis and 0.90 (95% CI 0.84-0.95) for complicated appendicitis. The sensitivity for complicated appendicitis was 100% at a score of &gt;= 4. The specificity for all appendicitis was 97% at a score of &gt;= 9.ConclusionsThe results of this study suggest that the AIR score may be a suitable diagnostic tool for risk stratification of pregnant women with abdominal pain and suspected appendicitis but further validation among pregnant women is needed.

Programming recently became mandatory in Swedish compulsory schools (age group 7-16); this article contributes to our understanding of novice learners’ different approaches when programming. The study builds on observations and informal conversations during programming lessons at three Swedish science centres. At the time of the study, science centres already had experience of programming education as they offered courses for pupils. This was used as a complement to teaching at compulsory school. We apply a design-for-learning perspective to help us understand how contextual aspects influence what novice pupils do and how they design their learning during programming lessons. During the analysis process, we combine thematic analysis with the Learning Design Sequence (LDS) model. We identify five qualitatively different approaches that pupils take to solve programming problems: mathematically, trial and error, step-by-step, routine as well as aesthetic. Each of these approaches allows pupils to use and practice different abilities that are important for programming. We discuss how these abilities can be compared to computational thinking (CT). The study provides an insight how pupils are involved in designing their own learning when using their abilities to solve programming assignments.

Within a theoretical framework grounded in design for learning, this article presents a research project about pupils’ engagement during programming education. In a design-theoretical perspective, everyone who is somehow engaged in a learning process is a designer. The results show that how pupils design their learning when programming is related to different types of engagement. By analysing pupils’ engagement when programming, the study contribute to an insight how behavioural, emotional, and cognitive engagement can be identified and understood. The study was carried out during programming lessons adapted for novice learners (age group 7–15), visiting Swedish science centres (SCs) as a part of their school day. SCs had experience of programming education and was used as complement to education at school ahead of the implementation of programming as a mandatory subject in Swedish compulsory schools.

Digital technologies have increasingly become part of society, and teachers and other pedagogues need to face digitisation in constructive ways. Among other things, this can include the use of different types of personnel and technical resources for teaching, both formal and informal. In municipalities where there is a Science Centre (SC), this is used as part of the education offered in compulsory school in Sweden. When computer programming was introduced into the curriculum for all grades, SC s already had experience in delivering programming education as part of their programming courses. This experience was used as a resource by teachers who sought support with teaching programming to their students. In this context, SC s can therefore be said to have played a pioneering role in the delivery of programming education in compulsory school. This chapter outlines how teachers who visited SC s with their students view the teaching of programming in compulsory school, why they chose to visit the SC with their class, and what they need in order to be able to teach programming themselves.

Low temperature hydrothermal methods have been utilized to synthesize Hematite/Zinc oxide alpha-Fe2O3/ZnO composite nano-heterojunction nanorods grown on FTO glass substrates while monitoring the effect of different concentrations of urea on the morphology of the composite nano-heterojunction. X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques were used for the structural characterization of the alpha-Fe2O3/ZnO different samples. UV-visible spectroscopy was used for the characteristic absorbance versus wavelength of alpha-Fe2O3/ZnO composite nano-heterojunction which shows an absorption edge from 400 to 560 nm. X-ray photoelectron spectroscopy (XPS) technique was applied to study of chemical composition of the alpha-Fe2O3/ZnO and the obtained information demonstrated a pure phase alpha-Fe2O3/ZnO has been achieved. The best efficiency among urea concentrations for the best composite nano-heterojunction sample was achieved when using 0.2 M of urea. The electrochemical properties of the composite nano-heterojunction were investigated using a three-electrode electrochemical cell. Estimation of the electrochemical area shows that both the composite nano-heterojunction and the bare alpha-Fe2O3 have similar values. This confirms that the enhanced electrochemical property of the composite nano-heterojunction is due to a synergetic effect as expected.

Arsenic is a toxic contaminant that can be found in drinking water. In this study, the development of an efficient electrode as an electrochemical sensor to detect arsenic(v) in drinking water is presented. The surface of ZnO nanorods (NRs) synthesized on a Ni-foam substrate was modified by depositing alpha-Fe2O3 nanoparticles (NPs) to fabricate an electrode for the detection of arsenic(v) contamination in drinking water. This electrode was synthesized through two separate growth steps: a hydrothermal (ZnO NRs) step followed by the dip-coating method (alpha-Fe2O3 NPs). The dip-coating method was repeated multiple times, 2 times (ZNF-2), 3 times (ZNF-3) and 4 times (ZNF-4), in order to achieve a uniform coverage of the ZnO NR surface. The electrodes were characterized using XRD, XPS, SEM and UV-vis spectroscopy. The best efficiency among the alpha-Fe2O3NP-modified nanorod samples was observed for the 3-time dip-coated ZNF-3 sample, which presented a uniform and homogeneous morphology, as observed from the SEM images, accompanied with the highest oxidation current. The electrochemical performance of the sensor electrodes was tested for a wide range of arsenic(v) concentrations from 0 to 50 ppb and was monitored using cyclic voltammetry. The results demonstrated a calibration plot that was linear over a concentration range of 0-50 ppb of arsenic(v), and the regression equation extracted from the calibration curve was found to be y = 0.003x - 0.6271 (with R2 = 0.991). The limit of detection (LOD) and limit of quantification (LOQ) were found to be 4.12 ppb and 13.74 ppb, respectively, which are lower than the maximum allowed value recommended by the World Health Organization (WHO) for arsenic in drinking water. This reasonable performance of the ZnO NRs/Ni-foam/alpha-Fe2O3NP nanocomposite electrode can be further enhanced, and the electrode can be utilized for efficient arsenic(v) detection in drinking water.

In this study, the development of an efficient nano-electrode for fabricating electrochemical sensors to detect arsenic(v) in drinking water is presented. This nano-electrode is composed of a metal-semiconductor hybrid, namely ZnO NRs/alpha-Fe2O3/Au NPs, denoted as (ZFA), which was synthesized in three separate steps, including the low-temperature hydrothermal and dip-coating methods. The properties of the nanocomposite were characterized by UV-vis, FESEM, XRD and XPS. Moreover, its electrochemical characteristics were analyzed via several techniques, such as linear sweep voltammetry and square wave voltammetry in different water solutions with a wide range of arsenic concentrations from 0 to 50 mu g L-1. Results indicate that the ZFA nanocomposites that were prepared with different concentrations of Au NPs showed different characteristics. From optical measurements, the best Au NP sample having the highest surface plasmon resonance (SPR) effect was determined, and this sample was further utilized for sensing. Moreover, using the optimized sample and from electrochemical studies, the arsenic(v) sensor's limit of detection was found to be 2.25 ppb, which is lower than the maximum dose recommended by the World Health Organization. In general, the results indicate that the addition of Au NPs led to better optical absorption properties. The findings of this study indicate that the addition of Au improves the electrochemical catalytic activity of the ZFA nanocomposite, which can be utilized as an electrode to further develop efficient arsenic(v) sensing systems for detection in drinking water.

In Sweden, treatment for children with (developmental) language disorder ((D)LD) is traditionally carried out at a speech-language pathology (SLP) clinic, and based on formal language tests, which may not entirely represent the child's everyday language and communication skills. SLP services that include video recordings have shown positive outcomes in terms of providing information about children's linguistic and communicative abilities in everyday life, but little is known about the use of video in clinical practice. The aim of this study is therefore to investigate how Swedish SLPs link their clinical practices (assessment, treatment, and evaluation of treatment outcome) to the everyday language and communication abilities of children with (D)LD. A further aim is to explore SLPs' utilisation of video recordings as a part of their clinical practices with the target group. A web-based questionnaire was distributed to SLPs in Sweden, who work with children with (D)LD. Results demonstrate that Swedish SLPs perceive that their intervention is in alignment with children's everyday language and communication needs to a fairly high degree. However, an exception is assessment, which is considered to have a weaker alignment with children's everyday communication abilities. The use of video recordings for clinical purposes is very limited. It is suggested here that incorporating video recordings from children's everyday life would be an easy and time-efficient way to strengthen the ecological validity of SLP practices for children with (D)LD.

This study aims to extend current knowledge about the possibilities and challenges encountered by Swedish speech and language pathologists (SLPs) in targeting everyday language and communication in children with developmental language disorder (DLD). To explore this matter, unstructured focus groups were conducted where 15 SLPs, working with children with DLD, shared their views on the alignment between their clinical practices and children's everyday lives. Thematic analysis was used to analyse the data, which resulted in five themes: It's everyday life that matters; As an SLP, you're not a part of the child's everyday life; How do we merge the different worlds?; Resources at home vary, and The employer sets the framework for clinical practices. The SLPs stressed the importance of targeting everyday skills and needs, but they experienced themselves as being detached from the children's daily context. Collaboration with caregivers and (pre)school staff was emphasised; however, the resources and capacity of the caregivers and staff varied, and this was experienced as a challenge for providing the most appropriate care. Some children and their families were situated in a multifaceted context and needed more extensive care, and this group was described as increasing. However, the services that the SLPs were able to offer varied and were largely regulated by organisational constraints. Individualised services are crucial for ensuring a positive development for children with DLD and for empowering caregivers to be effective collaborative partners in intervention. Therefore, it is essential for SLPs to have the time and resources to ensure high-quality care.

The deployment of High Capacity Transport (HCT) vehicles is in process in different countries. Although their performance has been assessed through simulations and test-track experiments, a question that remains unanswered is: how do these vehicles perform in real traffic? In this paper, the question is addressed for one of the transient manoeuvres, i.e., a lane change using Naturalistic Driving Data (NDD). First, an algorithm is proposed to extract lane changes from the NDD of HCT vehicles using GPS, road data and IMU signals. Following this, the performance of two A-double combinations is assessed in the extracted lane changes using measures commonly used in performance-based standards (PBS) schemes like offtracking and rearward amplification. The dependency of these measures on the factors such as the vehicle’s speed, load and lateral displacement is investigated. The assessment concludes that the vehicles satisfy the PBS requirements proposed for them and are driven safely in the extracted lane changes.

The focus of this paper is to use Naturalistic Driving Data to understand how the drivers manoeuvre an A-double combination in the roundabouts and evaluate performance in the roundabouts using measures like Low-Speed Swept Path (LSSP) and Tail Swing (TS). The analyses of the steering patterns and speed variations depict that the standard deviations of the responses of the drivers for a given travel direction in a roundabout are within 35o (17 % of the baseline) for the steering wheel angle and 8 km/h (40 % of the baseline) for the speed. It is also found that the cognitive workload of the drivers due to the steering pattern is higher in right turns compared to straight crossings through the roundabout. The performance analyses show a dependency of LSSP on the instantaneous radius obtained from the vehicle's path, and the vehicle's travel direction in the roundabout. LSSP ranges from 7.7 m for a left turn in a roundabout with an inner radius of 12 m to 3.1 m for a straight crossing in a roundabout with a 30 m inner radius. TS is observed in only one roundabout and its magnitude goes up to 0.4 m in a roundabout of 30 m inner radius.

This paper evaluates the performance of two different types of long combination vehicles (A-double and DuoCAT) using naturalistic driving data across four scenarios: lane changes, manoeuvring through roundabouts, turning in intersections, and negotiating tight curves. Four different performance-based standards measures are used to assess the stability and tracking performance of the vehicles: rearward amplification, high-speed transient offtracking, low-speed swept path, and high-speed steady-state offtracking. Also, the steering reversal rate metric is employed to estimate the cognitive workload of the drivers in low-speed scenarios. In the majority of the identified cases of the four scenarios, both combination types have a good performance. The A-double shows slightly better stability in high-speed lane changes, while the DuoCAT has slightly better manoeuvrability at low-speed scenarios like roundabouts and intersections.

This paper investigates the influence of tire-road friction on the performance of a long combination vehicle, specifically the A-double, during low-speed manoeuvres such as navigating roundabouts and intersections. Using real-world naturalistic driving data and applying the Performance-Based Standards scheme, the study assesses the low-speed swept path (LSSP) and the driver’s response to varying friction conditions. Results indicate that tire-road friction has minimal effect on the LSSP, which conforms with earlier simulation-based studies. However, it influences driver behaviour, particularly in roundabouts where speed reductions are observed under low-friction conditions. 

Time-to-collision (TTC) is a widely used measure for predicting rear-end collisions, assuming constant speed and heading for both vehicles in the prediction horizon. However, this conventional formulation cannot detect sideswipe collisions. A two-dimensional extension, TTC_2D, has been proposed in the literature to address lateral interactions. However, this formulation assumes both vehicles have the same heading and that their headings remain unchanged during the manoeuvre, in addition to the constant speed and heading assumptions in the prediction horizon. Moreover, its use for articulated vehicles like a tractor-semitrailer remains unclear. This paper proposes three enhanced versions of TTC_2D to overcome these limitations. The first incorporates the vehicle heading to account for directional differences. The standard assumption of constant speed and heading in the prediction horizon holds. The second adapts the formulation for articulated vehicles, and the third allows for constant acceleration, relaxing the constant speed assumption in the prediction horizon. All versions are evaluated in simulated cut-in scenarios, covering both sideswipe and rear-end collisions, using the CARLA simulation environment with a tractor-semitrailer model. Results show that the proposed versions predict sideswipe collisions with better accuracy compared to existing TTC2_D. They also detect rear-end collisions similar to the existing methods.

There is a need to personalize the treatment for rectal cancer patients. The aim of this study was to analyze therapy response and prognosis after preoperative radiotherapy in rectal cancer patients with mucinous adenocarcinoma compared to those with non-mucinous adenocarcinoma. The study included retrospectively collected data from 433 patients, diagnosed with rectal cancer in the South East health care region in Sweden between 2004 and 2012. Patients with non-mucinous adenocarcinoma that received short-course radiotherapy before surgery had better overall survival, cancer specific survival, and disease-free survival, as well as distant- and local-recurrence-free survival (p = 0.003, p = 0.001, p = 0.002, p = 0.002, and p = 0.033, respectively) compared to the patients that received long-course radiotherapy with concomitant capecitabine. The results were still significant after adjusting for sex, age, stage, differentiation, and chemotherapy in the neoadjuvant and/or adjuvant setting, except for local-recurrence-free survival that was trending towards significance (p = 0.070). In patients with mucinous adenocarcinoma, no difference in survival was seen when comparing patients that had short-course radiotherapy and patients that had long-course radiotherapy. However, none of 18 patients with mucinous adenocarcinoma treated with long-course radiotherapy had local tumor progression, compared to 7% of 67 patients with non-mucinous adenocarcinoma. The results indicate that mucinous adenocarcinoma and non-mucinous adenocarcinoma may respond differently to radiotherapy.

IntroductionThe value of adjuvant chemotherapy for rectal cancer patients is debated and varies in different subgroups. One such subgroup is mucinous adenocarcinoma (MAC), which is more treatment resistant compared to non-mucinous adenocarcinoma (NMAC). To date, mucinous histology is not taken into account when deciding on adjuvant treatment strategy. This is the first study to exclusively include patients with rectal cancer, then separate MAC and NMAC and compare the survival in patients that had or did not have adjuvant chemotherapy. Material and methodsThe study included retrospective register data from 365 Swedish patients with stage II-IV rectal adenocarcinoma, 56 patients with MAC and 309 patients with NMAC. All patients were considered curative, had surgery with total mesorectal excision in 2004-2013, and were followed up until death or 2021. ResultsPatients with MAC that had adjuvant chemotherapy had better overall survival (OS, HR 0.42; CI 95%: 0.19-0.93; p = 0.032) and a trend towards better cancer-specific survival (CSS, HR 0.41 CI 95%: 0.17-1.03; p = 0.057) compared to patients without chemotherapy (HR 0.42; CI 95%: 0.19-0.93; p = 0.032). The difference in OS was still significant even after adjusting for sex, age, stage, differentiation, neoadjuvant chemotherapy and preoperative radiotherapy (HR 0.40; CI 95%: 0.17-0.92; p = 0.031). There was no such difference in the NMAC patients except in the stage-by-stage subgroup analyses where patients in stage IV had better survival after adjuvant chemotherapy. ConclusionsThere may be a difference in treatment response to adjuvant chemotherapy between MAC and NMAC patients. Patients with MAC could possibly benefit from adjuvant chemotherapy in stages II-IV. Further studies are however needed to confirm these results.

Neurodegenerative diseases (NDs) are associated with accumulated misfolded proteins (MPs). MPs oligomerize and form multiple forms of amyloid fibril polymorphs that dictate fibril propagation and cellular dysfunction. Protein misfolding processes that impair protein homeostasis are implicated in onset and progression of NDs. A wide variety of molecular chaperones safeguard the cell from MP accumulation. A rather overlooked molecular chaperone is HSP10, known as a co-chaperone for HSP60. Due to the ubiquitous presence in human tissues and protein overabundance compared with HSP60, we studied how HSP10 alone influences fibril formation in vitro of Alzheimers disease-associated A beta 1-42. At sub-stoichiometric concentrations, eukaryotic HSP10s (human and Drosophila) significantly influenced the fibril formation process and the fibril structure of A beta 1-42, more so than the prokaryotic HSP10 GroES. Similar effects were observed for prion disease-associated prion protein HuPrP90-231. Paradoxically, for a chaperone, low concentrations of HSP10 appeared to promote fibril nucleation by shortened lag-phases, which were chaperone and substrate dependent. Higher concentrations of chaperone while still sub-stoichiometric extended the nucleation and/or the elongation phase. We hypothesized that HSP10 by means of its seven mobile loops provides the chaperone with high avidity binding to amyloid fibril ends. The preserved sequence of the edge of the mobile loop GGIM(V)L (29-33 human numbering) normally dock to the HSP60 apical domain. Interestingly, this segment shows sequence similarity to amyloidogenic core segments of A beta 1-42, GGVVI (37-41), and HuPrP90-231 GGYML (126-130) likely allowing efficient competitive binding to fibrillar conformations of these MPs. Our results propose that HSP10 can function as an important molecular chaperone in human proteostasis in NDs.

We investigate digital citizenship by exploring attitudes and experiences of digital inclusion and eHealth with data from a survey study based on face-to-face interviews in differentlanguages, in a marginalised hard to survey neighbourhood. Through public eHealth services,people can exercise digital citizenship. We explore differences between the marginalised neighbourhood and the national level, and among residents in the neighbourhood, with disaggregateddata. The results show that the respondents in Skäggetorp report lower usage of the internet,lower access to smartphones, a somewhat lower usage of BankID, higher concern for surveillance, and a higher number of respondents feel excluded from digital society in comparison tothe nationwide survey. The results in the disaggregated data show some differences in attitudesto and experience of digital inclusion among residents in Skäggetorp. We conclude that thestudies of digital citizenship need to be broadened to address feeling included, social rights,and difference.

Digital inclusion is the key for a sustainable andinclusive society. In particular, digital governmentalservices must be impartial, inclusive and available foreveryone eligible for the services. Digital inclusion is akey for trust of government in a more digital society.However, the motives access, use and competences to bedigital included varies in line with other forms socioeconomicstratification. It is also complicated to reachthose who are digital excluded in traditional surveymethods. This paper presents a field study on digitalinclusion in a disadvantaged Swedish suburb, where wemade a structured interview survey to reach groups thatare usually hard to survey. The analysis shows thatthose who find it easy to search on the Internet alsoexperience more inclusion in the Swedish society. Inaddition, more advanced use as on-line payments anduse of eID seems to increase the trust in publicauthorities. Thereby, digital inclusion can be seen as afactor enhancing even quality of government, that hasto be further investigated.

Aim: To describe the variation in ways that registered nurses perceive and understand cognitive impairment in cardiac arrest survivors. Design: A qualitative, inductive design with individual semi-structured interviews was applied. Data was analysed using a phenomenographic approach. Setting: The participants were nineteen Swedish registered nurses, experienced in cardiovascular care and providing follow-up care. Findings: The nurses perceived the cognitive impairment of the survivors in qualitatively different ways, as illustrated in two categories: The perceptible and obvious and The elusive and challenging. The nurses perceived a variety of signs of cognitive impairment, emotional expressions related to these, and recovery from cognitive impairment. They perceived confidence in capturing cognitive function when they understood the signs of cognitive impairment as severe and obvious. However, it was perceived as difficult to assess cognitive function when impairments were subtle, resulting in uncertainty in terms of how to make assessments. Nurses made use of their own strategies for assessments, which were sometimes found to be inadequate when they understood that they had misinterpreted the survivors cognitive impairment. Conclusion: Nurses feel uncertainty regarding detecting mild impairment in cardiac arrest survivors. By involving next of kin, nurses will gain a broader understanding of survivors cognitive function. (C) 2020 The Author(s). Published by Elsevier Ltd.

Objective The aim was to compare self-reported health between cardiac arrest survivors with good cerebral performance (CPC 1) and survivors with moderate cerebral disability (CPC 2). Methods This comparative register study was based on nationwide data from the Swedish Register of Cardiopulmonary Resuscitation. The study included 2058 in-hospital and out-of-hospital cardiac arrest survivors with good cerebral performance or survivors with moderate cerebral disability, 3-6 months postcardiac arrest. Survivors completed a questionnaire including the Hospital Anxiety and Depression Scale (HADS) and EQ-5D five-levels (EQ-5D-5L). Data were analysed using ordinal and linear regression models. Results For all survivors, the prevalence of anxiety and depression symptoms measured by the HADS was 14% and 13%, respectively. Using the EQ-5D-5L, the cardiac arrest survivors reported most health problems relating to pain/discomfort (57%), followed by anxiety/depression (47%), usual activities (46%), mobility (40%) and self-care (18%). Compared with the survivors with good cerebral performance, survivors with moderate cerebral disability reported significantly higher symptom levels of anxiety and depression measured with HADS, and poorer health in all dimensions of the EQ-5D-5L after adjusting for age, sex, place of cardiac arrest, aetiology and initial rhythm (p&lt;0.001). Conclusions These findings stress the importance of screening for health problems in all cardiac arrest survivors to identify those in need of professional support and rehabilitation, independent on neurological outcome.

Aim Self-reported cognitive function has been described as an important complement to performance-based measurements but has seldom been investigated in cardiac arrest (CA) survivors. Therefore, the aim was to describe self-reported cognitive function and its association with health status, psychological distress, and life satisfaction. Methods This study utilised data from the Swedish Register of Cardiopulmonary Resuscitation (2018–2021), registered 3–6 months post-CA. Cognitive function was assessed by a single question: “How do you experience your memory, concentration, and/or planning abilities today compared to before the cardiac arrest?”. Health status was measured using the EQ VAS, psychological distress with the Hospital Anxiety and Depression Scale, and overall life satisfaction with the Life Satisfaction checklist. Data were analysed using binary logistic regression. Results Among 4026 identified survivors, 1254 fulfilled the inclusion criteria. The mean age was 65.9 years (SD = 13.4) and 31.7% were female. Self-reported cognitive function among survivors was reported as: ‘Much worse’ by 3.1%, ‘Worse’ by 23.8%, ‘Unchanged’ by 68.3%, ‘Better’ by 3.3%, and ‘Much better’ by 1.5%. Declined cognitive function was associated with lower health status (OR = 2.76, 95% CI = 2.09–3.64), symptoms of anxiety (OR = 3.84, 95% CI = 2.80–5.24) and depression (OR = 4.52, 95% CI = 3.22–6.32), and being dissatisfied with overall life (OR = 2.74, 95% CI = 2.11–3.54). These associations remained significant after age, sex, place of CA, aetiology, initial rhythm, initial witnessed status, and cerebral performance were controlled. Conclusions Survivors experiencing declined cognitive function post-CA are at a higher risk of poorer health status, increased psychological distress, and reduced life satisfaction, and these risks should be acknowledged by healthcare professionals.

Background: The COVID-19 pandemic has been associated with various negative psychological consequences. This is a challenge for the society as regular psychological services cannot be offered to the same extent as before the pandemic. In addition to the requirement of social distancing, there is a need to adjust psychological treatment components like exposure to avoid increasing the spread of the infection. Internet-delivered cognitive behavior therapy (ICBT) has an established evidence base for a range of psychiatric problems and has been suggested as one possible approach to deal with the situation. This study aimed to conduct a randomized controlled pilot trial during the summer of 2020 with a broad focus on psychological distress and a treatment approach that tailors the intervention based on symptom profile and preferences.

Methods: Following the advertisement and interview, we included 52 participants with elevated levels of psychological distress. They were randomly allocated to either a 7-week-long individually tailored ICBT (n = 26) or a wait-list control condition (n = 26). Measures of depression and quality of life were used as primary outcomes. We also included secondary outcome measures of anxiety, insomnia, trauma, stress, anger, and alcohol use. For screening, we used the CoRonavIruS Health Impact Survey (CRISIS).

Results: Overall moderate to large between-group effects were found at post-treatment in favor of the treatment on measures of both depression [Beck Depression Inventory (BDI); Cohens d = 0.63; Patient Health Questionnaire (PHQ-9): d = 0.62] and anxiety [Generalized Anxiety Disorder-7-item scale (GAD-7); d = 0.82]. This was also observed for stress symptoms [Perceived Stress Scale (PSS-14); d = 1.04]. No effects were seen on measures of quality of life, insomnia, symptoms of post-traumatic stress, and anger. There was an effect on alcohol use [Alcohol Use Disorder Identification Test (AUDIT); d = 0.54], which was not of clinical relevance.

Conclusion: Individually tailored ICBT shows initial promise as a way to reduce psychological problems in association with the COVID-19 pandemic. A possible limitation was that the trial was conducted when the effects of the pandemic were decreasing and when fewer people were affected by the restrictions (e.g., the summer of 2020).

The COVID-19 pandemic influence mental health in both infected and non-infected populations. In this study we examined if individually tailored internet-based cognitive behavioral therapy (ICBT) could be an effective treatment for psychological symptoms related to the pandemic. Following recruitment we included 76 participants who were randomized to either a treatment group (n = 37) or a waitlist control group (n = 39). The treatment group received 8 modules (out of 16 possible) during 8 weeks with weekly therapist support. We collected data on symptoms of depression, experienced quality of life, anxiety, stress, anger, insomnia, PTSD, and alcohol use before, after the treatment and at one year follow-up. Using multiple regression analysis, group condition was found to be a statistically significant predictor for a decrease, favoring the treatment group, in symptoms of depression, insomnia, and anger with small to moderate effect sizes. The improvements remained at one year follow-up. Group condition did not significantly predict changing symptoms regarding experienced quality of life, anxiety, stress, PTSD and alcohol use. Findings indicate that ICBT is an effective intervention for some psychological symptoms associated with the COVID-19 pandemic. There is a need for further studies on mechanisms of change and on tailored ICBT for problems associated with crises like the pandemic.

Background: During the COVID-19 pandemic, both physical and psychological health were at risk. Internet-based cognitive behavioral therapy (ICBT) is a psychological treatment alternative that does not inherently increase the risk of virus transmission because face-to-face interactions are not required. ICBT has been found to be effective for a variety of mental health problems, both before and during the COVID-19 pandemic. Although the experiences of undergoing ICBT have been investigated in previous studies, the specific experiences of participating in ICBT during the COVID-19 pandemic have been less examined. Objective: This qualitative study aimed to investigate the experiences of participants undergoing individually tailored ICBT with weekly therapist support during the COVID-19 pandemic. Methods: We approached trial participants who had received ICBT for psychological symptoms related to the COVID-19 pandemic during the summer of 2020. A strategic sample, based on the number of log-ins to the treatment platform, among other factors, was selected in an effort to achieve the highest possible variation. Semistructured telephone interviews were conducted 4 to 6 months after treatment completion, depending on whether the participant was initially assigned to the treatment or control group. Data were transcribed and then analyzed based on thematic analysis. Results: A total of 16 participants aged between 23 and 78 years were interviewed. Four main themes and 10 subthemeswere derived from the thematic analysis: (1) functions of the treatment (initiating and motivating, perspective widening), (2) treatment equals work (experience of the treatment as demanding, going from text to action, posttreatment engagement, participant agency), (3) changes experienced (changes in relation to the COVID-19 pandemic, other changes not related to the COVID-19 pandemic), and (4) wishing for something else (individually tailored, contact with the therapist). Conclusions: The results closely align with those ofpreviousqualitativestudiesonexperiencesofICBT. Participants expressed appreciation of the treatment's content and format. Suggestions and wishes for changes were also expressed in the interviews. However, a unique finding was that participants described experiencing changes in well-being related to the COVID-19 pandemic. At the same time, there were also reports of changes in other symptoms not related to the pandemic. Further studies are needed on the experiences of participants who drop out of ICBT and the type of therapist contact they prefer.

Introduction SARS-CoV-2 and the accompanying COVID-19 pandemic had a great impact on people's well-being, both physically and mentally. The pandemic continued to affect people even after its end was declared. Internet-based cognitive behavioral therapy (ICBT) is a psychological treatment alternative that is effective for several types of psychological symptoms and conditions. This study aimed to investigate the feasibility of ICBT for psychological symptoms related to the COVID-19 pandemic in adults aged 18 years and older during the final phase of the pandemic. Since the psychological impact of the pandemic varies among individuals, individually tailored ICBT was examined, in which participants receive different treatment content based on their needs.Methods A within-group study was conducted with 24 participants, receiving individually tailored ICBT during eight weeks with weekly support from a therapist. Participants received one module per week, which was selected based on the participant's specific symptoms and needs. Of the 24 participants, 16 (66.7%) were assessed as probably meeting the diagnostic criteria for post-COVID syndrome. Pre- and post-treatment measurements using self-report questionnaires for several psychological symptoms were administered online.Results Statistically significant improvements were observed in symptoms of depression, anxiety, post-traumatic stress, loneliness, and exhaustion. Small increases were observed in a measure of CBT knowledge, whereas no significant changes were found in stress, quality of life, experience of cognitive failures, and economic stress. Participants completed on average 3.96 out of 8 modules, with five (20.8%) completing all modules. Fifteen (62.5%) of the 24 participants completed the post-treatment measurement. Three participants (12.5%) withdrew from the study.Conclusion Overall, the results indicate that individually tailored ICBT with weekly support from a therapist is a feasible treatment for psychological symptoms related to the COVID-19 pandemic in its final phase. However, larger studies with more participants are needed to draw further conclusions regarding the effects of ICBT during the final phase of a pandemic. The treatment could be further developed to benefit a broader range of participants.

We provide direct evidence for a spin-active V4+ defect center, likely in the form of a VO2+ complex, predominantly introduced in single crystals of vanadium-doped Cs2NaInCl6 halide double perovskites grown by the solution-processed hydrothermal method. The defect has C-4v point group symmetry, exhibiting an electron paramagnetic resonance (EPR) spectrum arising from an effective electron spin of S = 1/2 and a nuclear spin of I = 7/2 (corresponding to V-51 with nearly 100% natural abundance). The determined electron g-factor and hyperfine parameter values are g(perpendicular to)= 1.973, g(parallel to) = 1.945, A(perpendicular to) = 180 MHz, and A(parallel to) = 504 MHz, with the principal axis z along a &lt; 001 &gt; crystallographic axis. The controlled growth of V-doped Cs2NaInCl6 in an oxygen-free environment is shown to suppress the V4+ EPR signal. The defect model is suggested to have a VOCl5 octahedral coordination, where one of the nearest-neighbor Cl- of V is replaced by O2-, with octahedral compression along the V-O axis. This VO complex formation competes with the isolated V3+ substitution of In3+, which in turn provides a means for the charge-state tuning of V ions. This finding calls for a better understanding and control of defect formation in solution-grown halide double perovskites, which is critical for optimizing and tailoring material design for solution-processable optoelectronics and spintronics.

Many real-world recognition problems are characterized by long-tailed label distributions. These distributions make representation learning highly challenging due to limited generalization over the tail classes. If the test distribution differs from the training distribution, e.g. uniform versus long-tailed, the problem of the distribution shift needs to be addressed. A recent line of work proposes learning multiple diverse experts to tackle this issue. Ensemble diversity is encouraged by various techniques, e.g. by specializing different experts in the head and the tail classes. In this work, we take an analytical approach and extend the notion of logit adjustment to ensembles to form a Balanced Product of Experts (BalPoE). BalPoE combines a family of experts with different test-time target distributions, generalizing several previous approaches. We show how to properly define these distributions and combine the experts in order to achieve unbiased predictions, by proving that the ensemble is Fisher-consistent for minimizing the balanced error. Our theoretical analysis shows that our balanced ensemble requires calibrated experts, which we achieve in practice using mixup. We conduct extensive experiments and our method obtains new state-of-the-art results on three long-tailed datasets: CIFAR-100-LT, ImageNet-LT, and iNaturalist-2018. Our code is available at https://github.com/emasa/BalPoE-CalibratedLT.

Long-tailed semi-supervised learning (LTSSL) represents a practical scenario for semi-supervised applications, challenged by skewed labeled distributions that bias classifiers. This problem is often aggravated by discrepancies between labeled and unlabeled class distributions, leading to biased pseudo-labels, neglect of rare classes, and poorly calibrated probabilities. To address these issues, we introduce Flexible Distribution Alignment (FlexDA), a novel adaptive logit-adjusted loss framework designed to dynamically estimate and align predictions with the actual distribution of unlabeled data and achieve a balanced classifier by the end of training. FlexDA is further enhanced by a distillation-based consistency loss, promoting fair data usage across classes and effectively leveraging underconfident samples. This method, encapsulated in ADELLO (Align and Distill Everything All at Once), proves robust against label shift, significantly improves model calibration in LTSSL contexts, and surpasses previous state-of-of-art approaches across multiple benchmarks, including CIFAR100-LT, STL10-LT, and ImageNet127, addressing class imbalance challenges in semi-supervised learning. Our code is available at https://github.com/emasa/ADELLO-LTSSL.

Precision medicine relies on the identification of robust disease and risk factor signatures from omics data. However, current knowledge-driven approaches may overlook novel or unexpected phenomena due to the inherent biases in biological knowledge. In this study, we present a data-driven signature discovery workflow for DNA methylation analysis utilizing network-coherent autoencoders (NCAEs) with biologically relevant latent embeddings. First, we explored the architecture space of autoencoders trained on a large-scale pan-tissue compendium (n = 75 272) of human epigenome-wide association studies. We observed the emergence of co-localized patterns in the deep autoencoder latent space representations that corresponded to biological network modules. We determined the NCAE configuration with the strongest co-localization and centrality signals in the human protein interactome. Leveraging the NCAE embeddings, we then trained interpretable deep neural networks for risk factor (aging, smoking) and disease (systemic lupus erythematosus) prediction and classification tasks. Remarkably, our NCAE embedding-based models outperformed existing predictors, revealing novel DNA methylation signatures enriched in gene sets and pathways associated with the studied condition in each case. Our data-driven biomarker discovery workflow provides a generally applicable pipeline to capture relevant risk factor and disease information. By surpassing the limitations of knowledge-driven methods, our approach enhances the understanding of complex epigenetic processes, facilitating the development of more effective diagnostic and therapeutic strategies.

Introduction DNA methylation (DNAm) age clocks are powerful tools for measuring biological age, providing insights into aging risks and outcomes beyond chronological age. While traditional models are effective, their interpretability is limited by their dependence on small and potentially stochastic sets of CpG sites. Here, we propose that the reliability of DNAm age clocks should stem from their capacity to detect comprehensive and targeted aging signatures.Methods We compiled publicly available DNAm whole-blood samples (n = 17,726) comprising the entire human lifespan (0-112 years). We used a pre-trained network-coherent autoencoder (NCAE) to compress DNAm data into embeddings, with which we trained interpretable neural network epigenetic clocks. We then retrieved their age-specific epigenetic signatures of aging and examined their functional enrichments in age-associated biological processes.Results We introduce NCAE-CombClock, a novel highly precise (R2 = 0.978, mean absolute error = 1.96 years) deep neural network age clock integrating data-driven DNAm embeddings and established CpG age markers. Additionally, we developed a suite of interpretable NCAE-Age neural network classifiers tailored for adolescence and young adulthood. These clocks can accurately classify individuals at critical developmental ages in youth (AUROC = 0.953, 0.972, and 0.927, for 15, 18, and 21 years) and capture fine-grained, single-year DNAm signatures of aging that are enriched in biological processes associated with anatomic and neuronal development, immunoregulation, and metabolism. We showcased the practical applicability of this approach by identifying candidate mechanisms underlying the altered pace of aging observed in pediatric Crohn's disease.Discussion In this study, we present a deep neural network epigenetic clock, named NCAE-CombClock, that improves age prediction accuracy in large datasets, and a suite of explainable neural network clocks for robust age classification across youth. Our models offer broad applications in personalized medicine and aging research, providing a valuable resource for interpreting aging trajectories in health and disease.

Data-driven fault diagnosis requires training data that is representative of the different operating conditions of the system to capture its behavior. If training data is limited, one solution is to incorporate physical insights into machine learning models to improve their effectiveness. However, while previous works show the usefulness of hybrid approaches for isolation of faults, the impact of training data must be taken into consideration when drawing conclusions from data-driven residuals in a consistency-based diagnosis framework. By giving an understanding of the physical interaction between the signals, a hybrid fault diagnosis approach, can enforce model properties of residual generators to isolate faults that are not represented in training data. The objective of this work is to analyze the impact of limited training data when training neural network-based residual generators. It is also investigated how the use of structural information when selecting the network structure is a solution to limited training data and how to ameliorate the performance of hybrid approaches in face of this challenge.

Data-driven modeling and machine learning have received a lot of attention in fault diagnosis and system monitoring research. Since faults are rare events, conventional multi-class classification is complicated by incomplete training data and unknown faults. One solution is anomaly classification which can be used to detect abnormal behavior when only training data from the nominal operation is available. However, data-driven fault isolation is still a non-trivial task when training data is not representative of nominal and faulty behavior. In this work, the importance of redundancy for a set of known variables that are fed to a data-driven anomaly classification is discussed. It is shown that residual-based anomaly detection can be used to reject the nominal class which is not possible with one-class classifiers, such as one-class support vector machines. Based on these results, it is also discussed how data-driven residuals can be integrated with model-based fault isolation logic.

Effective fault diagnosis is crucial for improving the durability and reliability of automotive systems. Developing a diagnostic system with desirable fault isolability requires an accurate model and/or representative training data covering all possible faults. One promising approach involves using physics-based neural network residuals, known as grey-box models. These networks, designed to represent the system's nominal behavior and trained on fault-free data, are particularly advantageous when training data from faults are scarce. By incorporating causal relationships derived from physical insight, grey-box models retain the structural fault sensitivity of model-based residuals, enabling consistency-based diagnosis decision logic. However, despite their high accuracy in supervised learning benchmarks, neural networks often struggle with misclassification due to out of distribution data, a significant concern in diagnostic applications where false alarms are costly. This study highlights the importance of uncertainty quantification in neural network-based regression models and examines the interplay between different types of uncertainty in diagnostics. To address both epistemic and aleatoric uncertainties and achieve desirable fault isolation, the study applies adaptive thresholds and a measure for testing the validity of the residuals. Additionally, it proposes a consistency-based diagnosis framework using data-driven residuals, with its effectiveness demonstrated on an aftertreatment system of a heavy-duty truck under various drive cycles and fault scenarios.

Data-driven modeling and machine learning are widely used to model the behavior of dynamic systems. One application is the residual evaluation of technical systems where model predictions are compared with measurement data to create residuals for fault diagnosis applications. While recurrent neural network models have been shown capable of modeling complex non-linear dynamic systems, they are limited to fixed steps discrete-time simulation. Modeling using neural ordinary differential equations, however, make it possible to evaluate the state variables at specific times, compute gradients when training the model and use standard numerical solvers to explicitly model the underlying dynamic of the time-series data. Here, the effect of solver selection on the performance of neural ordinary differential equation residuals during training and evaluation is investigated. The paper includes a case study of a heavy-duty truck's after-treatment system to highlight the potential of these techniques for improving fault diagnosis performance.

BackgroundEmotion regulation difficulties have been identified as an underlying mechanism in the development and maintenance of psychopathology. The need to improve our understanding of emotion regulation difficulties to accurately assess and treat adolescents in child and adolescent psychiatric settings is essential.MethodIn the first part of the study, the psychometric qualities of the Difficulties in Emotion Regulation Scale, 16-item version (DERS-16) were examined in a clinical child and adolescent psychiatric (CAP) sample. In the second part, the DERS-16 was used to examine emotion regulation difficulties in the CAP sample (N = 281, 15-19-year-olds, 77.6% female) and in a community sample of adolescents (N = 3,169, 16-19-year-olds, 55.6% female). Subgroups were further explored in the CAP sample by two-step cluster analysis with log-likelihood distance measures.ResultsDERS-16 showed satisfactory psychometric qualities in the CAP sample. DERS-16 successfully distinguished adolescents in the clinical sample from adolescents in the community sample. Results showed significantly higher levels of self-reported emotion regulation difficulties in the CAP sample and in females. The two-step cluster analysis resulted in three clusters, named Minor, Moderate and Severe emotion regulation difficulties. Adolescents with the highest levels of emotion regulation difficulties had significantly more risk behaviors such as nonsuicidal self-injury and drug use, depression and anxiety, exposure to abuse, and higher levels of comorbidity.ConclusionsDERS-16 successfully distinguished clinical from community adolescents. The results illustrate the importance of identifying adolescents with high levels of emotion regulation difficulties in child and adolescent psychiatry due to higher levels of comorbidity and risk behaviors.

Difficulties with emotion regulation have been identified as an underlying mechanism in mental health. This pilot study aimed at examining whether group skills training in emotion regulation for adolescents and parents as an add-on intervention was feasible in an outpatient child and adolescent psychiatric clinic. We also investigated if the treatment increased knowledge and awareness of emotions and their functions, increased emotion regulation skills and decreased self-reported symptoms of anxiety and depression. Six skills training groups were piloted with a total of 20 adolescents and 21 adults. The treatment consisted of five sessions dealing with psychoeducation about emotions and emotion regulation skills training. Paired-samples t test was used to compare differences between before-and-after measures for adolescents and parents separately. The primary outcome measure, Difficulties in Emotion Regulation Scale, showed significant improvement after treatment for both adolescents and parents. For adolescents, measures of alexithymia were significantly reduced. Also, emotional awareness was significantly increased. Measures of depression and anxiety did not change. In conclusion, group skills training as an add-on treatment can be feasible and effective but further studies are needed.

BackgroundEmotion regulation difficulties underlie several psychiatric conditions, and treatments that focus on improving emotion regulation can have an effect on a broad range of symptoms. However, participants in-depth experiences of participating in emotion regulation treatments have not been much studied. In this qualitative study, we investigated participants experiences of a joint emotion regulation group skills training in a child and adolescent psychiatric outpatient setting.MethodsTwenty-one participants (10 adolescents and 11 parents) were interviewed about their experiences after they had participated in a seven-session transdiagnostic emotion regulation skills training for adolescents and parents. The aim of the skills training was to decrease emotion regulation difficulties, increase emotional awareness, reduce psychiatric symptoms, and enhance quality of life. The skills training consisted of psychoeducation about emotions and skills for regulating emotions. The interviews were transcribed and analysed using reflexive thematic analysis.ResultsThe analysis resulted in three overarching themes: Parent - Child processes, Individual processes, and Group processes. The result showed that participants considered an improved parent-child relationship to be the main outcome. Increased knowledge, emotion regulation skills and behavioural change were conceptualised as both mechanisms of change and outcomes. The group format, and the fact that parents and adolescents participated together, were seen as facilitators. Furthermore, the participants experienced targeting emotions in skills training as meaningful and helpful.ConclusionThe results highlight the potential benefits of providing emotion regulation skills training for adolescents and parents together in a group format to improve the parent-child relationship and enable the opportunity to learn skills.

Background: Host innate immune cells have been identified as key players in the early eradication of Mycobacterium tuberculosis and in the maintenance of an anti-mycobacterial immune memory, which we and others have shown are induced through epigenetic reprogramming. Studies on human tuberculosis immunity are dominated by those using peripheral blood as surrogate markers for immunity. We aimed to investigate DNA methylation patterns in immune cells of the lung compartment by obtaining induced sputum from M. tuberculosis- exposed subjects including symptom-free subjects testing positively and negatively for latent tuberculosis as well as patients diagnosed with active tuberculosis. Alveolar macrophages and alveolar T cells were isolated from the collected sputum and DNA methylome analyses performed (Illumina Infinium Human Methylation 450 k).Results: Multidimensional scaling analysis revealed that DNA methylomes of cells from the tuberculosis-exposed subjects and controls appeared as separate clusters. The numerous genes that were differentially methylated between the groups were functionally connected and overlapped with previous findings of trained immunity and tuberculosis. In addition, analysis of the interferon-gamma release assay (IGRA) status of the subjects demonstrated that the IGRA status was reflected in the DNA methylome by a unique signature.Conclusions: This pilot study suggests that M. tuberculosis induces epigenetic reprogramming in immune cells of the lung compartment, reflected as a specific DNA methylation pattern. The DNA methylation signature emerging from the comparison of IGRA-negative and IGRA-positive subjects revealed a spectrum of signature strength with the TB patients grouping together at one end of the spectrum, both in alveolar macrophages and T cells. DNA methylation-based biosignatures could be considered for further development towards a clinically useful tool for determining tuberculosis infection status and the level of tuberculosis exposure.

Background Tuberculosis (TB) is among the largest infectious causes of death worldwide, and there is a need for a time- and resource-effective diagnostic methods. In this novel and exploratory study, we show the potential of using buccal swabs to collect human DNA and investigate the DNA methylation (DNAm) signatures as a diagnostic tool for TB.Methods Buccal swabs were collected from patients with pulmonary TB (n = 7), TB-exposed persons (n = 7), and controls (n = 9) in Sweden. Using Illumina MethylationEPIC array, the DNAm status was determined.Results We identified 5644 significant differentially methylated CpG sites between the patients and controls. Performing the analysis on a validation cohort of samples collected in Kenya and Peru (patients, n = 26; exposed, n = 9; control, n = 10) confirmed the DNAm signature. We identified a TB consensus disease module, significantly enriched in TB-associated genes. Last, we used machine learning to identify a panel of 7 CpG sites discriminative for TB and developed a TB classifier. In the validation cohort, the classifier performed with an area under the curve of 0.94, sensitivity of 0.92, and specificity of 1.Conclusions In summary, the result from this study shows clinical implications of using DNAm signatures from buccal swabs to explore new diagnostic strategies for TB. In this work we show that individuals with tuberculosis display distinct DNA methylation patterns in the buccal mucosa compared to healthy controls and tuberculosis-exposed individuals, showing the potential of using this DNA methylation signature as a diagnostic tool. Graphical Abstract