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Research on developing deep learning techniques for autonomous spacecraft relative navigation challenges is continuously growing in recent years. Adopting those techniques offers enhanced performance. However, such approaches also introduce heightened apprehensions regarding the trustability and security of such deep learning methods through their susceptibility to adversarial attacks. In this work, we propose a novel approach for adversarial attack detection for deep neural network-based relative pose estimation schemes based on the explainability concept. We develop for an orbital rendezvous scenario an innovative relative pose estimation technique adopting our proposed Convolutional Neural Network (CNN), which takes an image from the chaser's onboard camera and outputs accurately the target's relative position and rotation. We perturb seamlessly the input images using adversarial attacks that are generated by the Fast Gradient Sign Method (FGSM). The adversarial attack detector is then built based on a Long Short Term Memory (LSTM) network which takes the explainability measure namely SHapley Value from the CNN-based pose estimator and flags the detection of adversarial attacks when acting. Simulation results show that the proposed adversarial attack detector achieves a detection accuracy of 99.21%. Both the deep relative pose estimator and adversarial attack detector are then tested on real data captured from our laboratory-designed setup. The experimental results from our laboratory-designed setup demonstrate that the proposed adversarial attack detector achieves an average detection accuracy of 96.29%. [ABSTRACT FROM AUTHOR]

Sweep cover is a basic issue in wireless sensor networks, which uses mobile sensors to inspect points of interest (PoIs) periodically. There are many studies on the problem assuming that all mobile sensors have a uniform velocity, while some literature shows that using heterogeneous velocities may greatly increase the difficulty of research. In this paper, we study a minimum energy partial sweep cover (MinEPSC) problem on a line, the goal of which is to minimize energy consumption to sweep-cover at least K PoIs, where the energy consumption of a mobile sensor is related with its velocity in somewhat arbitrary but monotone manner. We design algorithms with theoretically guaranteed approximation ratios under different assumptions on the candidate velocity sets. [ABSTRACT FROM AUTHOR]

This report summarizes the work of the EMMI Rapid Reaction Task Force on "Real and Virtual Photon Production at Ultra-Low Transverse Momentum and Low Mass at the LHC". We provide an overview of the soft-photon puzzle, i.e., of the long-standing discrepancy between experimental data and predictions based on Low's soft-photon theorem, also referred to as "anomalous" soft photon production, and we review the current theoretical understanding of soft radiation and soft theorems. We also focus on low-mass dileptons as a tool for determining the electrical conductivity of the medium produced in high-energy nucleus–nucleus collisions. We discuss how both topics can be addressed with the planned ALICE 3 detector at the LHC. [ABSTRACT FROM AUTHOR]

A simple but effective optical design is proposed to expand the measurement range of a surface encoder in the out-of-plane Z -direction, which had been much shorter than that in the in-plane X -direction. A zeroth-order and a first-order diffraction beams generated at a transparent grating are projected onto a parallelly aligned scale grating. The reflected zeroth-order beam from the scale grating interferes with a beam from a reference plane mirror for the Z -directional measurement over an expanded range of 13 mm. A single Littrow configuration is established for the first-order diffraction beam to travel to and from the scale grating on the same path so that it can interfere with the reflected zeroth-order beam for the X -directional measurement regardless of the Z -position of the scale grating. A prototype sensor is constructed for demonstrating the effectiveness of the proposed optical design for expansion of Z -range. Uncertainty analysis on the measurement results is also conducted. • A compact two-axis surface encoder is proposed for the measurement of in-plane and out-of-plane displacement. • A new single Littrow configuration is proposed for a simple structure and easy alignment process. • The out-of-plane measurement range of surface encoder is expanded. • Performance tests and uncertainty analysis are conducted to verify the feasibility of the design. [ABSTRACT FROM AUTHOR]

• Digital element inputs and outputs in mainland China from 2010 to 2021 were measured. • STI efficiency was estimated employing the global super-efficiency SBM model. • The driving factors of STI efficiency were identified by geographic detectors. • There was a gradually declining trend from 2010 to 2021 in the spatial correlation effect. • Multiple factors influenced STI efficiency and digital elements were the most prominent drivers. Scientific and technological innovation (STI) activities are facilitated under the influence of the digital economy and depend on digital elements to support innovation activities. This study measures digital element inputs and outputs using data related to the digital economy and estimates STI efficiency in 29 provincial regions in mainland China from 2010 to 2021 employing the global super-efficiency slacks-based measure (SBM) model. Then, spatial characteristics and driving forces of STI efficiency are quantified using spatial autocorrelation and geographic detectors. The results reveal that STI efficiency exhibits a fluctuating, W-shaped pattern, and the spatial correlation effect shows a gradually declining trend from 2010 to 2021. The findings reveal that the core drivers of STI efficiency are digital financial development, e-commerce development, digital access level, and related factors. Therefore, strengthening inter-regional innovation links, promoting the construction of 5 G mobile internet and accelerating the integration of digital industries into traditional industries are recommended. [ABSTRACT FROM AUTHOR]

Sensors utilizing mesoporous materials have garnered significant interest; however, they are primarily designed for detecting a single analyte. In this study, we successfully synthesized a three-dimensional (3D) hollow mesoporous α-Fe 2 O 3 using a nanocasting process for the purpose of sensing LPG and humidity. The α-Fe 2 O 3 obtained in this study maintained the cubic framework structure of MCM-48, demonstrating a mesoporous and hollow architecture. The Liquified Petroleum Gas (LPG) sensing characteristics of mesoporous α-Fe 2 O 3 were examined at different operating temperatures (170–210 °C). The gas sensing response was optimized 99.3 % at 190 °C and the response/recovery time comes out to be 11.79 s & 0.84 s respectively. The humidity sensor's traits were evaluated at room temperature, with relative humidity (RH%) ranging from 11 % to 98 %, using mesoporous α- Fe 2 O 3. The response/recovery time of mesoporous α-Fe 2 O 3 as a humidity sensor comes out to be 6.3 s & 7.2 s respectively. The highly sensitive nature of the sensor along with negligible hysteresis, excellent repeatability and considerable stability for 30 days makes it a promisable candidate for real-time subtle respiration monitoring. Meanwhile, mesoporous α-Fe 2 O 3 humidity sensor is also utilized for evaluation of sleep hypopnea-apnea syndrome. [ABSTRACT FROM AUTHOR]

• Radiation protection experiment conducted on the ISS. • A new polymer composite for protection against cosmic radiation has been developed. • 2 containers were made from a new material and sent into space. • The attenuation coefficients of the new composite were studied. • Studied the change in the properties of the composite after testing in space. The article presents the results of polymer composite testing on the Russian segment of the International Space Station (ISS) during 225 days. For the space experiment "Shielding Composite" two cylinder-shaped composite containers were manufactured. Inside the containers there were detectors for dose registration during the orbital space flight. Presents the results of research on the first container, which was lowered to Earth in 2022. As a result of the space experiment "Shielding Composite", it was found that the attenuation ratio of the absorbed dose of space ionizing radiation (Inner sensor value/Outdoor sensor value) with a shield wall thickness of 10 mm was 0.71 ± 0.02 for container No. 1. There is no induced radiation in the container after its descent to Earth. [ABSTRACT FROM AUTHOR]

The main goal of the TUS experiment was to search for and study ultra high-energy cosmic rays with energies E > 70 EeV. At the same time, the TUS detector registered a number of unusual events, the origin of which was unclear. Events that are unique and not similar to EAS are the subject of the study presented in this paper. Events such as gamma-ray bursts (GRBs), out-of-aperture upward going EASs accompanied by lightning flashes, as well as terrestrial gamma-ray flashes (TGFs) are considered as their possible sources. [ABSTRACT FROM AUTHOR]

Being one of toxic and flammable volatile organic compounds (VOC), n-butanol has brought about many potential health risks, there is an urgent demand for highly sensitive detection techniques to monitor its concentration in occupational environments and the air. In this paper, Ce-doped MOF:ZnO sensors under UV activation for room-temperature detection of n-butanol were synthesized by the co-precipitation method and systemically characterized by XRD, SEM, HRTEM, and XPS. The sensitive performances were evaluated by the use of a WS-30A gas sensor measurement system. The results showed that Ce doping has significantly enhanced the sensitivity of the MOF:ZnO sensors, and the response value of the 0.08 % Ce-doped ZnO sensor has achieved to 397.30, which was 9.32 times higher than that of the pristine MOF:ZnO. And the response and recovery times were 17 and 117 s respectively, demonstrating a speedy detection capability. In addition, the sensor gained excellent stability and reproducibility with special selectivity for n-butanol. The comprehensive achievements of this research would be promising to promote the development of volatile organic compound detection technology and beneficial to the well application in the fields of environmental monitoring, industrial safety, and public health. [ABSTRACT FROM AUTHOR]

The shoulder complex, which has the highest prevalence of instability, is currently, the subject of considerable debate regarding the methodologies used to assess shoulder stability during dynamic exercises. The primary aim is to summarize evidence on various methodologies used to evaluate shoulder stability during dynamic exercises. This scoping review included cross-sectional studies focusing on various evaluation techniques to assess shoulder forces, kinetics, and stability during dynamic movements. In analyzing each study, the selected data included population profile, sample size, exercise type, and evaluation methodology used. Twenty-seven studies with a total of 1187 subjects were included. Among the studies, various dynamic exercises were evaluated, including throwing exercises, movements with dumbbells or elastic bands, push-ups, and functional tasks. Most evaluation techniques were combined, with eleven studies using surface electromyography; seven used dynamometers to obtain direct strength measurements; two used six-force axis sensors; one utilized force platforms; and one was focused on the loss of speed using linear velocity transducers. Furthermore, motion capture systems such as high-speed cameras were used in fourteen studies. In conclusion, surface electromyography and high-speed cameras are the primary techniques for measuring muscle activity and kinetic and kinematic data. However, they do not directly measure glenohumeral stability, meaning further research is needed to develop reliable methodologies for this purpose. This study holds significant relevance in the field of shoulder instability and has clear clinical implications, as it establishes the primary tools for estimating glenohumeral stability, which could enable patient stratification and the design of optimal intervention programs based on these measurements. • Kinetic and kinematic data could be extrapolated as an indirect measure of glenohumeral stability. • The most reliable technique to evaluate stability in functional tasks is surface electromyography. • The strength measured through isokinetic dynamometers presents a direct relationship with the dynamic shoulder stability. • High-speed cameras stand out as valid instrument for the three-dimensional analysis of functionality in a complex spectrum. • There is an absence of precise and direct techniques of evaluation that could be applicable to the clinical context. [ABSTRACT FROM AUTHOR]

In this work, the ZnO microsphere is prepared by hydrothermal method and modified with different concentrations of Eu. The morphology of ZnO:Eu sample shows flower-like microspheres with many nanosheets. The gas performance of ZnO:Eu microsphere is investigated for detecting NO 2. Compared with pure ZnO, the response of ZnO:2 % Eu sensor is increased by 8 times, and the optimal operating temperature of that is decreased to 130 °C. Especially, the gas sensing properties of ZnO:2 % Eu sensor is enhanced under UV excitation. The recovery time of ZnO:Eu sensor is reduced by 1200 s, and the response is increased by 3.6 times under UV excitation. The above results show an increase in sensor response due to doping Eu and UV excitation. At last, the possible gas mechanism of ZnO:Eu is discussed with and without UV excitation. This finding provides important guidance for UV-assisted sensors to enhance NO 2 response. [ABSTRACT FROM AUTHOR]

A rigid-flexible dual-arm space robot offers promising potential for on-orbit operation due to complementary strengths of its rigid and flexible manipulators. The rigid manipulator has the advantage of large payload capacity and high motion accuracy. The segmented linkage flexible manipulator is ideal for maneuvering in narrow, unstructured environments like internal satellite inspections and maintenance, due to its flexibility and slender body. However, there are inevitable tracking errors due to the multiple cable-driven mechanisms in the flexible manipulator. It's difficult to get the configuration and end pose of flexible manipulator without adding external sensors. To address these issues, this paper presents a method for configuration reconstruction and all-joint synchronous measurement of the flexible manipulator. The flexible manipulator is captured by the stereovision system mounted on the rigid manipulator. The links' equivalent center points are recognized by central moment method and edge line extraction method based on the natural characteristics. Joint - to - link kinematic model of flexible manipulator is established to measure joint angles and reconstruct configuration. Several simulations and experiments are carried out to validate the proposed method. The experimental results showed links' average measurement position errors were less than 13 mm and joint angles reconstructed using the proposed method had an error of approximately 0.35 °. These results demonstrate the accuracy and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

With the increasing requirements from toxic and hazardous gas detection technologies, WO 3 -based gas sensors have garnered tremendous interest on account of their low operating temperatures, good cycling stability, and short response/recovery time. So far, considerable progress has been made in the design and preparation of different architectures of WO 3. The sensing mechanism of WO 3 -based gas sensors is relatively complex. To further optimize the capabilities of WO 3 -based gas sensors, the influencing factors of the sensing mechanism need to be deeply understood to seek more effective enhanced strategies. This review probes the application of WO 3 -based sensors for various dangerous gases and contrastively analyses the sensing behavior of WO 3 in detail. In addition, we pay special attention to the interfacial interaction pathways between the sensing material and the target gas. Nowadays, more efforts are being made to strengthen the sensing properties of WO 3 -based materials so that they can be used in more smart demanding and complex environments. The authors focus on four approaches, namely, morphology control, hybridization, defect engineering, and photoactivation, for enhancing gas sensors and providing a comprehensive study of WO 3 for gas-sensing applications. Finally, we discuss the current problems and improvement methods and provide an outlook on the development trend of WO 3 -based gas sensors. The WO 3 -based gas sensitive materials are reviewed from adsorption, reactive and transducing interfacial issues, and their sensitivity and selectivity can be improved prominently by quaternary strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing interest in the visual detection of micro aerial vehicles (MAVs) due to its importance in numerous applications. However, the existing methods based on either appearance or motion features encounter difficulties when the background is complex or the MAV is too small. In this paper, we propose a novel motion-guided MAV detector that can accurately identify small MAVs in complex and non-planar scenes. This detector first exploits a motion feature enhancement module to capture the motion features of small MAVs. Then it uses multi-object tracking and trajectory filtering to eliminate false positives caused by motion parallax. Finally, an appearance-based classifier and an appearance-based detector that operates on the cropped regions are used to achieve precise detection results. Our proposed method can effectively and efficiently detect extremely small MAVs from dynamic and complex backgrounds because it aggregates pixel-level motion features and eliminates false positives based on the motion and appearance features of MAVs. Experiments on the ARD-MAV dataset demonstrate that the proposed method could achieve high performance in small MAV detection under challenging conditions and outperform other state-of-the-art methods across various metrics. • We proposed a simple but effective method to aggregate pixel-level motion features by frame alignment and multi-frame difference. Compared with existing methods, our proposed method can effectively extract motion features of extremely small MAVs from complex backgrounds. • The false positives generated by motion parallax can be effectively removed by multi-object tracking, trajectory filtering, and appearance-based classification. This is because our proposed method can model the spatial and temporal features of MAVs that are different from false positives. • To validate the effectiveness of our method, we have conducted extensive experiments on the ARD- MAV dataset. The experimental results show that our proposed detector can effectively detect small MAVs under complex and non-planar scenes and outperforms the state-of-the-art algorithms on various metrics. [ABSTRACT FROM AUTHOR]

New technologies can help to achieve the sustainable development goals (SDGs) of the United Nations. We discuss the contribution of microfluidic electrochemical biosensors to advancing the SDGs. These sensors can be applied in various fields given their low cost, self-powering ability, environmental compatibility, ease of use, and small sample volume requirements. [ABSTRACT FROM AUTHOR]

Partial shading deteriorates the overall performance of photovoltaic (PV) arrays by reducing the power output. Various shading mitigation strategies have been proposed in the literature with vulnerabilities of limited applications, switches, sensor counts, design, cost, and complexities. In this paper, a multi-string differential power processing (MS-DPP) based voltage equalizer is proposed for power output improvement in the PV arrays during shading. The equalizer is utilized for the series-parallel array which is equipped with a shading detection system achieved from the optimal placement of minimum sensor counts. The technique uses the concept of a switching capacitor that balances the voltage ratio between the modules of individual strings to ensure higher power generation and convex power curves during shading. The system is simulated and validated in MATLAB simulation and further verified on the OPAL-RT 4510 hardware-in-loop FPGA-based real-time platform. The technique is executed on three array sizes and compared with existing techniques under static and dynamic partial shading cases. The analysis shows that MS-DPP enhances the array power output with a conversion efficiency higher than 99 % during shading with lower system size and 98.38 % and 95.05 % reduced counts of switches and sensors than dynamic reconfigurations. • A multi-string differential power processing (MS-DPP) voltage equalizer for PV arrays is proposed. • MS-DPP ensures higher power generation with smoother power curves during partial shading. • Validated in MATLAB and OPAL-RT environment under shading cases for multiple arrays. • Compared with conventional systems, power optimizer, static and dynamic reconfigurations. • Power conversion efficiency of higher than 99 % with 98.38 % and 95.05 % less switches and sensors than dynamic reconfiguration. [ABSTRACT FROM AUTHOR]

This paper presents the design of a Lyapunov matrix-based adaptive resilient controller for unmanned marine vehicles (UMVs) under state-dependent sensor attacks, input-dependent thruster attacks, and time delays. Different from the thruster attack model that depends on state information, the thruster attack model studied in this paper is related to control input, that is, the input-dependent thruster attacks. This implies that the designed correction signal is also affected by the attacks. To mitigate the impact of the considered sensor attacks and thruster attacks on UMVs, an adaptive mechanism is employed to estimate the attack factors. Furthermore, a Lyapunov matrix-based complete-type Lyapunov–Krasovskii functional (LKF) is introduced, in which more comprehensive time delay information are considered. Based on this, linear matrix inequality (LMI) method and Jensen's inequality are used to obtain sufficient conditions for the existence of the controller. The proposed controller guarantees that the state errors of UMVs converge asymptotically to zero with the adaptive H ∞ performance index no larger than γ 0. Finally, the efficacy of the proposed approach is verified by simulation results. • A novel Lyapunov matrix-based resilient control strategy is proposed. • Compensate for the impact of the correction signal being attacked. • Constructs a Lyapunov matrix based complete-type LKF. • Ensure that the state errors of UMVs converge asymptotically to zero and has the prescribed H ∞ performance index γ 0. [ABSTRACT FROM AUTHOR]

This paper investigates the estimation problem of a class of nonlinear systems with actuator and sensor faults. The primary objective is to design a distributed fault-tolerant observer which can estimate system states and actuator faults. Firstly, a distributed observer network with intermediate parameters is constructed to compensate the missing information of unobservable nodes of the system. Next, a class of redundant sensors is set up for each distributed observer node to obtain more output measurement samples. More importantly, when some of the redundant sensors occur faults, all sensor signals will be further processed and classified by a new algorithm. An index of sensor health level is constructed to characterize the quality of the fault-free or faulty sensor signals. By using the proposed algorithm, unhealthy sensor signals will be automatically filtered out, while healthy ones will be retained. Based on the healthy sensor signals, the system states and actuator faults are estimated. Finally, an example demonstrates that the proposed method is effective. • In this article, an improved distributed observer network is designed. The actuator fault can be estimated even if the sub-observer nodes are not observable. • We set up a class of redundant sensors to obtain more output measurement samples. Then, a novel algorithm is designed to filter out low quality output information. • We introduce a novel robustness term to against the effect of faulty sensors. The actuator fault can be observed in the case of sensor fault, which does not require employing extra fault detection mechanisms. [ABSTRACT FROM AUTHOR]

Real-time monitoring of structural health status is very important for supersonic aircraft, since the long-term operation in harsh service environments, such as high temperatures, can cause potential damage. Structural health monitoring (SHM) based on lamb wave has been approved to be a critical technique for the reliable operation of supersonic aircraft, but is limited by the operating temperature of conventional piezoelectric sensors, which makes it difficult to meet the high-temperature monitoring requirements. The BiFeO 3 –BaTiO 3 ceramics exhibit excellent piezoelectric properties and high Curie temperature (T c), making them promising for high-temperature SHM of supersonic aircraft. Here, we fabricated a piezoelectric sensor using 0.67BiFeO 3 -0.33BaTiO 3 -0.25%molMnO 2 (BF33BTMN-025) ceramic, which exhibits a piezoelectric charge constant (d 33) of 135 pC/N at room temperature and a T c of 448 °C. The BF33BTMN-025 ceramic sensor operates effectively at temperatures up to 200 °C and maintains stable damage monitoring sensitivity as well. Compared with Pb(Zr, Ti)O 3 (PZT), BaTiO 3 (BTO) and other piezoelectric sensors commonly used in SHM field, the BF33BTMN-025 ceramic sensor has a higher operating temperature and a comparable sensitivity. Our work demonstrates that the BF33BTMN-025 ceramic sensor can be employed as piezoelectric sensor for high-temperature SHM, which has a wide application potential in the field of real-time monitoring of supersonic aircraft. [ABSTRACT FROM AUTHOR]

For the on-line stable detection of TEA, mixed potential gas sensor based on GDC (gadolinium doped cerium oxide, Ce 0.8 Gd 0.2 O 1.95) solid electrolyte and MFe 2 O 4 (M = Ni, Cu, Zn) sensing electrode has been fabricated in this work. The influence of element type and sintering temperature of the sensing materials on the sensing performance were mainly discussed, the sensor manufactured with CuFe 2 O 4 sintered at 800 °C generates the highest response (−50.7 mV) to 20 ppm TEA compared with other sensors. The response value changed proportionally with the logarithm of TEA concentration, with the sensitivity of −21.9 and −43.6 mV/decade in the range of 0.5–5 and 5–100 ppm, respectively. The sensor exhibited excellent repeatability towards 2 and 10 ppm TEA for 7 continuous tests, and great selectivity for 10 various gases. Moreover, the sensor also demonstrated good moisture resistance and terrific long-term stability at 500 °C for 30 days continuous work. Based on the excellent sensing properties, this work supplied a stable TEA sensor fabricated with CuFe 2 O 4 sintered at 800 °C, which has a great potential application prospect for the accurate detection towards TEA. [Display omitted] [ABSTRACT FROM AUTHOR]

A hot spot which is a glowing orange local area appears in RE Ba 2 Cu 3 O y (RE : rare earth) ceramic rods when a voltage higher than a certain value is applied at room temperature. After the hot spot appears, the oxygen partial pressure in the ambient atmosphere changes the current through the rod, which can be used as an oxygen sensor without the need for a heating system. In this study, the authors investigated the oxygen-sensing characteristics and the power-saving effect of the sandwich structure in which the sensor layer was stacked between insulation layers. The sample rods were prepared by the solid-state reaction at 960 °C. Materials of 5 mol% Nd 2 BaCuO 5 -added Nd 1.4 Ba 1.6 Cu 3 O y and 20 mol% Nd 1.4 Ba 1.6 Cu 3 O y -added Nd 2 BaCuO 5 were used for the sensor layer and the insulation layer, respectively. The sensitivity to the oxygen increased with increasing voltage applied to the rod. Under the condition where 17.8 V was applied to the rod with the sandwich structure and 6.6 V to the rod with the monolithic structure, the sensitivities of both rods were almost the same. The sandwich structure had a reduced current value and consumed approximately 26 % less power than the monolithic structure. The response time for the sandwich structure and the monolithic structure were comparable, meaning that the insulation layer did not impair the response time. [ABSTRACT FROM AUTHOR]

3D printing has revolutionised the design and manufacturing of high-temperature thin/thick-film sensors (TFSs). However, existing printable high-temperature materials face cost-performance trade-offs. This study proposes a silicate and RuO 2 composite for the 3D printing of TFSs. A silicate compound (SiO 2 –Al 2 O 3 –CaO, SAC) was used as a sintering aid to reduce the sintering temperature of RuO 2 , forming a silicate glass phase that enhanced film density and substrate adhesion. The SAC also minimised RuO 2 particle volatilisation at high temperatures, thus enhancing the stability of the SAC/RuO 2 composite. The SAC/RuO 2 TFSs demonstrated exceptional performance, with a positive temperature coefficient (502 ppm/°C) from room temperature to 800 °C, high linearity, and stability (resistance drift rate of 0.1 %/h at 800 °C), extending the application temperature of RuO 2 by nearly 200 °C from the previous application temperature of 600 °C. Therefore, the SAC/RuO2 composite offers a new low-cost and high-performance solution for using 3D printing technology in harsh environmental sensors such as turbine blades. [ABSTRACT FROM AUTHOR]

A highly sensitive and repeatable humidity sensor that can measure relative humidity at room temperature (25 °C) was fabricated using activated carbon-ZnO (AC/ZnO) nanocomposites. The AC/ZnO nanocomposites with high oxygen vacancies were prepared by a facile one-pot synthesis method through carbonization of ZnCl 2 -impregnated biomass precursor. The sensor exhibited a better response (96 % at 0.5 V biasing), short response time (17.4 s), and recovery time (32.1 s). The same 96 % relative response at 0.5V biasing for all four consecutive cycles was observed without losing the response-recovery time, indicating excellent repeatability. On the other hand, biomass-derived single-phase activated carbon (AC) did not respond to humidity change at room temperature. The improved humidity sensing in AC/ZnO nanocomposites was ascribed to the synergistic effects of increased oxygen vacancies, increased active sites in the AC phase, and the formation of p–n heterojunction at the composite interface, substantiated with X-ray diffraction (XRD), Raman and X-ray photoelectron spectroscopy (XPS) studies. The sensing mechanism of AC/ZnO nanocomposite was discussed based on the enhanced reduction of H 2 O by adsorbed O 2 − at AC/ZnO heterojunction, leading to increasing sensor resistance. [Display omitted] [ABSTRACT FROM AUTHOR]

Changes in spatio-temporal gait parameters and their variability during balance-challenging tasks are markers of motor performance linked to fall risk. Radio frequency (RF) sensors hold great promise towards achieving continuous remote monitoring of these parameters. To establish the concurrent validity of RF-based gait metrics extracted using micro-Doppler (µD) signatures and to determine whether these metrics are sensitive to gait modifications created by multidirectional visual perturbations. Fifteen participants walked overground in a virtual environment (VE) and VE with medio-lateral (ML) and antero-posterior (AP) perturbations. An optoelectronic motion capture system and one RF sensor were used to extract the linear velocity of the trunk and estimate step time (ST), step velocity (SV), step length (SL), and their variability (STV, SVV, and SLV). Intra-class coefficient for consistency (ICC), mean and standard deviation of the differences (MD), 95 % limits of agreement, and Pearson correlation coefficients (r) were used to determine concurrent validity. One-way repeated-measures analysis of variance was used to analyze the main and interaction effects of visual conditions. All outcomes showed good to excellent reliability (r>0.795, ICC>0.886). Average gait parameters showed good to excellent agreement, with values obtained with the RF sensor systematically smaller than the values obtained with the markers (MD of 0.001 s, 0.09 m/s, and 0.06 m). Gait variability parameters showed poor to moderate agreement, with values obtained with the RF sensor systematically larger than those obtained with the markers (MD of 1.9 %-3.9 %). Both measurement systems reported decreased SL and SV during ML perturbations, but the gait variability parameters extracted with the radar were not able to detect the higher STV and SLV during this condition. The radar µD signature is a valid and reliable method for the assessment of average spatio-temporal gait parameters but gait variability measures need to be viewed with caution because of the lower levels of agreement and sensitivity to ML visual perturbations. This work represents an initial investigation for the development of a low-cost system that will facilitate aging-in-place by providing remote monitoring of gait in natural settings. • A Radio Frequency (RF) sensor was used to estimate gait parameters. • A virtual reality headset was used to deliver visual perturbations while walking. • The RF sensor can estimate gait parameters with good to excellent reliability. • The RF sensor can estimate gait parameters with poor to excellent agreement. • The RF gait variability measures need to be viewed with caution. [ABSTRACT FROM AUTHOR]

Sensitive measures to predict neuromotor outcomes from data collected early in infancy are lacking. Measures derived from the recordings of infant movement using wearable sensors may be a useful new technique. We collected full-day leg movement of 41 infants in rural Guatemala across 3 visits between birth and 6 months of age using wearable sensors. Average leg movement rate and fuzzy entropy, a measure to describe the complexity of signals, of the leg movements' peak acceleration time series and the time series itself were derived. We tested the three measures for the predictability of infants' developmental outcome, Bayley Scales of Infant and Toddler Development III motor, language, or cognitive composite score assessed at 12 months of age. We performed quantile regressions with clustered standard errors, accounting for the multiple visits for each infant. Fuzzy entropy was associated with the motor composite score at the 0.5 quantiles; this association was not found for the other two measures. Also, no leg movement characteristic was associated with language or cognitive composite scores. We propose that the entropy of leg movement associated peak accelerations calculated from the wearable sensor data collected for a full-day can be considered as one predictor for infants' motor developmental outcome assessed with Bayley Scales of Infant and Toddler Development III at 12 months of age. • We collected wearable sensor data of spontaneous infant limb movements in rural Guatemala. • Early entropy of peak acceleration per leg movement was associated with later motor development. • Prediction of developmental status may be enhanced by including wearable sensor measures. [ABSTRACT FROM AUTHOR]

Wearable technologies using inertial sensors are an alternative for gait assessment. However, their psychometric properties in evaluating post-stroke patients are still being determined. This systematic review aimed to evaluate the psychometric properties of wearable technologies used to assess post-stroke gait and analyze their reliability and measurement error. The review also investigated which wearable technologies have been used to assess angular changes in post-stroke gait. The present review included studies in English with no publication date restrictions that evaluated the psychometric properties (e.g., validity, reliability, responsiveness, and measurement error) of wearable technologies used to assess post-stroke gait. Searches were conducted from February to March 2023 in the following databases: Cochrane Central Registry of Controlled Trials (CENTRAL), Medline/PubMed, EMBASE Ovid, CINAHL EBSCO, PsycINFO Ovid, IEEE Xplore Digital Library (IEEE), and Physiotherapy Evidence Database (PEDro); the gray literature was also verified. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) risk-of-bias tool was used to assess the quality of the studies that analyzed reliability and measurement error. Forty-two studies investigating validity (37 studies), reliability (16 studies), and measurement error (6 studies) of wearable technologies were included. Devices presented good reliability in measuring gait speed and step count; however, the quality of the evidence supporting this was low. The evidence of measurement error in step counts was indeterminate. Moreover, only two studies obtained angular results using wearable technology. Wearable technologies have demonstrated reliability in analyzing gait parameters (gait speed and step count) among post-stroke patients. However, higher-quality studies should be conducted to improve the quality of evidence and to address the measurement error assessment. Also, few studies used wearable technology to analyze angular changes during post-stroke gait. • Validity, reliability and measurement error of the devices have been investigated. • Devices presented good reliability in measuring gait parameters post-stroke. • Evidence on reliability is sufficient but of low quality. • Evidence on measurement error is sufficient but of low quality. • Few studies use portable devices to analyze angular changes. [ABSTRACT FROM AUTHOR]

Despite deleterious biomechanics associated with injury, particularly as it pertains to load carriage, there is limited research on the association between physical demands and variables captured with wearable sensors. While inertial measurement units (IMUs) can be used as surrogate measures of ground reaction force (GRF) variables, it is unclear if these data are sensitive to military-specific task demands. Can wearable sensors characterise physical load and demands placed on individuals in different load, speed and grade conditions? Data were collected on 20 individuals who were self-reportedly free from current injury, recreationally active, and capable of donning 23 kg in the form of a weighted vest. Each participant walked and ran on flat, uphill (+6 %) and downhill (-6 %) without and with load (23 kg). Data were collected synchronously from optical motion capture (OMC) and IMUs placed on the distal limb and the pelvis. Data from an 8-second window was used to generate a participant-based mean of OMC and IMU variables of interest. Repeated Measures ANOVA was used to measure main and interaction effects of load, speed, and grade. Simple linear regression was used to elucidate a relationship between OMC measures and estimated metabolic cost (EMC) to IMU measures. Load reduces foot and pelvic accelerations (p<0.001) but elevate signal attenuation per step (p=0.044). Conversely, attenuation per kilometre is lowered with the addition of load (p=0.017). Uphill had the lowest attenuation per step (p=0.003) and kilometre (p≤0.033) in walking, while downhill had the greatest attenuation per step (p≤0.002) and per kilometre (p≤0.004). Attenuation measures are inconsistently moderately related to limb negative work (R≤0.57). EMC is moderately positively related to unloaded running (R≥0.39), and moderately negatively related to walking with and without load (R≤-0.52). While load reduces peak accelerations at both the pelvis and foot. However, it may increase demand on the lower extremity to attenuate the signal between the two sensors with each step, while attenuation over time reduces with load. • Load reduces foot and pelvis accelerations but increases signal attenuation per step. • Attenuation per kilometre is lower with the addition of load. • Uphill walking has lower signal attenuation compared to flat and downhill walking. • Uphill running has higher signal attenuation compared to flat and downhill running. • Estimated physiological cost is negatively related to attenuation while walking, but positively related to attenuation while running. [ABSTRACT FROM AUTHOR]

Intrinsic foot muscles are known to support the medial longitudinal arch (MLA) and stabilize the foot, and they are activated with weight bearing and increased postural demand. Various types of intrinsic foot muscle training have been reported, but one of the most useful of these, the short foot exercise, is challenging to perform effectively and requires practice, making it difficult to implement in ordinary clinical settings. What are the differences in abductor hallucis longus (ABH) muscle activity and MLA angle during intrinsic foot muscle exercises that employ weight bearing and balancing conditions when they are performed with minimal practice? Sixteen healthy volunteers performed nine different intrinsic foot muscle exercises, practiced once or twice. The exercises consisted of toe curl, short foot without pushing, short foot with pushing and toe spread exercises in sitting and standing positions, and single leg swing in a standing position. Each exercise was performed three times for five seconds. The activities of the ABH muscles were measured using surface electromyographic (EMG) sensors and the MLA angles during the exercises were captured using an optical motion tracking system. The integrals of the ABH EMG signals were calculated. Differences in the integral and maximum of the ABH EMG signal were found between the exercises (p < 0.001). Post-hoc pair-wise analysis revealed that the EMG activity was larger during the swing exercise than in exercises other than toe spread, both in sitting and standing positions, and short foot exercise with pushing while standing. The minimum MLA angle during each exercise was smaller for the toe spread exercise in a sitting position than other exercises (p < 0.023). A single leg swing exercise may be effective for self-exercise of intrinsic foot muscles, particularly when intensive supervised physiotherapy is not possible. • Abductor hallicus longus activated in single leg swing without lengthy practice. • The minimum longitudinal arch angle was larger in standing than in sitting. • Standing single leg swing may be effective exercise for foot intrinsic muscles. [ABSTRACT FROM AUTHOR]

Over the past decades, tremendous technological advances have emerged in human motion analysis (HMA). How has technology for analysing human motion evolved over the past decades, and what clinical applications has it enabled? The literature on HMA has been extensively reviewed, focusing on three main approaches: Fully-Instrumented Gait Analysis (FGA), Wearable Sensor Analysis (WSA), and Deep-Learning Video Analysis (DVA), considering both technical and clinical aspects. FGA techniques relying on data collected using stereophotogrammetric systems, force plates, and electromyographic sensors have been dramatically improved providing highly accurate estimates of the biomechanics of motion. WSA techniques have been developed with the advances in data collection at home and in community settings. DVA techniques have emerged through artificial intelligence, which has marked the last decade. Some authors have considered WSA and DVA techniques as alternatives to "traditional" HMA techniques. They have suggested that WSA and DVA techniques are destined to replace FGA. We argue that FGA, WSA, and DVA complement each other and hence should be accounted as "synergistic" in the context of modern HMA and its clinical applications. We point out that DVA techniques are especially attractive as screening techniques, WSA methods enable data collection in the home and community for extensive periods of time, and FGA does maintain superior accuracy and should be the preferred technique when a complete and highly accurate biomechanical data is required. Accordingly, we envision that future clinical applications of HMA would favour screening patients using DVA in the outpatient setting. If deemed clinically appropriate, then WSA would be used to collect data in the home and community to derive relevant information. If accurate kinetic data is needed, then patients should be referred to specialized centres where an FGA system is available, together with medical imaging and thorough clinical assessments. • Gait analysis by stereophotogrammetry provides highly accurate biomechanics of motion. • Wearable sensors enable ecological data collection at home and in community setting. • Deep-learning video analysis can perform motion capture without instruments on subjects. • Several authors suggest more modern technologies shall replace traditional gait analysis. • We argue that these three technologies complement each other and shall be "synergistic". [ABSTRACT FROM AUTHOR]

Human behavior patterns involve mutual interactions among psychology, physiology, and stress, which are all associated with gait at different grades. The study aims to reveal the interrelationship among personality, mental workload, and gait patterns by capturing gait variations using inertial sensors. It also assesses individual personality traits and simulates stress to construct a gait classification model. Sixty participants were instructed to perform regular, low, and high mental workload walking on the corridor to simulate a natural setting walking. Meanwhile inertial measurement units (IMUs) were placed on eight body parts. Mental workload was induced using the auditory n-back task, and their Big Five personality traits were evaluated. Gait data from IMUs were categorized into nine classifications of average, low, and high Big Five Inventory scores with three levels of mental workload walking. Subsequently, the segmentation gait data were used as input features for classifications in deep learning models, employing a sliding window long short-term memory network for nine classifications for different personality dimensions. The results indicated average accuracies of nine classifications were 83.6 % for Openness, 84.4 % for Conscientiousness, 82.0 % for Extraversion, 85.2 % for Agreeableness, and 84.5 % for Neuroticism across all IMU placements. Remarkably, gait data from the lower back IMU achieved the highest model performance, with an average accuracy of 92.7 %, in classifying the different levels of personality and mental workload walking. In contrast, the left wrist and chest showed several misclassifications among regular, low, and high mental workload walking across personality traits. Successful classification can help monitor an individual's mental state in real time and analyze personality dimensions, providing feedback and suggestions. The present study demonstrated that gait characteristics can contribute to more profound and personalized health information. • First one reveals gait variation across personality dimensions and mental workload. • 60 individuals with 8 IMUs completed walking tasks under varied mental workloads. • Over 82 % classification accuracies of five personalities across all IMU placements. • Gait data from the lower back IMU achieved the highest 93 % classification accuracy. [ABSTRACT FROM AUTHOR]

A R744 (CO 2) refrigeration system has been designed to cool down the Large Hadron Collider (LHC) silicon detectors ATLAS and CMS, located at CERN, Switzerland. The silicon detectors are subjected to high radiation levels. The system is composed of a pri- mary CO 2 trans-critical booster vapor compression loop operated with piston compressors, and an oil-free liquid pumped loop on the evaporation side, to preserve the detectors. To ensure the system's reliability, the cooling facility is designed to operate under a parallel operation mode of several modular 70 kW plant units providing evaporation temperature as low as -53 °C. This layout, is also useful in case of components failure and maintenance. A numerical model is developed using a dynamic simulation software Dymola that is based on the open source Modelica modelling language. The simulation results are proven on a first demonstration plant (System A) experimentally to explore the systems control logic and to validate the reliability of the system before it is built on the detectors side. In this paper the models development is explained and the results of the experimental validation of the numerical model are shown. [ABSTRACT FROM AUTHOR]

Here, Ce-doped ZnO flower-like nanosheets are prepared by one-step hydrothermal method. The sensor based on Ce–ZnO composite exhibits excellent gas-sensing properties to acetone. Compared with pure ZnO, the response of Ce–ZnO composite is increased by 5.5 times, and the optimum operating temperature is reduced by 60 °C. The gas-sensing properties of the sensor to acetone under different humidity conditions are investigated. The redox reaction of Ce element increases the anti-humidity of Ce–ZnO sensor. Finally, the gas sensing mechanism of Ce–ZnO nanomaterial and anti-humidity principle are discussed in detail. The result can provide a new material for develop high sensitivity acetone sensor and a new anti-humidity strategy for designing gas sensing materials. [ABSTRACT FROM AUTHOR]

Gas sensors with high sensitivity and high humidity resistance have broad application prospects in air monitoring and detection of exhaled biomarkers. Structural design and light-activated gas sensing technologies have been proposed as new strategies to improve the gas sensing performance of sensors. In this work, a series of Ca–Fe nanocomposite were prepared using a sol-gel method. The effects of annealing temperature on the phase structure and microstructure of the nanocomposites were systematically studied, and the sensing responses to ethanol vapour under different relative humidity (RH) and light conditions were compared. A novel CaFe 2 O 4 /Ca 2 Fe 2 O 5 (CF2/CF) nanocomposite with a p-p heterostructure was obtained by annealing at 700 °C. The microstructure of "nanorods + nanoparticles" indicated the formation of a composite phase structure. Notably, high ethanol sensing response of 3.95 was obtained for the CF2/CF-based sensor under 4 ppm ethanol at 69 % RH and moderate operating temperature of 160 °C, indicating high sensitivity and good humidity resistance. It was found that the ethanol sensing response of the CF2/CF-based sensor was significantly improved under light illumination. Compared to that in dark, the CF2/CF based sensor exhibited notably enhanced ethanol sensing responses of 20 %, 13.5 %, 8.5 %, and 7.9 % under 370 nm, 420 nm, and 470 nm light as well as natural light, respectively. The observed high sensitivity and high humidity resistance of the CF2/CF nanocomposites were attributed to the p-p heterojunction structure, light illumination and nature of both CF2 and CF materials. The p-p heterostructure CF2/CF nanocomposites contribute significantly to the development of gas sensors with high sensitivity. [ABSTRACT FROM AUTHOR]

A novel single-sensor method for monitoring rotating blade vibration is proposed and utilized to identify vibration parameters under the non-stationary condition. By analyzing the pulse-signal waveform, the blade tip displacement and vibration velocity are extracted. Then, the motion equation under the non-stationary condition is further developed to provide a theoretical basis. Finally, the optimization technology is applied to extract vibration parameters. Compared with multiple-sensor methods, the proposed method has lower installation difficulty, less equipment cost, fewer sensors, and no strict sensor layout requirement. Numerical simulations and experiments are conducted to validate the effectiveness and robustness of the proposed method. The relative error in the natural frequency does not exceed 0.1 %. Additionally, errors in other parameters are less than 8 % in the experiment. • A novel single-sensor method is proposed to identify the vibration parameters of the blade under non-stationary condition. • A novel measurement approach is proposed, which is based on the blade tip vibration velocity (BTVV). • Dynamic characteristic of the non-stationary vibration is investigated by the theoretical analysis. And the formula expression of BTVV under non-stationary condition is first derived. • Simulations and the experiment are performed to validate the proposed method. [ABSTRACT FROM AUTHOR]

• Seizure onset zone localization accuracy based on HFO rate was comparable for visual and automated HFO detection. • Optimizing automated HFO detection settings based on visual markings did not increase seizure onset zone localization accuracy. • For many patients, changing detection settings could improve SOZ localization accuracy, but new optimization methods are needed. High frequency oscillations (HFOs) are a biomarker of the seizure onset zone (SOZ) and can be visually or automatically detected. In theory, one can optimize an automated algorithm's parameters to maximize SOZ localization accuracy; however, there is no consensus on whether or how this should be done. Therefore, we optimized an automated detector using visually identified HFOs and evaluated the impact on SOZ localization accuracy. We detected HFOs in intracranial EEG from 20 patients with refractory epilepsy from two centers using (1) unoptimized automated detection, (2) visual identification, and (3) automated detection optimized to match visually detected HFOs. SOZ localization accuracy based on HFO rate was not significantly different between the three methods. Across patients, visually optimized detector settings varied, and no single set of settings produced universally accurate SOZ localization. Exploratory analysis suggests that, for many patients, detection settings exist that would improve SOZ localization. SOZ localization accuracy was similar for all three methods, was not improved by visually optimizing detector settings, and may benefit from patient-specific parameter optimization. Visual HFO marking is laborious, and optimizing automated detection using visual markings does not improve localization accuracy. New patient-specific detector optimization methods are needed. [ABSTRACT FROM AUTHOR]

Knowledge distillation (KD) has been one of the most potential methods to implement a lightweight detector, which plays a significant role in satellite in-orbit processing and unmanned aerial vehicle tracking. However, existing distillation paradigms exhibit limited accuracy in detecting arbitrary-oriented objects represented with rotated bounding boxes in remote sensing images. This issue is attributed to two aspects: (i) boundary discontinuity localization distillation, caused by angle periodicity of rotated bounding boxes, and (ii) spatial ossified feature distillation, induced by orientation-agnostic knowledge transitive regions, both of which contribute to ambiguous orientation estimation of objects. To address these issues, we propose an effective KD method called Orientation Distillation (OD) via anti-ambiguous spatial transformation, which consists of two modules. (i) Anti-ambiguous Location Prediction (ALP) module reformulates the regression transformation between teacher–student bounding boxes as Gaussian distributions fitting procedure. These distributions with distilled potential are optimized to accurately localize objects with the aid of boundary continuity cost. (ii) Orientation-guided Feature Calibration (OFC) module employs a learnable affine matrix to augment fixed CNN sampling grid into a spatially remapped one, which bridges between the multi-scale feature of teacher and student for effectively delivering the refined oriented awareness within adaptively distillation regions. Overall, OD customizes the spatial transformation of bounding box representation and sampling grid to transfer anti-ambiguous orientation knowledge, and significantly improves the performance of lightweight detectors upon non-axially arranged objects. Extensive experiments on multiple datasets demonstrate that our plug-and-play distillation framework achieves state-of-the-art performance. Codes are available at https://github.com/Molly6/OD. [ABSTRACT FROM AUTHOR]

Recently, there has been a greater emphasis on researching the potential use of ferrite nanoparticles as humidity-sensing materials. We report on the humidity-sensing properties of Mg 1-y Li y Fe 2 O 4 (y = 0, 0.01, 0.03 and 0.05), which were synthesized using the solution combustion synthesis route. According to the XRD analysis, it was observed that both the unit cell volume and the crystallite size increased as the concentration of lithium-ion increased. The crystallite size was measured to be 17–22 nm, indicating the presence of nanomaterials. Moreover, the material exhibited a single phase with the Fd-3m space group, suggesting its structural integrity and uniformity. The FE-SEM images revealed that the porous nature of the material became more pronounced with higher concentrations of Li, indicating potential benefits for sensing applications. The synthesized powder demonstrated promising characteristics for use in humidity sensors. Specifically, it was noted that increasing the Li composition led to a notable increase in resistance, particularly significant for the Li = 0.05 concentration, which exhibited the highest average sensitivity. This suggests that Li doping at this concentration effectively enhances resistance, a crucial aspect for sensor functionality. The response and recovery times of thin film humidity sensors fabricated from these materials were determined to be 9 and 12 s, respectively. These times indicate rapid and efficient sensing capabilities, essential for real-time monitoring applications. Moreover, the newly discovered sensing material exhibited exceptional stability and reproducibility, further highlighting its potential for practical sensor applications. In summary, the synthesized materials show great promise for humidity sensor applications due to their enhanced sensitivity, rapid response and recovery times, as well as their stability and reproducibility. These findings open up avenues for the development of advanced sensing technologies with improved performance and reliability. [ABSTRACT FROM AUTHOR]

Detection of volatile organic compounds (VOCs), particularly 2-butanone, has become crucial due to their widespread use and associated risks to human health. In this study, we present a novel synthesis method for spinel Co 3 O 4 nanoparticles (NPs) employing a microwave-assisted hydrothermal approach followed by calcination and investigate their efficiency in VOC sensing applications. The Co 3 O 4 NPs exhibit remarkable sensitivity and selectivity towards butanone at relatively low operating temperatures. VOC-sensing experiments reveal an optimal operating temperature of 250 ° C , showcasing an advantage over existing sensors. Notably, the sensor exhibits high selectivity for butanone, with signal values 1.6–4.5 times higher than those for other VOCs, including acetaldehyde, ethanol, isopropanol, methanol, acetone, m-xylene, toluene, and benzene. Additionally, the Co 3 O 4 NPs-based sensor demonstrates high sensitivity, detecting concentrations as low as 5 ppm of butanone, with fast response/recovery times of 41/86 s for 200 ppm of butanone and robust long-term stability. These findings underscore the potential of Co 3 O 4 NPs as promising candidates for low-temperature butanone detection, which is essential for environmental and human health monitoring purposes. [Display omitted] [ABSTRACT FROM AUTHOR]

This study explores integrating a novel cutaneous force feedback system for robotic-assisted surgery (RAS) systems aimed at improving tactile perception for surgical precision and safety. The system developed comprises two major components: a force-sensitive matrix sensor and a 4x4 tactile pin interface. Forces experienced by the sensors are mirrored through the tactile interface, conveying the sensation of knowing which part of the sensor is in contact and how much force is subjected to it. An algorithm called Dynamic Interval Localization (DIL) was developed to manipulate pin actuation by scheduling individualized dynamic oscillation. The system successfully detected operating forces from 0.1N to 5N while concurrently providing respective cutaneous feedback. The system's performance in force localization suggests significant potential and promises in elevating the haptic features of RAS systems. [ABSTRACT FROM AUTHOR]

This study evaluated the versatility of the MoJoXlab in conducting clinical movement analysis using inertial sensors from various manufacturers, including low-cost, non-proprietary, and open-protocol wearable options. Data were collected from 15 healthy participants who performed a range of clinically relevant activities and exercises using two sets of sensors. Dynamic time warping analysis of the sensor signals suggested that the collected dataset could be used for further algorithm development. The findings demonstrate that the current iteration of MoJoXlab can perform movement analysis using quaternions from sensors of any manufacturer. However, the accuracy of the resulting joint angles is not yet suitable for clinical applications across all sensor types, and only Xsens and NGIMU sensors are currently supported. This study also explored the potential for reducing the number of sensors required by MoJoXlab, which currently uses seven sensors to calculate joint angles for three joints (hip, knee and ankle) on both sides of the body. The creation of a comprehensive databank for lower limb movement analysis algorithms was an additional outcome of this work. Further research and development are necessary to expand MoJoXlab's support for multiple sensor manufacturers and improve the accuracy of joint angle calculations for clinical applications. [ABSTRACT FROM AUTHOR]

The state of object detection has quickly progressed due to the rapid development of hardware and deep learning models for the said task. The continuous development of the latter allowed its application in real-time. That is, from two-stage to one-stage detectors, which greatly reduced the processing time; and from anchor-based to anchor-free detectors, which allowed a more efficient and flexible model implementation. The purpose of this study is to explore the various YOLO versions available in Ultralytics to detect large office objects for obstacle avoidance. More specifically, this study observed how the versions, 3u, 5mu, 8 and 6m, from which the first three are anchor-free, perform over the dataset. Based from the results, it was found that there were no significant differences between the detectors, except for the anchor-based v6m, which has the worst scores. The four models, v8n, v8s, v8m, and v5mu, were, however, chosen as the candidate models due to their processing speed, ranging from 66 to 75 FPS on the NVIDIA GeForce RTX 3060 GPU. The said models were also subjected to an optimization process in terms of the confidence and IoU threshold values to find the pair that could provide the best metric scores. Results have provided candidate models for the study's detection task for obstacle avoidance in real-time. [ABSTRACT FROM AUTHOR]

• Compost organic matter was characterized with a color sensor. • Compost organic matter content was differentiated by principal components analysis. • Accurate compost organic matter quantification is possible in seconds. Composted materials serve as an effective soil nutrient amendment. Organic matter in compost plays an important role in quantifying composted materials overall quality and nutrient content. Measuring organic matter content traditionally takes considerable time, resources, and various laboratory equipment (e.g., oven, muffle furnace, crucibles, precision balance). Much like the quantitative color indices (e.g., sRGB R, sRGB G, sRGB B, CIEL*a* b*) derived from the low-cost NixPro2 color sensor have proven adept at predicting soil organic matter in-situ , the NixPro2 color sensor has the potential to be effective for predicting organic matter in composted materials without the need for traditional laboratory methods. In this study, a total of 200 compost samples (13 different compost types) were measured for organic matter content via traditional loss-on-ignition (LOI) and via the NixPro2 color sensor. The NixPro2 color sensor showed promising results with an LOI-prediction model utilizing the CIEL*a* b* color model through the application of the Generalized Additive Model (GAM) algorithm yielding an excellent prediction accuracy (validation R2 = 0.87, validation RMSE = 4.66 %). Moreover, the PCA scoreplot differentiated the three lowest organic matter compost types from the remaining 10 compost types. These results have valuable practical significance for the compost industry by predicting compost organic matter in real time without the need for laborious, time-consuming methods. [ABSTRACT FROM AUTHOR]

A double layer membrane humidity sensor was designed with a synergistic effect of force and hygroscopic expansion, capitalizing on the high sensitivity demonstrated by MXene material. This sensitivity was achieved through the modulation of resistance change associated with layer spacing of MXene. The double layer structure of sensor was made by vacuum filtration, with an inner layer of MXene for conductivity and an outer layer of cellulose nanofibers (CNF) for moisture absorption, which is rooted in the MXene through the CNFs, similar to the biomimetic structure of hairs rooted in the skin. The synergistic effect of humidity sensitivity is achieved by trapping and dissociating water molecules through the CNF layer generating a change in MXene stress and disrupting the conductive pathway of MXene upon swelling. The CNF/MXene humidity sensor showed a resistance change rate of 117.93 % from 11 % RH to 98 % RH, accompanied by a response time of 319s and a recovery time of 132s. Stable sensing performance is maintained even after 5 times adsorption and desorption cycling, prolonged exposure (7 days) or bending and folding. CNF/MXene bilayer membrane also has good electrical heating performance, reaching about 80 °C at 7V and maintaining stable performance under 5 cycles of heating and 10 min of long heating, respectively. The CNF/MXene membrane humidity sensor can monitor human respiration monitoring, fingertip humidity, pipeline leakage and artifact dehumidification, and combined with the function of electric heating can realize the cycle of dehumidification and humidity monitoring, which has a wide range of application prospects in flexible equipment. [ABSTRACT FROM AUTHOR]

In the work, a high-performance Eu 2 Sn 2 O 7 –SnO 2 (ES-2) humidity sensors were prepared through a one-step hydrothermal method. Eu 2 Sn 2 O 7 is a bimetallic material can increase the adsorption capacity to water molecules and promote electron transfer, thus improving the sensitivity of the sensor. The introduction of Eu 2 Sn 2 O 7 promotes the increase of the content of oxygen vacancies in the ES-2 composite material, which promotes the accelerated decomposition of water molecules, and facilitates the formation of the chemisorbed layer to improve the sensitivity of the sensor and the response time. The increase in specific surface area of ES-2 provided more adsorption sites for H 2 O and also provided a good transport channel for water molecules to diffuse into the interior of the material. ES-2 humidity sensor exhibits high sensitivity (22,405 ± 363), small humidity hysteresis (1 ± 0.3 %), short response/recovery time (7/6 ± 0.5 s), good repeatability and stability (11%–95 % RH). This study not only promotes the development of SnO 2 -based humidity sensors, but provides new ideas for the preparation of high-performance humidity sensors. [ABSTRACT FROM AUTHOR]

An optical fiber relative humidity (RH) sensor based on tapered no-core fiber (TNCF) coated with Ti 3 C 2 T x MXene is proposed. The fluoride etching method is used to prepare Ti 3 C 2 T x , which is used as the humidity sensitive material with a multi-layer structure, large specific surface area and rich hydrophilic groups, and optical deposition method is used to integrate Ti 3 C 2 T x with TNCF. The diameter of TNCF between two sections of SMF is reduced to 11.6 μ m to enhance RH sensitivity. The refractive index (RI) of Ti 3 C 2 T x changes as a result of variations in RH, and this ultimately causes a shift in the transmission spectrum. The sensitivity of the device is −77 pm/%RH in the range of 33 %RH to 75 %RH. In the region of 75 %RH to 91 %RH, the sensitivity increases to 685 pm/%RH, the linear correlation coefficients of the two regions are 0.9521 and 0.9940, respectively. On average, the response time is approximately 3.5 s and the recovery time is about 12.7 s. The sensor may be utilized in possible domains, including biological, chemical, and food processing. Its benefits include a simple construction, cheap cost, high reversibility, and stability. [ABSTRACT FROM AUTHOR]