Molecular diagnostics for sepsis is still a challenge due to the presence of compounds that interfere with gene amplification and bacteria at concentrations lower than the limit of detection (LOD). Here, we report on the development of a 3D printed modular microfluidic device (3Dpm mu FD) that preconcentrates bacteria of interest in whole blood and purifies their genomic DNA (gDNA). It is composed of a W-shaped microchannel and a conical microchamber. Bacteria of interest are magnetically captured from blood in the device with antibody conjugated magnetic nanoparticles (Ab-MNPs) at 5 mL/min in the W-shaped microchannel, while purified gDNA of the preconcentrated bacteria is obtained with magnetic silica beads (MSBs) at 2 mL/min in the conical microchamber. The conical microchamber was designed to be connected to the microchannel after the capturing process using a 3D-printed rotary valve to minimize the exposure of the MSBs to interfering compounds in blood. The pretreatment process of spiked blood (2.5 mL) can be effectively completed within about 50 min. With the 3Dpm mu FD, the LOD for the target microorganism Escherichia coli O157:H7 measured by both polymerase chain reaction (PCR) with electrophoresis and quantitative PCR was 10 colony forming unit (CFU) per mL of whole blood. The results suggest that our method lowers the LOD of molecular diagnostics for pathogens in blood by providing bacterial gDNA at high purity and concentration.
Procalcitonin (PCT) protein has recently been identified as a clinical marker for bacterial infections based on its better sepsis sensitivity. Thus, an increased level of PCT could be linked with disease diagnosis and therapeutics. In this study, we describe the construction of the photoelectrochemical (PEC) PCT immunosensing platform based on it situ grown photo-active CuWO4 nanospheres over reduced graphene oxide layers (CuWO4@rGO). The in situ growth strategy enabled the formation of small nanospheres (diameter of 200 nm), primarily composed of tiny self-assembled CuWO4 nanoparticles (2-5 nm). The synergic coupling of CuWO4 with rGO layers constructed an excellent photo-active heterojunction for photoelectrochemical (PEC) sensing. The platform was then considered for electrocatalytic (EC) mechanism-based detection of PCT, where inhibition of the photocatalytic oxidation signal of ascorbic acid (AA), subsequent to the antibody-antigen interaction, was recorded as the primary signal response. This inhibition detection approach enabled sensitive detection of PCT in a concentration range of 10 pgmL(-1) to 50 ng.mL(-1) with signal sensitivity achievable up to 0.15 pgmL(-1). The proposed PEC hybrid (CuWO4@rGO) could further be engineered to detect other clinically important species.
In this study honeycomb-like NiO nanostructures were grown on nickel foam by a simple hydrothermal growth method. The NiO nanostructures were characterized by field emission electron microscopy (FESEM), high resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) techniques. The characterized NiO nanostructures were uniform, dense and polycrystalline in the crystal phase. In addition to this, the NiO nanostructures were used in the development of a zinc ion sensor electrode by functionalization with the highly selective zinc ion ionophore 12-crown-4. The developed zinc ion sensor electrode has shown a good linear potentiometric response for a wide range of zinc ion concentrations, ranging from 0.001 mM to 100 mM, with sensitivity of 36 mV/decade. The detection limit of the present zinc ion sensor was found to be 0.0005 mM and it also displays a fast response time of less than 10 s. The proposed zinc ion sensor electrode has also shown good reproducibility, repeatability, storage stability and selectivity. The zinc ion sensor based on the functionalized NiO nanostructures was also used as indicator electrode in potentiometric titrations and it has demonstrated an acceptable stoichiometric relationship for the determination of zinc ion in unknown samples. The NiO nanostructures-based zinc ion sensor has potential for analysing zinc ion in various industrial, clinical and other real samples.
Ever since the discovery of the pH-sensing properties of ZnO crystals, researchers have been exploring their potential in electrochemical applications. The recent expansion and availability of chemical modification methods has made it possible to generate a new class of electrochemically active ZnO nanorods. This reduction in size of ZnO (to a nanocrystalline form) using new growth techniques is essentially an example of the nanotechnology fabrication principle. The availability of these ZnO nanorods opens up an entire new and exciting research direction in the field of electrochemical sensing. This review covers the latest advances and mechanism of pH-sensing using ZnO nanorods, with an emphasis on the nano-interface mechanism. We discuss methods for calculating the effect of surface states on pH-sensing at a ZnO/electrolyte interface. All of these current research topics aim to explain the mechanism of pH-sensing using a ZnO bulk- or nano-scale single crystal. An important goal of these investigations is the translation of these nanotechnology-modified nanorods into potential novel applications.
Recently ZnO has attracted much interest because of its usefulness for intracellular measurements of biochemical species by using its semiconducting, electrochemical, catalytic properties and for being biosafe and biocompatible. ZnO thus has a wide range of applications in optoelectronics, intracellular nanosensors, transducers, energy conversion and medical sciences. This review relates specifically to intracellular electrochemical (glucose and free metal ion) biosensors based on functionalized zinc oxide nanowires/nanorods. For intracellular measurements, the ZnO nanowires/nanorods were grown on the tip of a borosilicate glass capillary (0.7 mu m in diameter) and functionalized with membranes or enzymes to produce intracellular selective metal ion or glucose sensors. Successful intracellular measurements were carried out using ZnO nanowires/nanorods grown on small tips for glucose and free metal ions using two types of cells, human fat cells and frog oocytes. The sensors in this study were used to detect real-time changes of metal ions and glucose across human fat cells and frog cells using changes in the electrochemical potential at the interface of the intracellular micro-environment. Such devices are helpful in explaining various intracellular processes involving ions and glucose.
The production of a nanomaterial with enhanced and desirable electrocatalytic properties is of prime importance, and the commercialization of devices containing these materials is a challenging task. In this study, unique cupric oxide (CuO) nanostructures were synthesized using lysine as a soft template for the evolution of morphology via a rapid and boiled hydrothermal method. The morphology and structure of the synthesized CuO nanomaterial were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. The prepared CuO nanostructures showed high potential for use in the electrocatalytic oxidation of glucose in an alkaline medium. The proposed enzyme-free glucose sensor demonstrated a robust response to glucose with a wide linear range and high sensitivity, selectivity, stability, and reproducibility. To explore its practical feasibility, the glucose content of serum samples was successfully determined using the enzyme-free sensor. An analytical recovery method was used to measure the actual glucose from the serum samples, and the results were satisfactory. Moreover, the presented glucose sensor has high chemical stability and can be reused for repetitive measurements. This study introduces an enzyme-free glucose sensor as an alternative tool for clinical glucose quantification.
A potentiometric glucose biosensor based on immobilization of glucose oxidase (GOD) on ZnO nanorods (ZnO-NRs) has been developed for the indirect determination of environmental mercury ions. The ZnO-NRs were grown on a gold coated glass substrate by using the low temperature aqueous chemical growth (ACG) approach. Glucose oxidase in conjunction with a chitosan membrane and a glutaraldehyde (GA) were immobilized on the surface of the ZnO-NRs using a simple physical adsorption method and then used as a potentiometric working electrode. The potential response of the biosensor between the working electrode and an Ag/AgCl reference electrode was measured in a 1mM phosphate buffer solution (PBS). The detection limit of the mercury ion sensor was found to be 0.5 nM. The experimental results provide two linear ranges of the inhibition from 0.5 x 10(-6) mM to 0.5 x 10(-4) mM, and from 0.5 x 10(-4) mM to 20 mM of mercury ion for fixed 1 mM of glucose concentration in the solution. The linear range of the inhibition from 10(-3) mM to 6 mM of mercury ion was also acquired for a fixed 10 mM of glucose concentration. The working electrode can be reactivated by more than 70% after inhibition by simply dipping the used electrode in a 10 mM PBS solution for 7 min. The electrodes retained their original enzyme activity by about 90% for more than three weeks. The response to mercury ions was highly sensitive, selective, stable, reproducible, and interference resistant, and exhibits a fast response time. The developed glucose biosensor has a great potential for detection of mercury with several advantages such as being inexpensive, requiring minimum hardware and being suitable for unskilled users.
Although many chemical gas sensors report high sensitivity towards volatile organic compounds (VOCs), finding selective gas sensing technologies that can classify different VOCs is an ongoing and highly important challenge. By exploiting the synergy between virtual electronic noses and machine learning techniques, we demonstrate the possibility of efficiently discriminating, classifying, and quantifying short-chain oxygenated VOCs in the parts-per-billion concentration range. Several experimental results show a reproducible correlation between the predicted and measured values. A 10-fold cross-validated quadratic support vector machine classifier reports a validation accuracy of 91% for the different gases and concentrations studied. Additionally, a 10-fold cross-validated partial least square regression quantifier can predict their concentrations with coefficients of determination, R-2, up to 0.99. Our methodology and analysis provide an alternative approach to overcoming the issue of gas sensors selectivity, and have the potential to be applied across various areas of science and engineering where it is important to measure gases with high accuracy.
We describe a chemical sensor based on a simple synthesis of zinc oxide nanorods (ZNRs) for the detection of dopamine molecules by a potentiometric approach. The polar nature of dopamine leads to a change of surface charges on the ZNR surface via metal ligand bond formation which results in a measurable electrical signal. ZNRs were grown on a gold-coated glass substrate by a low temperature aqueous chemical growth (ACG) method. Polymeric membranes incorporating beta-cyclodextrin (beta-CD) and potassium tetrakis (4-chlorophenyl) borate was immobilized on the ZNR surface. The fabricated electrodes were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The grown ZNRs were well aligned and exhibited good crystal quality. The present sensor system displays a stable potential response for the detection of dopamine in 10(-2) mol.L-1 acetic acid/sodium acetate buffer solution at pH 5.45 within a wide concentration range of 1 x 10(-6) M-1 x 10(-1) M, with sensitivity of 49 mV/decade. The electrode shows a good response time (less than 10 s) and excellent repeatability. This finding can contribute to routine analysis in laboratories studying the neuropharmacology of catecholamines. Moreover, the metal-ligand bonds can be further exploited to detect DA receptors, and for bio-imaging applications.
In this paper, we show that the possibility of using polyethylene glycol (EG) as a hydrogen source and it is used to assist the hydrothermal synthesis of ZnO nanorods (ZNRs). EG doping in ZNRs has been found to significantly improve their optical and chemical sensing characteristics toward glutamate. The EG was found to have no role on the structural properties of the ZNRs. However, the x-ray photoelectron spectroscopy (XPS) suggests that the EG could induce donor impurities effect in ZnO. Photoluminescence (PL) and UV-Vis. spectra demonstrated this doping effect. Mott-Schottky analysis at the ZNRs/electrolyte interface was used to investigate the charge density for the doped ZNRs and showed comparable dependence on the used amount of EG. Moreover, the doped ZNRs were used in potentiometric measurements for glutamate for a range from 10(-6) M to 10(-3) M and the potential response of the sensor electrode was linear with a slope of 91.15 mV/decade. The wide range and high sensitivity of the modified ZNRs based glutamate biosensor is attributed to the doping effect on the ZNRs that is dictated by the EG along with the high surface area-to-volume ratio. The findings in the present study suggest new avenues to control the growth of n-ZnO nanostructures and enhance the performance of their sensing devices.
The increased utilization of the new types of cockpit communications, including controller pilot data link communications (CPDLC), puts the airplane at higher risk of hacking or interference than ever before. We review the technological characteristics and properties of the CPDLC and construct the corresponding threat model. Based on the limitations imposed by the system parameters, we propose several solutions for the improved security of the data messaging communication used in air traffic management (ATM). We discuss the applicability of elliptical curve cryptography (ECC), protected aircraft communications addressing and reporting systems (PACARs) and the Host Identity Protocol (HIP) as possible countermeasures to the identified security threats. In addition, we consider identity-defined networking (IDN) as an example of a genuine security solution which implies global changes in the whole air traffic communication system.
In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF) was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10−6 to 1 × 10−1 M) and excellent sensitivity of –62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10−7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples.
In the present work, NiCo2O4 nanostructures are fabricated in three dimensions (3D) on nickel foam by the hydrothermal method. The nanomaterial was characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The nanostructures exhibit nanoneedle-like morphology grown in 3D with good crystalline quality. The nanomaterial is composed of nickel, cobalt and oxygen atoms. By using the favorable porosity of the nanomaterial and the substrate itself, a sensitive glucose sensor is proposed by immobilizing glucose oxidase. The presented glucose sensor has shown linear response over a wide range of glucose concentrations from 0.005 mM to 15 mM with a sensitivity of 91.34 mV/decade and a fast response time of less than 10 s. The NiCo2O4 nanostructures-based glucose sensor has shown excellent reproducibility, repeatability and stability. The sensor showed negligible response to the normal concentrations of common interferents with glucose sensing, including uric acid, dopamine and ascorbic acid. All these favorable advantages of the fabricated glucose sensor suggest that it may have high potential for the determination of glucose in biological samples, food and other related areas.
Abstract: In this study, we have developed a sensitive and selective glucose sensor using novel CuO nanosheets which were grown on a gold coated glass substrate by a low temperature growth method. X-ray differaction (XRD) and scanning electron microscopy (SEM) techniques were used for the structural characterization of CuO nanostructures. CuO nanosheets are highly dense, uniform, and exhibited good crystalline array structure. X-ray photoelectron spectroscopy (XPS) technique was applied for the study of chemical composition of CuO nanosheets and the obtained information demonstrated pure phase CuO nanosheets. The novel CuO nanosheets were employed for the development of a sensitive and selective non-enzymatic glucose sensor. The measured sensitivity and a correlation coefficient are in order 5.20 × 102 µA/mMcm2 and 0.998, respectively. The proposed sensor is associated with several advantages such as low cost, simplicity, high stability, reproducibility and selectivity for the quick detection of glucose.
In this work, fabrication of gold coated glass substrate, growth of ZnO nanorods and potentiometric response of lactic acid are explained. The biosensor was developed by immobilizing the lactate oxidase on the ZnO nanorods in combination with glutaraldehyde as a cross linker for lactate oxidase enzyme. The potentiometric technique was applied for the measuring the output (EMF) response of L-lactic acid biosensor. We noticed that the present biosensor has wide linear detection range of concentration from 1 x 10(-4)-1 x 10(0) mM with acceptable sensitivity about 41.33 +/- 1.58 mV/decade. In addition, the proposed biosensor showed fast response time less than 10 s, a good selectivity towards L-lactic acid in presence of common interfering substances such as ascorbic acid, urea, glucose, galactose, magnesium ions and calcium ions. The present biosensor based on immobilized ZnO nanorods with lactate oxidase sustained its stability for more than three weeks.
The Constrained Application Protocol (CoAP) is a specialized web transfer protocol which is intended to be used for constrained networks and devices. CoAP and its extensions (e.g., CoAP observe and group communication) provide the potential for developing novel applications in the Internet-of-Things (IoT). However, a full-fledged CoAP-based application may require significant computing capability, power, and storage capacity in IoT devices. To address these challenges, we present the design, implementation, and experimentation with the CoAP handler which provides transparent CoAP services through the ICN core network. In addition, we demonstrate how the CoAP traffic over an ICN network can unleash the full potential of the CoAP, shifting both overhead and complexity from the (constrained) endpoints to the ICN network. The experiments prove that the CoAP Handler helps to decrease the required computation complexity, communication overhead, and state management of the CoAP server.
Advances in the miniaturization and portability of the chemical sensing devices have always been hindered by the external power supply problem, which has focused new interest in the fabrication of self-powered sensing devices for disease diagnosis and the monitoring of analytes. This review describes the fabrication of ZnO nanomaterial-based sensors synthesized on different conducting substrates for extracellular detection, and the use of a sharp borosilicate glass capillary (diameter, d = 700 nm) to grow ZnO nanostructures for intracellular detection purposes in individual human and frog cells. The electrocatalytic activity and fast electron transfer properties of the ZnO materials provide the necessary energy to operate as well as a quick sensing device output response, where the role of the nanomorphology utilized for the fabrication of the sensor is crucial for the production of the operational energy. Simplicity, design, cost, sensitivity, selectivity and a quick and stable response are the most important features of a reliable sensor for routine applications. The review details the extra- and intra-cellular applications of the biosensors for the detection and monitoring of different metallic ions present in biological matrices, along with the biomolecules glucose and cholesterol.
Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35–100 m2) and large (>100 m2) trees compared to small (<35 m2) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas.
A complementary metal-oxide-semiconductor (CMOS) chip biosensor was developed for cell viability monitoring based on an array of capacitance sensors utilizing a ring oscillator. The chip was packaged in a low temperature co-fired ceramic (LTCC) module with a flip chip bonding technique. A microcontroller operates the chip, while the whole measurement system was controlled by PC. The developed biosensor was applied for measurement of the proliferation stage of adherent cells where the sensor response depends on the ratio between healthy, viable and multiplying cells, which adhere onto the chip surface, and necrotic or apoptotic cells, which detach from the chip surface. This change in cellular adhesion caused a change in the effective permittivity in the vicinity of the sensor element, which was sensed as a change in oscillation frequency of the ring oscillator. The sensor was tested with human lung epithelial cells (BEAS-2B) during cell addition, proliferation and migration, and finally detachment induced by trypsin protease treatment. The difference in sensor response with and without cells was measured as a frequency shift in the scale of 1.1 MHz from the base frequency of 57.2 MHz. Moreover, the number of cells in the sensor vicinity was directly proportional to the frequency shift.
A device for measuring biological small volume liquid samples in real time is appealing. One way to achieve this is by using a microwave sensor based on reflection measurement. A prototype sensor was manufactured from low cost printed circuit board (PCB) combined with a microfluidic channel made of polymethylsiloxane (PDMS). Such a sensor was simulated, manufactured, and tested including a vacuum powered sample delivery system with robust fluidic ports. The sensor had a broad frequency band from 150 kHz to 6 GHz with three resonance frequencies applied in sensing. As a proof of concept, the sensor was able to detect a NaCl content of 125 to 155 mmol in water, which is the typical concentration in healthy human blood plasma.
Graphene in its pristine form has demonstrated a gas detection ability in an inert carrier gas. For practical use in ambient atmosphere, its sensor properties should be enhanced with functionalisation by defects and dopants, or by decoration with nanophases of metals or/and metal oxides. Excellent sensor behaviour was found for two types of single layer graphenes: grown by chemical vapour deposition (CVD) and transferred onto oxidized silicon (Si/SiO2/CVDG), and the epitaxial graphene grown on SiC (SiC/EG). Both graphene samples were functionalised using a pulsed laser deposited (PLD) thin V2O5 layer of average thickness approximate to 0.6 nm. According to the Raman spectra, the SiC/EG has a remarkable resistance against structural damage under the laser deposition conditions. By contrast, the PLD process readily induces defects in CVD graphene. Both sensors showed remarkable and selective sensing of NH3 gas in terms of response amplitude and speed, as well as recovery rate. SiC/EG showed a response that was an order of magnitude larger as compared to similarly functionalised CVDG sensor (295% vs. 31% for 100 ppm NH3). The adsorption site properties are assigned to deposited V2O5 nanophase, being similar for both sensors, rather than (defect) graphene itself. The substantially larger response of SiC/EG sensor is probably the result of the smaller initial free charge carrier doping in EG.
Plant Factory is a newly emerging industry aiming at transforming crop production to an unprecedented model by leveraging industrial automation and informatics. However, todays plant factory and vertical farming industry are still in a primitive phase, and existing industrial cyber-physical systems are not optimal for a plant factory due to diverse application requirements on communication, computing and artificial intelligence. In this paper, we review use cases and requirements for future plant factories, and then dedicate an architecture that incorporates the communication and computing domains to plant factories with a preliminary proof-of-concept, which has been validated by both academic and industrial practices. We also call for a holistic co-design methodology that crosses the boundaries of communication, computing and artificial intelligence disciplines to guarantee the completeness of solution design and to speed up engineering implementation of plant factories and other industries sharing the same demands.
Researches on the Internet of Things (IoT) and cloud computing have been pervasive in both the academic and industrial world. IoT and cloud computing are seen as cornerstones to digital transformation in the industry. However, restricted by limited resources and the lack of expertise in information and communication technologies, small- and medium-sized enterprises (SMEs) have difficulty in achieving digitalization of their business. In this paper, we propose a reference framework for SMEs to follow as a guideline in the journey of digital transformation. The framework features a three-stage procedure that covers business, technology, and innovation, which can be iterated to drive product and business development. A case study about digital transformation taking place in the vertical plant wall industry is detailed. Furthermore, some solution design principles that are concluded from real industrial practice are presented. This paper reviews the digital transformation practice in the vertical plant wall industry and aims to accelerate the pace of SMEs in the journey of digital transformation.
Active research in nanostructured materials aims to explore new paths for improving electronic device characteristics. In the field of gas sensors, those based on metal oxide single nanowires exhibit excellent sensitivity and can operate at extremely low power consumption, making them a highly promising candidate for a novel generation of portable devices. The mix of two different metal oxides on the same nanowire can further broaden the response of this kind of gas sensor, thus widening the range of detectable gases, without compromising the properties related to the active region miniaturization. In this paper, a first study on the synthesis, characterization and gas sensing performance of (GaxIn1-x)(2)O-3 nanowires (NWs) is reported. Carbothermal metal-assisted chemical vapor deposition was carried out with different mixtures of Ga2O3, In2O3 and graphite powders. Structural characterization of the NWs revealed that they have a crystalline structure close to that of In2O3 nanowires, with a small amount of Ga incorporation, which highly depends on the mass ratio between the two precursors. Dedicated gas nanosensors based on single NWs were fabricated and tested for both ethanol and nitrogen dioxide, demonstrating an improved performance compared to similar devices based on pure In2O3 or Ga2O3 NWs.
5,10,15,20-Tetraferrocenyl porphyrin, H2TFcP, a simple example of a donor-acceptor system, was tested as ligand for the development of a novel multi-transduction chemical sensors aimed at the determination of transition metal ions. The fluorescence energy transfer between ferrocene donor and porphyrin acceptor sub-units was considered. The simultaneously measured optical and potentiometric responses of solvent polymeric membranes based on H2TFcP permitted the detection of lead ions in sample solutions, in the concentration range from 2.7 × 10−7 to 3.0 × 10−3 M. The detection limit of lead determination was 0.27 μM, low enough to perform the direct analysis of Pb2+ in natural waters.
Accelerometers accuracy for sedentary time (ST) and moderate-to-vigorous physical activity (MVPA) classification depends on accelerometer placement, data processing, activities, and sample characteristics. As intensities differ by age, this study sought to determine intensity cut-points at various wear locations people more than 70 years old. Data from 59 older adults were used for calibration and from 21 independent participants for cross-validation purposes. Participants wore accelerometers on their hip and wrists while performing activities and having their energy expenditure measured with portable calorimetry. ST and MVPA were defined as <= 1.5 metabolic equivalents (METs) and >= 3 METs (1 MET = 2.8 mL/kg/min), respectively. Receiver operator characteristic (ROC) analyses showed fair-to-good accuracy (area under the curve [AUC] = 0.62-0.89). ST cut-points were 7 mg (cross-validation: sensitivity = 0.88, specificity = 0.80) and 1 count/5 s (cross-validation: sensitivity = 0.91, specificity = 0.96) for the hip; 18 mg (cross-validation: sensitivity = 0.86, specificity = 0.86) and 102 counts/5 s (cross-validation: sensitivity = 0.91, specificity = 0.92) for the non-dominant wrist; and 22 mg and 175 counts/5 s (not cross-validated) for the dominant wrist. MVPA cut-points were 14 mg (cross-validation: sensitivity = 0.70, specificity = 0.99) and 54 count/5 s (cross-validation: sensitivity = 1.00, specificity = 0.96) for the hip; 60 mg (cross-validation: sensitivity = 0.83, specificity = 0.99) and 182 counts/5 s (cross-validation: sensitivity = 1.00, specificity = 0.89) for the non-dominant wrist; and 64 mg and 268 counts/5 s (not cross-validated) for the dominant wrist. These cut-points can classify ST and MVPA in older adults from hip- and wrist-worn accelerometers.
Monitoring the indoor environment of historic buildings helps to identify potential risks, provide guidelines for improving regular maintenance, and preserve cultural artifacts. However, most of the existing monitoring systems proposed for historic buildings are not for general digitization purposes that provide data for smart services employing, e.g., artificial intelligence with machine learning. In addition, considering that preserving historic buildings is a long-term process that demands preventive maintenance, a monitoring system requires stable and scalable storage and computing resources. In this paper, a digitalization framework is proposed for smart preservation of historic buildings. A sensing system following the architecture of this framework is implemented by integrating various advanced digitalization techniques, such as Internet of Things, Edge computing, and Cloud computing. The sensing system realizes remote data collection, enables viewing real-time and historical data, and provides the capability for performing real-time analysis to achieve preventive maintenance of historic buildings in future research. Field testing results show that the implemented sensing system has a 2% end-to-end loss rate for collecting data samples and the loss rate can be decreased to 0.3%. The low loss rate indicates that the proposed sensing system has high stability and meets the requirements for long-term monitoring of historic buildings.
It is important to assess gait function in neurological disorders. A common outcome measure from clinical walking tests is average speed, which is reliable but does not capture important kinematical and temporal aspects of gait function. An extended gait analysis must be time efficient and reliable to be included in the clinical routine. The aim of this study was to add an inertial sensor system to a gait test battery and analyze the test-retest reliability of kinematic and temporal outcome measures. Measurements and analyses were performed in the hospital environment by physiotherapists using customized software. In total, 22 healthy persons performed comfortable gait, fast gait, and stair walking, with 12 inertial sensors attached to the feet, shank, thigh, pelvis, thorax, and arms. Each person participated in 2 test sessions, with about 3-6 days between the sessions. Kinematics were calculated based on a sensor fusion algorithm. Sagittal peak angles, sagittal range of motion, and stride frequency were derived. Intraclass-correlation coefficients were determined to analyze the test-retest reliability, which was good to excellent for comfortable and fast gait, with exceptions for hip, knee, and ankle peak angles during fast gait, which showed moderate reliability, and fast gait stride frequency, which showed poor reliability. In stair walking, all outcome measures except shoulder extension showed good to excellent reliability. Inertial sensors have the potential to improve the clinical evaluation of gait function in neurological patients, but this must be verified in patient groups.
Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.
The evaluation of disposable lab-on-a-chip (LOC) devices on cell phones is an attractive alternative to migrate the analytical strength of LOC solutions to decentralized sensing applications. Imaging the micrometric detection areas of LOCs in contact with intact phone cameras is central to provide such capability. This work demonstrates a disposable and morphing liquid lens concept that can be integrated in LOC devices and refocuses micrometric features in the range necessary for LOC evaluation using diverse cell phone cameras. During natural evaporation, the lens focus varies adapting to different type of cameras. Standard software in the phone commands a time-lapse acquisition for best focal selection that is sufficient to capture and resolve, under ambient illumination, 50 mu m features in regions larger than 500 x 500 mu m(2). In this way, the present concept introduces a generic solution compatible with the use of diverse and unmodified cell phone cameras to evaluate disposable LOC devices.
This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.
Gases, such as nitrogen dioxide, formaldehyde and benzene, are toxic even at very low concentrations. However, so far there are no low-cost sensors available with sufficiently low detection limits and desired response times, which are able to detect them in the ranges relevant for air quality control. In this work, we address both, detection of small gas amounts and fast response times, using epitaxially grown graphene decorated with iron oxide nanoparticles. This hybrid surface is used as a sensing layer to detect formaldehyde and benzene at concentrations of relevance (low parts per billion). The performance enhancement was additionally validated using density functional theory calculations to see the effect of decoration on binding energies between the gas molecules and the sensor surface. Moreover, the time constants can be drastically reduced using a derivative sensor signal readout, allowing the sensor to work at detection limits and sampling rates desired for air quality monitoring applications.
In this work, we investigated the sensing performance of epitaxial graphene on Si-face 4H-SiC (EG/SiC) for liquid-phase detection of heavy metals (e.g., Pb and Cd), showing fast and stable response and low detection limit. The sensing platform proposed includes 3D-printed microfluidic devices, which incorporate all features required to connect and execute lab-on-chip (LOC) functions. The obtained results indicate that EG exhibits excellent sensing activity towards Pb and Cd ions. Several concentrations of Pb2+ solutions, ranging from 125 nM to 500 mu M, were analyzed showing Langmuir correlation between signal and Pb2+ concentrations, good stability, and reproducibility over time. Upon the simultaneous presence of both metals, sensor response is dominated by Pb2+ rather than Cd2+ ions. To explain the sensing mechanisms and difference in adsorption behavior of Pb2+ and Cd2+ ions on EG in water-based solutions, we performed van-der-Waals (vdW)-corrected density functional theory (DFT) calculations and non-covalent interaction (NCI) analysis, extended charge decomposition analysis (ECDA), and topological analysis. We demonstrated that Pb2+ and Cd2+ ions act as electron-acceptors, enhancing hole conductivity of EG, due to charge transfer from graphene to metal ions, and Pb2+ ions have preferential ability to binding with graphene over cadmium. Electrochemical measurements confirmed the conductometric results, which additionally indicate that EG is more sensitive to lead than to cadmium.
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct "beyond graphene" domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials.
The optical properties of graphene nanodots (GND) and their interaction with phosphate ions have been investigated to explore their potential for optical sensing applications. The absorption spectra of pristine GND and modified GND systems were analyzed using time-dependent density functional theory (TD-DFT) calculation investigations. The results revealed that the size of adsorbed phosphate ions on GND surfaces correlated with the energy gap of the GND systems, leading to significant modifications in their absorption spectra. The introduction of vacancies and metal dopants in GND systems resulted in variations in the absorption bands and shifts in their wavelengths. Moreover, the absorption spectra of GND systems were further altered upon the adsorption of phosphate ions. These findings provide valuable insights into the optical behavior of GND and highlight their potential for the development of sensitive and selective optical sensors for phosphate detection.
This paper presents a novel multi-sensor framework to efficiently identify, track, localise and map every piece of fruit in a commercial mango orchard. A multiple viewpoint approach is used to solve the problem of occlusion, thus avoiding the need for labour-intensive field calibration to estimate actual yield. Fruit are detected in images using a state-of-the-art faster R-CNN detector, and pair-wise correspondences are established between images using trajectory data provided by a navigation system. A novel LiDAR component automatically generates image masks for each canopy, allowing each fruit to be associated with the corresponding tree. The tracked fruit are triangulated to locate them in 3D, enabling a number of spatial statistics per tree, row or orchard block. A total of 522 trees and 71,609 mangoes were scanned on a Calypso mango orchard near Bundaberg, Queensland, Australia, with 16 trees counted by hand for validation, both on the tree and after harvest. The results show that single, dual and multi-view methods can all provide precise yield estimates, but only the proposed multi-view approach can do so without calibration, with an error rate of only 1.36% for individual trees.
Low-dimensional InN/InGaN quantum dots (QDs) are demonstrated for realizing highly sensitive and efficient potentiometric biosensors owing to their unique electronic properties. The InN QDs are biochemically functionalized. The fabricated biosensor exhibits high sensitivity of 97 mV/decade with fast output response within two seconds for the detection of cholesterol in the logarithmic concentration range of 1 x 10(-6) M to 1 x 10(-3) M. The selectivity and reusability of the biosensor are excellent and it shows negligible response to common interferents such as uric acid and ascorbic acid. We also compare the biosensing properties of the InN QDs with those of an InN thin film having the same surface properties, i.e., high density of surface donor states, but different morphology and electronic properties. The sensitivity of the InN QDs-based biosensor is twice that of the InN thin film-based biosensor, the EMF is three times larger, and the response time is five times shorter. A bare InGaN layer does not produce a stable response. Hence, the superior biosensing properties of the InN QDs are governed by their unique surface properties together with the zero-dimensional electronic properties. Altogether, the InN QDs-based biosensor reveals great potential for clinical diagnosis applications.
This paper presents a prototype wireless remote glucose monitoring system interfaced with a ZnO nanowire arrays-based glucose sensor, glucose oxidase enzyme immobilized onto ZnO nanowires in conjunction with a Nafion (R) membrane coating, which can be effectively applied for the monitoring of glucose levels in diabetics. Global System for Mobile Communications (GSM) services like General Packet Radio Service (GPRS) and Short Message Service (SMS) have been proven to be logical and cost effective methods for gathering data from remote locations. A communication protocol that facilitates remote data collection using SMS has been utilized for monitoring a patients sugar levels. In this study, we demonstrate the remote monitoring of the glucose levels with existing GPRS/GSM network infra-structures using our proposed functionalized ZnO nanowire arrays sensors integrated with standard readily available mobile phones. The data can be used for centralized monitoring and other purposes. Such applications can reduce health care costs and allow caregivers to monitor and support to their patients remotely, especially those located in rural areas.
In the present work zinc oxide nanoflakes (ZnO-NF) structures with a wall thickness around 50 to 100 nm were synthesized on a gold coated glass substrate using a low temperature hydrothermal method. The enzyme uricase was electrostatically immobilized in conjunction with Nafion membrane on the surface of well oriented ZnO-NFs, resulting in a sensitive, selective, stable and reproducible uric acid sensor. The electrochemical response of the ZnO-NF-based sensor vs. a Ag/AgCl reference electrode was found to be linear over a relatively wide logarithmic concentration range (500 nM to 1.5 mM). In addition, the ZnO-NF structures demonstrate vast surface area that allow high enzyme loading which results provided a higher sensitivity. The proposed ZnO-NF array-based sensor exhibited a high sensitivity of similar to 66 mV/ decade in test electrolyte solutions of uric acid, with fast response time. The sensor response was unaffected by normal concentrations of common interferents such as ascorbic acid, glucose, and urea.
The concept of recognition and biofunctionality has attracted increasing interest in the fields of chemistry and material sciences. Advances in the field of nanotechnology for the synthesis of desired metal oxide nanostructures have provided a solid platform for the integration of nanoelectronic devices. These nanoelectronics-based devices have the ability to recognize molecular species of living organisms, and they have created the possibility for advanced chemical sensing functionalities with low limits of detection in the nanomolar range. In this review, various metal oxides, such as ZnO-, CuO-, and NiO-based nanosensors, are described using different methods (receptors) of functionalization for molecular and ion recognition. These functionalized metal oxide surfaces with a specific receptor involve either a complex formation between the receptor and the analyte or an electrostatic interaction during the chemical sensing of analytes. Metal oxide nanostructures are considered revolutionary nanomaterials that have a specific surface for the immobilization of biomolecules with much needed orientation, good conformation and enhanced biological activity which further improve the sensing properties of nanosensors. Metal oxide nanostructures are associated with certain unique optical, electrical and molecular characteristics in addition to unique functionalities and surface charge features which shows attractive platforms for interfacing biorecognition elements with effective transducing properties for signal amplification. There is a great opportunity in the near future for metal oxide nanostructure-based miniaturization and the development of engineering sensor devices.
Producing molecular imprinting-based materials has received increasing attention due to recognition selectivity, stability, cast effectiveness, and ease of production in various forms for a wide range of applications. The molecular imprinting technique has a variety of applications in the areas of the food industry, environmental monitoring, and medicine for diverse purposes like sample pretreatment, sensing, and separation/purification. A versatile usage, stability and recognition capabilities also make them perfect candidates for use in forensic sciences. Forensic science is a demanding area and there is a growing interest in molecularly imprinted polymers (MIPs) in this field. In this review, recent molecular imprinting applications in the related areas of forensic sciences are discussed while considering the literature of last two decades. Not only direct forensic applications but also studies of possible forensic value were taken into account like illicit drugs, banned sport drugs, effective toxins and chemical warfare agents in a review of over 100 articles. The literature was classified according to targets, material shapes, production strategies, detection method, and instrumentation. We aimed to summarize the current applications of MIPs in forensic science and put forth a projection of their potential uses as promising alternatives for benchmark competitors.