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We combine a near‐infrared (NIR) sensitive organic photodetector with a high‐resolution 508 ppi oxide TFT backplane to create a large‐area thin NIR detector. Using a NIR light source the detector is capable of imaging the (pattern of) veins under the skin in reflection, leading to improved biometric authentication. [ABSTRACT FROM AUTHOR]

The rapid and accurate detection of ammonia is very important for manufacture and environmental monitoring, which needs to be developed urgently. Herein, a thin film‐based fluorescence sensor is fabricated by using a ternary europium (III) complex probe for ammonia. The new complex Eu(TPM)3(2‐PBO) (1) was designed and synthesized by utilizing a trifluoromethyl substituted β‐diketone ligand TPM and a diimine ligand 2‐PBO (TPM = 1,1,1‐trifluoro‐5,5‐dimethyl‐2,4‐hexanedione, 2‐PBO = 2‐(2′‐pyridyl)‐benzoxazole). This complex probe was synthetically characterized by elemental analysis, crystallographic and spectroscopic analysis, and photoluminescence (PL) study. The crystallographic analysis revealed complex 1 as a neutral complex structure with the Eu(III) center in a distorted square antiprism EuO6N2 coordination polyhedron. Based on this complex probe, a thin film fluorescence sensor with highly sensitive and selective response to ammonia was developed by polymethyl methacrylate (PMMA): complex composite and cellulose paper support. When the paper‐based sensor was exposed to ammonia, its PL emission showed a sensing behavior of rapid quenching. Surprisingly, this new method can achieve excellent limit of detection as low as 2.740 × 10−6 ppm. [ABSTRACT FROM AUTHOR]

We apply a photolithographic patterning process to integrate a green phosphorescent organic light emitting diode (OLED) with a polymer‐based organic photodetector (OPD) side‐by‐side with resolution up to 635 ppi. The characteristics of OLED and OPD before and after patterning are investigated. The crosstalk between OLED and OPD subpixels and the linearity of the integrated OPD under different luminance are also studied. The results indicate that photolithography enabled integration is an encouraging route of organic and hybrid electronics (OHEs) manufacturing. [ABSTRACT FROM AUTHOR]

TEMPUS is a new detector system being developed for photon science. It is based on the Timepix4 chip and, thus, it can be operated in two distinct modes: a photon‐counting mode, which allows for conventional full‐frame readout at rates up to 40 kfps; and an event‐driven time‐stamping mode, which allows excellent time resolution in the nanosecond regime in measurements with moderate X‐ray flux. In this paper, the initial prototype, a single‐chip device, is introduced, and the readout system described. Moreover, and in order to evaluate its capabilities, some tests were performed at PETRA III and ESRF for which results are also presented. [ABSTRACT FROM AUTHOR]

Novel multiple emitting amphiphilic conjugated polythiophene‐coated CdTe quantum dots for picogram level determination of the 2,4,6‐trinitrophenol (TNP) explosive are developed. Four biocompatible sensors, cationic polythiophene nanohybrids (CPTQDs), nonionic polythiophene nanohybrids (NPTQDs), anionic polythiophene nanohybrids (APTQDs), and thiophene copolymer nanohybrids (TCPQDs), are designed using an in situ polymerization method, which shows highly enhanced fluorescence intensity and quantum yield (up to 78%). All sensors are investigated for nitroexplosive detection to provide a remarkable fluorescence quenching for TNP and the quenching efficiency reached 96% in the case of TCPQDs. The fluorescence of the sensors are quenched by TNP through inner filter effect, electrostatic, π−π, and hydrogen bonding interactions. Under optimal conditions, the detection limits of CPTQDs, NPTQDs, APTQDs, and TCPQDs are 2.56, 7.23, 4.12, and 0.56 × 10−9m, respectively, within 60 s. More importantly, portable, cost effective, and simple to use paper strips and chitosan film are successfully applied to visually detect as little as 2.29 pg of TNP. The possibility of utilizing a smartphone with a color‐scanning APP in the determination of TNP is also established. Moreover, the practical application of the developed sensors for TNP detection in tap and river water samples is described with satisfactory recoveries of 98.02−107.50%. Amphiphilic conjugated polythiophene‐coated CdTe quantum dots with enhanced biocompatibility, fluorescence intensity, and quantum yield are developed for the selective detection of nitroexplosives. The applicability of the method is extended using a portable and cost‐effective chitosan film and a paper‐based sensor coupled with smartphone. This work reveals unique opportunities for detection of nitroexplosives in national security and environment protection. [ABSTRACT FROM AUTHOR]

Detecting antibodies in blood is as simple as it can get. In their Communication on page 15369 ff., D. Citterio, M. Merkx et al. integrate antibody‐targeting bioluminescent sensing proteins and other essential assay components into a microfluidic paper‐based analytical device. A drop of blood, a digital camera, and twenty minutes are all that is required to detect the presence and the concentration of multiple antibodies in whole blood based on the color of the emitted light. [ABSTRACT FROM AUTHOR]

A facile and digital do‐it‐yourself technique is proposed to fabricate inexpensive sensors on flexible substrates (paper, cloth, and plastic film). A set of office‐grade equipment (i.e., laserjet printer, thermal laminator, computer‐aided paper cutter), and commercially available supplies (i.e., baking wax paper, furniture restoration metal‐leaf) are used. Forming electrodes through traditional printing and defining a fluidic confinement region through crafting practice enable fabrication of a wide range of devices without requiring customized specialty instruments, costly infrastructure, and complicated fabrication steps, unlike previously introduced methods. Three different levels of experiments are designed to assess the comprehensiveness and responsiveness of the proposed method to the needs of existing research fields. The performances of the fabricated features at each level are evaluated to cover various application domains in environmental monitoring and biomedical diagnostics utilizing conductometric, colorimetric, biochemical, and chemoresistive detection principles. Devices with varying size of features, from nanometers to centimeters, are fabricated and characterized. This method provides an alternative route to decentralized production of low‐cost flexible sensors and other devices, with a minimal step, time, and facilities. The operation of such devices is simple and can be further empowered by smartphones for data analysis and transmission. [ABSTRACT FROM AUTHOR]

SUMMARY This paper is concerned with the distributed [ABSTRACT FROM AUTHOR]

We are investigating sensor applications of thin‐film devices, such as, visible‐light sensor, infrared‐light sensor, temperature sensor, and magnetic‐field sensor. Particular in this presentation, it is found that the magnetic‐filed sensor can detect the spatial direction of the magnetic field. [ABSTRACT FROM AUTHOR]

Increasing concerns about global food safety and security demands innovative solutions, particularly in food packaging technologies. This review paper investigates the advanced integration of natural colourimetric sensors with biopolymer‐based packaging materials, with a focus on developments over the past 5 years. These sensors change colour in response to environmental stimuli such as oxygen, temperature, pH and relative humidity, intuitively indicating food freshness and safety. The paper emphasizes the recent advancements in using natural colourants, such as alizarin, anthocyanins, betacyanins, chlorophyll, curcumin and shikonin. When combined with either natural or synthetic biopolymers, these colourants contribute to a sustainable and eco‐friendly approach to food packaging. Such technological advances could notably decrease the incidence of foodborne illnesses by signaling potential spoilage or contamination, while also addressing food wastage by providing clear indications of edibility. Although challenges remain in sensor longevity and widespread adoption, the prospects for biopolymer‐based food packaging with embedded natural colourimetric sensors are promising. [ABSTRACT FROM AUTHOR]

Bolt looseness may occur on wind turbine (WT) blades exposed to operational and environmental variability conditions, which sometimes can cause catastrophic consequences. Therefore, it is necessary to monitor the loosening state of WT blade root bolts. In order to solve this problem, this paper proposes a method to monitor the looseness of blade root bolts using the sensors installed on the WT blade. An experimental platform was first built by installing acceleration and strain sensors for monitoring bolt looseness. Through the physical experiment of blade root bolts' looseness, the response data of blade sensors is then obtained under different bolt looseness numbers and degrees. Afterwards, the sensor signal of the blade root bolts is analyzed in time domain, frequency domain, and time‐frequency domain, and the sensitivity features of various signals are extracted. So the eigenvalue category as the input of the state discrimination model was determined. The LightGBM (light gradient boosting machine) classification algorithm was applied to identify different bolt looseness states for the multi‐domain features. The impact of different combinations of sensor categories and quantities as the data source on the identification results is discussed, and a reference for the selection of sensors is provided. The proposed method can discriminate four bolt states at an accuracy of around 99.8% using 5‐fold cross‐validation. [ABSTRACT FROM AUTHOR]

International Conference on Display Technology 2020 (V olume 52, Issue S1) 332 Fingerprint Sensor System Based on High Mobility Oxide TFT Lei Zhou*, Miao Xu**, Jian-Hua Zou*, Wei-Jing Wu**, Lei Wang**, and Jun-Biao Peng** *Guangzhou New Vision Optoelectronic Co., Ltd., Guangzhou, China (zhoulei@newvision-cn.com) **State Key Laboratory of Luminescent Materials and Devices, South China University of Technology, Guangzhou, China (1 line spacing) In this paper, we introduce a fingerprint sensing system based on oxide thin film transistor (TFT) panel and TI AFE2256 read out IC(ROIC) driver. To get the fingerprint image data from the sensor array, the ROIC senses a capacitance, which is formed by a bank material between a human finger and an electrode of each pixel of the sensor array. [Extracted from the article]

Our goal is to be able to align objects in an RGB-D image with 3D models from a library. Our pipeline for this task involves detecting and segmenting objects and estimating coarse pose using a convolutional neural network, followed by inserting the rendered model in the scene. [ABSTRACT FROM AUTHOR]

In this paper, various integration schemes for in-cell capacitive touch panels will be reviewed. Continuous efforts have been made to eliminate the interference between display and touch sensor structure. A in-cell LCD module with self-capacitance touch sensor integrated will be presented. [ABSTRACT FROM AUTHOR]

Increasing environmental concerns raised by the accumulation of electronic waste draws attention to the development of sustainable materials for short‐lived electronics. In this framework, printed capacitive humidity sensors and temperature resistive detectors composed exclusively of biodegradable materials: shellac, carbon‐derived particles, and egg‐albumin are reported. The sensor platform comprises interdigitated electrodes serving as a capacitive transducer for humidity sensing, and a serpentine used as a resistive temperature detector. Both the interdigitated and serpentine electrodes are manufactured by screen‐printing carbon ink on a shellac substrate. The humidity sensors are constructed by drop‐coating egg albumin on the interdigitated carbon electrodes and the temperature detector is prepared by encapsulating the serpentine design with shellac. Shellac is shown to be a biodegradable alternative to hydrophilic cellulose‐derived substrates, with the capacitive humidity sensors demonstrating a sensitivity of 0.011% RH−1. The response and recovery times on shellac are 12 and 20 times faster than on cellulose‐based substrate, and the serpentine resistive temperature detectors have a temperature coefficient of 5300 ppm K−1. At the end of their service‐life, the sensors produced are home compostable and can be environmentally friendly disposed, potentially enabling their future use for sustainable and environmentally friendly smart‐packaging, agricultural sensing, or point‐of‐care testing. [ABSTRACT FROM AUTHOR]

Capacitive sensors show promising applications for human–computer interface due to their potential capabilities of both pressure and proximity sensing. However, the sensitivity loss at large strain and the complicated process of fabrication technology limit related applications. Herein, inspired by gradient and hierarchical structures in biological systems and using porous materials with different stiffness, a capacitive flexible sensor with both proximity and pressure sensing abilities is proposed. Such hierarchical structures effectively reduce the attenuation of sensitivity as the pressure increases, realizing an ultrawide detection range with high sensitivity. A theoretical mathematical model is developed and the corresponding capacitive sensor is fabricated by using the high‐performance porous impregnated dust‐free paper as the electrode and expandable polyethylene (EPE)/loofah‐like polyurethane sponge (LPS) as double‐layer porous dielectric. This sensor has an ultrawide detection range up to 3000 kPa with a significantly low sensitivity loss of 0.0195% kPa−1 and the noncontact sensing mode reaches a sensing range up to 28 cm (0.122 cm−1). Notably, a strategy is provided to design the high sensitivity sensor over an ultrawide detection range from approaching to pressuring, and eventually its promising application is presented as human–computer interaction. [ABSTRACT FROM AUTHOR]

We exploited the stability of Donor‐Acceptor polymer on the cylindrical nanopores structure to realize the sensors with a high sensitivity and stability. Then, we propose a double active layer (DL) strategy that exploits an ultra‐thin layer of Poly(3‐hexylthiophene‐2,5‐diyl) (P3HT) to serve as a work function buffer to enhance the operational current. The DL sensor exhibits a sustainable enhanced operational current of microampere level and a stable sensing response even with the presence of P3HT layer. This effect is carefully examined with different aspects, including vertical composition profile of DL configuration, lifetime testing on different sensing layer, morphological analysis, and the versatility of the DL strategy. Finally, we utilize the DL sensor to conduct a tracing of BA concentration in two HD patients before and after HD, and correlate it with the blood urea nitrogen (BUN) levels. A good correlation coefficient of 0.96 is achieved. [ABSTRACT FROM AUTHOR]

Aristolochic acids (AAs) have caused widespread concern as highly nephrotoxic and carcinogenic substances. Therefore, it is essential to explore a simple and feasible method to detect AAs for disease prevention and clinical diagnosis. In this work, we designed and synthesized a novel luminescent metal organic framework (Zn-MOF), which has excellent structural stability and fluorescence stability. Notably, the luminescent Zn-MOF exhibits strong blue emission owing to ligand-centered electronic transitions, while being capable as a selective sensor for the quantitative detection of AAs in biological fluids with low detection limit. The fluorescence analysis method, possessing the advantages of reliability and high accuracy, further demonstrated that Zn-MOF has potential applications in monitoring the carcinogen biomarker AAs. Moreover, a paper-based sensor has been devised by depositing Zn-MOF on filter paper, which provides a novel strategy for visual, rapid, and on-site AAs detection with the naked eye. [ABSTRACT FROM AUTHOR]

Background: In x‐ray computed tomography (CT), the gain inconsistency of detector units leads to ring artifacts in the reconstructed images, seriously destroys the image structure, and is not conducive to image recognition. In addition, to reduce radiation dose and scanning time, especially photon counting CT, low‐dose CT is required, so it is important to reduce the noise and suppress ring artifacts in low‐dose CT images simultaneously. Purpose: Deep learning is an effective method to suppress ring artifacts, but there are still residual artifacts in corrected images. And the feature recognition ability of the network for ring artifacts decreases due to the effect of noise in the low‐dose CT images. In this paper, a method is proposed to achieve noise reduction and ring artifact removal simultaneously. Methods: To solve these problems, we propose a ring artifact correction method for low‐dose CT based on detector shifting and deep learning in this paper. Firstly, at the CT scanning stage, the detector horizontally shifts randomly at each projection to alleviate the ring artifacts as front processing. Thus, the ring artifacts are transformed into dispersed noise in front processed images. Secondly, deep learning is used for dispersed noise and statistical noise reduction. Results: Both simulation and real data experiments are conducted to evaluate the proposed method. Compared to other methods, the results show that the proposed method in this paper has better effect on removing ring artifacts in the low‐dose CT images. Specifically, the RMSEs and SSIMs of the two sets of simulated and experiment data are better compared to the raw images significantly. Conclusions: The method proposed in this paper combines detector shifting and deep learning to remove ring artifacts and statistical noise simultaneously. The results show that the proposed method is able to get better performance. [ABSTRACT FROM AUTHOR]

Heavy metals and metalloid pollution poses a severe threat to the environment and human health. Various anthropogenic sources are responsible for the release of these contaminants into the water and food chain of humans and animals. To protect the environment and human health, the detection of heavy metals in various environmental matrices becomes vital. Sophisticated lab‐based instruments require more time, effort, and huge investments which warrants the requirement of field‐based disposable sensors. Various optical and electrochemical sensors are reported to demonstrate good sensitivity, selectivity, and detection limits (LOD). The disposable electrodes comprised of glass, paper, plastic, and fabric are gaining importance owing to the ease of application in field analysis, reproducibility, and low cost. The majority of these sensors are based on noble/precious metals namely gold, silver, and platinum. However, limited availability and high cost of these receptors restrict wide spread applicability of these sensors. Numerous earth‐abundant materials and non‐noble metal‐based sensors are also evolving recently due to several advantages namely large‐scale availability, ease of modifications, stability, and shelf life which overcomes the limitations of noble/precious metals‐based sensors. The present review provides a review of recent advances in various non‐noble and earth‐abundant micro and nanomaterials used as receptors in optical and electrochemical biosensors for the detection of metals/metalloids in various matrices. The review also highlights the strategies for the design and fabrication of disposable electrodes, their modification methods, detection strategy, and mechanism involved in the detection of heavy metals. Various gaps existing in the reported sensor systems and future perspectives are also delineated in the present manuscript. [ABSTRACT FROM AUTHOR]

Summary: This paper studies the problem of sensor fault estimation for linear systems in the presence of unknown inputs in both input and output channels. Relying on matrix equation theory, the unknown inputs are first removed from the output channel. Second, an augmented descriptor system is constructed by treating both system state and sensor fault as (pseudo)‐state variables. Third, the augmented descriptor system is transformed into a regular one, followed by the elimination of the unknown input from the state equation. Finally, a reduced‐order prescribed‐time sensor fault estimator is obtained by using periodic delayed observers. This matrix equation based approach is then complemented by an alternative one, which relies on successive transformations of state, input and outputs. This approach sheds light on the adopted solvability conditions throughout the paper and on the role of different directions in the output space in handling unknown inputs, sensor faults and the core state estimation problem. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed methodologies. [ABSTRACT FROM AUTHOR]

Pinch gestures for scaling an image were recognized successfully on a surface-capacitive touch screen that has only a single-touch function without increasing manufacturing cost. An algorithm for recognizing the gestures was developed, which calculates the distance between two touching points without detecting each position of the two points. [ABSTRACT FROM AUTHOR]

In this paper, we proposed ambient light sensor (ALS) and color temperature sensor (CTS) circuit integrated in the edge of LCD display panel. The designed circuit is based on the thin film transistor (TFT) technology, the photo TFT can produce high photo current under light for sensor realizing ambient light from 0~50000Lux. Also, CTS circuit are based on ALS circuit but covered with color filter. The result shows that CTS can discriminate different color temperature in ambient light. The biggest advantage of this sensor is that it is compatible with TFT process in manufacturing, and it is small in size and high in efficiency. It has the potential to replace photodiode sensors. [ABSTRACT FROM AUTHOR]

Low sensitivity of fluorescent sensors with "turn‐off" response for identifying Al3+ has limited their wide application in the field of ion sensing. Herein, this paper reports a novel fluorescence sensor (L) endowing with "turn‐on" fluorescence response based on imidazo[2,1‐b]thiazole for recognizing Al3+ in aqueous solutions. Results show that the L exhibits high selectivity and sensitivity with "turn‐on" fluorescence response towards Al3+, but also has strong anti‐interference to other common ions. In addition, the excellent color change can be distinguished by naked eyes under UV light and the test papers show great potential for detecting Al3+ in tap water. The supposed sensing mechanism of L to Al3+ could be attributed to the inhibition of photo‐induced electron transfer (PET) and chelation‐enhanced fluorescence (CHEF). Such a novel design pathway is expected to offer helpful guidance for fabricating various sensors with "turn‐on" fluorescence response. [ABSTRACT FROM AUTHOR]

Detection of trace magnesium ion (Mg2+) is important in environmental and health monitoring. In this work, high‐performance Mg2+ sensor was developed from label‐free carbon dots. The novel carbon dots were prepared for the first time from natural rubber through the two‐step pyrolysis and hydrothermal method. They showed selectivity towards Mg2+ against a range of metal ions in solution and yielded a detection limit of 4.3 μM. The Mg2+ detection in real water samples showed an excellent recovery of 97.21 to 99.21 %. A paper‐based sensor was also fabricated as a portable device, showing a detection limit of 8.0 μM. UV‐vis and X‐ray absorption studies provided some evidences of the unique dynamic interactions between carbon dots and Mg2+ ions. In summary, the novelty of this work lies upon (i) developing a methodology of converting abundant, low‐cost natural rubber into carbon dots and (ii) fabricating sensitive and selective sensors from the label‐free carbon dots for the detection of Mg2+ both in solution and as paper‐based devices. The findings in this work will therefore have potential for environmental and health monitoring applications. [ABSTRACT FROM AUTHOR]

Calibration is the backbone of any sensor and measurement philosophy. The conventional calibration techniques for electrical parameter measurement using nonlinear sensors are affected by the repeating analogue signals and lead to errors in measurement. This research paper investigates different regression‐based mathematical models to calibrate the Hall sensor for measuring RMS and the fundamental frequency. The novelty of this research work lies in the feature‐based input modelling to measure RMS current and frequency with an error of 3.37e‐12% and 7.61e‐9%, respectively. The conventional Fourier transform method is compared with six different bio‐inspired metaheuristic algorithms to estimate the frequency components of the analogue signal received from the measurement setup. Apart from the conventional sine waveforms, this paper investigates sawtooth and square waveforms as the periodic signals for determining the frequency components. The results from the comparison study show that the Whale Optimization Algorithm exhibits 1.25% lesser error whilst predicting the features in measured frequency components. Apart from this, the paper identifies a unique combination of features that effectively measures the instantaneous electrical parameter with RMSE, NRMSE, and R2 value of 158.8, 0.51, and 0.44, respectively. Experimentally it is found that the decision tree and random forest regression models calibrate the Hall sensor with 93% less error than their linear and polynomial counterparts. [ABSTRACT FROM AUTHOR]

We describe a suite of software tools for image system simulation. The tools model the three-dimensional scene radiance, image formation by the optics, sensor transduction, image processing and display rendering. [ABSTRACT FROM AUTHOR]

The pyridine-containing DA monomer, DA-Py (Figure 1(a)), is converted to the cadmium complex form, DA-Cd-DA (Figure 1(b)). (a, b) Structures of the pyridine-containing diacetylene DA-Py (a) and its cadmium-bridged bisdiacetylene DA-Cd-DA (b). (c) Absorbance at 650 nm as a function of UV irradiation time of a DA-Cd-DA-coated filter paper. gl Figure 3(a) shows colorimetric responses of PDA-immobilized filter papers upon exposure to ATP. We found that the cadmium complexed DA monomer, DA-CD-DA was not soluble in THF while the cadmium uncoupled DA-Py display a good solubility in THF. [Extracted from the article]

Summary: This paper investigates optimizing the collaborative energy power consumption between nodes with energy harvesting (EH) capability at the fusion center (FC) and multi‐antenna sensors using game theory. Using multi‐antennas at FC on sensor networks (SNs), we can benefit from the spatial diversity in receiving the data and using multi‐antenna sensors and energy to transfer the data and optimize the SN, respectively. Also, in this paper, the data transmission in the network is formulated by considering the limitations of storage resources of each sensor, minimum data receiving, minimum EH, and maximum collaboration among sensors. In this paper, some modes are suggested to minimize the collaborative energy among sensors for transmitting the data and energy among sensors in the collaboration of sensors to optimize the power control and allocation power policy. Suggestions have been studied based on the number of antennae to transmit, using the cooperative games in sharing the data and the energy and auction game in transmitting to FC. The simulation results of the proposed problem using MATLAB software show optimization in participation function, EH, allocation in cooperation time, and transferring to FC to improve the detection of the transmitted data based on the increasing number of antennas in FC. [ABSTRACT FROM AUTHOR]

Aircraft coating process has been an important part in manufacturing process of modern aviation products. For coating defect detection, the manual observation with naked eyes is usually utilized, which leads to low production efficiency. In this paper, the authors propose the improved YOLOv5‐OBB with the channel‐spatial attention block (CSAB), feature pyramid non‐local module (FPNM) and structured sparsity slimming criterion (SSSC). The CSAB can pay more attention to effective channel information features from the channel dimension and the target information area from the spatial dimension. The effective non‐local module called FPNM is proposed to further improve the detection accuracy. The authors utilize the oriented bounding boxes (OBB) to reduce redundant background information for coating defect detection. In addition, the SSSC is proposed to achieve network slimming and trade‐off between the efficiency and accuracy. The experimental results on several datasets demonstrate the effectiveness of the authors' scheme, which achieves superior performance. [ABSTRACT FROM AUTHOR]

The low‐light environment is integral to everyday activities but poses significant challenges in object detection. Due to the low brightness, noise, and insufficient illumination of the acquired image, the model's object detection performance is reduced. Opposing recent studies mainly developing using supervised learning models, this paper suggests LIDA‐YOLO, an approach for unsupervised adaptation of low‐illumination object detectors. The model improves the YOLOv3 by using normal illumination images as the source domain and low‐illumination images as the target domain and achieves object detection in low‐illumination images through an unsupervised learning strategy. Specifically, a multi‐scale local feature alignment and global feature alignment module are proposed to align the overall attributes of the image and feature biases such as background, scene, and target layout are thus reduced. The experimental results of LIDA‐YOLO on the ExDark dataset achieved the highest performance mAP score of 56.65% compared to several current state‐of‐the‐art unsupervised domain adaptation object detection methods. Compared to I3Net, the performance improvement is 4.04%, and compared to OSHOT, the performance improvement is 6.5%. LIDA‐YOLO achieves a performance improvement of 2.7% compared to the supervised baseline method YOLOv3. Overall, the suggested LIDA‐YOLO model requires fewer samples and presents a stronger generalization ability than previous works. [ABSTRACT FROM AUTHOR]

In order to improve the recognition accuracy of construction machinery and equipment and materials in low contrast scenes, a construction machinery material recognition algorithm based on multisource sensor information fusion is proposed. In the paper, the millimeter wave radar is fused with the camera considering its strong penetration ability in rainy and foggy days and dim environments. Firstly, the spatial coordinates of radar and camera are unified by establishing a spatial fusion model of millimeter wave and camera; then the target acquired by millimeter wave is projected onto the image and the detection frame intersection and ratio model is used to generate the region of interest of the camera; finally, the improved YOLOv2 algorithm is used to identify the region of interest, and in the improved idea, the low‐level information is first connected with the high‐level information in multilayer depth. At the same time, a multiscale feature pyramid network structure is used to achieve recognition of objects of different scales. This model effectively reduces interference from other feature categories while improving the recognition efficiency of the system. The algorithm can effectively improve the recognition accuracy of mechanical materials in low‐contrast scenes, as demonstrated by the validation of different scenes. [ABSTRACT FROM AUTHOR]

An improved filtering algorithm, called the EttAF adaptive filtering, is proposed in this paper. Compared with the available algorithm, the equivalent observation error in the fusion centre from the external sensor is considered, which makes the observation noise matrix of the filter dynamically adjust according to the relative relationship between the fusion centre and the external sensor. The strong manoeuvring target is modelled based on the CS‐jerk model, and the error adaptive variation equation is derived for the external data. Simulation results show that compared to traditional algorithm the EttAF algorithm can effectively improve the accuracy of position and velocity by 10.8% and 22.3% respectively. [ABSTRACT FROM AUTHOR]

The ability to utilize a hybrid-photon-counting detector to its full potential can significantly influence data quality, data collection speed, as well as development of elaborate data acquisition schemes. This paper facilitates the optimal use of EIGER2 detectors by providing theory and practical advice on (i) the relation between detector design, technical specifications and operating modes, (ii) the use of corrections and calibrations, and (iii) new acquisition features: a doublegating mode, 8-bit readout mode for increasing temporal resolution, and lines region-of-interest readout mode for frame rates up to 98 kHz. Examples of the implementation and application of EIGER2 at several synchrotron sources (ESRF, PETRA III/DESY, ELETTRA, AS/ANSTO) are presented: high accuracy of high-throughput data in serial crystallography using hard X-rays; suppressing higher harmonics of undulator radiation, improving peak shapes, increasing data collection speed in powder X-ray diffraction; faster ptychography scans; and cleaner and faster pump-and-probe experiments. [ABSTRACT FROM AUTHOR]

Flexible sensing technology has shown great application value in motion monitoring and physiological signal detection. In many applications, the detected signal has the characteristics of low strength and wide range, thus improving the sensitivity and measurement range of sensors becomes extremely important. An enhancing method based on folding structure is proposed in this paper. Through the analysis of folding structure characteristics, the theoretical model of the folding structure effect in flexible sensors is established and the enhancement effect of sensitivity and measurement range is testified through three kinds of commonly used sensors, resistive, capacitive, and inductive sensors. Through changing the number of folding units, the sensitivity and measurement range of sensors can achieve to be adjusted. Folding sensors also have good hysteresis and repeatability properties and show the great performance in the application of human motion monitoring, such as limbs bending and rotating, muscle powering. The proposed method has the characteristics of simple, economical, environment friendly, and widely suitable, meanwhile avoiding the complexity of other ways to improve performance. This work has potential to enhance the sensitivity and measurement range for more kinds of flexible sensors and is of great value to fabricate high performance sensors based on folding structure. [ABSTRACT FROM AUTHOR]

We present breakthrough touchscreens having dual capacitive and force-sensing technologies. NDT's screen-printed force-sensing module is attached directly under the capacitive touchscreens, thus providing high sensitivity, fine spatial resolution and scalability to bigger display sizes. This is in contrast to present force-sensing displays with capacitive plates or force-sensing resistors on the display periphery. [ABSTRACT FROM AUTHOR]

Waterborne bacteria cause many dangerous diseases as well as several health‐related issues hence detection of them is a global challenge today. A plus‐shaped graphene sensor to detect waterborne bacteria is presented in this paper. The detection mechanism is based upon the refractive index difference between waterborne bacteria sample and pure water which causes a change in resonance peak in the transmittance graph. The use of graphene material increases the sensitivity and also gives the tuning behavior by changing its potential. The effect of various parameters such as sensitivity (S), Q factor, figure of merit (FOM), and detection limit are discussed in the paper. The maximum values Q factor and FOM are 13.46 and 4.03 RIU−1 respectively. The minimum detection limit is 0.277 RIU. The proposed sensor exhibits the highest sensitivity of 255 GHz/RIU at the optimum condition which is comparably higher than previously published papers on biosensors. The proposed design with its highest sensitivity and good detection parameters can be helpful in detecting waterborne bacteria. [ABSTRACT FROM AUTHOR]

Cross‐domain object detection aims to generalize the distribution of features extracted by an object detector from an annotated domain to an unknown and unlabelled domain. Although one‐stage cross‐domain object detectors have significant advantages in deployment than two‐stage ones, they suffer from two problems. First, neglect of category features and inaccurate alignment between multiple category features would lead to decreased domain adaptation efficiency. Second, one‐stage detectors are more sensitive to imbalance of samples and negative samples severely affect the alignment process of domain adaptation. To overcome these two problems, an innovative category‐related attention domain adaptive method that refines discrimination for each category's feature has been proposed in this paper. In the proposed method, a group of domain discriminators is assigned to each category to refine the fine‐grained features between categories. The discriminators are trained via an adversarial discriminant framework to align the fine‐grained distributions cross different domains. A category attention alignment (CAA) module is proposed to navigate more attention to the foreground regions in instance‐level, which effectively alleviates the negative migration problem caused by the positive and negative sample imbalance of the one‐stage detector. Specifically, two sub‐modules in the CAA module are developed: a local CAA module and a global CAA module. These modules aim to optimize the domain offsets in both the local and global dimensions. In addition, a progressive global alignment module is designed to align image‐level features, offering prior knowledge of migration for the CAA module. The progressive global alignment module and CAA module collaboratively engage in benign competition with the backbone network across various levels. Extensive transferring experiments are conducted among cityscapes, foggy cityscapes, SIM10K, and KITTI. Experimental results show that the proposed method has much superior performance than other one‐stage cross‐domain detectors. [ABSTRACT FROM AUTHOR]

Object detection on fused images of visible and infrared modals is of great importance for many applications, for example, surveillance and rescue at low‐light conditions. However, current detectors have difficulty for robust fused image detection for mainly two reasons. First, objects are presented in various shapes and sizes, making some hard samples cannot be localized accurately. Second, the same object category in the fused images will have different appearance due to changing weather condition, temperature and intrinsic heat. Such a contradiction will degrade the classification task of a detection network, since it cannot merge commonalities and distinguish differences well. In this paper, we propose to reconstruct the detection pipeline of current detectors, and enhance the detection ability on difficult samples in fused images. Specifically, a Dilation Pyramid Network (DPN) is designed at the lateral connection to generate and aggregate features of various receptive field, without increasing pyramid layers. To strengthen the classification, a Semantic Category Attention Module (SCAM) is proposed to capture attention centers of semantics in fused images, rather than object centers. Abundant experiments on two fusion datasets show that the proposed method achieves a satisfying performance, and both modules can greatly improve current generic detectors on fused images. [ABSTRACT FROM AUTHOR]

Grid‐connected inverters are the core equipment in the renewable power system. There are multiple current sensors which may affect the driving module of the switch in inverter. In multiple current sensor fault diagnosis, the coupling between fault components makes fault diagnosis difficult. This paper presents an offset fault diagnosis method of multiple current sensors based on the average modulation voltage model. Based on the influence of current sensor offset fault in the system, the average modulation voltage model is established in three‐phase stationary coordinates. The difference between the measured value of the current and the actual value is estimated through the model when the offset fault occurs. And then the fault is located. Experimental results show that the fault can be located accurately and fault tolerant control can be performed by this method when there are offset faults in multiple sensors simultaneously. [ABSTRACT FROM AUTHOR]

Abnormal glucose level can cause irreversible damage, including diabetes. In this work, a sensor was designed that mimics the peroxidase property of the natural horseradish peroxidase (HRP). The proposed sensor detects the presence of glucose through the reduction of hydrogen peroxide (H2O2) and the oxidation of tetramethylbenzidine (TMB). This sensor shows linear behaviour in the range of 0.001–50 μM with a limit of detection down to 0.8 nM. In addition, a paper‐based format of this sensing platform was performed which enables fast and sensitive detection and further reduces the expenses. In this method the linear behaviour of the sensor is between 0.005–40 μM and the detection limit is as low as 2.4 nM. The glucose detection in human saliva was also performed, showing an acceptable accuracy. Thus the sensor is practically suitable for the non‐invasive detection of glucose. [ABSTRACT FROM AUTHOR]

In the expanding field of physiological pH skin sensors, thin temporary tattoo‐based devices have gained attention because of ultra‐conformal adhesion while providing excellent water vapor transmission. Here, a pH sensor tattoo made of temporary tattoo paper, screen‐printed poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate electrodes, and pH‐responsive hydrogel deposited via initiated chemical vapor deposition, is proposed. The tattoo sensor is easily transferred on skin, maintaining full functionality, and shows excellent conformability to topographical features of epidermis. The investigation of the morphology of all layers within the sensor verifies full control of the desired width of electrodes, thickness of hydrogel, and deposition shielded areas. The hydrogel layer exhibits a reversible pH‐responsive swelling of 24.7 ± 0.3% to 38 ± 1%, with respect to the dry state, at pH 4 to pH 6, respectively. Impedance spectroscopy identifies the phase shift at 10 and 1000 Hz as an excellent pH‐related property of the sensor, which can be only ascribed to the presence of the hydrogel. The sensors ability to be operated with non‐sophisticated read‐out hardware and software is also demonstrated. [ABSTRACT FROM AUTHOR]

Skin‐like sensitivity, or the capability to recognize tactile information, is essential for future robots in elder care, search and rescue, entertainment and other applications involving unstructured environments. In this paper, we propose the design of a flexible one‐dimensional pressure‐sensing system that can localize deformation along a long strip and measure its magnitude with an integrated pair of sensors. The sensor system is fabricated with piezoresistive conductive foils and copper sheets encapsulated by adhesive tape with a total thickness of 0.7 mm. For the purpose of demonstration, the sensor is used to monitor the location and magnitude of kink deformation of an inflatable tube. Finite‐element modeling and simulation are conducted to investigate the behavior of the soft sensor system when subjected to kink deformation. The model‐predicted sensor output achieves good agreement with the experimental data for different deformation magnitudes. Finally, extensive experiments on a sensor prototype with dimensions of 35 × 500 mm mounted on an inflatable tube are conducted to demonstrate the capability of the proposed scheme in simultaneous measurement of deformation location and magnitude. It is shown that the specific design approach minimizes the coupling of location and magnitude measurements, resulting in minimal complexity for data processing. [ABSTRACT FROM AUTHOR]

This paper theoretically and experimentally analyzes the influence of different sensor array schemes and optical collimation structures on fingerprint recognition. Considering the process yield, cost and the quality of fingerprint image, we find the appropriate size ranges of microlenses and sensors are 20~30 μm and 35~50 μm respectively, and the bonding process between the optical collimating film and the sensor substrate has little damage to the sensor, which is conducive to mass production. [ABSTRACT FROM AUTHOR]

Inkjet printing is a popular technique for depositing high-precision ink lines. This study reports the printing parameters' influence on the electrical properties of the sensing devices. The electrochemical sensors are fabricated with a commercial piezoelectric printer and silver ink. Different substrates are evaluated in the printing process, including paper, polyimide, and polyvinyl chloride (PVC) tapes. Ink depositions' temperature, ink drop spacing, length, and the number of the ink layer are also evaluated in this study. Higher temperatures (40 °C) make the substrate surface smoother, improving the printing quality. Controlling the ink drop spacing produces narrow continuous ink lines. The number of ink layers changes the film thickness, altering their electroactive surface area. The best printing parameters are PVC tape at 40 °C, 17 µm drop spacing, one layer, and 13 mm length. Under optimized conditions, three-electrode electrochemical systems are fully printed with silver ink, showing batch-to-batch reproducibility (RSD = 3%). Their analytical performance is evaluated for picric acid, hydrogen peroxide, and glucose quantification. The sensors are modified with glucose oxidase to quantify glucose in artificial saliva, confirming their analytical applicability. Therefore, this work reports fundamental aspects of inkjet printing, bringing valuable findings to guide new research involving inkjet-printed electrochemical biosensors/sensors ((bio)sensors). [ABSTRACT FROM AUTHOR]

Polarization detection technology is developing toward miniaturization and high integration from the early time‐division type, amplitude‐division type, aperture‐division type, etc., to a more integrated focal plane‐integrated array type. Focal plane detectors that rely on metal nanogrids are not able to guarantee both temporal and spatial resolution for lossless polarized light detection with a guaranteed level of integration. Inspired by Agabus japonicus, the black phosphorus (BP)‐based absorbing bionic stacked structured linear polarization detector (BSLD) is proposed. The BSLD exploits the polarization absorption properties of BP to achieve near‐lossless linear polarization detection. The design includes two orthogonally aligned polarization‐ and angle‐sensitive BP photodetectors. The detection performance of the detector is investigated and analyzed under a green laser beam (wavelength 532 nm). The BSLD designed in this paper can simultaneously measure the multi‐angle component information of the incident light at one point in space in order to resolve the polarization state of the incident light, providing a potential solution for an integrated, real‐time, and high‐resolution loss‐free polarization image sensor. [ABSTRACT FROM AUTHOR]

The article reports on the sensor printed on paper developed by the scientists in Australia to determine if the wearers are at risk of sunburn. Researcher Parisa Kiabani at the University of New South Wales in Sydney, New South Wales states that the paper-based sunburn sensor works when ultraviolet (UV) light activates titanium dioxide. It mentions that the sensor is made by inkjet printing a suspension.

The pursuit of ultraflexible sensors has arisen from the recent implementation of electrochemical sensors into wearable clothing where extensive mechanical stress upon the sensing platform is likely to occur. Such scenarios have witnessed screen-printed electrodes being incorporated into the waistband of undergarments for the determination of key analytes while others have reported incorporation into a neoprene wetsuit. In these conformations, the substrates which the sensors are printed upon need to be ultraflexible and capable of withstanding extensive individual mechanical stress. Therefore the composition, thickness and its combination of screen-printed ink require extensive consideration. A common short-coming within the field of screen-printed derived sensors is the lack of consideration towards the substrate material employed, and is rather in favour of the development of new electrode geometries and screen-printing inks. In this paper we explore the screen-printing of graphite based electroanalytical sensing platforms onto graphic paper commonly used in house-hold printers, and for the first time both tracing paper and ultraflexible polyester-based substrates are used. These sensors are electrochemically benchmarked with the redox probes hexaammine-ruthenium(III) chloride and potassium ferrocyanide(II). The effect of mechanical contortion upon two types of electrode substrates is also performed where it was found that these ultraflexible based polyester-based electrodes are superior to the previously reported ultraflexible paper electrodes since they can withstand extensive mechanical contortion, yet they still give rise to useful electrochemical performances. Most importantly the ultraflexible polyester electrodes do not suffer from capillary action as observed in the case of paper-based sensors causing the solution to wick-up the electrode towards the electrical connections resulting in electrical shorting, therefore compromising the electrochemical measurement; as such this new substrate can be used as a replacement for paper-based substrates and yet still be resilient to extreme mechanical contortion. A new configuration is also explored using these electrode substrate supports where the working carbon electrode contains the electrocatalyst, cobalt(II) phthalocyanine (CoPC), and is benchmarked towards the electroanalytical sensing of the model analytes citric acid and hydrazine which demonstrate excellent sensing capabilities in comparison to previously reported screen-printed electrodes. [ABSTRACT FROM AUTHOR]

Transmission lines are affected by aeolian vibration, sandstorms and acid rain, which cause structural damage and eventually lead to line breaking accidents. In this paper, the structural health monitoring technology of conductors is researched, and a structural monitoring system for conductors is designed. First, based on the structure of the ACSR (Aluminum Conductor Steel Reinforced) conductor and the dynamic equation, the relation between the natural frequencies and the structure of the conductor is obtained. Then, an online health monitoring system of the conductor structure is proposed, and key issues, such as the power supply solution of sensors, data preprocessing technology, multiple‐sensor synchronization method, are analyzed in detail. Finally, the structural health monitoring of overhead transmission lines designed in this paper is tested on 110‐kV experimental transmission lines. The experimental results show that from the system proposed the operation parameters of the conductors can be well obtained. [ABSTRACT FROM AUTHOR]