bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Lactone- and Ketone-Brassinosteroids of the 28-Homobrassinolide Series on Barley Plants under Water Deficit
Authors: Kolomeichuk Liliya V. , Murgan Ol’ga K. , Danilova Elena D. , Serafimovich Mariya V. , Khripach Vladimir A. , Litvinovskaya Raisa P. , Sauchuk Alina L. , Denisiuk Daria V. , Zhabinskii Vladimir N. , Kuznetsov Vladimir V. , Efimova Marina V.
Published: May 2024

The aim of this work was to study the ability of 28-homobrassinolide (HBL) and 28-homocastasterone (HCS) to increase the resistance of barley (Hordeum vulgare L.) plants to drought and to alter their endogenous brassinosteroid status. Germinated barley seeds were treated with 0.1 nM HBL or HCS solutions for two hours. A water deficit was created by stopping the watering of 7-day-old plants for the next two weeks. Plants responded to drought through growth inhibition, impaired water status, increased lipid peroxidation, differential effects on antioxidant enzymes, intense proline accumulation, altered expression of genes involved in metabolism, and decreased endogenous contents of hormones (28-homobrassinolide, B-ketones, and B-lactones). Pretreatment of plants with HBL reduced the inhibitory effect of drought on fresh and dry biomass accumulation and relative water content, whereas HCS partially reversed the negative effect of drought on fresh biomass accumulation, reduced the intensity of lipid peroxidation, and increased the osmotic potential. Compared with drought stress alone, pretreatment of plants with HCS or HBL followed by drought increased superoxide dismutase activity sevenfold or threefold and catalase activity (by 36%). The short-term action of HBL and HCS in subsequent drought conditions partially restored the endogenous B-ketone and B-lactone contents. Thus, the steroidal phytohormones HBL and HCS increased barley plant resistance to subsequent drought, showing some specificity of action.
Patterned Liquid Crystal Polymer Thin Films Improved Energy Conversion Efficiency at High Incident Angles for Photovoltaic Cells
Authors: Wu Gwomei
Published: May 2024

In this report, micro-patterned silicon semiconductor photovoltaic cells have been proposed to improve the efficiency in various incident sunlight angles, using homeotropic liquid crystal polymers. The anisotropic liquid crystal precursor solution based on a reactive mesogen has good flowing characteristics. It can be evenly coated on the silicon solar cells’ surface by a conventional spreading technique, such as spin coating. Once cured, the polymers exhibit asymmetric transmittance properties. The optical retardation characteristics of the coated polymer films can be eventually determined by the applicable coating and curing parameters during the processes. The birefringence of light then influences the optical path and the divergence of any encountered sunlight. This allows more photons to enter the active semiconductor layers for optical absorption, resulting in an increase in the photon-to-electron conversion, and thus improving the photovoltaic cell efficiency. This new design is straightforward and could allow various patterns to be created for scientific development. The experimental results have evidenced that the energy conversion efficiency could be improved by 2–3% for the silicon photovoltaic cells, under direct sunlight or at no inclination, when the liquid crystal polymer precursor solution is prepared at 5%. In addition, the efficiency could be much more significantly improved to 14–16% when the angle is inclined to 45°. The unique patterned liquid crystal polymer thin films provide enhanced energy conversion efficiency for silicon photovoltaic cells. The design could be further evaluated for other solar cell applications.
Optimization of Mechanical Properties and Evaluation of Fatigue Behavior of Selective Laser Sintered Polyamide-12 Components
Authors: Sommer David , Stockfleet Henry , Hellmann Ralf
Published: May 2024

In this paper, a comprehensive study of the mechanical properties of selective laser sintered polyamide components is presented, for various different process parameters as well as environmental testing conditions. For the optimization of the static and dynamic mechanical load behavior, different process parameters, e.g., laser power, scan speed, and build temperature, were varied, defining an optimal parameter combination. First, the influence of the different process parameters was tested, leading to a constant energy density for different combinations. Due to similarities in mechanical load behavior, the energy density was identified as a decisive factor, mostly independent of the input parameters. Thus, secondly, the energy density was varied by the different parameters, exhibiting large differences for all levels of fatigue behavior. An optimal parameter combination of 18 W for the laser power and a scan speed of 2666 mm/s was determined, as a higher energy density led to the best results in static and dynamic testing. According to this, the variation in build temperature was investigated, leading to improvements in tensile strength and fatigue strength at higher build temperatures. Furthermore, different ambient temperatures during testing were evaluated, as the temperature-dependent behavior of polymers is of high importance for industrial applications. An increased ambient temperature as well as active cooling during testing was examined, having a significant impact on the high cycle fatigue regime and on the endurance limit.
The Effect of the Microstructure and Viscosity of Modified Bitumen on the Strength of Asphalt Concrete
Authors: Dyuryagina Antonina , Byzova Yuliya , Ostrovnoy Kirill , Demyanenko Alexandr , Tyukanko Vitaliy , Lutsenko Aida
Published: May 2024

The purpose of these studies was to establish the influence of the microstructural and rheological characteristics of modified bitumen compositions on the strength indicators of asphalt concrete. The effect of additives concentration on the rheological characteristics and microstructure of binary “bitumen–surfactant”, “bitumen-AG-4I”, and ternary “bitumen-AG-4I-AG-4I” systems has been studied. To assess the effect of bitumen dispersion on the physical and mechanical characteristics of modified asphalt concrete samples, the compressive strength value was determined. The following chemicals have been used as additives: the original product AS-1, industrial additive AMDOR-10, and used sealant AG-4I, a product based on polyisobutylene and petroleum oils. At an increased content of AG-4I (C ≥ 1.0 g/dm3) in ternary systems, the contribution of the emerging intermolecular polyisobutylene network to the development of structuring processes increases while the viscous effect of the surfactant AS-1 decreases. It has been established that the minimum size of bee-like bitumen structures (1.66 µm) is recorded with the joint presence of additives in the bitumen, AS-1 at a level of 1.0 g/dm3 and AG-4I at a level of 1.0 g/dm3. Under the same concentration regimes of the ternary bitumen composition, the maximum increase in compressive strength RD was achieved with the smallest size of bee-like structures of modified bitumen.
Simple Electrospinning Method for Biocompatible Polycaprolactone β-Carotene Scaffolds: Advantages and Limitations
Authors: Yoshikawa Orion , Basoli Valentina , Boschetto Francesco , Rondinella Alfredo , Lanzutti Alex , Zhu Wenliang , Greco Enrico , Thieringer Florian Markus , Xu Huaizhong , Marin Elia
Published: May 2024

In this study, electrospun scaffolds were fabricated using polycaprolactone (PCL) loaded with varying concentrations of β-carotene (1.2%, 2.4%, and 3.6%) via the electrospinning technique. The electrospinning process involved the melting of PCL in acetic acid, followed by the incorporation of β-carotene powder under constant stirring. Raman spectroscopy revealed a homogeneous distribution of β-carotene within the PCL matrix. However, the β-carotene appeared in particulate form, rather than being dissolved and blended with the PCL matrix, a result also confirmed by thermogravimetric analysis. Additionally, X-ray diffraction analysis indicated a decrease in crystallinity with increasing β-carotene concentration. Mechanical testing of the scaffolds demonstrated an increase in ultimate strain, accompanied by a reduction in ultimate stress, indicating a potential plasticizing effect. Moreover, antimicrobial assays revealed a marginal antibacterial effect against Escherichia coli for scaffolds with higher β-carotene concentrations. Conversely, preliminary biological assessment using KUSA-A1 mesenchymal cells indicated enhanced cellular proliferation in response to the scaffolds, suggesting the potential biocompatibility and cell-stimulating properties of β-carotene-loaded PCL scaffolds. Overall, this study provides insights into the fabrication and characterization of electrospun PCL scaffolds containing β-carotene, laying the groundwork for further exploration in tissue engineering and regenerative medicine applications.
Molecular Simulation of Covalent Adaptable Networks and Vitrimers: A Review
Authors: Karatrantos Argyrios V. , Couture Olivier , Hesse Channya , Schmidt Daniel F.
Published: May 2024

Covalent adaptable networks and vitrimers are novel polymers with dynamic reversible bond exchange reactions for crosslinks, enabling them to modulate their properties between those of thermoplastics and thermosets. They have been gathering interest as materials for their recycling and self-healing properties. In this review, we discuss different molecular simulation efforts that have been used over the last decade to investigate and understand the nanoscale and molecular behaviors of covalent adaptable networks and vitrimers. In particular, molecular dynamics, Monte Carlo, and a hybrid of molecular dynamics and Monte Carlo approaches have been used to model the dynamic bond exchange reaction, which is the main mechanism of interest since it controls both the mechanical and rheological behaviors. The molecular simulation techniques presented yield sufficient results to investigate the structure and dynamics as well as the mechanical and rheological responses of such dynamic networks. The benefits of each method have been highlighted. The use of other tools such as theoretical models and machine learning has been included. We noticed, amongst the most prominent results, that stress relaxes as the bond exchange reaction happens, and that at temperatures higher than the glass transition temperature, the self-healing properties are better since more bond BERs are observed. The lifetime of dynamic covalent crosslinks follows, at moderate to high temperatures, an Arrhenius-like temperature dependence. We note the modeling of certain properties like the melt viscosity with glass transition temperature and the topology freezing transition temperature according to a behavior ruled by either the Williams–Landel–Ferry equation or the Arrhenius equation. Discrepancies between the behavior in dissociative and associative covalent adaptable networks are discussed. We conclude by stating which material parameters and atomistic factors, at the nanoscale, have not yet been taken into account and are lacking in the current literature.
Selective Modifications of Sheep Wool Usable in Non-Textile Applications
Authors: Braniša Jana , Koóšová Karin , Porubská Mária
Published: May 2024

The traditional textile use of wool as a valuable renewable material needs alternative applications in order to, besides sheep milk and meat, valorize currently unnecessary wool. Each type of product containing sheep wool requires wool with customized properties. Finding suitable physical and chemical modifications needed to develop new products while minimizing harmful side effects is a challenge for scientists. The presented review provides a brief overview of works published over the last decade associated with innovative wool scouring, dyeing, antifelting, and modification of its structure without the ambition to present complete, detailed data.
Preparation and Investigation of High Surface Area Aerogels from Crosslinked Polypropylenes
Authors: Coufal Radek , Fijalkowski Mateusz , Adach Kinga , Bu Huaitian , Karl Christian W. , Mikysková Eliška , Petrík Stanislav
Published: May 2024

Polypropylene-based aerogels with high surface area have been developed for the first time. By chemical crosslinking of polypropylene with oligomeric capped-end amino compounds, followed by dissolution, thermally induced phase separation, and the supercritical CO2 drying process or freeze-drying method, the aerogels exhibit high specific surface areas up to 200 m2/g. Moreover, the silica-cage multi-amino compound was utilized in a similar vein for forming hybrid polypropylene aerogels. According to the SEM, the developed polypropylene-based aerogels exhibit highly porous morphology with micro-nanoscale structural features that can be controlled by processing conditions. Our simple and inexpensive synthetic strategy results in a low-cost, chemically resistant, and highly porous material that can be tailored according to end-use applications.
Tracking Water Quality and Macrophyte Changes in Lake Trasimeno (Italy) from Spaceborne Hyperspectral Imagery
Authors: Fabbretto Alice , Bresciani Mariano , Pellegrino Andrea , Alikas Krista , Pinardi Monica , Mangano Salvatore , Padula Rosalba , Giardino Claudia
Published: May 2024

This work aims to show the potential of imaging spectroscopy in assessing water quality and aquatic vegetation in Lake Trasimeno, Italy. Hyperspectral reflectance data from the PRISMA, DESIS and EnMAP missions (2019–2022, summer periods) were compared with in situ measurements from WISPStation and used as inputs for water quality product generation algorithms. The bio-optical model BOMBER was run to simultaneously retrieve water quality parameters (Chlorophyll-a (Chl-a) and Total Suspended Matter, (TSM)) and the coverage of submerged and emergent macrophytes (SM, EM); value-added products, such as Phycocyanin concentration maps, were generated through a machine learning approach. The results showed radiometric agreement between satellite and in situ data, with R2 > 0.9, a Spectral Angle < 10° and water quality mapping errors < 30%. Both SM and EM coverage varied significantly from 2019 (135 ha, 0 ha, respectively) to 2022 (2672 ha, 343 ha), likely influenced by changes in rainfall and lake levels. The areas of greatest variability in Chl-a and TSM were identified in the littoral zones in the western side of the lake, while the highest variation in the fractional cover of SM and density of EM were observed in the south-eastern region; this information could support the water authorities’ monitoring activities. To this end, further developments to improve the reference field data for the validation of water quality products are recommended.
HGR Correlation Pooling Fusion Framework for Recognition and Classification in Multimodal Remote Sensing Data
Authors: Zhang Hongkang , Huang Shao-Lun , Kuruoglu Ercan Engin
Published: May 2024

This paper investigates remote sensing data recognition and classification with multimodal data fusion. Aiming at the problems of low recognition and classification accuracy and the difficulty in integrating multimodal features in existing methods, a multimodal remote sensing data recognition and classification model based on a heatmap and Hirschfeld–Gebelein–Rényi (HGR) correlation pooling fusion operation is proposed. A novel HGR correlation pooling fusion algorithm is developed by combining a feature fusion method and an HGR maximum correlation algorithm. This method enables the restoration of the original signal without changing the value of transmitted information by performing reverse operations on the sample data. This enhances feature learning for images and improves performance in specific tasks of interpretation by efficiently using multi-modal information with varying degrees of relevance. Ship recognition experiments conducted on the QXS-SROPT dataset demonstrate that the proposed method surpasses existing remote sensing data recognition methods. Furthermore, land cover classification experiments conducted on the Houston 2013 and MUUFL datasets confirm the generalizability of the proposed method. The experimental results fully validate the effectiveness and significant superiority of the proposed method in the recognition and classification of multimodal remote sensing data.
Spatiotemporal Evolution and Factors Influencing Regional Ecological Land in a Multidimensional Perspective: A Case Study of the Beijing–Tianjin–Hebei Region
Authors: Wang Xingbang , Xu Ze , Huang Jing , Zhang Zhengfeng
Published: May 2024

A systematic analysis of the spatiotemporal evolution patterns and factors influencing ecological land (EL) can support the optimization of EL protection policies and ensure the stability of regional ecosystems. Based on remote sensing data, using the gravity center shift model, the landscape pattern index, and the equivalent factor method, the characteristics of EL evolution in the Beijing–Tianjin–Hebei (BTH) region from 1980 to 2020 were analyzed. A fixed-effects model was used to quantitatively explore the factors influencing EL evolution and heterogeneity analysis. The results are as follows: (1) The EL area exhibited a trend of initial decrease followed by a subsequent increase during the study period. The most significant area transfer occurred between cropland and EL, but, after the 21st century, the proportion of area transfer between construction land and EL noticeably increased. (2) The compactness and fragmentation of EL showed a certain spatiotemporal stability, but the spatial distribution of compactness and fragmentation hot and cold spots exhibited significant differences. The fragmentation hot spots mainly displayed a strip distribution, while those of compactness showed a clustered distribution. (3) Although the ecosystem service value in the BTH region demonstrated dynamic “M”-shaped changes, the distribution of hot and cold spots still exhibited spatial stability. Regulating services consistently occupied a higher proportion of the sub-service functions, while cultural services still needed further enhancement. (4) Factors influencing the evolution of areas and values demonstrated similarities. The landscape was significantly influenced by construction land, showing a non-linear “U”-shaped relationship with fragmentation. Different economic development gradients and altitudes exhibited differentiated characteristics in terms of their influencing factors. This study provides scientific support for dynamically and precisely adjusting governmental EL management policies, contributing to the sustainable development of regional socio-economics.
Effectiveness of Telerehabilitation in Dizziness: A Systematic Review with Meta-Analysis
Authors: Grillo Davide , Zitti Mirko , Cieślik Błażej , Vania Stefano , Zangarini Silvia , Bargellesi Stefano , Kiper Pawel
Published: May 2024

Dizziness can be a debilitating condition with various causes, with at least one episode reported in 17% to 30% of the international adult population. Given the effectiveness of rehabilitation in treating dizziness and the recent advancements in telerehabilitation, this systematic review aims to investigate the effectiveness of telerehabilitation in the treatment of this disorder. The search, conducted across Medline, Cochrane Central Register of Controlled Trials, and PEDro databases, included randomized controlled trials assessing the efficacy of telerehabilitation interventions, delivered synchronously, asynchronously, or via tele-support/monitoring. Primary outcomes focused on dizziness frequency/severity and disability, with secondary outcomes assessing anxiety and depression measures. Seven articles met the eligibility criteria, whereas five articles contributed to the meta-analysis. Significant findings were observed regarding the frequency and severity of dizziness (mean difference of 3.01, p < 0.001), disability (mean difference of −4.25, p < 0.001), and anxiety (standardized mean difference of −0.16, p = 0.02), favoring telerehabilitation. Telerehabilitation shows promise as a treatment for dizziness, aligning with the positive outcomes seen in traditional rehabilitation studies. However, the effectiveness of different telerehabilitation approaches requires further investigation, given the moderate methodological quality and the varied nature of existing methods and programs.
Biosensor-Driven IoT Wearables for Accurate Body Motion Tracking and Localization
Authors: Almujally Nouf Abdullah , Khan Danyal , Al Mudawi Naif , Alonazi Mohammed , Alazeb Abdulwahab , Algarni Asaad , Jalal Ahmad , Liu Hui
Published: May 2024

The domain of human locomotion identification through smartphone sensors is witnessing rapid expansion within the realm of research. This domain boasts significant potential across various sectors, including healthcare, sports, security systems, home automation, and real-time location tracking. Despite the considerable volume of existing research, the greater portion of it has primarily concentrated on locomotion activities. Comparatively less emphasis has been placed on the recognition of human localization patterns. In the current study, we introduce a system by facilitating the recognition of both human physical and location-based patterns. This system utilizes the capabilities of smartphone sensors to achieve its objectives. Our goal is to develop a system that can accurately identify different human physical and localization activities, such as walking, running, jumping, indoor, and outdoor activities. To achieve this, we perform preprocessing on the raw sensor data using a Butterworth filter for inertial sensors and a Median Filter for Global Positioning System (GPS) and then applying Hamming windowing techniques to segment the filtered data. We then extract features from the raw inertial and GPS sensors and select relevant features using the variance threshold feature selection method. The extrasensory dataset exhibits an imbalanced number of samples for certain activities. To address this issue, the permutation-based data augmentation technique is employed. The augmented features are optimized using the Yeo–Johnson power transformation algorithm before being sent to a multi-layer perceptron for classification. We evaluate our system using the K-fold cross-validation technique. The datasets used in this study are the Extrasensory and Sussex Huawei Locomotion (SHL), which contain both physical and localization activities. Our experiments demonstrate that our system achieves high accuracy with 96% and 94% over Extrasensory and SHL in physical activities and 94% and 91% over Extrasensory and SHL in the location-based activities, outperforming previous state-of-the-art methods in recognizing both types of activities.
Expert–Novice Level Classification Using Graph Convolutional Network Introducing Confidence-Aware Node-Level Attention Mechanism
Authors: Seino Tatsuki , Saito Naoki , Ogawa Takahiro , Asamizu Satoshi , Haseyama Miki
Published: May 2024

In this study, we propose a classification method of expert–novice levels using a graph convolutional network (GCN) with a confidence-aware node-level attention mechanism. In classification using an attention mechanism, highlighted features may not be significant for accurate classification, thereby degrading classification performance. To address this issue, the proposed method introduces a confidence-aware node-level attention mechanism into a spatiotemporal attention GCN (STA-GCN) for the classification of expert–novice levels. Consequently, our method can contrast the attention value of each node on the basis of the confidence measure of the classification, which solves the problem of classification approaches using attention mechanisms and realizes accurate classification. Furthermore, because the expert–novice levels have ordinalities, using a classification model that considers ordinalities improves the classification performance. The proposed method involves a model that minimizes a loss function that considers the ordinalities of classes to be classified. By implementing the above approaches, the expert–novice level classification performance is improved.
Research on Human Posture Estimation Algorithm Based on YOLO-Pose
Authors: Ding Jing , Niu Shanwei , Nie Zhigang , Zhu Wenyu
Published: May 2024

In response to the numerous challenges faced by traditional human pose recognition methods in practical applications, such as dense targets, severe edge occlusion, limited application scenarios, complex backgrounds, and poor recognition accuracy when targets are occluded, this paper proposes a YOLO-Pose algorithm for human pose estimation. The specific improvements are divided into four parts. Firstly, in the Backbone section of the YOLO-Pose model, lightweight GhostNet modules are introduced to reduce the model’s parameter count and computational requirements, making it suitable for deployment on unmanned aerial vehicles (UAVs). Secondly, the ACmix attention mechanism is integrated into the Neck section to improve detection speed during object judgment and localization. Furthermore, in the Head section, key points are optimized using coordinate attention mechanisms, significantly enhancing key point localization accuracy. Lastly, the paper improves the loss function and confidence function to enhance the model’s robustness. Experimental results demonstrate that the improved model achieves a 95.58% improvement in mAP50 and a 69.54% improvement in mAP50-95 compared to the original model, with a reduction of 14.6 M parameters. The model achieves a detection speed of 19.9 ms per image, optimized by 30% and 39.5% compared to the original model. Comparisons with other algorithms such as Faster R-CNN, SSD, YOLOv4, and YOLOv7 demonstrate varying degrees of performance improvement.
MDE and LLM Synergy for Network Experimentation: Case Analysis of Wireless System Performance in Beaulieu-Xie Fading and κ-µ Co-Channel Interference Environment with Diversity Combining
Authors: Krstic Dragana , Suljovic Suad , Djordjevic Goran , Petrovic Nenad , Milic Dejan
Published: May 2024

Channel modeling is a first step towards the successful projecting of any wireless communication system. Hence, in this paper, we analyze the performance at the output of a multi-branch selection combining (SC) diversity receiver in a wireless environment that has been distracted by fading and co-channel interference (CCI), whereby the fading is modelled by newer Beaulieu-Xie (BX) distribution, and the CCI is modelled by the κ-µ distribution. The BX distribution provides the ability to include in consideration any number of line-of-sight (LOS) useful signal components and non-LOS (NLOS) useful signal components. This distribution contains characteristics of some other fading models thanks to its flexible fading parameters, which also applies to the κ-µ distribution. We derived here the expressions for the probability density function (PDF) and cumulative distribution function (CDF) for the output signal-to-co-channel interference ratio (SIR). After that, other performances are obtained, namely: outage probability (Pout), channel capacity (CC), moment-generating function (MGF), average bit error probability (ABEP), level crossing rate (LCR), and average fade duration (AFD). Numerical results are presented in several graphs versus the SIR for different values of fading and CCI parameters, as well as the number of input branches in the SC receiver. Then, the impact of parameters on all performance is checked. From our numerical results, it is possible to directly obtain the performance for all derived and displayed quantities for cases of previously known distributions of fading and CCI by inserting the appropriate parameter values. In the second part of the paper, a workflow for automated network experimentation relying on the synergy of Large Language Models (LLMs) and model-driven engineering (MDE) is presented, while the previously derived expressions are used for evaluation. Due to the aforementioned, the biggest value of the obtained results is the applicability to the cases of a large number of other distributions for fading and CCI by replacing the corresponding parameters in the formulas for the respective performances.
Correction: Soršak et al. Design and Investigation of Optical Properties of N-(Rhodamine-B)-Lactam-Ethylenediamine (RhB-EDA) Fluorescent Probe. Sensors 2018, 18, 1201
Authors: Soršak Eva , Volmajer Valh Julija , Korent Urek Špela , Lobnik Aleksandra
Published: May 2024

In the published publication [...]
A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor
Authors: Hossain Md Billal , LaMunion Samuel R. , Crouter Scott E. , Melanson Edward L. , Sazonov Edward
Published: May 2024

Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and energy expenditure (EE) estimation. Traditionally, sensors are attached to the hip or wrist. The primary aim of this research is to investigate the use of an eyeglass-mounted wearable energy intake sensor (Automatic Ingestion Monitor v2, AIM-2) for simultaneous recognition of physical activity (PAR) and estimation of steady-state EE as compared to a traditional hip-worn device. Study data were collected from six participants performing six structured activities, with the reference EE measured using indirect calorimetry (COSMED K5) and reported as metabolic equivalents of tasks (METs). Next, a novel deep convolutional neural network-based multitasking model (Multitasking-CNN) was developed for PAR and EE estimation. The Multitasking-CNN was trained with a two-step progressive training approach for higher accuracy, where in the first step the model for PAR was trained, and in the second step the model was fine-tuned for EE estimation. Finally, the performance of Multitasking-CNN on AIM-2 attached to eyeglasses was compared to the ActiGraph GT9X (AG) attached to the right hip. On the AIM-2 data, Multitasking-CNN achieved a maximum of 95% testing accuracy of PAR, a minimum of 0.59 METs mean square error (MSE), and 11% mean absolute percentage error (MAPE) in EE estimation. Conversely, on AG data, the Multitasking-CNN model achieved a maximum of 82% testing accuracy in PAR, a minimum of 0.73 METs MSE, and 13% MAPE in EE estimation. These results suggest the feasibility of using an eyeglass-mounted sensor for both PAR and EE estimation.
A Circularly Polarized Non-Resonant Slotted Waveguide Antenna Array for Wide-Angle Scanning
Authors: Han Guodong , Liu Weihang
Published: May 2024

A compact circularly polarized non-resonant slotted waveguide antenna array is proposed with the aim of achieving wide-angle scanning, circular polarization, and low side-lobe levels. The designed antenna demonstrates a scanning range of +11° to +13° in the frequency domain and a beam scanning range of −45° to +45° in the phase domain. This design exhibits significant advantages for low-cost two-dimensional electronic scanning circularly polarized arrays. It employs a compact element that reduces the aperture area by 50% compared to traditional circular polarization cavities. Additionally, the staggered array method is employed to achieve an element spacing of 0.57λ within the azimuth plane. Isolation gaps were introduced into the array to enhance the circular polarization performance of non-resonant arrays. The Taylor synthesis method was employed to reduce the side-lobe levels. A prototype was designed, fabricated, and measured. The results indicate superior radiation efficiency, favorable VSWR levels, and an axis ratio maintenance below 3 dB across the scanning range. The proposed antenna and methodology effectively broaden the beam scanning angle of circularly polarized slotted waveguide array antennas.
The Validity and Reliability of a Real-Time Biofeedback System for Lumbopelvic Control Training in Baseball Players
Authors: Wang Shiu-Min , Jiang Po-Hsien , Chan Kuei-Yuan , Hsu Wei-Li
Published: May 2024

Background: This study validates real-time biofeedback for lumbopelvic control training in baseball. The lumbopelvic region is crucial for generating kinetic energy in pitching. Real-time biofeedback enhances training effectiveness and reduces injury risk. The validity and reliability of this system were examined. Purpose: This study was to investigate the validity and reliability of the real-time biofeedback system for lumbopelvic control training. Methods: Twelve baseball players participated in this study, with data collected in two sessions separated by a week. All participants needed to do the lateral slide exercise and single-leg squat exercise in each session. Pelvic angles detected by the real-time biofeedback system were compared to the three-dimensional motion capture system (VICON) during training sessions. Additionally, pelvic angles measured by the biofeedback system were compared between the two training sessions. Results: The real-time biofeedback system exhibited moderate to strong correlations with VICON in both exercises: lateral slide exercise (r = 0.66–0.88, p < 0.05) and single-leg squat exercise (r = 0.70–0.85, p < 0.05). Good to excellent reliability was observed between the first and second sessions for both exercises: lateral slide exercise (ICC = 0.76–0.97) and single-leg squat exercise (ICC = 0.79–0.90). Conclusions: The real-time biofeedback system for lumbopelvic control training, accurately providing the correct pelvic angle during training, could enhance training effectiveness.
DSOMF: A Dynamic Environment Simultaneous Localization and Mapping Technique Based on Machine Learning
Authors: Yue Shengzhe , Wang Zhengjie , Zhang Xiaoning
Published: May 2024

To address the challenges of reduced localization accuracy and incomplete map construction demonstrated using classical semantic simultaneous localization and mapping (SLAM) algorithms in dynamic environments, this study introduces a dynamic scene SLAM technique that builds upon direct sparse odometry (DSO) and incorporates instance segmentation and video completion algorithms. While prioritizing the algorithm’s real-time performance, we leverage the rapid matching capabilities of Direct Sparse Odometry (DSO) to link identical dynamic objects in consecutive frames. This association is achieved through merging semantic and geometric data, thereby enhancing the matching accuracy during image tracking through the inclusion of semantic probability. Furthermore, we incorporate a loop closure module based on video inpainting algorithms into our mapping thread. This allows our algorithm to rely on the completed static background for loop closure detection, further enhancing the localization accuracy of our algorithm. The efficacy of this approach is validated using the TUM and KITTI public datasets and the unmanned platform experiment. Experimental results show that, in various dynamic scenes, our method achieves an improvement exceeding 85% in terms of localization accuracy compared with the DSO system.
Self-Calibration Method for Circular Encoders Based on Inertia and a Single Read-Head
Authors: Wang Xiaoyi , Xiao Longyuan , Zheng Kunlei , Zhao Chengxiang , Liu Mingkang , Yao Tianyang , Zhu Dongjie , Liang Gaojie , Shi Zhaoyao
Published: May 2024

This article proposes a new self-calibration method for circular encoders based on inertia and a single read-head. The velocity curves of the circular encoder are fitted with polynomials and, based on the principle of circle closure and the periodicity of the distribution for angle intervals, the proportionality between the theoretical value and the actual value of each angle interval is obtained. In the experimental system constructed, the feasibility of the proposed method was verified through self-calibration experiments, repeatability experiments, and comparative experiments with the time-measurement dynamic reversal (TDR) method. In addition, this article also proposes an iterative method to improve the self-calibration accuracy. Experimental verification was carried out, and the results show that the new method can effectively compensate for the error of angle measurement in the circular encoder. The peak-to-peak value of the error of angle measurement was reduced from 239.343” to 11.867”, and the repeatability of the calibration results of the new method was less than 2.77”.
Engineering the Signal Resolution of a Paper-Based Cell-Free Glutamine Biosensor with Genetic Engineering, Metabolic Engineering, and Process Optimization
Authors: Free Tyler J. , Talley Joseph P. , Hyer Chad D. , Miller Catherine J. , Griffitts Joel S. , Bundy Bradley C.
Published: May 2024

Specialized cancer treatments have the potential to exploit glutamine dependence to increase patient survival rates. Glutamine diagnostics capable of tracking a patient’s response to treatment would enable a personalized treatment dosage to optimize the tradeoff between treatment success and dangerous side effects. Current clinical glutamine testing requires sophisticated and expensive lab-based tests, which are not broadly available on a frequent, individualized basis. To address the need for a low-cost, portable glutamine diagnostic, this work engineers a cell-free glutamine biosensor to overcome assay background and signal-to-noise limitations evident in previously reported studies. The findings from this work culminate in the development of a shelf-stable, paper-based, colorimetric glutamine test with a high signal strength and a high signal-to-background ratio for dramatically improved signal resolution. While the engineered glutamine test is important progress towards improving the management of cancer and other health conditions, this work also expands the assay development field of the promising cell-free biosensing platform, which can facilitate the low-cost detection of a broad variety of target molecules with high clinical value.
Automated Vibroacoustic Monitoring of Trees for Borer Infestation
Authors: Potamitis Ilyas , Rigakis Iraklis
Published: May 2024

In previous research, we presented an apparatus designed for comprehensive and systematic surveillance of trees against borers. This apparatus entailed the insertion of an uncoated waveguide into the tree trunk, enabling the transmission of micro-vibrations generated by moving or digging larvae to a piezoelectric probe. Subsequent recordings were then transmitted at predetermined intervals to a server, where analysis was conducted manually to assess the infestation status of the tree. However, this method is hampered by significant limitations when scaling to monitor thousands of trees across extensive spatial domains. In this study, we address this challenge by integrating signal processing techniques capable of distinguishing vibrations attributable to borers from those originating externally to the tree. Our primary innovation involves quantifying the impulses resulting from the fracturing of wood fibers due to borer activity. The device employs criteria such as impulse duration and a strategy of waiting for periods of relative quietness before commencing the counting of impulses. Additionally, we provide an annotated large-scale database comprising laboratory and field vibrational recordings, which will facilitate further advancements in this research domain.
Image Fusion Method Based on Snake Visual Imaging Mechanism and PCNN
Authors: Wang Qiang , Yan Xuezhi , Xie Wenjie , Wang Yong
Published: May 2024

The process of image fusion is the process of enriching an image and improving the image’s quality, so as to facilitate the subsequent image processing and analysis. With the increasing importance of image fusion technology, the fusion of infrared and visible images has received extensive attention. In today’s deep learning environment, deep learning is widely used in the field of image fusion. However, in some applications, it is not possible to obtain a large amount of training data. Because some special organs of snakes can receive and process infrared information and visible information, the fusion method of infrared and visible light to simulate the visual mechanism of snakes came into being. Therefore, this paper takes into account the perspective of visual bionics to achieve image fusion; such methods do not need to obtain a significant amount of training data. However, most of the fusion methods for simulating snakes face the problem of unclear details, so this paper combines this method with a pulse coupled neural network (PCNN). By studying two receptive field models of retinal nerve cells, six dual-mode cell imaging mechanisms of rattlesnakes and their mathematical models and the PCNN model, an improved fusion method of infrared and visible images was proposed. For the proposed fusion method, eleven groups of source images were used, and three non-reference image quality evaluation indexes were compared with seven other fusion methods. The experimental results show that the improved algorithm proposed in this paper is better overall than the comparison method for the three evaluation indexes.
A Vision/Inertial Navigation/Global Navigation Satellite Integrated System for Relative and Absolute Localization in Land Vehicles
Authors: Zhang Yao , Chu Liang , Mao Yabin , Yu Xintong , Wang Jiawei , Guo Chong
Published: May 2024

This paper presents an enhanced ground vehicle localization method designed to address the challenges associated with state estimation for autonomous vehicles operating in diverse environments. The focus is specifically on the precise localization of position and orientation in both local and global coordinate systems. The proposed approach integrates local estimates generated by existing visual–inertial odometry (VIO) methods into global position information obtained from the Global Navigation Satellite System (GNSS). This integration is achieved through optimizing fusion in a pose graph, ensuring precise local estimation and drift-free global position estimation. Considering the inherent complexities in autonomous driving scenarios, such as the potential failures of a visual–inertial navigation system (VINS) and restrictions on GNSS signals in urban canyons, leading to disruptions in localization outcomes, we introduce an adaptive fusion mechanism. This mechanism allows seamless switching between three modes: utilizing only VINS, using only GNSS, and normal fusion. The effectiveness of the proposed algorithm is demonstrated through rigorous testing in the Carla simulation environment and challenging UrbanNav scenarios. The evaluation includes both qualitative and quantitative analyses, revealing that the method exhibits robustness and accuracy.
Enhancing Si3N4 Selectivity over SiO2 in Low-RF Power NF3–O2 Reactive Ion Etching: The Effect of NO Surface Reaction
Authors: Tung Nguyen Hoang , Lee Heesoo , Dinh Duy Khoe , Kim Dae-Woong , Lee Jin Young , Eom Geon Woong , Kim Hyeong-U , Kang Woo Seok
Published: May 2024

Highly selective etching of silicon nitride (Si3N4) and silicon dioxide (SiO2) has received considerable attention from the semiconductor community owing to its precise patterning and cost efficiency. We investigated the etching selectivity of Si3N4 and SiO2 in an NF3/O2 radio-frequency glow discharge. The etch rate linearly depended on the source and bias powers, whereas the etch selectivity was affected by the power and ratio of the gas mixture. We found that the selectivity can be controlled by lowering the power with a suitable gas ratio, which affects the surface reaction during the etching process. X-ray photoelectron spectroscopy of the Si3N4 and QMS measurements support the effect of surface reaction on the selectivity change by surface oxidation and nitrogen reduction with the increasing flow of O2. We suggest that the creation of SiOxNy bonds on the surface by NO oxidation is the key mechanism to change the etch selectivity of Si3N4 over SiO2.
A Step Forward Understanding Directional Limitations in Markerless Smartphone-Based Gait Analysis: A Pilot Study
Authors: Martiš Pavol , Košutzká Zuzana , Kranzl Andreas
Published: May 2024

The progress in markerless technologies is providing clinicians with tools to shorten the time of assessment rapidly, but raises questions about the potential trade-off in accuracy compared to traditional marker-based systems. This study evaluated the OpenCap system against a traditional marker-based system—Vicon. Our focus was on its performance in capturing walking both toward and away from two iPhone cameras in the same setting, which allowed capturing the Timed Up and Go (TUG) test. The performance of the OpenCap system was compared to that of a standard marker-based system by comparing spatial-temporal and kinematic parameters in 10 participants. The study focused on identifying potential discrepancies in accuracy and comparing results using correlation analysis. Case examples further explored our results. The OpenCap system demonstrated good accuracy in spatial-temporal parameters but faced challenges in accurately capturing kinematic parameters, especially in the walking direction facing away from the cameras. Notably, the two walking directions observed significant differences in pelvic obliquity, hip abduction, and ankle flexion. Our findings suggest areas for improvement in markerless technologies, highlighting their potential in clinical settings.
Feasibility Study of Scanning Spectral Imaging Based on a Birefringence Flat Plate
Authors: Gadasi Ilan , Arieli Yoel
Published: May 2024

Hyper-spectral imaging (HSI) systems can be divided into two main types as follows: a group of systems that includes a dedicated dispersion/filtering component whose role is to physically separate the different wavelengths and a group of systems that sample all wavelengths in parallel, so that the separation into wavelengths is performed by signal processing (interferometric method). There is a significant advantage to systems of the second type in terms of the integration time required to obtain a signal with a high signal-to-noise ratio since the signal-to-noise ratio of methods based on scanning interferometry (Windowing method) is better compared to methods based on dispersion. The current research deals with the feasibility study of a new concept for an HSI system that is based on scanning interferometry using the “push-broom” method. In this study, we investigated the viability of incorporating a simple birefringent plate into a scanning optical system. By exploiting the motion of the platform on which the system is mounted, we extracted the spectral information of the scanned region. This approach combines the benefits of scanning interferometry with the simplicity of the setup. According to the theory, a chirped cosine-shaped interferogram is obtained for each wavelength due to the nonlinear behavior of the optical path difference of light in the birefringent plate as a function of the angle. An algorithm converts the signal from a superposition of chirped cosine signals to a scaled interferogram such that Fourier transforming (FT) the interferogram retrieves the spectral information. This innovative idea can turn a simple monochrome camera into a hyperspectral camera by adding a relief lens and a birefringent plate.