Smart Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) will contribute to vehicle decision-making in the Intelligent Transportation System (ITS). Multi-Vehicle Pursuit games (MVP), a multi-vehicle cooperative ability to capture mobile targets, is becoming a hot research topic gradually. Although there are some achievements in the field of MVP in the open space environment, the urban area brings complicated road structures and restricted moving spaces as challenges to the resolution of MVP games. We define an Observation-constrained MVP (OMVP) problem in this paper and propose a Transformer-based Time and Team Reinforcement Learning scheme (T3OMVP) to address the problem. First, a new multi-vehicle pursuit model is constructed based on decentralized partially observed Markov decision processes (Dec-POMDP) to instantiate this problem. Second, by introducing and modifying the transformer-based observation sequence, QMIX is redefined to adapt to the complicated road structure, restricted moving spaces and constrained observations, so as to control vehicles to pursue the target combining the vehicle’s observations. Third, a multi-intersection urban environment is built to verify the proposed scheme. Extensive experimental results demonstrate that the proposed T3OMVP scheme achieves significant improvements relative to state-of-the-art QMIX approaches by 9.66%~106.25%. Code is available at https://github.com/pipihaiziguai/T3OMVP.

Abstract: Thermal desalination is yet a reliable technology in the treatment of brackish water and seawater; however, its demanding high energy requirements have lagged it compared to other non-thermal technologies such as reverse osmosis. This review provides an outline of the development and trends of the three most commercially used thermal or phase change technologies worldwide: Multi Effect Distillation (MED), Multi Stage Flash (MSF), and Vapor Compression Distillation (VCD). First, state of water stress suffered by regions with little fresh water availability and existing desalination technologies that could become an alternative solution are shown. The most recent studies published for each commercial thermal technology are presented, focusing on optimizing the desalination process, improving efficiencies, and reducing energy demands. Then, an overview of the use of renewable energy and its potential for integration into both commercial and non-commercial desalination systems is shown. Finally, research trends and their orientation towards hybridization of technologies and use of renewable energies as a relevant alternative to the current problems of brackish water desalination are discussed. This reflective and updated review will help researchers to have a detailed state of the art of the subject and to have a starting point for their research, since current advances and trends on thermal desalination are shown.

Abstract: The expansion of global industries results in the release of harmful volatile acid vapors into the environment, posing a threat to various life forms. Hence, it's crucial to prioritize the development of swift sensing systems capable of monitoring these volatile acid vapors. This initiative holds great importance in safeguarding a clean and safe environment. This paper presents the synthesis and characterization of pyrene-based covalent organic frameworks (COFs) demonstrating exceptional crystallinity, thermal stability, and intense fluorescence. Three COFs—PP-COF, PT-COF, and PE-COF—were synthesized, showcasing large surface areas and robust thermal stability up to 400 °C. The fluorescence properties and intramolecular charge transfer within these COFs were significantly influenced by their Schiff base bonding types and π-stacking degrees between COF layers. Notably, PE-COF emerged as the most fluorescent among the three COFs and exhibited exceptional sensitivity and rapid response as a fluorescent chemosensor for detecting HCl in solution. The reversible protonation of imine bonds in these COFs allowed for the creation of highly sensitive acid vapor sensors, showcasing a shift in spectral absorption while maintaining structural integrity. This research highlights the potential of COFs as reliable and reusable sensors for detecting harmful acid vapors, addressing environmental concerns arising from industrial activities.

ZnO thin films with a thickness of 300 nm were deposited on Si and Al2O3 substrates using electron beam evaporation technique with the aim to be tested as low cost and low power consumption gas sensors for ozone (O3). To characterize the surface roughness and the grain size, which are the main parameters recognized to enhance gas sensitivity since they directly influence the effective sensing area, surface morphology and roughness analyses of the films were performed using scanning electron microscopy and atomic force microscopy, respectively. The crystalline structure and elemental composition were studied through Raman spectroscopy and X-ray photoelectron spectroscopy. Gas tests were conducted at room temperature and zero-bias voltage to assess the sensitivity and response as a function of time of the films to O3 pollutant. The results indicate that the films deposited on Al2O3 exhibit promising characteristics, such as high sensitivity and a very short response time (< 2 s) to the gas concentration. Additionally, it was observed that the films display pronounced degradation effects after a significant exposure to O3.

With the wide application of flow sensor, their reliability under extreme conditions has been concerned in recent years. The reliability of a Micro Electro Mechanical Systems flow sensor under temperature (Ts) is researched in this paper. Firstly, the Step-stress accelerated degradation test is designed. Because this flow sensor consists flow sensor chip and signal processing system, the accelerated degradation testing is implemented, respectively. While the results show that the biggest drift is 3.15% for flow sensor chips with 150℃ conditions, and 32.91% for this flowmeter. By analysis, it could be found that the attenuation of the signal processing system is significant to the degeneration of this flowmeter. The minimum drift of the signal processing system accounts for 82.01% of this flowmeter. Secondly, using the Coffin-Manson model, the relationship between cycle-index and Ts is established. And the lifetime with different Ts is estimated by the Arrhenius model. In addition, the Weibull distribution is applied to evaluate the lifetime distribution. Finally, the reliability function of the Weibull distribution is demonstrated, and the survival rate within one year is 87.69% with 85℃ conditions. Thus, by the application of accelerated degradation testing, the acquired results are innovative and original. This research illustrates the reliability research, which provides a relational database for the application of this flow sensor.

Virtual validation of radar sensor models is becoming increasingly important for the safety validation of adf. Therefore, methods for quantitative comparison of radar measurements in the context of model validation need to be developed. This paper presents a novel methodology for accessing and quantifying validation measurements of radar sensor models. This method uses edf and the so-called dvm to effectively quantify deviations between distributions. By applying this metric, the study measures the consistency, reproducibility and repeatability of radar sensor measurements. Different interfaces and different levels of detail are investigated. By comparing the radar signals from real world experiments where different objects are present, valuable insights are gained into the performance of the sensor. In particular, the research extends to assessing the impact of varying rain intensities on the measurement results, providing a comprehensive understanding of the sensor’s behaviour under these conditions. This holistic approach significantly advances the evaluation of radar sensor capabilities and enables the quantification of the maximum required quality of radar simulation models.

Antioxidants are very beneficial for health because they protect the body from the effects of free radicals on various degenerative diseases caused by food contamination, air pollution, sunlight, etc. In general, methods for measuring the capacity of antioxidants generally use accurate meth-ods such as spectrophotometry and chromatography. Still, it takes time, sample preparation and must be done in a laboratory with particular expertise. Therefore, a new, more practical method needs to be developed for determining antioxidants, namely the electrochemical method. The electrochemical method is promising to develop because it has several advantages, including high sensitivity and fast response. The electrochemical method discussed in this article reviews sensors, biosensors, and nanosensors. This paper comprehensively analyzes contemporary developments in electrochemical biosensor techniques and antioxidant evaluation methodologies. The discussion centers on utilizing multiple biosensors. Electrochemical biosensors have been determined to be prevalent in analyzing food quality, assessing active factor functionality, and screening practical components. The present study outlines the difficulties linked with electrochemical bio-sensor technology and provides insights into the potential avenues for future research in this domain.

In this work we successfully prepared a modified cobalt oxide (Co3O4) carbon paste electrode to detect Levofloxacin (LEV). By synthesizing Co3O4 nanoparticles through the chemical coprecipitation method, the electrochemical properties of the electrode and LEV were thoroughly investigated using CV, SWV, EIS, while material properties were scrutinized using ICP-OES, TEM, SEM, and XRD. The results showed that the prepared electrode displayed a better electrocatalytic response than the bare carbon paste electrode. After optimizing SWV, the electrode exhibited a wide linear working range from 1 to 85 μM at pH 5 of BRBS as the supporting electrolyte. The selectivity of the proposed method was satisfactory, with good repeatability and reproducibility, strongly suggesting a potential application for determining LEV in real samples, particularly in pharmaceutical formulations. The practicality of the approach was demonstrated through good recoveries, and the morphology of the materials was found to be closely related to other parameters, indicating that the developed method can provide a cost-effective, rapid, selective, and sensitive means for LEV monitoring. Overall, this project has made significant progress towards developing a reliable method for detecting LEV and has opened up new opportunities for future research in this field.

In this study, the preparation of the composite 3% Au/graphite-C3N4 (3% Au/g-C3N4) sensing material was prepared by doping 3% Au onto the surface of graphitic carbonitride (C3N4) for detection pimobendan. By the way of sensing materials characterization, the X-ray diffraction analysis (XRD) and transmission electron Microscope (TEM) were performed. The cyclic voltammetry (CV) was used to measure the concentration and redox properties of pimobendan. It can be seen that when the voltage value is 0.05 V, and a reduction peak was appeared and the pimobendan concentration (0 to 55 μM) has a relationship with the reduction current value. At low concentrations of pimobendan concentration from 0.0 to 0.8 μM, the linearity R2 = 0.9642 with a detection limit of 0.28 μM. A possible pimobendan sensing mechanism on 3% Au/g-C3N4 was proposed.

Modern agriculture demands for comprehensive information about the plant itself. Conventional chemistry-based analytical methods - due to their low throughput and high associated cost - are no longer capable of providing these data. In recent years, remote reflectance-based characterization has developed as one of the most promising solutions for rapid assessments for plant attributes. However, in many cases, expensive equipment is required because accurate quantifications need assessment of the full reflectance spectrum. We examined the versatility of visible colour sensors as reflectance measuring devices for biological / biochemical quantifications on sweet basil (Ocimum basilicum). Our results indicate for the wide potential of spectral colour sensors for quantitative determination of leaf phenolic compounds, flavonoids in particular, and non-invasive plant phenotyping in agricultural applications by low-cost sensors.

Early identification of viruses leads to more efficient disease management and control, and is extremely important. A possible new approach for creating virus sensors is the Electromagnetic echo effect (EMEE). An important feature is that the signal from EMEE is highly dependent on the state of the irradiated body. This makes it possible to control ongoing reactions, even if these reactions are invisible to the human eye or other equipment. This article shows the possibility of registering reaction occurring in the presence of an avian coronavirus causing infectious bronchitis, strain Massachusetts. The same methodology can be applied for other types of viruses as well.

Nitroxyl radical catalysts oxidize alcohols under an applied electric potential. It is possible to quantify the alcohol concentration from the resulting oxidation current. In this work, we evaluated the catalytic activity of nitroxyl radicals (or their corresponding hydroxylamines), including 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) as representative nitroxyl radicals, acetoamido-TEMPO, which shows higher oxidation potential than TEMPO owing to the acetoamido group, AZADO, Nor-AZADO, and NNO as less-hindered bicyclic nitroxyl radicals, and NHPI as an N,N-diacyl-type hydroxylamine, in acetonitrile solution. TEMPO, AZADO and NNO were also evaluated for their ability to oxidize alcohols in organic solvents, and their reactivity was compared with the electrochemical response. The most active NNO was used for electrochemical detection of cyclosporin A, a drug with a hydroxyl group.

The aim of the current study was to determine the effectiveness of two surgical techniques regarding the cow respiratory rates, heart rates, and rumination time using two sensors: an experimental device that was created by the Institute of Biomedical Engineering of Kaunas University of Technology (Lithuania) and the “SCR” (SCR Engineers Ltd., Netanya, Israel) system. The cows were divided into two groups: PA1—cows treated by percutaneous abomasopexy (n = 10), and RSO2—cows treated by right side omentopexy (n = 8). For the control group (KH), according to the principle of analogues (number of lactations, breed, and days in milk), we selected clinically healthy cows (n = 9). After the surgical treatment for the abomasal displacement, the experimental device was applied for the recording of the heart and breathing rates; 12 hour tracking of the rumination time (RT) was implemented using the system ''SCR''; and the body temperature was measured. After 12 hours, the blood was taken for biochemical and morphological tests. The experimental device recorded 12 hours of the respiratory rate (RR) and heart beat rate (HBR) information. We determined the concentrations of the blood serum beta-hydroxybutyrate (BHB), calcium (Ca), phosphorus (Phos), magnesium (Mg), and iron (Fe), as well as the activities of aspartarte aminotransferase (AST) and gamma-glutamyl transferase (GGT). According to searches for relationships between the traditional blood biochemical and morphological parameters, and the parameters measured by the experimental device, the more efficient abomasal displacement surgical method was the right side omentopexy. With the sensors, we found, after right side omentopexy, a 5.19 beats/min lower (1.10-times) average value of the respiratory rate, 1.13-times higher level of the heart rate, a 0.15 oC higher temperature, and a 3.29-times lower rumination time compared to the clinical healthy cows. Further research with larger numbers of animals and longer experimental periods are needed prior to practical applications.

Surface Plasmon Resonance (SPR) is an attracting property of certain transition metals when they are synthesized in nano-range giving rise to promising optical applications. However, most SPR and associated applications are limited to the noble metal nanoparticles, which limits their potential due to high production cost. We report surface plasmon resonance in copper-copper oxide core-shell quantum dots synthesized via chemical route studied by using UV-Visible spectrophotometry. Tuning of the plasmonic resonance with respect to the particle diameter is achieved by an inexpensive all chemical route. Photoluminescence measurements also support the data. This size reduction leads to remarkable changes in its optical response as compared to the bulk metal. The results point towards applications of these materials in tunable SPR based biosensors.

An antenna sensor is proposed to execute dual functions of antenna and sensor in the wireless sensor system, in order to reduce data loss and to increase transmission rate by omitting a certain interface. The as-made sensor was test at a center frequency of 46 MHz for measuring human finger postures using principle of dipole antenna. The antenna sensor was attached on a wearable glove. The results showed that the motion sensor can accurately identify finger angles at 0°, 20°, 40°, 60° and 80°.

People with Down syndrome present cognitive difficulties that affect their reading skills. In this study we present results about the use of gestural interaction with Kinect sensor to improve the reading skills of students with Down syndrome. Following a case of study method for small samples with disabilities, measuring different variables related to reading skills in an experimental group and in a control group. We found improvements in the visual association, visual comprehension, sequential memory, and visual integration after this stimulation in the experimental group compared to the control group. Also, we found that the number of error and delay time of interaction decrease between sessions in the experimental group.

The subject of the research is to Development of laser ablation method for Fabrication of surface acoustic wave sensors on quartz wafer, the target of the GQW – is to design Acoustic wave sensor by using laser ablation method. By using the surface acoustic wave theory to sense by the signal and using this physical phenomenon, We will design the sensor which transduce an input electrical signal into a mechanical wave which unlike an electrical signal, can be easily influenced by physical phenomena. The device then transducers this wave back into an electrical signal on the secondary terminal of the sensor. Changes in amplitude, phase, frequency, or time-delay between the input and output electrical signals can be used to measure the presence of the desired Our work in this part, especially the practical part like temperature, vibration ,etc. we design a combs on the waver of quartz to make like an electrode primary electrode & secondary electrode by putting coats of cuppers & vanadium on the waver and then using the fiber optic laser regime to design this combs to can able transfer the signal by ablation the most important here to use the regime of fiber optic laser then we using this sensor in any electronic circuit How we will select the suitable kind of laser to design, this is the most important part, and what it will be the diameter of that combs of secondary and primary , how much the value of the wave length to select the micro distant combs to avoid any inductance and interference for transferred signal , also take the benefit of using MEMS theory in our project.

In this work, two embroidered textile moisture sensors are characterized with three different conductive yarns. The sensors are based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidered conductor yarn. The performance comparison of 3 different type of conductive yarns has been addressed. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 30% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity and the used conductor yarns. This dependence points out the optimum conductive yarn to be used to develop wearable applications for moisture measurement.

Detection of formaldehyde is very important in terms of life protection, as it can cause serious injury to eyes, skin, mouth and gastrointestinal function if indirectly inhaled and hence researchers are putting effort in developing novel and sensitive device. In this work, we have fabricated an electro-chemical sensor in the form of a field effect transistor (FET) to detect formaldehyde over wide range (10 nM to 1 mM). For this, ZnO nanosheets (NS) were first synthesized by hydrothermal method with in-situ deposition on cleaned SiO₂ coated Si (100) substrate. The synthesized materials were characterized for morphology and purity and surface area (31.718 m²/g). The developed device was tested for formaldehyde detection at room temperature that resulted in a linear response with concentration (96%), sensitivity value of 0.27 mA/M/cm² and a low detection limit of 210 nM, and a high 0.93194 return.

The deformation of underground gateroads tends to be asymmetric and complex. Traditional instrumentation fails to accurately and conveniently monitor the full cross-sectional deformation of underground gateroads. Here, a full cross-sectional laser scanner was developed together with a visualization software package. The developed system used polar coordinate measuring method and the full cross-sectional measurement was realized by 360° rotation of laser sensor driven by an electrical motor. Later on, the potential impact of gateroad wall flatness, roughness and geometrical profile as well as coal dust environment on the performance of the developed laser scanner were evaluated. The studies show that a high-level flatness is favorable in application of the developed full cross-sectional deformation monitoring system. For a smooth surface of gateroad, the sensor cannot receive reflected light when the incidence angle of laser beam is large, causing data loss. Conversely, the roughness surface shows its priority as the diffuse reflection light can be received by the sensor. With regards to the coal dust in measurement environment, the fine particles of floating coal dust in the air can lead to the loss of measurement data to some certain due to scattering of laser beam.

This paper presents a piezoresistive pressure sensor with a shield layer for improved stability. Compared with the conventional piezoresistive pressure sensors, p-type piezoresistors are covered by an n-type shield layer, which is formed by ion implantation. The proposed pressure sensors have been successfully fabricated by bulk micromachining techniques. The impact of electrical field on piezoresistors is studied by simulation. The temperature drift of the pressure sensor has been investigated by both simulation and experimental measurement. Characteristics of developed pressure sensors are tested from -40 C to 125 C. A sensitivity of 0.022 mV/V/KPa and a maximum non-linearity of 0.085% FS are measured for the fabricated sensor in a pressure range of 1 MPa. The temperature coefficients of resistance of shielded piezoresistors are found to be smaller than those of un-shielded ones. It is demonstrated that the shield layer is able to reduce the drift caused by electrical field and ambient temperature variation.

In recent years, the integration of sensors in agriculture has emerged as a pivotal catalyst for transforming conventional farming practices into precision agriculture. Sensor application is impacting the everyday objects that enhance human life. In this special issue, the main objective was to address recent advantages of sensor application in agriculture covering a wide range of topics in this field. This provides overview of diverse application of sensors in agriculture, highlighting their role in enhancing productivity, sustainability, and resource management. sensors are instrumental in monitoring various agriculture parameter such as soil condition, weather, crop health and livestock wellbeing. By collecting real-time data and providing valuable insight, sensors enable precision farming, optimize resource allocation, and minimize environmental impacts. we have to explore the key sensor types used in agriculture, their applications, benefits, and future prospects, emphasizing their crucial roles in the modernization of agriculture and global quest for food security and crop production.

To study and monitor the adverse health consequences from using electronic cigarettes, a user’s puff topography, which are quantification parameters of the user’s vaping habits, plays a central role. In this work, we introduce a topography sensor to measure the mass of total particulate matter generated in every puff and to estimate the nicotine yield. The sensor is compact and low-cost, and is integrated into the electronic cigarette device to promptly and conveniently monitor the user’s daily puff topography. The topography sensor is comprised of a photometric sensor and a pressure sensor. The photometric sensor measures the mass concentration of the aerosol, based on scattering of near-infrared light from airborne particles, while the pressure sensor measures the flow rate. The topography sensor was experimented under various conditions with a wide range of atomizer power, puff duration, and inhalation pressure. The sensor’s accuracy was validated by comparing the sensor’s readings with reference measurements, and the results matched closely with the trends reported by existing studies on electronic cigarettes. An example application of tracking a user’s puff topography was also demonstrated. Our topography sensor holds great promise in mitigating health risks of vaping, and in promoting quality control of electronic cigarette products.

A planar microwave sensor devoted to the detection of humidity in underwear and clothes in general is proposed. The ultimate goal of the sensor is to detect the presence of liquids in fabrics, of interest to aid patients that suffer from certain pathologies, such as hyperhidrosis and enuresis. The main target in the design of the sensor, considering the envisaged application, is simplicity. Thus, the sensor operates at a single frequency, and the working principle is the variation in the mag-nitude of the transmission coefficient of a matched line loaded with an open-ended quar-ter-wavelength sensing stub resonator. The stub, which must be in contact with the so-called fabric under test (FUT), generates a notch in the transmission coefficient with a resonance frequency that depends on the humidity level of the fabric. By designing the stub with a moderately high quality factor, the variation in the resonance frequency causes a significant change in the magnitude level at the operating frequency, the resonance frequency when the sensing stub is loaded with the dry fabric, and the presence of liquid can be detected by means of an amplitude detector. A prototype device is proposed and experimentally validated.

Five years ago, the concept of addressed fiber Bragg structures (AFBS) was proposed, which simultaneously perform the functions of a two-frequency radiation shaper, the difference frequency of which is the AFBS address, and a sensitive element, since the value of the difference frequency is invariant to measured physical fields, and the set of difference frequencies, moreover, is orthogonal in the array of such sensors, enabling their address multiplexing. In this article, we provide an overview of the theory and technology of AFBS, including the structures with three or more spectral components with various combinations of difference frequencies, symmetrical and asymmetric, performing the functions of the address and converting information signals to the low-frequency range at the same time, along with other functions. The subjects of interrogation of these structures, their fabrication and calibration are discussed as well. We also consider a wide range of applications in which AFBS can be used, covering such areas as oil and gas production, power engineering, transport, medicine, etc. In addition, the prospects of AFBS further development are proposed.

This paper presents an in-depth contextualized tutorial on Agricultural IoT (Agri-IoT), covering the fundamental concepts, assessment of routing architectures and protocols, and performance optimization techniques via systematic survey and synthesis of related literature. The negative impacts of climate change and the increasing global population on food security and unemployment threats have motivated the adoption of the wireless sensor network (WSN)-based Agri-IoT as an indispensable underlying technology in precision agriculture and greenhouses to improve food production capacities and quality. However, most related Agri-IoT testbed solutions have failed to achieve their performance expectations due to the lack of an in-depth and contextualized reference tutorial that provides a holistic overview of communication technologies, routing architectures, and performance optimization modalities based on users’ expectations. Thus, although IoT applications are founded on a common idea, each use case (e.g., Agri-IoT) varies based on specific performance and users expectations as well as its technological, architectural, and deployment requirements. Likewise, the agricultural setting is a unique and hostile area where conventional IoT technologies do not apply, hence the need for this tutorial. Consequently, this tutorial addresses these via the following contributions: (1) a systematic overview of the fundamental concepts, technologies, and architectural standards of WSN-based Agri-IoT, (2) an evaluation of the technical design requirements of a robust, location-independent, and affordable Agri-IoT, (3) a comprehensive survey of the benchmarking fault tolerance techniques, communication standards, routing and medium access control (MAC) protocols, and WSN-based Agri-IoT testbed solutions, and (4) an in-depth case study on how to design a self-healing, energy-efficient, affordable, adaptive, stable, autonomous, and cluster-based WSN-specific Agri-IoT from a proposed taxonomy of multi-objective optimization (MOO) metrics that can guarantee an optimized network performance. Furthermore, this tutorial established new taxonomies of faults, architectural layers, and MOO metrics for cluster-based Agri-IoT (CA-IoT) networks and a 3-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

Real-world optimization problems are often governed by one or more constraints. Over the last few decades, extensive research has been performed in Constrained Optimization Problems (COPs) fueled by advances in computational intelligence. In particular, Evolutionary Algorithms (EAs) are a preferred tool for practitioners for solving these COPs within practicable time limits. We propose an ensemble of multi- method hybrid EA framework with four mutation operators, two crossover operators, multi-search [Differential Evolution (DE) & Gaining Sharing Knowledge (GSK)] optimization algorithm, and ensemble of constraint handling techniques to solve global real- world constrained optimization problem. The proposed frame- work FEPEA has an ascendancy of multiple adaptation strategies concerning the control parameters, search mechanisms, two sub-populations as well as uses knowledge sharing mechanism between junior and senior phases. The algorithm also combines the power of four popular constraint handling techniques (CHT) and uses a voting mechanism to select any particular CHT. On top of that, this algorithm also uses both linear and non- linear population size reduction in every step of the evolutionary process. We test our method on 57 real-world problems provided as part of the CEC 2020 special session & competition on real- world constrained optimization benchmark suite. Experimental results indicate that FEPEA is able to achieve state-of-the- art performance on real-world constrained global optimization when compared against other well-known real-world constrained optimizers.

The hybrid bond graph has been studied in depth for scalar bond graphs, but how does this translate to the multi-bond graph? Here, the controlled junction – used to model structural switching such as contact – is extended to the multi-bond case. This is a simple process, assuming that all bonds switch simultaneously (which makes physical sense). A controlled 0-junction is applied to multi-bond graph of a car, which can lose contact with the ground in cornering. Dynamic causality features, but this can be accommodated using an equational submodel in 20-Sim (in a manner similar to that used with scalar bond graphs). The junction is proposed for subsequent work to develop a validated multi-body dynamics car model in cornering.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

The framework of product life cycle (PLC) cost analysis is one of the most important evaluation tools for a contemporary high-tech company in an increasingly competitive market environment. The PLC-purchasing strategy provides the framework for a procurement plan and examines the sourcing strategy of a firm. The marketing literature emphasizes that ongoing technological change and shortened life cycles are important elements in commercial organizations. From a strategic viewpoint, the vendor has an important position between supplier, buyer and manufacturer. The buyer seeks to procure the products from a set of vendors to take advantage of economies of scale and to exploit opportunities for strategic relationships. However, previous studies have seldom considered vendor selection (VS) based on PLC cost (VSPLCC) analysis. The purpose of this paper is to solve the VSPLCC problems considering the situation of a single-buyer-multiple-supplier. For this issue, a new VSPLCC procurement model and solution procedure are derived by this paper to minimize net cost, rejection rate, late delivery and PLC cost subject to vendor capacities and budget constraints. Moreover, a real case in Taiwan is provided to show how to solve the VSPLCC procurement problem.

In this paper, a new approach to the sliding-mode control of single-phase inverters under linear and non-linear loads is introduced. The main idea behind this approach is to utilize a non-linear, flexible and multi-slope function in controller structure. This non-linear function makes the controller possible to control the inverter by a non-linear multi-slope sliding surface. In general, this sliding surface has two parts with different slopes in each part and the flexibility of the sliding surface makes the multi-slope sliding-mode controller (MSSMC) possible to reduce the total harmonic distortion, to improve the tracking accuracy, and to prevent overshoots leading to undesirable transient-states in output voltage which are occurred when the load current sharply rises. In order to improve the tracking accuracy and to reduce the steady-state error, an integral term of the multi-slope function is also added to the sliding surface. The improved performance of the proposed controller is confirmed by simulations and finally, the results of the proposed approach are compared with a conventional SMC and a SRFPI controller.

Fragmentation processes of multiply charged ions of C10H8 isomers produced in fast proton collision (velocity between 1.41 and 2.4 a.u.) is discussed in view of their fundamental molecular dynamics. Especially so in the mechanisms to produce a variety of carbon clusters from such ions. This aspect is assessed with the help of a multihit analysis of daughter ions in coincidence with elimination of H+ and CHn+ (n = 0 to 3). The elimination of H+/C+ was found to be very different from CH3+ loss. The loss of CH3+ was found to be accompanied with the formation of heavy ions like C9H5+, C9H5++ and C7H3+ by a cascade of momentum correlated dissociations. The most probable structures of large fragment ions in the CH3+ loss cascade are predicted with the help of computed electronic energy and the multihit ToF correlations of second and third hit. In addition, we report observation of super-dehydrogenation of naphthalene and azulene targets, with evidence of complete dehydrogenation in a single collision.

This paper proposes a multi-terminal adaptive collaborative operation method to solve the problem of unstable internal force tracking in clamping and handling unknown objects by multi-terminal robots. In the proposed method, the internal command force changes the complex internal force control problem into an internal force tracking problem from multi-slave to master. Moreover, we develop an algorithm for multi-slave setups to estimate object stiffness and motion uncertainty in the direction of the internal command force according to Lyapunov theory. Finally, the impedance control generates a reference trajectory for the multi-slave to maintain the desired internal force and track the master’s motion. Several experiments are conducted on a self-made robot equipped. The experimental results show that the oscillation amplitude of each slave end is less than 1 mm, the directional oscillation amplitude is less than 1 degree during the tracking of the desired commanded internal force. For objects with low stiffness, the error of the commanded internal force is less than 1 N (6%) per slave. The error in tracking the commanded internal force for objects with high stiffness is less than 2 N (8%). The results prove the feasibility and effectiveness of the proposed method.

In gravitational theory and astrophysical dynamics, singular initial value problems (IVPs) are frequently encountered. Finding the solutions to this class of IVPs can be challenging due to their complex nature. This study strives to circumvent the complexity by proposing a numerical method for solving such problems. The approach proposed in the current research seeks solutions to the IVP by partitioning the domain [0,L] of the problem into two intervals and solving the problem on each domain. The study seeks a closed-form solution to the IVP in the interval containing the singular point. A linearization technique and piecewise partitioning of the domain not containing the singularity are applied to the nonlinear IVP. The resulting linearized differential equation is solved using the Chebyshev spectral collocation method. Some examples are presented to illustrate the efficiency of the proposed method. Numerical analysis of the solution and residual errors are shown to ascertain convergence and accuracy. The results suggest that the technique gives accurate convergent solutions using a few collocation points.

Dracunculiasis (also known as Guinea worm disease) is caused by Dracunculus medinensis parasite and it spreads by drinking water containing Larvae of Guinea worm. The lack of safe water facilities, preventions and treatments resulted in highly dangerous consequences in its endemic regions. The economy of the affected regions totally falls down due to less production which is the result of agricultural field worker’s bad health. In this study, a multi epitope vaccine was designed against Dracunculus medinensis by using immune-informatics. The vaccine was designed by using T-Cell and B-Cell epitopes derived from Dracunculus medinensis proteins (Lactamase-B domain-containing protein, G-Domain containing protein and Ferrochelatase) in addition to Adjuvants and Linkers. The tertiary structure, physiochemical properties and immunogenic elements of vaccine were achieved. The validation of tertiary structure was accessed, and quality was achieved. In addition, the world coverage of parasite’s CTL and HTL epitopes is 95.61%. The stability of the chimeric vaccine was achieved through disulfide engineering. The molecular docking with Toll Like Receptor 4 (TLR-4) of vaccine showed its binding efficiency followed by Molecular Dynamic Simulation. The immune simulation suggested the mediated cell immunity and repeated antigen clearance. At the end, the optimized codon was used in in silico cloning to ensure vaccine’s higher exposure in bacterium E. coli strain K12. With further assessments, it is believed that the proposed multi epitope vaccine has strong immunogen to control Dracunculus medinensis which may result in better social and economic conditions of endemic regions.

Introduction Tuberculosis is common in Pakistan. Due to various factors including socioeconomic factors, compliance is poor to anti-tuberculosis drugs, leading to resistance. We aim to determine the prevalence of Multidrug resistance (MDR) tuberculosis in Pakistani population.Methods A prospective observational study was conducted from April 1, 2019, to December 31, 2019, in the Pulmonology department of a tertiary care hospital in Pakistan. Culture and sensitivity were assessed using a sputum sample or, in cases of an absent sputum sample, from Broncho alveolar lavage.ResultsApproximately 71.3% percent patients who had tuberculosis were found to be resistant to Isoniazid and around 48.6% did not respond to Rifampin. Multi-drug resistant was found in 29.4% participants.ConclusionMulti-drug resistance tuberculosis is very prevalent in Pakistan, which may increase burden on health care system and may lead to various complications of tuberculosis.

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.

In the framework of maritime surveillance, vessel detection techniques based on spaceborne Synthetic Aperture Radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. The paper deal with this topic presenting a novel approach exploiting a cascade application of a pre-screening, and discrimination phase. The latter leverage the SAR spectrum by means of sub-looks analysis. For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images. For a future syngergic exploitation of more SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM and COSMO-SkyMed images, is comprehensive of multiple images gathered over the same area with short time lag (below 15 minutes). Finally, the diversified processing chains and the results for each mission product and scenarios are discussed. Being the first dataset of SLC (Single Look Complex) SAR multi-frequency data, the present work intends to encourage additional research in this promising field of research.

Biometric fingerprint identification hinges on the reliability of its sensors, however, calibrating and standardizing these sensors poses significant challenges, particularly in regard to repeatability and data diversity. To tackle these issues, we propose methodologies for fabricating synthetic 3D fingerprint targets, or phantoms, that closely emulate real human fingerprints. These phantoms enable the precise evaluation and validation of fingerprint sensors under controlled and repeatable conditions. Our research employs laser engraving, 3D printing, and CNC machining techniques, utilizing different materials. We assess the phantoms' fidelity to synthetic fingerprint patterns, intra-class variability, and interoperability across different manufacturing methods. The findings demonstrate that a combination of laser engraving or CNC machining with silicone casting produces finger-like shaped phantoms with high accuracy and consistency for rolled fingerprint recordings. For slap recordings, direct laser engraving of flat silicone targets excels and in the contactless fingerprint sensor setting, 3D printing and silicone filling provides the most favorable attributes. Our work enables a comprehensive, method-independent comparison of various fabrication methodologies, offering a unique perspective on the strengths and weaknesses of each approach. This facilitates a broader understanding of fingerprint recognition system validation and performance assessment.

In this study, a novel flexible ethanol gas sensor was created by the deposition of CoFe2O4 (CFO) thin film was on a thin mica substrate using pulsed laser deposition. Transition electron microscopy (TEM) investigations clearly demonstrated the successful growth of CFO on the mica, where a well-defined interface was observed. Ethanol gas-sensing studies showed optimal performance at 200 °C, with the highest response, 19.2, to 100 ppm ethanol. Operating the sensor in self-heating mode under 7 V applied voltage, which was corresponds to a temperature of approximately 200 °C, produced a maximal response to ethanol of 19.2. This aligned with the highest responses observed during testing at 200 °C, confirming the sensor’s accuracy and sensitivity to ethanol under self-heating conditions. In addition, the sensor exhibited good selectivity to ethanol and excellent flexibility; maintaining its high performance after bending and tilting up to 5000 times. As this is the first report on flexible self-heated CFO gas sensors, we believe that this research holds great promise for the future development of high-quality sensors based on this approach.

Effective detection of isopropyl methylfluorophosphonate (GB, sarin), a type of organophosphine poisoning agent, is an urgent issue to be addressed in maintaining public safety. In this research, a gas-sensitive film material defined as poly (4-hydroxy-4,4-bis trifluoromethyl) - butyl-1-enyl) - si-loxane (SXFA) with the structure of hexafluoroisopropyl (HFIP) functional group was synthesized by using methyl vinylpropyl dichlorosilane and hexafluoroacetone trihydrate as initial materials. Synthesis process products were characterized by FTIR. SXFA was prepared on a 200 MHz shear surface wave delay line with spin coating method for GB detected. Detection limit of ＜ 0.1 mg/m3 was obtained through conditional experiments. Meanwhile, we also obtained the maximum re-sponse of 2.168 mV at 0.1 mg/m3 concentration, which indicting a much lower detection limit of SAW-SXFA sensor. Additionally, the maximum response standard deviation of 0.11 mV with a co-efficient of variation of 0.01, as well as the maximum recovery standard deviation of 0.22 mV with a coefficient of variation of 0.02 were also obtained through 5 repeated experiments. Results showed that the SAW-SXFA sensor has strong selectivity and reproducibility, good selectivity, positive detection ability, high sensitivity, and fast alarm performance for sarin detection.

Ischemia, the inadequate blood flow, can arise from pre-existing or traumatic events, remain an undetectable issue, and impact the body's ability to provide oxygen to necessary limbs, organs, muscles, or tissue. New technology involving wearable ultrasonic devices allows medical professionals to gain real-time insight into the cardiovascular system of their patients. A non-invasive, postage-stamp-sized ultrasonic sensor can be attached to a patient, allowing for continuous monitoring of the patient’s blood pressure outside of the hospital. After reviewing 16 papers on ultrasonic sensors, this paper intends to review the current use of wearable ultrasonic sensors and the advantages and limitations of the technology used to obtain accurate blood pressure readings. This review will bring attention to the evolving and expanding world of wearable ultrasonic sensors for medical applications.

Cellulose-based carbon (CBC) has been widely concerned with its porous structure, high specific surface area, and is liable to adsorb gas molecules and macromolecular pollutants. However, the application of CBC in gas sensing has been little studied. In this paper, ZnO/CBC heterojunction was formed by means of simple co-precipitation and high temperature carbonization. As a new ammonia sensor, the prepared ZnO/CBC sensor can detect ammonia compared with that of the previous pure ZnO ammonia sensor can not at room temperature. It has great gas sensing response, stability and selectivity to ammonia concentration at 200 ppm. This study provides a new idea for the design and synthesis of biomass carbon-metal oxide composites.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

In this paper, we introduced a comprehensive study, based on both numerical and experimental analyses, of side polished (SP) single mode fibers (SMF) to investigate their evanescent field interaction with air and liquid analytes. In particular, the finite element method (FEM) and the beam propagation method (BPM) are employed to predict the optical properties of the SP-SMF. An ad-hoc experimental setup has been designed and built to characterize the side polished single mode fiber when air, water, and isopropanol are set in the side polished region. The sensitivity of the analytes is obtained as 1.207 V/RIU. The performance in terms of effective refractive index and transmittance are reported to show how these SP-SMF can be efficiently used for calculating the liquid refractive index. The simulation and experimental results display the significant performance of the SP-SMF as a sensing element.

Regulatory monitoring networks are often too sparse to support community-scale PM2.5 exposure assessment while emerging low-cost sensors have the potential to fill in the gaps. Recent advances in air quality monitoring have produced portable, easy-to use, low-cost, sensor-based monitors, which has given a new dimension to the air pollutant monitoring and has democratized the air quality monitoring process by making monitors and results directly available at community level. This study used PurpleAir(c) sensors for PM2.5 assessment in California, USA. Evaluation of PM2.5 from sensors included Quality Assurance &amp; Quality Control (QAQC) procedures, assessment with respect to reference monitored PM2.5 concentrations, and formulation of a decision support system integrating these observations using geostatistical techniques. The hourly and daily average observed PM2.5 concentrations from PurpleAir monitors followed the trends of observed PM2.5 at regulatory monitors. PurpleAir monitored PM2.5 also captured the peak PM2.5 concentrations due to incidents like forest fire. In comparison with reference monitored PM2.5 levels, it was found that PurpleAir PM2.5 concentrations were mostly higher. The most important reason for PurpleAir higher PM2.5 concentrations was the inclusion of moisture or water vapor as aerosol in contrast to measurements of PM2.5 excluding water content in FEM/FRM and non-FEM/FRM monitors. On long term assessment (2016-2020), R2 was between 0.54 and 0.86 at selected collocated PurpleAir and regulatory monitors for hourly PM2.5 concentrations. Past research studies have been conducted for mostly shorter time periods (&lt;3-4 months) that resulted in higher R2 values between 0.80 to 0.98. This study aims to provide reasonable estimations of PM2.5 concentrations with high spatiotemporal resolutions based on statistical models using PurpleAir measurements. The methods of Kriging and IDW, geostatistical interpolation techniques, showed similar spatio-temporal patterns. Overall, this study revealed that low-cost, sensor based PurpleAir sensors could be effective and reliable tools for episodic and long-term ambient air quality monitoring.

This chapter aims to construct a relatively complete, universal, and highly reliable road surface state monitoring and perception system through the research of the A1 contact road reconstruction project of an international airport (hereinafter referred to as the “airport”). The system design is based on on-the-spot investigation, theoretical analysis, and engineering practice, using vibrating string type and resistive strain sensors as sensing means, real-time high-frequency signal acquisition technology as the guide, 4G router for wireless communication technology as the media, and storage technology for monitoring system based on server storage terminals. In combination with engineering background, aircraft motion state, main landing gear configuration, sensor selection and evaluation, and other major factors, the actual monitoring information needs of the plane are fully taken into account, as well as the difference in sensor information types, and the system design is carried out by stratification and classification.

Detecting low concentrations of thyroxine hormone (T4) is of utmost importance to prevent diseases and medical issues caused by hypothyroidism. In this work, we propose the use of a simple technique for T4 sensing, the well-known surface-enhanced Raman spectroscopy (SERS). Spherical Au and Ag nanoparticles (NPs) and functionalized with ascorbic acid and tannic acid, respectively. They synthesized by a seed-mediated growth method, were used as SERS substrates to quantify T4 at different concentrations. The NPs were characterized by UV-VIS spectroscopy and scanning electron microscopy. Both, Au and Ag NPs, have an average diameter of 50 nm, the first ones have a surface plasmon resonance at 537 nm, while the latter have it at 421 nm. It was noticed the SERS substrates are composed of isolated and agglomerated NPs. From theoreti-cal-numerical calculations, we identified the hot spots |E| of the agglomerate NPs is at least 7 times more intense than that of the isolated NPs. We show the substrates can detect up to 0.01 mM and, for the range of concentration studied, the Ag substrate is more sensitive than Au. Thus, the proposed substrates and the SERS technique constitute a potential prospect for sensing hormones and organic molecules at low concentrations.

This study aimed to improve sensitivity of ferrous particle sensors used in various mechanical systems such as wind power gearboxes to detect abnormalities by measuring the amount of ferrous wear particles generated by metal-to-metal contact. Existing sensors collect ferrous particles using a permanent magnet. However, its ability to detect abnormalities is limited because it only measures amounts of ferrous particles collected on the top of the sensor. To overcome this limitation, this study evaluated sensibility of an existing sensor using a multi-physics analysis method and improved it by changing the core shape inside the sensor. The detection ability of the improved sensor was analytically shown to be better than the existing sensor. This study highlights the use of analytical methods and multi-physics analysis for developing a ferrous particle sensor and presents a method to compare sensibility analytically. Results of the improved sensor are expected to enhance the ability to detect abnormalities in the lubrication system where ferrous wear particles are generated. This study will contribute to the development of more effective ferrous particle sensors, which can potentially improve the performance and reliability of mechanical systems.

The fourth industrial revolution, also known as Industry 4.0, has led to an increased transition towards automation and reliance on data-driven innovations and strategies. Companies in the manufacturing sector are heavily integrating Industry 4.0 technologies, including cloud compu-ting, cyber-physical systems (CPS), big data analytics, horizontal and vertical system integration, the internet of things (IoT), and additive manufacturing (3d printing). The interconnected systems and processes have significantly increased operational efficiency, enhanced organizational capacity to monitor and control functions, reduced costs, and improved product quality. One significant way that companies have achieved these benefits is by integrating diverse sensor technologies within these innovations, allowing critical data collection on products, equipment performance, and maintenance. The sensors connect systems and machines, allowing them to communicate and track operations for enhanced operations. While numerous research has been conducted to show the role of sensors in industry 4.0, limited studies show how these innovations can leverage product design to maximize benefits and opportunities. Given the rapidly changing market conditions, Industry 4.0 requires new products and business models to ensure companies adjust to the current and future changes. These requirements call for the evolutions in product design processes to accommodate design features and principles applicable in the current dynamic business environment. This research paper employs a systematic bibliometric literature review (LRSB) methodology to explore and synthesize data on how Industry 4.0 and sensors can leverage product design. The results show that various product design features create opportunities to be leveraged to guarantee the success of Industry 4.0 and sensor technologies. However, the research also identifies numerous challenges that undermine the ongoing transition towards intelligent factories and products.

Glyphosate　(GLYP)　is a broad-spectrum, non-selective, organic phosphine post emergence herbicide registered for use on many food and non-food field. Herein, we developed a biosensor (Mbs@dsDNA) based on carboxylated modified magnetic beads incubated with NH2-polyA and then hybridized with polyT-glyphosate aptamer and complementary DNA. Afterward, a quantitative detection method based on qPCR was established.　When the glyphosate aptamer on Mbs@dsDNA specifically recognized glyphosate, a complementary DNA is released and then enters the qPCR signal amplification process. The linear range of the method was 0.1-5 μg/mL, and the detection limit was set at 0.1 μg/mL. The recoveries in tap water were ranged from 103.4 ~ 104.9%, and the relative standard deviations (RSDs) were < 1%. The aptamer proposed in this study has a good potential for recognizing glyphosate. The detection method combined with qPCR might have a good application prospect in detecting and supervising other pesticide residues.

Magnetoelectric sensors based on microelectromechanical cantilevers consisting of TiN / AlN / Ni are investigated using finite element simulations in regard of the anisotropy of the E effect and its impact on the sensor sensitivity. The E effect is derived from the anisotropic magnetostriction and magnetization of single crystalline Nickel. The magnetic hardening of Nickel in saturation is demonstrated for the (110) as well as the (111) orientation. It is shown further, that magnetostrictive bending of the cantilever has a negligible impact on the eigenfrequency and thus sensitivity. The intrinsic E effect of Nickel decreases in magnitude depending on the crystal orientation when integrated into the magnetoelectric sensor design. The transitions of the individual magnetic domain states are found to be the dominant influencing factor on the sensitivity for all crystal orientations. The peak sensitivity was determined to 41.3 T-1 for (110) in-plane orientated Nickel at a magnetic bias flux of 1.78 mT. It is found, that the transition from domain wall shift to domain rotation along the hard axes yields much higher sensitivity than the transition from domain rotation to magnetization reversal. The results achieved in this work show that Nickel as hard magnetic material is able to reach almost identical sensitivities as soft magnetic materials, such as FeCoSiB.

The increasingly affordable price point of terrestrial laser scanners has led to a democratization of instrument availability, but the most common low-cost instruments have yet to be compared in terms of the consistency to measure forest structural attributes. Here, we compared two low-cost terrestrial laser scanners (TLS): the Leica BLK360 and the Faro Focus 120 3D. We evaluate the instruments in terms of point cloud quality, forest inventory estimates, tree-model reconstruction, and foliage profile reconstruction. Our direct comparison of the point clouds showed reduced noise in filtered Leica data. Tree diameter and height were consistent across instruments (4.4% and 1.4% error, respectively). Volumetric tree models were less consistent across instruments, with ~29% bias, depending on model reconstruction quality. In the process of comparing foliage profiles, we conducted a sensitivity analysis of factors affecting foliage profile estimates, showing a minimal effect from instrument maximum range (for forests less than ~50 m in height) and surprisingly little impact from degraded scan resolution. Filtered unstructured TLS point clouds must be artificially re-gridded to provide accurate foliage profiles. The factors evaluated in this comparison point towards necessary considerations for future low-cost laser scanner development and application in detecting forest structural parameters.

We consider the problem of calibrating distance measurement of Light Detection and Ranging (lidar) sensor without using additional hardware, but rather exploiting assumptions on the environment surrounding the sensor during the calibration procedure. More specifically we consider the assumption of calibrating the sensor by placing it in an environment so that its measurements lie in a 2D plane that is parallel to the ground, and so that its measurements come from fixed objects that develop orthogonally w.r.t. the ground, so that they may be considered as fixed points in an inertial reference frame. We moreover consider the intuition that moving the distance sensor within this environment implies that its measurements should be such that the relative distances and angles among the fixed points above remain the same. We thus exploit this intuition to cast the sensor calibration problem as making its measurements comply with this assumption that “fixed features shall have fixed relative distances and angles”. The resulting calibration procedure does thus not need to use additional (typically expensive) equipment, nor deploying special hardware. As for the proposed estimation strategies, from a mathematical perspective we consider models that lead to analytically solvable equations, so to enable deployment in embedded systems. Besides proposing the estimators we moreover analyse their statistical performance both in simulation and with field tests, reporting thus the dependency of the MSE performance of the calibration procedure as a function of the sensor noise levels, and observing that in field tests the approach can lead to a ten-fold improvement in the accuracy of the raw measurements.

To quantify damage to reinforced concrete (RC) column members after an earthquake, an engineer needs to know the maximum applied force that was generated by the earthquake. Therefore, in this work, piezoceramic transducers are used to detect the applied force on an RC column member under dynamic loading. To investigate the use of post-embedded piezoceramic sensors in detecting the force that is applied to RC columns, eight full-size RC column specimens with various failure modes are tested under specific earthquake loadings. Post-embedded piezoceramic sensors are installed at a range of depths (70-80 mm) beneath the surface of a column specimen to examine the relationship between the signals that are obtained from them and the force applied by the dynamic actuator. The signals that are generated by the post-embedded piezoceramic sensors, which correlate with the applied force, are presented. These results indicate that the post-embedded piezoceramic sensors have great potential as tools for measuring the maximum applied force on an RC column in an earthquake. Restated, signals that are obtained from post-embedded piezoceramic sensors on an RC column in an earthquake can be used to determine the applied force and corresponding damage or residual seismic capacity.

Paper-based sensors, microfluidic platforms and electronic devices have attracted attention in the past couple of decades because they are flexible, can be recycled easily, environmentally friendly, and inexpensive. Here we report a paper aptamer-based potentiometric sensor to detect the whole Zika virus for the first time with a minimum sensitivity of 2.6 nV/Zika and the minimum detectable signal (MDS) of 0.8x1e6 Zika. Our paper sensor works very similar to a P-N junction where a junction is formed between two different wet regions with different electrochemical potentials near each other on the paper. These two regions with slightly different ionic contents, ionic species and concentrations, produce a potential difference given by the Nernst equation. Our paper sensor consisted of a 2-3 mm x 10 mm segments of a paper with a conducting silver paint contact patches on its two ends. The paper is soaked in a buffer solution containing aptamers designed to bind to the capsid proteins on Zika. Atomic force microscopy studies were carried out to show both the aptamer and Zika become immobilized in the paper. We then added the Zika (in its own buffer or simulant Urine) to the region close to one of the silver-paint contacts. The Zika virus (40 nm diameter with 43 kDa or 7.1x10-20 gm weight), became immobilized in the paper’s pores and bonded with the resident aptamers creating a concentration gradient. The potential measured between the two silver paint contacts reproducibly became more negative as upon adding the Zika. We also showed that an LCD powered by the sensor, can be used to detect the sensor output.

Paper-based sensors, microfluidic platforms and electronic devices have attracted attention in the past couple of decades because they are flexible, can be recycled easily, environmentally friendly, and inexpensive. Here we report a paper aptamer-based potentiometric sensor to detect the whole Zika virus for the first time with a minimum sensitivity of 2.6 nV/Zika and the minimum detectable signal (MDS) of 1.2x10⁶ Zika. Our paper sensor works very similar to a P-N junction where a junction is formed between two different wet regions with different electrochemical potentials near each other on the paper. These two regions with slightly different ionic contents, ionic species and concentrations, produce a potential difference given by the Nernst equation. Our paper sensor consisted of a 2-3 mm x 10 mm segments of a paper with a conducting silver paint contact patches on its two ends. The paper is soaked in a buffer solution containing aptamers designed to bind to the capsid proteins on Zika. Atomic force microscopy studies were carried out to show both the aptamer and Zika become immobilized in the paper. We then added the Zika (in its own buffer) to the region close to one of the silver-paint contacts. The Zika virus (40 nm diameter with 43 kDa or 7.1x10^-20 gm weight), became immobilized in the paper’s pores and bonded with the resident aptamers creating a concentration gradient. The potential measured between the two silver paint contacts reproducibly became more negative as upon adding the Zika. We also showed that an LCD powered by the sensor, can be used to detect the sensor output.

A method for infrared and cameras sensor fusion, applied to indoor positioning in intelligent spaces, is proposed in this work. The fused position is obtained with a maximum likelihood estimator from infrared and camera independent observations. Specific models are proposed for variance propagation from infrared and camera observations (phase shifts and image respectively) to their respective position estimates and to the final fused estimation. Model simulations are compared with real measurements in a setup designed to validate the system. The difference between theoretical prediction and real measurements is between 0.4 cm (fusion) and 2.5 cm (camera), within a 95% confidence margin. The positioning precision is in the cm level (sub-cm level can be achieved at most tested positions) in a 4x3 m locating cell with 5 infrared detectors on the ceiling and one single camera, at distances from target up to 5 m and 7 m respectively. Due to the low cost system design and the results observed, the system is expected to be feasible and scalable to large real spaces.

The paper describes preliminary studies on the influence of humidity on the electrical resistance of a textile sensor made of carbon fibers. The concept of the sensor refers to externally bonded fiber reinforcement commonly used to strengthen building structures. However, the zig-zag arrangement of carbon fiber tow allows measuring strains, as it is done in popular resistive strain gauges. The sensor tests proved its effectiveness in the measurement of strains, but also showed a high sensitivity to changes in the temperature and humidity which unfavorably affects the readings and their interpretation. The influence of these factors must be compensated. Due to the size of the sensor, there is not possible electrical compensation by the combining of several sensors into the half or full Wheatstone bridge circuit. Only mathematical compensation based on known humidity resistance functions is possible. The described research is the first step to develop such relations. The tests were carried out at temperatures of 10 °C, 20 °C and 30 °C, with changing the humidity in the range of 30-90%.

In this work, an embroidered textile moisture sensor is presented. The sensor is based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidery conductor yarn composed by 99% pure silver plated nylon yarn 140/17 dtex. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 25% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity. Moreover, the reproducibility of the sensor performance subject to the manufacturing process variability and washing process is also evaluated. The results show that the manufacturing variability introduce a moisture measurement error up to 4%. The washing process impact on the sensor behavior after applying the first washing cycle implies a sensitivity reduction higher than 14%. Despite these effect, the textile sensor keeps its functionality and can be reused in standard conditions. Therefore, these properties point out the usefulness of the proposed sensor to develop wearable applications on health and fitness scope including the user needs to have a life cycle longer than one-time use

Multiple sensor nodes known as detection stations make the sensor networks; each node is light and portable. Every sensor node contains power source, microcomputer, transducer and transceiver. Power source provides power to each node. Micro-computer is used for storing and processing the output coming from the sensors. The transducer is used to generate the signals and the transceiver is used to receive and transmit data to the central computer. Eavesdropping gets facilitated with wireless communication, and it has many useful applications in military, homeland, hostile and uncontrolled environments. So it is prone to the high level of security. The process in which information is gathered to form a summarized type for analysis is known as data aggregation, as it is used to reduce the energy consumption in wireless sensor networks. The security issues have become crucial in data aggregation, especially when gets deployed in hostile and remote environment. In wireless sensor networks many secure aggregations have been proposed. It still faces some resource constrained that’s why new techniques are needed. In our survey we will discuss those approaches and their pros and cons.

Human motion analysis using inertial measurement units (IMUs) has recently been shown to provide accuracy similar to the gold standard, marker-based optical motion capture, but at much lower costs and while being less restrictive and time-consuming. However, IMU-based motion analysis requires precise knowledge of the orientation in which the sensor is attached to the body segments. This knowledge is commonly obtained via an anatomical calibration procedure based on precisely defined poses or motions, which is time-consuming and error-prone. In the present work, we propose a self-calibrating approach for magnetometer-free joint angle tracking that is suitable for joints with two degrees of freedom (DoF), such as the elbow, ankle, and metacarpophalangeal finger joints. The proposed methods exploit kinematic constraints to simultaneously identify the joint axes and the heading offset. The experimental evaluation shows that the proposed methods are able to estimate plausible and consistent joint axes from just ten seconds of arbitrary elbow joint motion. Comparison with optical motion capture shows that the proposed methods yield joint angles with similar accuracy as a conventional IMU-based method while being much less restrictive. Therefore, the proposed methods improve the practical usability of IMU-based motion tracking in many clinical and biomedical applications.

This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent localization is performed using time-of-arrival (TOA) data which are indicative of the distance between anchors and the target thereby achieving range-based localization. The short word-length techniques considered are delta modulation and sigma-delta modulation. The energy efficiency is due to the reduction of the data volume transmitted from anchors to the fusion center by employing any of the two delta modulation variants with compressive sensing techniques. Delta modulation allows the transmission of one bit per TOA sample. The communication energy efficiency is increased by RⱮ, R≥1, where R is the sample reduction ratio of compressive sensing and Ɱ is the number of bits originally present in a TOA-sample word. It is found that the localization system involving sigma-delta modulation has a superior performance to that using delta-modulation or pure compressive sampling alone, in terms of both energy efficiency and localization error in the presence of TOA measurement noise, owing to the noise shaping property of sigma-delta modulation.

A Wireless Body Area Sensor Network (WBASN) is combination of numerous sense nodes, positioned onto/close or inside a person body. Wireless Body Area Sensor Networks (WBASN) is a developing automation trend that exploits wireless sensor nodes to put instantaneous wearable well-being of ill person to improve individual’s existence. The sensor nodes might be used outwardly to observe abundant health parameters (like heart activity, blood pressure and cholesterol) of an ill person at a vital site within hospital. Hence the goal of WBASN is much crucial, enhancing the lifetime of nodes is compulsory to sustain many issues such as utility and efficiency. It is essential to evaluate time that when the first node will die it we want to refresh or change the battery reason is that loss of crucial information is not tolerable. The lifetime is termed as the time interval when a first node dies out due to battery exhaustion. In our proposed protocol life time of a network is the main concern as well other protocol related issues such as throughput, path loss, and residual energy. Bio-sensors are used for deployment on human body. Poisson distribution and equilibrium model techniques have been used for attaining the required results. Multi-hop network topology and random network node deployment used to achieve minimum energy consumption and longer network lifetime.

Deep convolutional neural network (CNN) has shown their great advantages in the single image deraining task. However, most existing CNN-based single image deraining methods still suffer from residual rain streaks and details lost. In this paper, we propose a deep neural network including the Multi-scale feature extraction module and the channel attention module, which are embed in the feature extraction sub-network and the rain removal sub-network respectively. In the feature extraction sub-network, the Multi-scale feature extraction module is constructed by a Multi-layer Laplacian pyramid, and is then integrated multi-scale feature maps by a feature fusion module. In the rain removal sub-network, the channel attention module, which assigns different weights to the different channels, is introduced for preserving image details. Experimental results on visually and quantitatively comparison demonstrate that the proposed method performs favorably against other state-of-the-art approaches

Defect detection in ferromagnetic substrates is often hampered by non-magnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of non-magnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multi-frequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3 % for an extended lift-off range of up to 10 mm.

Porous ceramics can be realized by different methods and are used for manifold applications, like cross-flow-membranes or wall-flow-filters, porous burners, solar receivers, structural design elements or catalytic supports. Within this paper three different alternative process routes are presented, which can be used to manufacture porous ceramic components with different properties or even graded porosity. The first process route bases on additive manufacturing (AM) of macro porous ceramic components, the second on AM of a polymeric template, which is used to manufacture porous ceramic components via replica technique. Finally, the third process route bases on an AM technology, which allows the manufacturing of multi-material or multi-property ceramic components, like components with dense and porous volumes in one complex shaped component.

In this article, we introduce some multi-messenger studies of blazars. Main contents contain the following parts, 1. the subclasses of blazars and the observational characteristics, 2. emission variabilities from the multi-messenger observations, 3. the physical origin for the multi-messenger studies. Based on mid-IR observations collected from the $WISE$ database, we collect two sources (BZQ J1700+6830 and BZQ J1842+6809) to analyze the mid-IR variabilities. \\ (1) For BZQ J1700+6830, the period is $P\approx$ 42 hr at the four bands ($W1$, $W2$, $W3$, $W4$); for BZQ J1842+6809, the period is $P\approx$ 123 hr at the two bands ($W1$, $W2$). \\ (2) Using the periodicities, we calculate that the central black hole mass ($BH$) should be $M = (5.44\sim33.0)\times10^8M_{\odot}$ for BZQ J1700+6830 and $M = (1.13\sim6.88)\times10^9M_{\odot}$ for BZQ J1842+6809.\\ (3) For the two sources, during the flaring stage, we find anti-clockwise variation trends based on the time-based relations built by the spectral indices ($\alpha$) and flux densities ($F$).\\ (4) We calculate the Doppler factor ($\delta$) when the sources are in the dimming or brightening stages, and find that with the frequency increasing, the Doppler factor become stronger.

The paper considers new effects of the nanoscale state of matter, which open up prospects for the creation of electronic devices using new physical principles. The contact of chemically homogeneous different sizes hydrated nanoparticles of yttrium-stabilized zirconium oxide (ZrO2 – x %mol Y2O3, x=0, 3, 4, 8; YSZ) with particle sizes of 7.5 nm and 7,5 nm; 7.5 nm and 9 nm; 7.5 nm and 11 nm; 7.5 nm and 14 nm in the form of compacts obtained using high hydrostatic pressure (HP-compacts of 300MPa) was studied at direct and alternating current. A unique size effect of the nonlinear (semiconductor) dependence of the electrical properties (in the region U <2.5 V, I ≤ 2.7 mA) of the contact of different-sized YSZ nanoparticles of the same chemical composition is revealed, which indicates the possibility of creating semiconductor structures of a new type based on chemically homogeneous nanostructured systems. The electronic structure of the near-surface regions of nanoparticles of a special type of oxide materials and the possibility, on this basis, to obtain specifically rectifying properties of the contacts were studied theoretically. Models of surface states of the Tamm type are constructed, but considering the Coulomb long-range action. The discovered variance and its dependence on the curvature of the surface of nanoparticles made it possible to study the conditions for the formation of a contact potential difference in cases of nanoparticles of the same radius (synergistic effect), different radii (doped and undoped variants), as well as to discover the possibility of describing a group of powder particles from material within the Anderson model. The established effect makes it possible to solve the problem of diffusion instability of semiconductor heterojunctions and opens up prospects for creating electronics devices with a fundamentally new level of properties for use in various fields of the national economy and breakthrough critical technologies.

Fluorescence microscopy provides an unparalleled tool for imaging biological samples. However, producing high-quality volumetric images quickly and without excessive complexity remains a challenge. Here, we demonstrate a simple multi-camera structured illumination microscope (SIM) capable of simultaneously imaging multiple focal planes, allowing for the capture of 3D fluorescent images without any axial movement of the sample. This simple setup allows for the acquisition of many different 3D imaging modes, including 3D time lapses, high-axial-resolution 3D images, and large 3D mosaics.

Our work uses Iterative Boltzmann Inversion (IBI) to study the coarse-grained interaction between 20 amino acids and the representative carbon nanotube CNT55L3. IBI is a multi-scale simulation method that has attracted the attention of many researchers in recent years. It can effectively modify the coarse-grained model derived from the Potential of Mean Force (PMF). IBI is based on the distribution result obtained by All-Atom molecular dynamics simulation, that is, the target distribution function, the PMF potential energy is extracted, and then the initial potential energy extracted by the PMF is used to perform simulation iterations using IBI. Our research results have gone through more than 100 iterations, and finally, the distribution obtained by coarse-grained molecular simulation (CGMD) can effectively overlap with the results of all-atom molecular dynamics simulation (AAMD). In addition, our work lays the foundation for the study of force fields for the simulation of the coarse-graining of super-large proteins and other important nanoparticles.

Multi-morbidity and polypharmacy are common in older people and pose a challenge for health and social care systems especially in context of global population ageing. They are complex and interrelated concepts in the care of older people that require early detection and patient centred decision making that are underpinned by the principles of multidisciplinary led comprehensive geriatric assessment (CGA). Personalised care plans need to remain responsive and adaptable to the needs of a patient, enabling an individual to maintain their independence.

Polyphenols are the most common organic compounds in wine. They improve both the sensory aspects of wine and human health by activating antioxidant systems. Therefore, there is a great need for a simple, fast and accessible method to determine the polyphenol content of wine. The aim of this study is to characterize polyphenolic compounds in natural wine samples using an electrochemical method and a modified carbon paste electrode with TiO2 nanoparticles. This work is motivated by the promising improvement of the sensing properties of a TiO2 nanoparticle-modified carbon paste electrode observed in the electrooxidation of different polyphenols. Since the voltammetric response of wine is largely irreversible, another motivation was the possibility of improving the processing of voltammograms to obtain data indicative of wine polyphenols, based on the approach described in the seminal work by Espinoza et al. The modified electrode studied provides an improved and reproducible voltammetric response of gallic acid in wine samples and provides a good basis for further development of an integrated sensor/data system with the possibility of wider application for the quantification of gallic acid as a flavor and visually relevant parameter in winemaking.

Conventional methods for pathogen detection in water rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 hours to up to a week. However, in recent years, significant efforts have been made towards the development of biosensing technologies enabling rapid and close-to-real-time detection of waterborne pathogens. In previous studies, we developed a plastic optical fiber (POF) immunosensor using an optoelectronic configuration consisting of a U-Shape probe connected to an LED and a photodetector. Bacterial detection was evaluated with the immunosensor immersed in a bacterial suspension in water with a known concentration. Here, we report on the sensitivity of a new optoelectronic configuration consisting of two POF U-Shape probes, one as the reference and the other as the immunosensor, for the detection of Escherichia coli. In addition, another way of detection was tested where the sensors were calibrated in the air, before immersed in bacterial suspension and then read in the air, making the immunosensor more sensitive and with a faster detection time. This new sensor detected the presence of E. coli at 104 CFU/mL in less than 10 minutes. Currently sub 10 minutes is faster than previous studies using fiber-optic based biosensors. It is also a much simpler and quicker methodology when compared with conventional laboratory technology.

Rainwater infiltration presents substantial challenges for urban wastewater management systems. This article delves into enhancing the quality of wastewater systems by proposing a novel device designed to tackle this issue comprehensively. The focal point of our research revolves around the conceptualization, construction, rigorous testing, and the potential multifaceted applications of this innovative wastewater device. Our study is dedicated to assessing the viability of a cutting-edge apparatus that empowers municipal entities in swiftly identifying rainwater ingress points within channels during precipitation events. Our findings vividly showcase the device's remarkable capability to directly measure moisture levels along the channel's path, eliminating the arduous need for manual data input, extensive data collection, and intricate water analysis procedures. To ensure the seamless flow of both sewage and water within the sewer channel, the use of a relatively slender strap is conventionally favored. However, factoring in the requisite structural robustness, we recommend a minimum thickness of 4 mm for 3D printing applications. For instances where maintaining the channel's cross-sectional area integrity is paramount, opting for a armlet with wet circuit measurement thickness of up to 7 mm is prudent. In the realm of material selection, our investigation advocates for the utilization of PC/ABS (polycarbonate/ Acrylonitrile Butadiene Styrene), ABS, ASA (Acrylonitrile Styrene Acrylate), or HIPS (High Impact Polystyrene) for the strap housing. For sewer diameters surpassing 315 mm, the application of thin-walled PVC (Poly Vinyl Chloride) emerges as a practical recommendation. Notably, the incorporation of PVC flat bars is discouraged, as their presence might potentially hinder the fluidity of sewage flow, thereby compromising the precision of wet circuit measurements. The pivotal innovation lies in the armlet with wet circuit measurement system, harboring immense potential for broad-scale integration across municipal facilities. This solution emerges as a streamlined and efficient strategy, offering a comprehensive avenue for continuously monitoring, fine-tuning, and optimizing the structural soundness and operational efficacy of sewer systems.

Soluble noble metal salts are widely used for loading noble metals as nano-catalysts in many applications. In this paper, Pt-SnO2 composite nanoceramics were prepared from SnO2 nanoparticles and H2PtCl6 using two Pt-loading methods separately: For the solution reduction method, the H2PtCl6 solution was added to a suspension of SnO2 and zinc powder to form Pt on SnO2 nanoparticles; and for the impregnation method, Pt was formed from H2PtCl6 in the course of sintering. Although a series of samples prepared using both Pt loading methods showed a strong response to H2 at room temperature, the ones prepared using the solution reduction method exhibited much better room temperature hydrogen sensing characteristics. For two samples of 0.5 wt% Pt and sintered at 825°C, the response value for the sample prepared using the solution reduction method was 5300 to 1% H2-20% O2-N2, which was much larger than that of 150 for the sample prepared using the impregnation method. Samples prepared using the two Pt loading methods have similar microstructures as characterized by XRD, FESEM, EDS, TEM, and HRTEM. However, the residual chlorine content in those using the impregnation method was found to be higher than that using the solution reduction method through analysis. It is proposed that the striking difference in the room temperature hydrogen sensing characteristics among samples prepared using these two different Pt loading methods separately resulted from their different chlorine removal process. This study demonstrates the importance of a proper method in loading noble metals from their soluble salts as nano-catalysts in many applications.

Pipe leakage is an inevitable phenomenon in water distribution networks (WDNs), leading to energy waste and economic damage. Leakage events can be reflected quickly by pressure values, and the deployment of pressure sensors is significant for minimizing the leakage ratio of WDNs. Concerning the restriction of realistic factors, including project budgets, available sensor installation locations, and sensor fault uncertainties, a practical methodology is proposed in this paper to optimize pressure sensor deployment for leak identification in terms of these realistic issues. Two indexes are identified to evaluate the leak identification ability, that is, detection coverage rate (DCR) and total detection sensitivity (TDS), and the principle is to determine priority to ensure an optimal DCR and retain the largest TDS with an identical DCR. Leakage events are generated by a model simulation and the essential sensors for maintaining the DCR are obtained by subtraction. In the event of a surplus budget, and if we suppose the partial sensors have failed, then we can determine the supplementary sensors that can best complement the lost leak identification ability. Moreover, a typical WDN Net3 is employed to show the specific progress, and the result shows that the methodology is largely appropriate for real projects.

This work presents an LC resonant passive wireless gas sensor with a novel structure designed to mitigate the negative impact of substrate. The LC sensor antenna with the new structure and the reader antenna were designed and optimized utilizing HFSS software to improve the transfer efficiency. The superiority of the designed structure compared with the general ones is highlighted and verified. The change in the substrate capacitance has essentially no interference with the parameters to be measured of the LC sensor. The sensor with the new structure was prepared by combining etching and sputtering methods. The structure of the ZnO nanowires (NWs) was characterized to confirm their high purity and wurtzite crystal structure. The LC gas sensors demonstrated excellent wireless sensing performance including a low detection limit of 0.5 ppm NO2, high response of 1.058 and outstanding stability at 180 °C. The developed new sensor structure not only prevented interference from the substrate during gas sensing testing, but also expanded the choice of sensor substrates, playing a critical role in the development of sensors based on LC resonance principle.

Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, such as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose, however, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally.

This report aimed to know the performance of local mineral-based composite ceramic. The materials used consist of Indonesian local minerals, which are jarosite and manganite minerals as sources of oxide iron and Mangan. The materials were synthesized using the precipitation method, whereas composite ceramic was fabricated using a screen printing method and fired at 600 oC using a furnace. The results of the characterizations indicate that the sample forms three phases on diffraction peaks. The differences in the resistance values in ambient and ethanol environments indicate that the sample has very different responses. The high porosity of the sample greatly support the gas adsorption process. Thus, the sample has a high level of sensitivity. With the above characteristics, the composite ceramic which was fabricated has the potential to be applied to gas sensors, especially ethanol gas sensors.

Locomotor impairment is a high-prevalent and significant source of disability and significantly impacts a large population’s quality of life. Despite decades of research in human locomotion, the challenges of simulating human movement to study the features of musculoskeletal drivers and clinical conditions remain. Most recent efforts in utilizing reinforcement learning (RL) techniques are promising to simulate human locomotion and reveal musculoskeletal drives. However, these simulations often failed to mimic natural human locomotion because most reinforcement strategies have yet to consider any reference data regarding human movement. To address these challenges, in this study, we designed a reward function based on the trajectory optimization rewards (TOR), and bio-inspired rewards, which includes the rewards obtained from reference motion data captured by a single Intertial Moment Unit (IMU) sensor. The sensor was equipped on the participants’ pelvis to capture reference motion data. Also, we adapted the reward function by leveraging previous research in walking simulation for TOR. The experimental results showed that the simulated agents with the modified reward function performed better in mimicking the collected IMU data from participants, which means the simulated human locomotion was more realistic. Also, as this bio-inspired defined cost, IMU data enhanced the agent’s capacity to converge during the training process. As a result, the models’ convergence is faster than those developed without reference motion data. Consequently, human locomotion can be simulated more quicker and in a broader range of environments with a better simulation performance.

The need for miniaturized shear force sensors is expanding, particularly for biomedical applications. Examples include measuring interfacial shear stresses between a human and an external device (e.g., footwear or a prosthesis). However, there are considerable challenges in designing a shear sensor for these applications due to the need for a small package, low power requirements, and resistance to interference from motion artifact and electromagnetic fields. This paper presents the design, fabrication, and characterization sensor that measures two-axis shear force by detecting displacement between a color panel and a red, green, and blue light-sensing photodiode. The sensor response to applied displacements and forces was characterized under benchtop testing conditions. We also present the design of a prototype wireless version of the sensor for integration into footwear. The sensor exhibited strong agreement with gold standard measurements for two axis shear displacements (R2>0.99, RMSE≤5.0 µm) and forces (R2>0.99, RMSE≤0.94 N). This performance, along with the sensor’s scalability, miniaturized form, and low power requirements make it well-suited a variety of biomedical applications.

Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from the hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, less data transmission to the Base station (BS). In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol ( HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. Results show that the proposed routing scheme outperforms two existing ones.

The distributed long-range sensing system using the standard telecommunication single-mode optical fiber in a function of a distributed sensor for sensing of mechanical vibrations is described. Various events generating vibrations such as walking or running person, moving cars, trains and others can be detected, localized and classified. The sensor and related sensing system components were designed and constructed and the system was tested both in the laboratory and in the real situation with 88 km telecom optical link, and the results are presented.

Surveillance along the Kenya-Somalia border has been a big challenge that has continuously puzzled the security personnel, due to insurgency of armed militia Al-Shabaab from Somalia , the Kenyan government proposed construction of a barrier wall. This project developed a low cost wireless sensor network surveillance system to be deployed along the Kenya-Somalia border. The research study utilized two PIR sensor for detecting human intrusion, one motion is detected the sensor transmit the data via an Xbee module. Arduino microcontroller was used to process the data collected by the sensor before transmission. The system developed has two units, the Transmitter unit and a User Graphic interface running on Tuna Term software that displays the received data. During testing, the prototype system detected human intrusion, using the Arduino serial monitor the results were displayed before being package for transmission.

The technological development of piezoelectric materials is crucial for developing wearable and flexible electromechanical devices. There are many inorganic materials with piezoelectric effects, such as piezoelectric ceramics, aluminum nitride, and zinc oxide. They all have very high piezoelectric coefficients and large piezoelectric response ranges. The characteristics of high hardness and low tenacity make inorganic piezoelectric materials unsuitable for flexible devices that require frequent bending. Polyvinylidene fluoride (PVDF) and its derivatives are the most popular materials used in flexible electromechanical devices in recent years and have high flexibility, high sensitivity, high ductility, and a certain piezoelectric coefficient. Owing to increasing the piezoelectric coefficient of PVDF, researchers are committed to optimizing PVDF materials and enhancing their polarity by a series of means to further improve their mechanical–electrical conversion efficiency. This paper reviews the latest PVDF-related optimization materials, related processing and polarization methods, and the applications of these materials such as those in wearable functional devices, chemical sensors, biosensors, and flexible actuator devices for flexible micro-electromechanical devices. We also discuss the challenges of wearable devices based on flexible piezoelectric polymer, consider where further practical applications could be.

Conventional method for monitoring the IgG levels suffered from some apparent problems such as long assay time, multistep processing, and high overall cost. An effective and suitable optical platform for label-free biosensing has been investigated by the implementation of antibody/antigen immunoassays. Thus, the ultrasensitive detection of IgG levels can be achieved by exploiting the dispersion turning point (DTP) existed in the tapered two-mode fibers (TTMFs) due to the sensitivity will reach ±∞ on either side of the DTP. Tracking the resonant wavelength shift it was found that the fabricated TTMF device exhibited limits of detection (LOD) down up to concentrations of 10 fg/mL of IgG in PBS solution. Such immunosensors based on the DTP have great significance on trace detection of IgG due to simple detection scheme, quick response time, and miniaturation.

Indoor navigation systems must deal with absence of GPS signals, since they are only available in outdoor environments. Therefore, indoor systems have to rely upon other techniques for positioning users. Recently various indoor navigation systems have been designed and developed to help visually impaired people. In this paper an overview of some existing indoor navigation systems for visually impaired people are presented and they are compared from different perspectives. The evaluated techniques are ultrasonic systems, RFID-based solutions, computer vision aided navigation systems, ans smartphone-based applications.

Wireless sensor networks are widely used in many applications such as environmental monitoring, health care, smart grid and surveillance. Many security protocols have been proposed and intensively studied due to the inherent nature of wireless networks. In particular, Wu et al. proposed a promising authentication scheme which is sufficiently robust against various attacks. However, according to our analysis, Wu et al.'s scheme has two serious security weaknesses against malicious outsiders. First, their scheme can lead to user impersonation attacks. Second, user anonymity is not preserved in their scheme. In this paper, we present these vulnerabilities of Wu et al.'s scheme in detail. We also propose a new scheme by fixing such vulnerabilities and improving the performance of the protocol.

NiFe alloy nanoparticles/graphene oxide hybrid (NiFe/GO) was prepared for electrochemical glucose sensing. The as-prepared NiFe/GO hybrid was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The results indicated that NiFe alloy nanoparticles can be successfully deposited on GO. The electrochemical glucose sensing performance of the as-prepared NiFe/GO was studied by cyclic voltammetry and amperometric measurement. Results showed that NiFe/GO modified glassy carbon electrode had sensitivity of 173 μA mM⁻¹cm⁻² for glucose sensing with a linear range up to 5 mM, which was superior to commonly used Ni nanoparticles. Furthermore, high selectivity for glucose detection can be achieved by NiFe/GO. All the results demonstrated that NiFe/GO hybrid was promising for using in electrochemical glucose sensing.

Monitoring of structures is one of the engineering challenges of the 21st century. At the same time, as a result of changes in the conditions of use, design errors, many building structures require strengthening. The article presents research on the development of the external strengthening carbon fiber textile with an option of self-sensing. The idea is based on the pattern of resistive strain gauge, where thread is provided in a zig-zag of parallel lines. Already the first laboratory tests showed the high efficiency of the system in the measurement of strains, but also revealed the sensitivity of measurement to environmental conditions. The article presents studies on the influence of temperature and humidity on the measurement. To separate those effects, resistance changes were tested on unloaded concrete and wooden samples. The models were placed in a climatic chamber and the daily cycle of temperature and humidity changes was simulated. The results of the research confirm preliminary observations. Resistivity growths with the temperature. This effect is more visible on concrete samples, presumably due to its greater natural humidity. The strain measurement with carbon fibers is very sensitive to temperature changes and application of this method in practice requires compensation.

Visual inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when solving highly non-linear problems. Further, their performance significantly depends on the accuracy of the initialization of inertial measurement unit (IMU) parameters. In this paper, we propose a novel VIO algorithm of estimating the motional state of UAVs with high accuracy. The main technical contributions are the fusion of visual information and pre-integrated inertial measurements in a joint optimization framework, and the stable initialization of scale and gravity using relative pose constraints. To count for ambiguity and uncertainty of VIO initialization, a local scale parameter is adopted in the online optimization. Quantitative comparisons with the state-of-the-art algorithms on the EuRoC dataset verify the efficacy and accuracy of the proposed method.

We address Multi-Wall Carbon NanoTubes (MWCNTs) for structural health monitoring in adhesive bonds such as in building structures. MWCNT-loaded composites are employed to sense strain changes under tension load using an AC impedance measurement setup. Different weight percentages of 1, 1.5, 2 and 3 wt.% MWCNT are added to the base epoxy resin using different dispersion times, i.e. 5, 10 and 15 minutes. The equivalent parallel resistance of the specimens is measured by applying an alternating voltage at different frequencies. To determine the mechanical as well as sensory properties, the specimens are subjected to a tensile test with concurrent impedance measurement. Using alternating voltage, a higher sensitivity of the impedance reading can be achieved. Employing these sensors in buildings and combining the readings of a network of such devices can significantly improve the buildings’ safety. Additionally, networks of such sensors can be used to identify necessary maintenance actions and locations.

The unpredictable increase in electrical demand affects the quality of theenergy throughout the network. A solution to the problem is the increase of distributedgeneration units which burn fossil fuels.While this is an immediate solution to theproblem the ecosystem gets affected by the emission of CO2.A promising solutionis the integration of Distributed Renewable Energy Sources (DRES) to the conventionalelectrical system, thus, introducing the concept of smart microgrids (SMG) that requirea safe, reliable and technically planned two-way communication system. This documentpresents a heuristic based on planning capable of providing a bidirectional communicationnear optimal route map, following the structure of an hybrid Fiber-Wireless (FiWi) with thepurpose of obtaining information of electrical parameters that help us to manage the useof energy by integrating conventional electrical system to SMG. A FiWi network is basedon the integration of wireless access and optical networks. This integration increases thecoverage and reliability at a lower cost. The optimization model is based on clusteringtechniques, through the construction of balanced conglomerates. The method is used forthe development of the clusters along with the Nearest-Neighbor Spanning Tree Algorithm(N-NST). Additionally, Optimal Delay Balancing (ODB) model will be used to minimizethe end to end delay of each grouping. In addition, the heuristic observes real designparameters such as: capacity and coverage. Using the Dijkstra algorithm, the routes arebuilt following the minimum shorter path. Therefore, this paper presents a heuristic able to plan the deployment of smart meters (SMs) through a tree-like hierarchical topology for theintegration of SMG at the lowest cost.

Given their severity and non-healing nature, diabetic chronic wounds are a significant concern to the 30.3 million Americans diagnosed with diabetes mellitus (2015). Peripheral arterial diseases, neuropathy, and infection contribute to the development of these wounds, which lead to an increased incidence of lower extremity amputations. Early recognition, debridement, offloading, and controlling infection are imperative for timely treatment. However, wound characterization and treatment are highly subjective and based largely on the experience of the treating clinician. Many wound dressings have been designed to address particular clinical presentations, but a prescriptive method is lacking for identifying the particular state of chronic, non-healing wounds. The authors suggest that recent developments in wound dressings and biosensing may allow for the quantitative, real-time representation of the wound environment, including exudate levels, pathogen concentrations, and tissue regeneration. Development of such sensing capability could enable more strategic, personalized care at the onset of ulceration and limit the infection leading to amputation. This review presents an overview of the pathophysiology of diabetic chronic wounds, a brief summary of biomaterial wound dressing treatment options, and biosensor development for biomarker sensing in the wound environment.

There is a continuous growth of heat pump installations in residential buildings in Germany. The heat pumps were not only used for space heating and domestic hot water consumption but also to offer flexibility to the grid. the high coefficient of performance and the low cost of heat storages made the heat pumps an optimal candidate for the power to heat applications. Thus, several questions are raised about the optimal integration and control of the heat pump system with buffer storages to maximize its operation efficiency and minimize the operation costs. In this paper, an experimental investigation is performed to study the performance of a ground source heat pump (GSHP) with a combi-storage under several configurations and control factors. The experiments were performed on an innovative modular testbed that is capable of emulating a ground source to provide the heat pump with different temperature levels at different times of the day. Moreover, it can emulate the different building loads such as the space heating load and the domestic hot water consumption in real-time. The data gathered from the testbed and different experimental studies were used to develop a simulation model based on Modelica that can accurately simulate the dynamics of a GSHP in a building. The model was validated based on different metrics. Energetically, the difference between the developed model and the measured values was only 3.08\% and 4.18\% for the heat generation and electricity consumption, respectively.

We believe that a natural focus of the Physics Education Research community is on understanding and improving student learning in our physics courses. For this purpose, we are introducing smartphones in the physics laboratory. Current smartphones measure each component of the magnetic field, bearing in mind that any current perpendicular to a magnetic field produces a small potential difference, transversal to the said current, being this voltage easily measurable by Hall sensors. In this work, we have considered the magnetic field created by a linear quadrupole and we have studied its dependence on distance. Using an experimental procedure that is simple we have measured the magnetic field using the Hall sensor that most smartphones have, together with the corresponding app. The purpose of this work is to show that the laboratory is a powerful tool that increases significant learning under three conditions: 1) the practice must not be too sophisticated; 2) students must handle objects in the lab; and 3) the practice must be scientifically accurate, including the adjustments by minimum squares, and the following and necessary error calculation.

Breast cancer is the most common malignancies in women and the second leading cause of cancer death in women. Triple negative breast cancer (TNBC) subtype is a breast cancer subset without ER, PR and HER2 expression, limiting treatment options and presenting a poorer survival rate. Thus, we investigated whether HDACi would be used as potential anti-cancer therapy on breast cancer cells. In this study, we found TNBC and HER2-enrich breast cancers are extremely sensitive to Panobinostat, Belinostat of HDACi via experiments of cell viability assay, apoptotic marker identification and flow cytometry measurement. On the other hand, we developed a bioluminescence based live cell non-invasive apoptosis detection sensor (IADS) detection system to evaluate the quantitative and kinetic analyses of apoptotic cell death by HDAC treatment on breast cancer cells. In addition, the use of HDACi may also be accompanied with chemotherapeutic agent such as doxorubicin to synergic drug sensitivity on TNBC cell (MDA-MB-231), but not in breast normal epithelia cells (MCF-10A), providing therapeutic benefits against breast tumor in clinic.

Most of the existing calibration methods for binocular stereo vision sensor (BSVS) depend on high-accuracy target with feature points that are difficult to manufacture and costly. In complex light conditions, optical filters are used for BSVS, but they affect imaging quality. Hence, the use of a high-accuracy target with certain-sized feature points for calibration is not feasible under such complex conditions. To solve these problems, a calibration method based on unknown-sized elliptical stripe images is proposed. With known intrinsic parameters, the proposed method adopts the elliptical stripes located on the parallel planes as a medium to calibrate BSVS online. In comparison with the common calibration methods, the proposed method avoids utilizing high-accuracy target with certain-sized feature points. Therefore, the proposed method is not only easy to implement but is a realistic method for the calibration of BSVS with optical filter. Changing the size of elliptical curves projected on the target solves the difficulty of applying the proposed method in different fields of view and distances. Simulative and physical experiments are conducted to validate the efficiency of the proposed method. When the field of view is approximately 400 mm × 300 mm, the proposed method can reach a calibration accuracy of 0.03 mm, which is comparable with that of Zhang’s method.