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Background: Motion Tape (MT) is a low-profile, disposable, self-adhesive wearable sensor that measures skin strain. Preliminary studies have validated MT for measuring lower back movement. However, further analysis is needed to determine if MT can be used to measure lower back muscle engagement. The purpose of this study was to measure differences in MT strain between conditions in which the lower back muscles were relaxed versus maximally activated. Methods: Ten participants without low back pain were tested. A matrix of six MTs was placed on the lower back, and strain data were captured under a series of conditions. The first condition was a baseline trial, in which participants lay prone and the muscles of the lower back were relaxed. The subsequent trials were maximum voluntary isometric contractions (MVICs), in which participants did not move, but resisted the examiner force in extension or rotational directions to maximally engage their lower back muscles. The mean MT strain was calculated for each condition. A repeated measures ANOVA was conducted to analyze the effects of conditions (baseline, extension, right rotation, and left rotation) and MT position (1–6) on the MT strain. Post hoc analyses were conducted for significant effects from the overall analysis. Results: The results of the ANOVA revealed a significant main effect of condition (p < 0.001) and a significant interaction effect of sensor and condition (p = 0.01). There were significant differences in MT strain between the baseline condition and the extension and rotation MVIC conditions, respectively, for sensors 4, 5, and 6 (p = 0.01–0.04). The largest differences in MT strain were observed between baseline and rotation conditions for sensors 4, 5, and 6. Conclusions: MT can capture maximal lower back muscle engagement while the trunk remains in a stationary position. Lower sensors are better able to capture muscle engagement than upper sensors. Furthermore, MT captured muscle engagement during rotation conditions better than during extension. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) semiconductor components have excellent physical attributes, such as excellent mechanical ductility, high mobility, low dielectric constant, and tunable bandgap, which have attracted much attention to the fields of flexible devices, optoelectronic conversion, and microelectronic devices. Additionally, one-dimensional (1D) semiconductor materials with unique physical attributes, such as high surface area and mechanical potency, show great potential in many applications. However, isolated 1D and 2D materials often do not meet the demand for multifunctionality. Therefore, more functionality is achieved by reconstructing new composite structures from 1D and 2D materials, and according to the current study, it has been demonstrated that hybrid dimensional integration yields a significant enhancement in performance and functionality, which is widely promising in the field of constructing novel electronic and optoelectronic nanodevices. In this review, we first briefly introduce the preparation methods of 1D materials, 2D materials, and 1D/2D heterostructures, as well as their advantages and limitations. The applications of 1D/2D heterostructures in photodetectors, gas sensors, pressure and strain sensors, as well as photoelectrical synapses and biosensors are then discussed, along with the opportunities and challenges of their current applications. Finally, the outlook of the emerging field of 1D/2D heterojunction structures is given. [ABSTRACT FROM AUTHOR]

This study investigates the development of electrically conductive panels for application as emergency detection sensors in smart house systems. These panels, composed of wood chips coated with polymeric methylene diphenyl isocyanate, were modified with carbon black and carbon fibers to enable detection of moisture, temperature, and pressure variations. Manufactured via hot pressing, the panels retained standard mechanical properties and exhibited stable performance under diverse environmental conditions. Carbon black-filled panels achieved electrical percolation at a lower filler concentration (5%) compared to carbon fiber-filled panels. The incorporation of carbon black reduced the electrical resistivity to 8.6 ohm·cm, while the addition of carbon fibers further decreased it to 7.7 ohm·cm. In terms of sensor capabilities, panels containing carbon fibers demonstrated superior sensitivity to moisture and pressure changes. However, carbon black was ineffective for temperature sensing. Among the carbon fiber-filled panels, those with 20 wt.% concentration exhibited the best performance for moisture and pressure detection, whereas panels with 40 wt.% carbon fiber content displayed the most reliable and consistent temperature-sensing properties. [ABSTRACT FROM AUTHOR]

Nonlinear acoustic signals, specifically the parametric effect, offer significant advantages over linear signals because the low frequencies generated in the medium due to the intermodulation of the emitted frequencies are highly directional and can propagate over long distances. Due to these characteristics, a detailed analysis of these signals is necessary to accurately estimate the Time of Arrival (ToA) and amplitude parameters. This is crucial for various communication applications, such as sonar and underwater location systems. The research addresses a notable gap in the literature regarding comparative methods for analyzing nonlinear acoustic signals, particularly focusing on ToA estimation and amplitude parameterization. Two types of nonlinear modulations are examined: parametric Frequency-Shift Keying (FSK) and parametric sine-sweep modulation, which correspond to narrowband and broadband signals, respectively. The first study evaluates three ToA estimation methods—threshold, power variation (Pvar), and cross-correlation methods for the modulations in question. Following ToA estimation, the amplitude of the received signals is analyzed using acoustic signal processing techniques such as time-domain, frequency-domain, and cross-correlation methods. The practical application is validated through controlled laboratory experiments, which confirm the robustness and effectiveness of the existing methods proposed under study for nonlinear (parametric) acoustic signals. [ABSTRACT FROM AUTHOR]

The exponential demand for real-time monitoring applications has altered the course of sensor development, from sensor electronics miniaturization, e.g., resorting to printing techniques, to low-cost, flexible and functional wearable materials. Humidity sensing has been used in the prevention and diagnosis of medical conditions, as well as in the assessment of physical comfort. This paper presents a resistive flexible humidity sensor composed of silver interdigitated electrodes (IDTs) screen printed onto polyimide film and an active layer of multiwall carbon nanotubes (MWCNT) dispersed in a water-soluble polymer, polyvinyl alcohol (PVA). Different MWCNT/PVA sensor sizes and MWCNT percentages are tested to study their effect on the initial electrical resistance (Ri) values and sensor response at different humidity percentages. The results show that the Ri values decrease with the increase in % MWCNT. The sensor size did not influence the sensor response, while the % MWCNT affected the sensor behavior upon relative humidity (RH) increments. The 1% MWCNT/PVA sensor showed the best response, reaching a relative electrical resistance, ΔR/R0, of 509% at 99% RH. Comparable with other reported sensors, the produced MWCNT/PVA flexible sensor is simpler, greener and shows a good sensitivity to humidity, being easily incorporated in wearable monitoring applications, from sports to medical fields. [ABSTRACT FROM AUTHOR]

The ability and rapid access to execution data and information in manufacturing workshops have been greatly improved with the wide spread of the Internet of Things and artificial intelligence technologies, enabling real-time unmanned integrated control of facilities and production. However, the widespread issue of data quality in the field raises concerns among users about the robustness of automatic decision-making models before their application. This paper addresses three main challenges relative to field data quality issues during automated real-time decision-making: parameter identification under measurement uncertainty, sensor accuracy selection, and sensor fault-tolerant control. To address these problems, this paper proposes a risk assessment framework in the case of continuous production workshops. The framework aims to determine a method for systematically assessing data quality issues in specific scenarios. It specifies the preparation requirements, as well as assumptions such as the preparation of datasets on typical working conditions, and the risk assessment model. Within the framework, the data quality issues in real-time decision-making are transformed into data deviation problems. By employing the Monte Carlo simulation method to measure the impact of these issues on the decision risk, a direct link between sensor quality and risks is established. This framework defines specific steps to address the three challenges. A case study in the steel industry confirms the effectiveness of the framework. This proposed method offers a new approach to assessing safety and reducing the risk of real-time unmanned automatic decision-making in industrial settings. [ABSTRACT FROM AUTHOR]

Acetone detection is of significant importance in various industries, from cosmetics to pharmaceuticals, bioengineering, and paints. Sensor manufacturing involves the use of different semiconductor materials as well as different metals for doping and functionalization, allowing them to achieve advanced or unique properties in different sensor applications. In the healthcare field, these sensors play a crucial role in the non-invasive diagnosis of various diseases, offering a potential way to monitor metabolic conditions by analyzing respiration. This article presents the synthesis method, using chemical solutions and rapid thermal annealing technology, to obtain Al-functionalized and Ni-doped copper oxide (Al/CuO:Ni) nanostructured thin films for biosensors. The nanocrystalline thin films are subjected to a thorough characterization, with examination of the morphological properties by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD) analysis. The results reveal notable changes in the surface morphology and structure following different treatments, providing insight into the mechanism of function and selectivity of these nanostructures for gases and volatile compounds. The study highlights the high selectivity of developed Al/CuO:Ni nanostructures towards acetone vapors at different concentrations from 1 ppm to 1000 ppm. Gas sensitivity is evaluated over a range of operating temperatures, indicating optimum performance at 300 °C and 350 °C with the maximum sensor signal (S) response obtained being 45% and 50%, respectively, to 50 ppm gas concentration. This work shows the high potential of developed technology for obtaining Al/CuO:Ni nanostructured thin films as next-generation materials for improving the sensitivity and selectivity of acetone sensors for practical applications as breath detectors in biomedical diagnostics, in particular for diabetes monitoring. It also emphasizes the importance of these sensors in ensuring industrial safety by preventing adverse health and environmental effects of exposure to acetone. [ABSTRACT FROM AUTHOR]

This review reports on the use of sensors in wheelchair sports to monitor and analyze performance during match and training time. With rapid advancements in electronics and related technologies, understanding performance metrics in wheelchair sports is essential. We reviewed nine studies using various sensor types, including electric motors, inertial measurement units, miniaturized data loggers with magnetic reed switches, and smartphones with inbuilt accelerometers and gyroscopes, operating at frequencies from 8 Hz to 1200 Hz. These studies measured parameters such as angular and translational velocities, distance, number of starts/pushes, and other performance indicators in sports such as basketball, rugby, tennis, and racing. Despite differences in sport types and methodologies, most studies found sensor-derived data effective for assessment of performance. Future developments and research in this field should focus on multi-sensor systems that could provide real-time match analysis and deeper insights into performance metrics. Overall, sensor technologies show significant potential for improving wheelchair sport performance diagnostics, contributing to better athlete training and future wheelchair design, and enhancing competitive outcomes. This review emphasizes the need for continued innovation and standardization in applying sensor technologies in wheelchair sports. [ABSTRACT FROM AUTHOR]

In this paper, a kind of metastructure–photonic crystal (MPC) with multi-frequency asymmetric absorption–transmission properties is proposed. It is composed of various dielectric layers arranged in a periodically tilting pattern. When electromagnetic waves (EMWs) enter from the opposite direction, MPC shows an obvious asymmetry. EMWs are absorbed at 13.71 GHz, 14.37 GHz, and 17.10 GHz in forward incidence, with maximum absorptions of 0.919, 0.917, and 0.956, respectively. In the case of backward incidence, transmission above 0.877 is achieved. Additionally, the MPC is utilized for refractive index (RI) sensing, allowing for wide RI range detection. The refractive index unit is denoted as RIU. The RI detection range is 1.4~3.0, with the corresponding absorption peak variation range being 17.054~17.194 GHz, and a sensitivity of 86 MHz/RIU. By adjusting the number of MPC cycles and tilt angle, the sensing performance and operating frequency band can be tailored to meet various operational requirements. This MPC-based RI sensor is simple to fabricate and has the potential to be used in the development of high-performance and compact sensing devices. [ABSTRACT FROM AUTHOR]

The work is devoted to the consideration of methods for determining the strain of objects using fiber Bragg gratings under a high-frequency vibration or pulsed mechanical action, which is difficult to perform using widespread methods and devices. The methods are based on numerical processing of the time dependence of the radiation power reflected from the fiber Bragg grating at various wavelengths, which makes it possible to measure strain parameters in a wide range of magnitude and frequencies. The efficiency of the proposed methods is demonstrated by numerical simulation. It is shown that it is possible to restore the strain dependence on time in the range ± 1000   μ ϵ or more from simultaneously measured power dependencies reflected by the fiber Bragg grating using common fiber-optic components. The case of sequential registration of reflected radiation power at different wavelengths to determine the probability density of the distribution of the strain values is also considered. The results of signal processing obtained both by numerical simulation and experimentally for the case of a linear vibration are presented. The technical problems of using the proposed methods are discussed. [ABSTRACT FROM AUTHOR]

Shape memory alloys (SMAs) are becoming a more important factor in actuation technology. Due to their unique features, they have the potential to save weight and installation space as well as reduce energy consumption. The system integration of the generally small-diameter NiTi wires is an important cornerstone for the emerging technology. Crimping, a common method for the mechanical and electrical connection of SMA wires, has several drawbacks when it comes to miniaturization and high-force outputs. For high-force applications, for example, multiple SMA wires in parallel are needed to keep actuation frequencies high while scaling up the actuation force. To meet these challenges, the proposed study deals with the development of a resistance-welding process for manufacturing NiTi wire bundles. The wires are welded to a sheet metal substrate, resulting in promising functional properties and high joint strengths. The welding process benefits from low costs, easy-to-control parameters and good automation potential. A method for evaluating the resistance-welding process parameters is presented. With these parameters in place, a manufacturing process for bundled wire actuators is discussed and implemented. The welded joints are examined by peel tests, microscopy and fatigue experiments. The performance of the manufactured bundle actuators is demonstrated by comparison to a single wire with the same accumulated cross-sectional area. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are equipped with various sensors to facilitate control and navigation. However, UAV sensors are highly susceptible to damage under complex flight environments, leading to severe accidents and economic losses. Although fault diagnosis methods based on deep neural networks have been widely applied in the mechanical field, these methods often fail to integrate multi-source information and overlook the importance of system prior knowledge. As a result, this study employs a spatial-temporal difference graph convolutional network (STDGCN) for the fault diagnosis of UAV sensors, where the graph structure naturally organizes the diverse sensors. Specifically, a difference layer enhances the feature extraction capability of the graph nodes, and the spatial-temporal graph convolutional modules are designed to extract spatial-temporal dependencies from sensor data. Moreover, to ensure the accuracy of the association graph, this research introduces the UAV's dynamic model as prior knowledge for constructing the association graph. Finally, diagnostic accuracies of 94.93%, 98.71%, and 92.97% were achieved on three self-constructed datasets. In addition, compared to commonly used data-driven approaches, the proposed method demonstrates superior feature extraction capabilities and achieves the highest diagnostic accuracy. [ABSTRACT FROM AUTHOR]

A Lamb wave is a guided wave that propagates within plate-like structures, with its vibration mode resulting from the coupling of a longitudinal wave and a shear vertical wave, which can be applied in sensors, filters, and frequency control devices. The working principle of Lamb wave sensors relies on the excitation and propagation of this guided wave within piezoelectric material. Lamb wave sensors exhibit significant advantages in various sensing applications due to their unique wave characteristics and design flexibility. Compared to traditional surface acoustic wave (SAW) and bulk acoustic wave (BAW) sensors, Lamb wave sensors can not only achieve higher frequencies and quality factors in smaller dimensions but also exhibit superior integration and multifunctionality. In this paper, we briefly introduce Lamb wave sensors, summarizing methods for enhancing their sensitivity through optimizing electrode configurations and adjusting piezoelectric thin plate structures. Furthermore, this paper systematically explores the development of Lamb wave sensors in various sensing applications and provides new insights into their future development. [ABSTRACT FROM AUTHOR]

In this article, we report a novel pressure sensing method based on the Hall effect and a hard magnet magnetorheological elastomer (hmMRE). The elastic property of the MRE under pressure was used to generate spatial variation in the magnetic flux density around the MRE, and the variation was detected by the Hall effect device underneath. As the first development in this kind of pressure sensing mechanism, we conducted research for the following three purposes: (1) to verify the Hall effect on the output signal, (2) to understand the sensor output variations under different modes of operation, and (3) to utilize the mechanism as a pressure sensor. We characterized the sensor with its operation parameters, such as signal polarity switching depending on wiring directions, signal amplitude, and offset shift depending on the input voltage. Based on the analyses, we concluded that the Hall voltage represents the pressure applied on the hmMRE, and the new pressure sensing mechanism was devised successfully. [ABSTRACT FROM AUTHOR]

This article discusses the development of an enhanced monitoring and control system for helicopter turboshaft engines during flight operations, leveraging advanced neural network techniques. The research involves a comprehensive mathematical model that effectively simulates various failure scenarios, including single and cascading failure, such as disconnections of gas-generator rotor sensors. The model employs differential equations to incorporate time-varying coefficients and account for external disturbances, ensuring accurate representation of engine behavior under different operational conditions. This study validates the NARX neural network architecture with a backpropagation training algorithm, achieving 99.3% accuracy in fault detection. A comparative analysis of the genetic algorithms indicates that the proposed algorithm outperforms others by 4.19% in accuracy and exhibits superior performance metrics, including a lower loss. Hardware-in-the-loop simulations in Matlab Simulink confirm the effectiveness of the model, showing average errors of 1.04% and 2.58% at 15 °C and 24 °C, respectively, with high precision (0.987), recall (1.0), F1-score (0.993), and an AUC of 0.874. However, the model's accuracy is sensitive to environmental conditions, and further optimization is needed to improve computational efficiency and generalizability. Future research should focus on enhancing model adaptability and validating performance in real-world scenarios. [ABSTRACT FROM AUTHOR]

The flexible piezoelectric pressure sensor is essential in areas such as machine sensing and human activity monitoring. Here, 0-dimensional PZT piezoelectric ceramic nanoparticles with carbon coating were synthesized by a surface-modified technique. The excellent electrical conductivity of the carbon shell causes redistribution and accumulation of mobile charges in the carbon layer, resulting in a greatly increased piezoelectric effect by inducing an enhanced electric field. A series of organic–inorganic composite films were prepared by the spin-coating method using polydimethylsiloxane (PDMS) as the matrix. The as-fabricated flexible PZT@C/PDMS composite film with 40 wt% PZT@C powder exhibits an excellent output voltage of ~74 V, a peak of output current ~295 nA, as well as a big sensitivity of 5.26 V N−1. Moreover, the composite film can be used as a pressure sensor to detect changes in force as well as for monitoring limb movements such as finger flexion, wrist flexion, and pedaling. This study reveals the promising applications of flexible 40%PZT@C/PDMS composite film for limb motion monitoring and pressure sensing. [ABSTRACT FROM AUTHOR]

Fluorescent materials for sensing have gained attention for the visual detection of different substances as metals and pesticides for environmental monitoring. This work presents fluorescent nanocomposites in solution, film, and paper obtained without capping and stabilizing agents, coming from quantum dots of cadmium sulfide (CdS QDs) and anionic–cationic polymer matrices. Fluorescent films were formed by casting and fluorescent paper by impregnation from the solutions. The optical properties of CdS QDs in solution showed absorption between 418 and 430 nm and a maximum emission at 460 nm. TEM analysis evidenced particle size between 3 and 6 nm and diffraction patterns characteristic of CdS nanocrystals. Infrared spectra evidenced changes in the wavenumber in the fluorescent films. The band gap values (2.95–2.82 eV) suggested an application for visible transmitting film. Fluorescent solutions by UV-vis and fluorescence evidenced a chemical interaction with glyphosate standard between 1 and 100 µg/mL concentrations. The analysis of red, green, and blue color codes (RGB) evidenced a color response of the fluorescent paper at 10 and 100 µg/mL, but the fluorescent films did not show change. Nanocomposites of chitosan and pectin, in solution and on paper, exhibited a behavior "turn-on" sensor, while carboxymethylcellulose had a "turn-off" sensor. This methodology presents three fluorescent materials with potential applications in visual sensing. [ABSTRACT FROM AUTHOR]

A simple, sensitive and reliable sensing system based on nitrogen-rich porous carbon (NRPC) and transition metals, NRPC/Ni, NRPC/Mn and NRPC/NiMn was developed and successfully applied as electrode materials for the quantitative determination of carbendazim (CBZ). The synergistic effect of NRPC and bimetals with acceptable pore structure together with flower-like morphology resulted in producing a highly conductive and interconnected network in NRPC/NiMn@GCE, which significantly enhanced the detection performance of CBZ. The electrochemical behavior investigated by cyclic voltammetry (CV) showed improved CBZ detection for NRPC/NiMn, due to the controlled adsorption/diffusion process of CBZ by the NRPC/NiMn@GCE electrode. The influences of various factors such as pH, NRPC/NiMn concentration, CBZ concentration and scan rate were studied. Under optimal conditions, 0.1 M phosphate-buffered saline (PBS) with a pH of 7.0 containing 30 µg/mL NRPC/NiMn, a favourable linear range detection of CBZ from 5 to 50 µM was obtained. Moreover, a chronoamperometric analysis showed excellent repeatability, reproducibility and anti-interfering ability of the fabricated NRPC/NiMn@GCE sensor. Furthermore, the sensor showed satisfactory results for CBZ detection in real samples with acceptable recoveries of 96.40–104.98% and low RSD values of 0.25–3.45%. [ABSTRACT FROM AUTHOR]

Polymer actuators are promising, as they are widely used in various fields, such as sensors and soft robotics, for their unique properties, such as their ability to form high-quality films, sensitivity, and flexibility. In recent years, advances in structural and fabrication processes have significantly improved the reliability of polymer sensing-based actuators. Polymer actuators have attracted considerable attention for use in artificial or biohybrid systems, as they have the potential to operate under diverse conditions with high durability. This review briefly describes different types of polymer actuators and provides an understanding of their working mechanisms. It focuses on actuation modes controlled by diverse or multiple stimuli. Furthermore, it discusses the fabrication processes of polymer actuators; the fabrication process is an important consideration in the development of high-quality actuators with sensing properties for a wide range of applications in soft robotics. Additionally, the high potential of polymer actuators for use in sensing technology is examined, and the latest developments in the field of polymer actuators, such as the development of biohybrid polymers and the use of polymer actuators in 4D printing, are briefly described. [ABSTRACT FROM AUTHOR]

Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems have been designed to monitor users' gait patterns, they commonly spend a lot of time and effort to extract gait metrics from signal data. This study aims to design an artificial intelligence-empowered and economic-friendly gait monitoring system. A pair of intelligent shoes with a single inertial sensor and a smartphone application were developed as a gait monitoring system to detect users' gait cycle, stand phase time, swing phase time, stride length, and foot clearance. We recruited 30 participants (24.09 ± 1.89 years) to collect gait data and used the Vicon motion capture system to verify the accuracy of the gait metrics. The results show that the gait monitoring system performs better on the assessment of the gait metrics. The accuracy of stride length and foot clearance is 96.17% and 92.07%, respectively. The artificial intelligence-empowered gait monitoring system holds promising potential for improving gait analysis and monitoring in the medical and healthcare fields. [ABSTRACT FROM AUTHOR]

Triazine pesticide (atrazine and its derivatives) detection sensors have been developed to thoroughly check for the presence of these chemicals and ultimately prevent their exposure to humans. Sensitive coatings were designed by utilizing molecular imprinting technology, which aims to create artificial receptors for the detection of chlorotriazine pesticides with gravimetric transducers. Initially, imprinted polymers were developed, using acrylate and methacrylate monomers containing hydrophilic and hydrophobic side chains, specifically for atrazine, which shares a basic heterocyclic triazine structure with its structural analogs. By adjusting the ratio of the acid to the cross-linker and introducing acrylate ester as a copolymer, optimal non-covalent interactions were achieved with the hydrophobic core of triazine molecules and their amino groups. A maximum sensor response of 546 Hz (frequency shift/layer height equal to 87.36) was observed for a sensitive coating composed of 46% methacrylic acid and 54% ethylene glycol dimethacrylate, with a demonstrated layer height of 250 nm (6.25 kHz). The molecularly imprinted copolymer demonstrated fully reversible sensor responses, not only for atrazine but also for its metabolites, like des-ethyl atrazine, and structural analogs, such as propazine and terbuthylazine. The efficiency of modified molecularly imprinted polymers for targeted analytes was tested by combining them with a universally applicable quartz crystal microbalance transducer. The stable selectivity pattern of the developed sensor provides an excellent basis for a pattern recognition procedure. [ABSTRACT FROM AUTHOR]

There has been a recent increase in the frequency of mass disaster events. Following these events, the rapid location of victims is paramount. Currently, the most reliable search method is scent detection dogs, which use their sense of smell to locate victims accurately and efficiently. Despite their efficacy, they have limited working times, can give false positive responses, and involve high costs. Therefore, alternative methods for detecting volatile compounds are needed, such as using electronic noses (e-noses). An e-nose named the 'NOS.E' was developed and has been used successfully to detect VOCs released from human remains in an open-air environment. However, the system's full capabilities are currently unknown, and therefore, this work aimed to evaluate the NOS.E to determine the efficacy of detection and expected sensor response. This was achieved using analytical standards representative of known human ante-mortem and decomposition VOCs. Standards were air diluted in Tedlar gas sampling bags and sampled using the NOS.E. This study concluded that the e-nose could detect and differentiate a range of VOCs prevalent in ante-mortem and decomposition VOC profiles, with an average LOD of 7.9 ppm, across a range of different chemical classes. The NOS.E was then utilized in a simulated mass disaster scenario using donated human cadavers, where the system showed a significant difference between the known human donor and control samples from day 3 post-mortem. Overall, the NOS.E was advantageous: the system had low detection limits while offering portability, shorter sampling times, and lower costs than dogs and benchtop analytical instruments. [ABSTRACT FROM AUTHOR]

The time dynamics of charge accumulation at the electrochemical interface between graphene and water is important for supercapacitors, batteries, and chemical and biological sensors. By using impedance spectroscopy, we have found that measured capacitance (Cm) at this interface with the gate voltage Vgate ≈ 0.1 V follows approximate laws Cm~T1.2 and Cm~T0.11 (T is Vgate period) in frequency ranges (1000–50,000) Hz and (0.02–300) Hz, respectively. In the first range, this dependence demonstrates that the interfacial capacitance (Cint) is only partially charged during the charging period. The observed weaker frequency dependence of the measured capacitance (Cm) at frequencies below 300 Hz is primarily determined by the molecular relaxation of the double-layer capacitance (Cdl) and by the graphene quantum capacitance (Cq), and it also implies that Cint is mostly charged. We have also found a voltage dependence of Cm below 10 Hz, which is likely related to the voltage dependence of Cq. The observation of this effect only at low frequencies indicates that Cq relaxation time is much longer than is typical for electron processes, probably due to Dirac cone reconstruction from graphene electrons with increased effective mass as a result of their quasichemical bonding with interfacial molecular charges. [ABSTRACT FROM AUTHOR]

One of the significant advantages of technological evolution is the greater ease of collecting and analyzing data. Miniaturization, wireless communication protocols and IoT allow the use of sensors to collect data, with all the potential to support decision making in real time. In this paper, we describe the design and implementation of a digital solution to guide the intensity of training or physical activity, based on heart rate wearable sensors applied to participants in group sessions. Our system, featuring a unified engine that simplifies sensor management and minimizes user disruption, has been proven effective for real-time monitoring. It includes custom alerts during variable-intensity workouts, and ensures data preservation for subsequent analysis by physiologists or clinicians. This solution has been used in sessions of up to six participants and sensors up to 12 m away from the gateway device. We describe some challenges and constraints we face in collecting data from multiple and possibly different sensors simultaneously via Bluetooth Low Energy, and the approaches we follow to overcome them. We conduct an in-depth questionnaire to identify potential obstacles and drivers for system acceptance. We also discuss some possibilities for extension and improvement of our system. [ABSTRACT FROM AUTHOR]

The research problem of this systematic review was whether green 6G networks can integrate energy-efficient Industrial Internet of Things (IIoT) in terms of distributed artificial intelligence, green 6G pervasive edge computing communication networks and big-data-based intelligent decision algorithms. We show that sensor data fusion can be carried out in energy-efficient IoT smart industrial urban environments by cooperative perception and inference tasks. Our analyses debate on 6G wireless communication, vehicular IoT intelligent and autonomous networks, and energy-efficient algorithm and green computing technologies in smart industrial equipment and manufacturing environments. Mobile edge and cloud computing task processing capabilities of decentralized network control and power grid system monitoring were thereby analyzed. Our results and contributions clarify that sustainable energy efficiency and green power generation together with IoT decision support and smart environmental systems operate efficiently in distributed artificial intelligence 6G pervasive edge computing communication networks. PRISMA was used, and with its web-based Shiny app flow design, the search outcomes and screening procedures were integrated. A quantitative literature review was performed in July 2024 on original and review research published between 2019 and 2024. Study screening, evidence map visualization, and data extraction and reporting tools, machine learning classifiers, and reference management software were harnessed for qualitative and quantitative data, collection, management, and analysis in research synthesis. Dimensions and VOSviewer were deployed for data visualization and analysis. [ABSTRACT FROM AUTHOR]

There is limited validation for portable methods in evaluating high-speed running biomechanics, with inertial measurement unit (IMU) systems commonly used as wearables for this purpose. This study aimed to evaluate the validity of an IMU system in high-speed running compared to a 3D motion analysis system (MAS). One runner performed incremental treadmill running, from 12 to 18 km/h, on two separate days. Sagittal angles for the shank, knee, hip and pelvis were measured simultaneously with three IMUs and the MAS at the point of contact (POC), the timing when the foot initially hits the ground, as identified by IMU system acceleration, and compared to the POC identified via force plate. Agreement between the systems was evaluated using intra-class correlation coefficients, Pearson's r, Bland–Altman limits of agreements, root mean square error and paired t-tests. The IMU system reliably determined POC (which subsequently was used to calculate stride time) and measured hip flexion angle and anterior pelvic tilt accurately and consistently at POC. However, it displayed inaccuracy and inconsistency in measuring knee flexion and shank angles at POC. This information provides confidence that a portable IMU system can aid in establishing baseline running biomechanics for performance optimisation, and/or inform injury prevention programs. [ABSTRACT FROM AUTHOR]

The detection of dopamine is of great significance for human health. Herein, Pd nanoparticles were loaded on Cu nanoplates (Pd/Cu NPTs) by a novel liquid phase reduction method. A novel dopamine (DA) electrochemical sensor based on the Pd NPs/Cu/glass carbon electrode (Pd/Cu NPTs/GCE) was constructed. This sensor showed a wide linear range of 0.047 mM to 1.122 mM and a low limit of detection (LOD) of 0.1045 μM (S/N = 3) for DA. The improved performance of this sensor is attributed to the obtained tiny Pd nanoparticles which increase the catalytic active sites and electrochemical active surface areas (ECSAs). Moreover, the larger surface area of two–dimensional Cu nanoplates can load more Pd nanoparticles, which is another reason to improve performance. The Pd/Cu NPTs/GCE sensor also showed a good reproducibility, stability, and excellent anti–interference ability. [ABSTRACT FROM AUTHOR]

Rumination behavior in cattle can provide valuable information for monitoring health status and animal welfare, but continuous monitoring is essential to detect changes in rumination behavior. In a previous study validating the use of a respiration rate sensor equipped with a triaxial accelerometer, the regurgitation process was also clearly visible in the pressure and accelerometer data. The aim of the present study, therefore, was to measure the individual lengths of rumination cycles and to validate whether the sensor data showed the same number of regurgitations as those counted visually (video or direct observation). For this purpose, 19 Holstein Friesian cows equipped with a respiration rate sensor were observed for two years, with a focus on rumination behavior. The results showed a mean duration of 59.27 ± 9.01 s (mean ± SD) per rumination cycle and good agreement (sensitivity: 99.1–100%, specificity: 87.8–95%) between the two methods (sensor and visual observations). However, the frequency of data streaming (continuously or every 30 s) from the sensor to the data storage system strongly influenced the classification performance. In the future, an algorithm and a data cache will be integrated into the sensor to provide rumination time as an additional output. [ABSTRACT FROM AUTHOR]

Vibration sensors are widely applied in the detection of faults and analysis of operational states in engineering machinery and equipment. However, commercial vibration sensors with a feature of high hardness hinder their usage in some practical applications where the measured objects have irregular surfaces that are difficult to install. Moreover, as the operating environments of machinery become increasingly complex, there is a growing demand for sensors capable of working in wet and humid conditions. Here, we present a flexible, superhydrophobic vibration sensor with parallel microcracks. The sensor is fabricated using a femtosecond laser direct writing ablation strategy to create the parallel cracks on a PDMS film, followed by spray-coating with a conductive ink composed of MWCNTs, CB, and PDMS. The results demonstrate that the developed flexible sensor exhibits a high-frequency response of up to 2000 Hz, a high acceleration response of up to 100 m/s2, a water contact angle as high as 159.61°, and a linearity of 0.9812 between the voltage signal and acceleration. The results indicate that the sensor can be employed for underwater vibration, sound recognition, and vibration monitoring in fields such as shield cutters, holding significant potential for mechanical equipment vibration monitoring and speech-based human–machine interaction. [ABSTRACT FROM AUTHOR]

Electro-conductive films with excellent flexibility and thermal behavior have great potential in the fields of wearable electronics, artificial muscle, and soft robotics. Herein, we report a super-elastic and electro-conductive composite film with a sandwich structure. The composite film was constructed by spraying Polyvinyl alcohol (PVA) polymers onto a buckled conductive carbon nanotube-polydimethylsiloxane (CNTs-PDMS) composite film. In this system, the PVA and PDMS provide water sensing and stretchability, while the coiled CNT film offers sufficient conductivity. Notably, the composite film possesses high stretchability (205%), exceptional compression sensing ability, humility sensing ability, and remarkable electrical stability under various deformations. The produced CNT composite film exhibited deformation (bending/twisting) and high electro-heating performance (108 °C) at a low driving voltage of 2 V. The developed CNT composite film, together with its exceptional sensing and electrothermal performance, provides the material with promising prospects for practical applications in wearable electronics. [ABSTRACT FROM AUTHOR]

In the present paper, the use of programmable microprocessors to develop a computerized stand for the preparation of a mixture of flammable/toxic/explosive gases in order to obtain mixtures at concentrations in explosive range is presented. The operating principle of the stand is based on the mixing of two volumetric flows, controlled with the help of microprocessors, where gases are stored and circulated at atmospheric pressure through cylindrical injectors, driven by stepper motors so that the gas circuit does not require valves. The exit of the stand is a homogenization chamber, with agitator and sensor to confirm the desired concentration of the mixture. This automated stand eliminates mechanical, electric or pneumatic valves from the gas circuits, avoiding elements with high mechanical resistance suitable for high pressures/depressions, removing the possibility of the return of the gas flow, without sensitivity to sudden pressures variations. [ABSTRACT FROM AUTHOR]

In the context of the increasing frequency of urban flooding disasters caused by extreme weather, the accurate and timely identification and monitoring of urban flood risks have become increasingly important. This article begins with a bibliometric analysis of the literature on urban flood monitoring and identification, revealing that since 2017, this area has become a global research hotspot. Subsequently, it presents a systematic review of current mainstream urban flood monitoring technologies, drawing from both traditional and emerging data sources, which are categorized into sensor-based monitoring (including contact and non-contact sensors) and big data-based monitoring (including social media data and surveillance camera data). By analyzing the advantages and disadvantages of each technology and their different research focuses, this paper points out that current research largely emphasizes more "intelligent" monitoring technologies. However, these technologies still have certain limitations, and traditional sensor monitoring techniques retain significant advantages in practical applications. Therefore, future flood risk monitoring should focus on integrating multiple data sources, fully leveraging the strengths of different data sources to achieve real-time and accurate monitoring of urban flooding. [ABSTRACT FROM AUTHOR]

The measurement of apparent dielectric permittivity (εs) by low-frequency capacitance sensors and its conversion to the volumetric water content of soil (θ) through a factory calibration is a valuable tool in precision irrigation. Under certain soil conditions, however, εs readings are substantially affected by the bulk soil electrical conductivity (ECb) variability, which is omitted in default calibration, leading to inaccurate θ estimations. This poses a challenge to the reliability of the capacitance sensors that require soil-specific calibrations, considering the ECb impact to ensure the accuracy in θ measurements. In this work, a multivariate calibration equation (multivariate) incorporating both εs and ECb for the determination of θ by the capacitance WET sensor (Delta-T Devices Ltd., Cambridge, UK) is examined. The experiments were conducted in the laboratory using the WET sensor, which measured θ, εs, and ECb simultaneously over a range of soil types with a predetermined actual volumetric water content value (θm) ranging from θ = 0 to saturation, which were obtained by wetting the soils with four water solutions of different electrical conductivities (ECi). The multivariate model's performance was evaluated against the univariate CAL and the manufacturer's (Manuf) calibration methods with the Root Mean Square Error (RMSE). According to the results, the multivariate model provided the most accurate θ estimations, (RMSE ≤ 0.022 m3m−3) compared to CAL (RMSE ≤ 0.027 m3m−3) and Manuf (RMSE ≤ 0.042 m3m−3), across all the examined soils. This study validates the effects of ECb on θ for the WET and recommends the multivariate approach for improving the capacitance sensors' accuracy in soil moisture measurements. [ABSTRACT FROM AUTHOR]

Owing to their physical and chemical properties and stimuli-responsive nature, gels and hydrogels play vital roles in diverse application fields. The three-dimensional polymeric network structure of hydrogels is considered an alternative to many materials, such as conductors, ordinary films, constituent components of machines and robots, etc. The most recent applications of gels are in different devices like sensors, actuators, flexible screens, touch panels, flexible storage, solar cells, batteries, and electronic skin. This review article addresses the devices where gels are used, the progress of research, the working mechanisms of hydrogels in those devices, and future prospects. Preparation methods are also important for obtaining a suitable hydrogel. This review discusses different methods of hydrogel preparation from the respective raw materials. Moreover, the mechanism by which gels act as a part of electronic devices is described. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) technology connects the real and network worlds by integrating sensors and internet technology, which has greatly changed people's lifestyles, showing its broad application prospects. However, traditional materials for the sensors and power components used in the IoT limit its development for high-precision detection, long-term endurance, and multi-scenario applications. Metal halide perovskite, with unique advantages such as excellent photoelectric properties, an adjustable bandgap, flexibility, and a mild process, exhibits enormous potential to meet the requirements for IoT development. This paper provides a comprehensive review of metal halide perovskite's application in sensors and energy supply modules within IoT systems. Advances in perovskite-based sensors, such as for gas, humidity, photoelectric, and optical sensors, are discussed. The application of indoor photovoltaics based on perovskite in IoT systems is also discussed. Lastly, the application prospects and challenges of perovskite-based devices in the IoT are summarized. [ABSTRACT FROM AUTHOR]

The paper proposes a novel automatic control system for the attitude of the mini-satellites equipped with an actuator having N = 2 DGMSCMGs (Double Gimbal Magnetically Suspended Control Moment Gyros) in parallel and orthogonal configuration, as well as a DGMSCMG-type sensor for the measurement of the satellite absolute angular rate. The proportional-derivative controller, designed based on the Lyapunov-functions theory, elaborates the control law according to which the angular rates applied to the servo systems for the actuation of the DGMSCMGs gyroscopic gimbals are computed. The gimbal's angular rates create gyroscopic couples acting on the satellite in order to control its attitude with respect to the local orbital frame. The new proposed control architecture was software implemented and validated, and the analysis of the obtained results proved the cancellation of the convergence errors and excellent angular rate precision. [ABSTRACT FROM AUTHOR]

Fish are one of the main sources of protein in Cambodia but they are highly perishable. This requires immediate consumption or processing for later use. In processing, fish drying is very common, but most processors practice traditional drying methods although solar dryers have been introduced, or gradually used, in Cambodia. There is a large variation in terms of drying efficiency due to large differences in solar radiation, temperature, and humidity conditions in traditional drying methods and solar dryers. However, there is limited information on the actual variation in these two systems, which should be documented in Cambodia. Using sensors to monitor micro-climatic changes inside the drying chamber will be useful to improve efficiency and performance. Therefore, the objectives of this research were to (1) design a fish dryer from locally available inputs; (2) determine changes in solar radiation over time; (3) compare relative humidity and temperatures between traditional sun-drying and the solar dryer; (4) determine the relationship among the climatic parameters; and (5) compare some physical, chemical, and biological properties of dried fish in both drying techniques with the Cambodian dried fish standards. The study was conducted in collaboration with a fish processor in the Siem Reap Province between December 2023 and January 2024 using a sensor-mounted solar dryer fabricated by the Royal University of Agriculture to dry fish and compared with traditional sun-drying. Three experiments were carried out from 8:00 to 16:00 following the common drying practices in Cambodia. In each experiment, 80–100 kg of raw giant snakehead, or 56–70 kg of prepared fish (1.04 ± 0.05 kg each fish), was prepared for drying. Data on environmental conditions were measured and analyzed. The results show that the solar dryer had higher temperatures (almost 60 °C) and lower relative humidity (about 20%) during peak hours when compared with traditional sun-drying (36.8 °C and 40%, respectively). In all cases, relative humidity decreased with rising solar radiation and temperatures. The final weight and moisture of dried fish in the solar dryer were lower than those in traditional sun-drying in eight hours. Salmonella was detected with traditional sun-drying but E. coli was not. Bacterial presence may be harmful to human health. Nevertheless, the time spent for drying in both techniques was the same, so future studies should focus on improving ventilation to remove moisture faster out of the solar dryer, which can help with faster drying and more time saving. Hybrid solar dryers should also be considered to maintain high temperatures at night, while bacteria should be counted for safety reasons. [ABSTRACT FROM AUTHOR]

In this work, TiO2 spherical nanoparticles with a mean diameter of 10.08 nm (SD = 4.54 nm) were synthesized using Aloe vera extract. Rutile, brookite, and anatase crystalline phases were identified. The surface morphology of a carbon paste electrode does not change in the presence of nanoparticles; however, the surface chemical composition does. The voltammetric response to dicresyl dithiophosphate was higher when the electrode was modified with TiO2 nanoparticles. After an electrochemical response study from pH 1.0 to 12.0, pH 7.0 was selected for the electroanalysis. The electroactive area of the modified sensor was 0.036 cm2, while it was 0.026 cm2 for the bare electrode. The oxidation process showed mixed adsorption-diffusion control. The charge transfer resistance of the modified sensor (530.1 Ω, SD = 4.08 Ω) was much lower than that of the bare electrode (4298 Ω, SD = 8.53 Ω). The linear quantitative range by square wave voltammetry was from 5 to 150 μmol/L, with a limit of detection of 1.89 μmol/L and a limit of quantification of 6.26 μmol/L under optimal pulse parameters of 50 Hz frequency, 1 mV step potential, and 25 mV pulse amplitude. The sensor response was repeatable and reproducible over 30 days. The results on real flotation and synthetically contaminated soil samples were statistically equivalent to those obtained by UV-vis spectrophotometry. A dithiocarbamate showed an interfering effect on the sensor response to dithiophosphate. [ABSTRACT FROM AUTHOR]

Saccharides, being one of the fundamental molecules of life, play essential roles in the physiological and pathological functions of cells. However, their intricate structures pose challenges for detection. Nanopore technology, with its high sensitivity and capability for single-molecule-level analysis, has revolutionized the identification and structural analysis of saccharide molecules. This review focuses on recent advancements in nanopore technology for carbohydrate detection, presenting an array of methods that leverage the molecular complexity of saccharides. Biological nanopore techniques utilize specific protein binding or pore modifications to trigger typical resistive pulses, enabling the high-sensitivity detection of monosaccharides and oligosaccharides. In solid-state nanopore sensing, boronic acid modification and pH gating mechanisms are employed for the specific recognition and quantitative analysis of polysaccharides. The integration of artificial intelligence algorithms can further enhance the accuracy and reliability of analyses. Serving as a crucial tool in carbohydrate detection, we foresee significant potential in the application of nanopore technology for the detection of carbohydrate molecules in disease diagnosis, drug screening, and biosensing, fostering innovative progress in related research domains. [ABSTRACT FROM AUTHOR]

Triethylamine (TEA) is a typical volatile organic compound (VOC) widely present in air and water, produced in industrial production activities, with high toxicity and great harm. Fluorescence detection and resistive sensing are effective methods for detecting pollutants. Here, In-doped interpenetrating twin ZIF-8 and its annealed derivatives have been successfully designed and prepared as a multifunctional TEA sensor. On the one hand, ZIF-8-In exhibits excellent fluorescence emission enhancement at 450 nm in a dose-dependent manner to TEA in water within the concentration range of 1–100 ppm, with a detection limit as low as 1 ppm. On the other hand, the annealed ZIF-8-In derivative is ZnO/In2O3 with a porous hierarchical structure, which is a perfect sensitive material for manufacturing gas sensors. Within the concentration range of 1–100 ppm, the ZnO/In2O3 gas sensor has a high response for 100 ppm TEA, reaching 107.7 (Ra/Rg), and can detect TEA gas as low as 1 ppm. Furthermore, the response of ZnO/In2O3 sensors to TEA is at least 10 times that of the other four VOC gases, demonstrating excellent gas selectivity. This multifunctional sensor can adapt to complex detection situations, demonstrating good application prospects. [ABSTRACT FROM AUTHOR]

The accuracy of aerial work platform weighing is essential for safety. However, in practice, the same weight placed at different locations on the platform can yield varying readings, which is a phenomenon known as eccentric load. Measurement errors caused by eccentric loads can lead to missed detections and false alarms in the vehicle safety system, seriously affecting the safety of aerial work. To overcome the influence of eccentric load, the current engineering practice relies on multiple measurements at multiple points and averaging the results to eliminate the eccentric load, which greatly increases the work intensity of workers. To address the aforementioned issues, this paper proposes a three-dimensional force/torque shear force compensation scheme based on bending torque and torsional torque for pressure. The goal is to ensure that the sensor on the aerial work vehicle platform can accurately measure the anti-eccentric load under single-point measurement conditions. A three-box structure anti-eccentric load-weighing sensor for the aerial work platform was designed. Its structure has the advantages of high mechanical strength and no radial effect, ensuring the safety of aerial work, improvement of measurement sensitivity, and enabling of real-time and accurate acquisition of force/torque in three directions. In order to further improve the measurement accuracy of 3D force/torque compensation, a particle swarm optimization algorithm was adopted to optimize the 3D force/torque shear force compensation, thereby improving the safety of engineering operations. Through the verification of a self-made testing platform, the anti-eccentric load sensor designed in this study can ensure that the measurement error of objects at any position on the platform is less than 1.5%, effectively improving the safety of high-altitude platform engineering operations. [ABSTRACT FROM AUTHOR]

Medication adherence is an essential aspect of healthcare for patients and is important for achieving medical objectives. However, the lack of standard techniques for measuring adherence is a global concern, making it challenging to accurately monitor and measure patient medication regimens. The use of sensor technology for medication adherence monitoring has received much attention lately since it makes it possible to continuously observe patients' medication adherence behavior. Sensor devices or smart wearables utilize state-of-the-art machine learning (ML) methods to analyze intricate data patterns and provide predictions accurately. The key aim of this work is to develop a sensor-based hand gesture recognition model to predict medication activities. In this research, a smart sensor device-based hand gesture prediction model is developed to recognize medication intake activities. The device includes a tri-axial gyroscope, geometric, and accelerometer sensors to sense and gather data from hand gestures. A smartphone application gathers hand gesture data from the sensor device, which is then stored in the cloud database in a.csv format. These data are collected, processed, and classified to recognize the medication intake activity using the proposed novel neural network model called Sea Horse Optimization–Deep Neural Network (SHO-DNN). The SHO technique is implemented to update the biases and weights and the number of hidden layers in the DNN model. By updating these parameters, the DNN model is improved in classifying the samples of hand gestures to identify the medication activities. The research model demonstrates impressive performance, with an accuracy of 98.59%, sensitivity of 97.82%, precision of 98.69%, and an F1 score of 98.48%. Hence, the proposed model outperformed the most available models in all the aforementioned aspects. The results indicate that this model is a promising approach for medication adherence monitoring in healthcare applications, instilling confidence in its effectiveness. [ABSTRACT FROM AUTHOR]

A thick-lens, structured-light measurement model is introduced to overcome the oversights in traditional models, which often disregard the impact of lens thickness. This oversight can lead to inaccuracies in Scheimpflug camera calculations, causing systematic errors and diminished measurement precision. By geometrical optics, the model treats the camera as a thick lens, factoring in the locations of its principal points and the spatial shifts due to image plane tilting. The model deduces the positional relationship of the thick lens with a tilted optical axis and establishes a linear-structured-light measurement model. Simulations confirm that the model can precisely calculate the 3D coordinates of subjects from image light strip data, markedly reducing systematic errors across the measurement spectrum. Moreover, experimental results suggest that the refined sensor model offers enhanced accuracy and lower standard deviation. [ABSTRACT FROM AUTHOR]

This review highlights the most recent applications of Cd(II)-carboxylate-based coordination polymers (Cd(II)-CBCPs), such as sensors, catalysts, and storage materials, in comparison with those of Zn(II) counterparts. A wide range of species with luminescence properties were designed by using proper organic fluorophores, especially a carboxylate bridging ligand combined with an ancillary N-donor species, both with a rigid structure. These characteristics, combined with the arrangement in Cd(II)-CBCPs' structure and the intermolecular interaction, enable the sensing behavior of a plethora of various inorganic and organic pollutants. In addition, the Lewis acid behavior of Cd(II) was investigated either in developing valuable heterogeneous catalysts in acetalization, cyanosilylation, Henry or Strecker reactions, Knoevenagel condensation, or dyes or drug elimination from wastewater through photocatalysis. Furthermore, the pores structure of such derivatives induced the ability of some species to store gases or toxic dyes. Applications such as in herbicides, antibacterials, and electronic devices are also described together with their ability to generate nano-CdO species. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are small, non-coding RNAs that play a crucial role in regulating gene expression. Dysfunction in miRNAs can lead to various diseases, including cancers, neurological disorders, and cardiovascular conditions. To date, approximately 2000 miRNAs have been identified in humans. These small molecules have shown promise as disease biomarkers and potential therapeutic targets. Therefore, identifying miRNA biomarkers for diseases and developing effective miRNA drug delivery systems are essential. Nanotechnology offers promising new approaches to addressing scientific and medical challenges. Traditional miRNA detection methods include next-generation sequencing, microarrays, Northern blotting, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Nanotechnology can serve as an effective alternative to Northern blotting and RT-qPCR for miRNA detection. Moreover, nanomaterials exhibit unique properties that differ from larger counterparts, enabling miRNA therapeutics to more effectively enter target cells, reduce degradation in the bloodstream, and be released in specific tissues or cells. This paper reviews the application of nanotechnology in miRNA detection and drug delivery systems. Given that miRNA therapeutics are still in the developing stages, nanotechnology holds great promise for accelerating miRNA therapeutics development. [ABSTRACT FROM AUTHOR]

L-tryptophan is an amino acid that significantly impacts metabolic activity in both humans and herbivorous animals. It is also known as a precursor for melatonin and serotonin, and its levels must be regulated in the human body. Therefore, there is a need to develop a cost-effective, simple, sensitive, and selective method for detecting L-tryptophan. Herein, we report the fabrication of an L-tryptophan sensor using a nickel-doped tungsten oxide ceramic-modified electrode. The Ni-WO3 was synthesized using simple strategies and characterized by various advanced techniques such as powder X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and photoelectron X-ray spectroscopy. Furthermore, a glassy carbon electrode was modified with the synthesized Ni-WO3 and explored as the L-tryptophan (L-TRP) sensor. Cyclic voltammetry and differential pulse voltammetry were used to investigate the sensing ability of the modified electrode (Ni-WO3/GC). The Ni-WO3/GC exhibited an excellent limit of detection of 0.4 µM with a good dynamic linear range. The Ni-WO3/GC also demonstrated excellent selectivity in the presence of various electroactive molecules. The Ni-WO3/GC also showed decent reproducibility, repeatability, stability, and storage stability. This work proposes the fabrication of novel Ni-WO3/GC for the sensing of L-tryptophan. So far, no report is available on the use of Ni-WO3/GC for the sensing of L-TRP. This is the first report on the use of Ni-WO3/GC for the sensing of L-TRP sensing applications. [ABSTRACT FROM AUTHOR]

This study explores the potential of β-SnSe monolayers as a promising material for ozone (O3) sensing using density functional theory (DFT) combined with the non-equilibrium Green's function (NEGF) method. The adsorption characteristics of O3 molecules on the β-SnSe monolayer surface were thoroughly investigated, including adsorption energy, band structure, density of states (DOSs), differential charge density, and Bader charge analysis. Post-adsorption, hybridization energy levels were introduced into the system, leading to a reduced band gap and increased electrical conductivity. A robust charge exchange between O3 and the β-SnSe monolayer was observed, indicative of chemisorption. Recovery time calculations also revealed that the β-SnSe monolayer could be reused after O3 adsorption. The sensitivity of the β-SnSe monolayer to O3 was quantitatively evaluated through current-voltage characteristic simulations, revealing an extraordinary sensitivity of 1817.57% at a bias voltage of 1.2 V. This sensitivity surpasses that of other two-dimensional materials such as graphene oxide. This comprehensive investigation demonstrates the exceptional potential of β-SnSe monolayers as a highly sensitive, recoverable, and environmentally friendly O3 sensing material. [ABSTRACT FROM AUTHOR]

The online detection of fertilizer solution information is a crucial link in the implementation of intelligent and precise variable fertilization techniques. However, achieving simultaneous rapid online detection of multiple fertilizer components is still challenging. Therefore, a rapid detection method based on spectrophotometry for qualitative and quantitative identification of four fertilizers (typical N, P, and K fertilizers: KNO3, (NH4)2SO4, KH2PO4, and K2SO4) was proposed in this work. Full-scan absorption spectra of fertilizer solutions at varying concentrations were obtained using a UV–visible/near-infrared spectrophotometer. By assessing the linear fit between fertilizer concentration and absorbance at each wavelength within the characteristic band, the characteristic wavelengths for KNO3, (NH4)2SO4, KH2PO4, and K2SO4 were identified as 214 nm, 410 nm, 712 nm, and 1708 nm, respectively. The identification method of fertilizer type and the prediction model of concentration were constructed based on characteristic wavelength and the Lambert–Beer law. Based on the above analysis, a four-channel photoelectric sensor was designed with four LEDs emitting wavelengths closely matched to characteristic wavelengths for fertilizer detection. A detection strategy of "qualitative analysis followed by quantitative detection" was proposed to realize the online detection of four fertilizer types and their concentrations. Evaluation of the sensor's performance showed its high stability, with an accuracy of 81.5% in recognizing fertilizer types. Furthermore, the relative error of the sensor detection was substantially less than ±15% for the fertilizer concentrations not exceeding 80 mg/L. These results confirm the capability of the sensor to meet the practical requirements for online detection of four fertilizer types and concentrations in the field of agricultural engineering. [ABSTRACT FROM AUTHOR]

This study aimed to establish an economical and rapid response system for carcass leachate leakage using a real-time groundwater monitoring system with sensors. In this work, four parameters, namely electrical conductivity (EC), chloride (Cl), nitrate nitrogen (NO3-N), and ammonia nitrogen (NH4-N), were monitored. Three actual livestock burial sites were selected as pilot areas and monitored for three years, from 2019 to 2021, using these four parameters. As a result of sensor quality control, the accuracy and precision range of the four parameters were found to be acceptable, within 75~125% and ±25%, respectively. When compared to the laboratory measurement value, the field measurement value recorded by the sensors was 1.1 times higher for EC, 1.6 times higher for Cl, and 2.5 times higher for NO3-N. The correlation analysis between the lab measurement and sensor measurement results showed that the EC had the highest correlation coefficient of 0.3837. Additionally, the factor extraction results showed that the EC showed a relatively significant correlation compared to the other parameters. In summary, based on the results of this study, EC may be considered a key sensor parameter for evaluating leachate leakage from groundwater near disposal sites. [ABSTRACT FROM AUTHOR]

Wearable electronic devices have emerged as a pivotal technology in healthcare and artificial intelligence robots. Among the materials that are employed in wearable electronic devices, organic thermoelectric materials possess great application potential due to their advantages such as flexibility, easy processing ability, no working noise, being self-powered, applicable in a wide range of scenarios, etc. However, compared with classic conductive materials and inorganic thermoelectric materials, the research on organic thermoelectric materials is still insufficient. In order to improve our understanding of the potential of organic thermoelectric materials in wearable electronic devices, this paper reviews the types of organic thermoelectric materials and composites, their assembly strategies, and their potential applications in wearable electronic devices. This review aims to guide new researchers and offer strategic insights into wearable electronic device development. [ABSTRACT FROM AUTHOR]