bluuebunny/crossref_metadata_2025 huggingface dataset:
Aggregatibacter actinomycetemcomitans Dispersin B: The Quintessential Antibiofilm Enzyme
Authors: Kaplan Jeffrey B. , Sukhishvili Svetlana A. , Sailer Miloslav , Kridin Khalaf , Ramasubbu Narayanan
Published: August 2024

The extracellular matrix of most bacterial biofilms contains polysaccharides, proteins, and nucleic acids. These biopolymers have been shown to mediate fundamental biofilm-related phenotypes including surface attachment, intercellular adhesion, and biocide resistance. Enzymes that degrade polymeric biofilm matrix components, including glycoside hydrolases, proteases, and nucleases, are useful tools for studying the structure and function of biofilm matrix components and are also being investigated as potential antibiofilm agents for clinical use. Dispersin B is a well-studied, broad-spectrum antibiofilm glycoside hydrolase produced by Aggregatibacter actinomycetemcomitans. Dispersin B degrades poly-N-acetylglucosamine, a biofilm matrix polysaccharide that mediates biofilm formation, stress tolerance, and biocide resistance in numerous Gram-negative and Gram-positive pathogens. Dispersin B has been shown to inhibit biofilm and pellicle formation; detach preformed biofilms; disaggregate bacterial flocs; sensitize preformed biofilms to detachment by enzymes, detergents, and metal chelators; and sensitize preformed biofilms to killing by antiseptics, antibiotics, bacteriophages, macrophages, and predatory bacteria. This review summarizes the results of nearly 100 in vitro and in vivo studies that have been carried out on dispersin B since its discovery 20 years ago. These include investigations into the biological function of the enzyme, its structure and mechanism of action, and its in vitro and in vivo antibiofilm activities against numerous bacterial species. Also discussed are potential clinical applications of dispersin B.
Multi-Wavelength Computational Ghost Imaging Based on Feature Dimensionality Reduction
Authors: Wang Hong , Wang Xiaoqian , Gao Chao , Wang Yu , Zhao Huan , Yao Zhihai
Published: August 2024

Multi-wavelength ghost imaging usually involves extensive data processing and faces challenges such as poor reconstructed image quality. In this paper, we propose a multi-wavelength computational ghost imaging method based on feature dimensionality reduction. This method not only reconstructs high-quality color images with fewer measurements but also achieves low-complexity computation and storage. First, we utilize singular value decomposition to optimize the multi-scale measurement matrices of red, green, and blue components as illumination speckles. Subsequently, each component image of the target object is reconstructed using the second-order correlation function. Next, we apply principal component analysis to perform feature dimensionality reduction on these reconstructed images. Finally, we successfully recover a high-quality color reconstructed image. Simulation and experimental results show that our method not only improves the quality of the reconstructed images but also effectively reduces the computational and storage burden. When extended to multiple wavelengths, our method demonstrates greater advantages, making it more feasible to handle large-scale data.
A Numerical Study of Microwave Frequency Comb Generation in a Semiconductor Laser Subject to Modulated Optical Injection and Optoelectronic Feedback
Authors: Xue Chenpeng , Chen Wei , Zhu Beibei , Zhang Zuxing , Hong Yanhua
Published: August 2024

This study presents a comprehensive numerical investigation on the generation of a microwave frequency comb (MFC) using a semiconductor laser subjected to periodic-modulated optical injection. To enhance performance, optoelectronic feedback is incorporated through a dual-drive Mach–Zehnder modulator. The results show that the first optoelectronic feedback loop, with a delay time inversely proportional to the modulation frequency, can optimize MFC generation through a mode-locking effect and the second optoelectronic feedback loop with a multiple delay time of the first one can further enhance the performance of the MFC. The comb linewidth appears to decrease with the increase in the second-loop delay time in the power function. These results are consistent with experimental observations reported in the literature. We also explore the impact of the feedback index on comb contrast, the statistical characteristics of the central 128 lines within the MFC, and side peak suppression. The simulation results demonstrate the presence of an optimal feedback index. The study also reveals that linewidth reduction, through increasing the feedback index and delay time, comes at the cost of declining side peak suppression. These findings collectively contribute to a deeper understanding of the factors influencing MFC generation and pave the way for the design and optimization of high-performance MFC systems for various applications.
Analyses of an Ultra-Wideband Absorber from UV-B to Middle-IR Utilizing a Square Nanopillar and a Square Hollow Embedded in a Square Cavity of the Top Layer of Multilayer Metamaterials
Authors: Liao Chia-Te , Ke Pei-Xiu , Ho Chia-Min , Yang Cheng-Fu , Wu Tung-Lung
Published: August 2024

In this study, an ultra-wideband absorber spanning from UV-B to middle-IR was designed and analyzed using a novel structure. The multilayer metamaterial, arranged from bottom to top, consisted of an Al metal layer, a lower SiO2 layer, a graphite layer, another SiO2 layer, a thin Ti layer, and a top SiO2 layer. The top layer of SiO2 had a 200 nm square cavity etched out, and then a square Ti nanopillar and a square Ti hollow outside a Ti nanopillar were embedded. This specific arrangement was chosen to maximize the absorption properties across a broad spectrum. The absorption spectrum of the designed absorber was thoroughly analyzed using the commercial finite element analysis software COMSOL Multiphysics® (version 6.0). This analysis confirmed that the combination of these various components achieved perfect absorption and an ultra-wideband response. The synergistic interaction between the layers and the nanopillars structure contributed significantly to the absorber’s efficiency, making it a promising candidate for applications requiring broad-spectrum absorption. The comprehensive analyses of the parameters for different structures demonstrated that the effects of guided-mode resonance, coupling resonance, optical impedance matching, and propagating surface plasmon resonance existed in the investigated structure. The optimal model, determined through analyses using COMSOL Multiphysics®, showed that the broadband absorption in the range of 270 to 3600 nm, spanning from UV-B to middle-IR, exceeded 90.0%. The average absorption rate within this range was 0.967, with the highest reaching a near-perfect absorptivity of 99.9%. We also compared three absorption spectra in this study: the t1–t6 flat structure, the t1–t5 flat structure with t6 featuring a square cavity, and the structure proposed in this study. This demonstrates that a square nanopillar and a square hollow embedded in a square cavity can enhance the absorptive properties of the absorber.
Improving the Performances of Optical Tweezers by Using Simple Binary Diffractive Optics
Authors: Aït-Ameur Kamel , Hasnaoui Abdelkrim
Published: August 2024

Usually, optical tweezers for trapping atoms or nanoparticles are based on the focusing of a Gaussian laser beam (GB). The optical trap is characterised by its longitudinal stability (LS), expressed as the ratio of the backward axial gradient and the forward scattering forces. Replacing the GB with a LGp0 beam (one central peak surrounded by p rings) does not improve the LS because the on-axis intensity distribution is the same whatever the mode order p. However, it has been recently demonstrated that a restructured LGp0 beam can improve greatly the LS. In this paper, we consider the restructuring of a LGp0 beam when passing through a simple binary diffracting optical element called a circular π-plate (CPP). For a particular radius of the dephasing zone of the CPP, it is found that the LS is multiplied by a factor corresponding to a relative increase of about 220% to 320%.
Revealing the Complex Interplay of Biostimulant Applications
Authors: Yuan Ye , Dickinson Nicholas
Published: August 2024

Some biostimulant products provide proven benefits to plant production, potentially offering more environmentally friendly, sustainable, and natural inputs into production systems. However, the transference and predictability of known benefits between different growth environments, application protocols, and management systems are fraught with difficulty. In this study, we carried out carefully controlled glasshouse and in vitro assays with applications of humic acids, protein hydrolysates, and seaweed extract to compare the variability of biostimulant effects and dosage-dependent variations across diverse conditions, encompassing a sufficient range to comprehensively assess their full spectrum of impacts. The results demonstrated a clear trend of dosage-dependent effects with each biostimulant exhibiting a significant growth-promoting effect within a critical concentration range, but detrimental effects when the concentration fell outside this range. While substantial growth-promoting effects were observed under glasshouse conditions, biostimulant applications tended to be more sensitive and generally led to negative impacts in sterilised conditions. The combined use of biostimulants mostly resulted in detrimental and toxicological responses with only two combined treatments showing marginal synergistic effects. The findings demonstrated a complex interplay between biostimulants and the growth conditions of plants. Lack of knowledge of the indirect effects of different growth media may result in negative impacts of biostimulant applications and combinations of products outside narrow critical concentration ranges.
CIRCADIAN CLOCK-ASSOCIATED1 Delays Flowering by Directly Inhibiting the Transcription of BcSOC1 in Pak-choi
Authors: He Ying , Xiao Dong , Jiang Cheng , Li Yiran , Hou Xilin
Published: August 2024

Flowering is critical to the success of plant propagation. The MYB family transcription factor CIRCADIAN CLOCK-ASSOCIATED1 (CCA1) is an essential component of the core loop of the circadian clock and plays a crucial role in regulating plant flowering time. In this study, we found that photoperiod affects the expression pattern and expression level of BcCCA1, which is delayed flowering time under short-day conditions in Pak-choi [Brassica campestris (syn. Brassica rapa) ssp. chinensis]. We detected overexpression and silencing of BcCCA1 in Pak-choi, resulting in delayed and promoted flowering time, respectively. Furthermore, we also discovered that FLOWERING LOCUS C (BcFLC) and SUPPRESSOR OF CONSTANS1 (BcSOC1) were expressed significantly differently in BcCCA1 overexpression and silencing plants compared with control plants. Therefore, we further investigated the interaction relationship between BcCCA1, BcFLC, and BcSOC1, and the results showed that BcCCA1 and BcFLC as a complex interacted with each other. Moreover, both BcCCA1 and BcFLC can directly bind to the promoter of BcSOC1 and repress its transcription, and BcCCA1 can form a complex with BcFLC to enhance the transcriptional inhibition of BcSOC1 by BcFLC. This study reveals a new mechanism by which the circadian clock regulates flowering time.
The Systematics and Evolution of Gymnosperms with an Emphasis on a Few Problematic Taxa
Authors: Yang Yong , Yang Zhi , Ferguson David Kay
Published: August 2024

Gymnosperms originated in the Middle Devonian and have experienced a long evolutionary history with pulses of speciation and extinction, which resulted in the four morphologically distinct extant groups, i.e., cycads, Ginkgo, conifers and gnetophytes. For over a century, the systematic relationships within the extant gymnosperms have been debated because different authors emphasized different characters. Recent phylogenomic studies of gymnosperms have given a consistent topology, which aligns well with extant gymnosperms classified into three classes, five subclasses, eight orders, and 13 families. Here, we review the historical opinions of systematics of gymnosperms with special reference to several problematic taxa and reconsider the evolution of some key morphological characters previously emphasized by taxonomists within a phylogenomic context. We conclude that (1) cycads contain two families, i.e., the Cycadaceae and the Zamiaceae; (2) Ginkgo is sister to cycads but not to conifers, with the similarities between Ginkgo and conifers being the result of parallel evolution including a monopodial growth pattern, pycnoxylic wood in long shoots, and the compound female cones, and the reproductive similarities between Ginkgo and cycads are either synapomorphic or plesiomorphic, e.g., the boat-shaped pollen, the branched pollen tube, and the flagellate sperms; (3) conifers are paraphyletic with gnetophytes nested within them, thus gnetophytes are derived conifers, and our newly delimited coniferophytes are equivalent to the Pinopsida and include three subclasses, i.e., Pinidae, Gnetidae, and Cupressidae; (4) fleshy cones of conifers originated multiple times, the Podocarpaceae are sister to the Araucariaceae, the Cephalotaxaceae and the Taxaceae comprise a small clade, which is sister to the Cupressaceae; (5) the Cephalotaxaceae are distinct from the Taxaceae, because the former family possesses typical female cones and the fleshy part of the seed is derived from the fleshiness of integument, while the latter family has reduced female cones and preserves no traces of the seed scale complexes.
Development of Ultraviolet-Shielding Bamboo/Silk Fibroin Hybrid Films with Good Mechanical Properties: A Proof Study on Human Keratinocyte Cells
Authors: Bittolo Bon Silvia , Libera Valeria , Ceccarini Maria Rachele , Malaspina Rocco , Codini Michela , Valentini Luca
Published: August 2024

In this study, we report the preparation and characterization of water-stable films with UV-shielding and good mechanical properties, exploiting the synergistic effect of regenerated silk fibroin and bamboo-derived cellulose. Silk fibroin (SF)/bamboo (B) hybrid films are achieved by solubilizing both silk and bamboo fibers in formic acid with added CaCl2. Infrared spectroscopy indicates that SF, when combined with bamboo, undergoes a conformational transition, providing evidence of an increase in SF crystallinity. Exploiting the intrinsic absorption of SF in the ultraviolet region, UV–Vis spectroscopy was used to assess the glass transition temperature (Tg) of SF/B films, showing a decrease in Tg by increasing the SF content. The addition of 10 wt% SF to the B matrix improved the elastic modulus by about 10% while conserving the strain at break with respect to the neat B films, increasing the UV shielding properties, while water absorption suggested the material’s hydrophilic and swelling capacity even after one month. The hybrid films showed, under solar irradiation, a photoprotective behavior on keratinocyte human cells by increasing cellular viability. These findings may find potential applications in functional fabrics.
Modeling Approach for Reactive Injection Molding of Polydisperse Suspensions with Recycled Thermoset Composites
Authors: Jetty Bhimesh , Wittemann Florian , Kärger Luise
Published: August 2024

Recycling production waste in the reactive injection molding (RIM) process is a step towards sustainability and efficient material usage. The recycled thermoset composite (RTC) material obtained by shredding the production waste is reused with a virgin thermoset composite (VTC). This study presents a mold-filling simulation approach considering this polydisperse suspension of RTC and VTC. Mold-filling simulations can assist in predicting processability and assessing the impact of reinforced RTC on the final part of production. State-of-the-art mold-filling simulations use the Cross–Castro–Macosko (CCM) model or anisotropic fiber-orientation-dependent viscosity models. The rheological parameters are determined either for the VTC or neat resin. However, these models do not account for changes in viscosity due to the reinforcing of fillers such as RTC. An effective viscosity model is developed by extending the CCM model using the stress–strain amplification approach to overcome this gap. This model is implemented in the computational fluid dynamics code OpenFOAM, and simulations are performed using an extended multiphase solver. To validate the simulations, experimental trials were executed using a two-cavity mold equipped with pressure sensors. Molding compounds with different compositions of VTC and RTC were injected at different speeds. Reinforcing VTC with RTC increases the viscosity. Results demonstrate that RTC-reinforced compounds require higher injection pressure for mold filling than VTC alone. The qualitative agreement of pressure profiles from simulations and experiments for different proportions of reinforcing RTC and different injection speeds shows that the implemented viscosity model can reproduce the experimental mold-filling behavior.
Functionalised Sodium–Carboxymethylcellulose–Collagen Bioactive Bilayer as an Acellular Skin Substitute for Future Use in Diabetic Wound Management: The Evaluation of Physicochemical, Cell Viability, and Antibacterial Effects
Authors: Thambirajoo Maheswary , Md Fadilah Nur Izzah , Maarof Manira , Lokanathan Yogeswaran , Mohamed Mohd Ambri , Zakaria Sarani , Bt Hj Idrus Ruszymah , Fauzi Mh Busra
Published: August 2024

The wound healing mechanism is dynamic and well-orchestrated; yet, it is a complicated process. The hallmark of wound healing is to promote wound regeneration in less time without invading skin pathogens at the injury site. This study developed a sodium–carboxymethylcellulose (Na-CMC) bilayer scaffold that was later integrated with silver nanoparticles/graphene quantum dot nanoparticles (AgNPs/GQDs) as an acellular skin substitute for future use in diabetic wounds. The bilayer scaffold was prepared by layering the Na-CMC gauze onto the ovine tendon collagen type 1 (OTC-1). The bilayer scaffold was post-crosslinked with 0.1% (w/v) genipin (GNP) as a natural crosslinking agent. The physical and chemical characteristics of the bilayer scaffold were evaluated. The results demonstrate that crosslinked (CL) groups exhibited a high-water absorption capacity (>1000%) and an ideal water vapour evaporation rate (2000 g/m2 h) with a lower biodegradation rate and good hydrophilicity, compression, resilience, and porosity than the non-crosslinked (NC) groups. The minimum inhibitory concentration (MIC) of AgNPs/GQDs presented some bactericidal effects against Gram-positive and Gram-negative bacteria. The cytotoxicity tests on bilayer scaffolds demonstrated good cell viability for human epidermal keratinocytes (HEKs) and human dermal fibroblasts (HDFs). Therefore, the Na-CMC bilayer scaffold could be a potential candidate for future diabetic wound care.
Analysis of Despeckling Filters Using Ratio Images and Divergence Measurement
Authors: Gómez Luis , Cardona-Mesa Ahmed Alejandro , Vásquez-Salazar Rubén Darío , Travieso-González Carlos M.
Published: August 2024

This paper presents an analysis of different despeckling filters applied on both synthetically corrupted optical images and actual Synthetic Aperture Radar (SAR) images. Several authors use optical images as ground truth and then the images are corrupted by using a Gamma model to simulate the speckle, while other approaches use methods like multitemporal fusion to generate a ground truth using actual SAR images, which provides a result somehow equivalent to the one from the common multi look technique. Well-known filters, like local, and non-local and some of them based on artificial intelligence and deep learning, are applied to these two types of images and their performance is assessed by a quantitative analysis. One last validation is performed with a newly proposed method by using ratio images, resulting from the mathematical division (Hadamard division) of filtered and noisy images, to measure how similar the initial and the remaining speckle are by considering its Gamma distribution and divergence measurement. Our findings suggest that despeckling models relying on artificial intelligence exhibit notable efficiency, albeit concurrently displaying inflexibility when applied to particular image types based on the training dataset. Additionally, our experiments underscore the utility of the divergence measurement in ratio images in facilitating both visual inspection and quantitative evaluation of residual speckles within the filtered images.
Macaron Attention: The Local Squeezing Global Attention Mechanism in Tracking Tasks
Authors: Wang Zhixing , Luo Hui , Liu Dongxu , Li Meihui , Liu Yunfeng , Bao Qiliang , Zhang Jianlin
Published: August 2024

The Unmanned Aerial Vehicle (UAV) tracking tasks find extensive utility across various applications. However, current Transformer-based trackers are generally tailored for diverse scenarios and lack specific designs for UAV applications. Moreover, due to the complexity of training in tracking tasks, existing models strive to improve tracking performance within limited scales, making it challenging to directly apply lightweight designs. To address these challenges, we introduce an efficient attention mechanism known as Macaron Attention, which we integrate into the existing UAV tracking framework to enhance the model’s discriminative ability within these constraints. Specifically, our attention mechanism comprises three components, fixed window attention (FWA), local squeezing global attention (LSGA), and conventional global attention (CGA), collectively forming a Macaron-style attention implementation. Firstly, the FWA module addresses the multi-scale issue in UAVs by cropping tokens within a fixed window scale in the spatial domain. Secondly, in LSGA, to adapt to the scale variation, we employ an adaptive clustering-based token aggregation strategy and design a “window-to-window” fusion attention model to integrate global attention with local attention. Finally, the CGA module is applied to prevent matrix rank collapse and improve tracking performance. By using the FWA, LSGA, and CGA modules, we propose a brand-new tracking model named MATrack. The UAV123 benchmark is the major evaluation dataset of MATrack with 0.710 and 0.911 on success and precision, individually.
Optimizing Temporal Weighting Functions to Improve Rainfall Prediction Accuracy in Merged Numerical Weather Prediction Models for the Korean Peninsula
Authors: Byun Jongyun , Kim Hyeon-Joon , Kang Narae , Yoon Jungsoo , Hwang Seokhwan , Jun Changhyun
Published: August 2024

Accurate predictions are crucial for addressing the challenges posed by climate change. Given South Korea’s location within the East Asian summer monsoon domain, characterized by high spatiotemporal variability, enhancing prediction accuracy for regions experiencing heavy rainfall during the summer monsoon is essential. This study aims to derive temporal weighting functions using hybrid surface rainfall radar-observation data as the target, with input from two forecast datasets: the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) and the KLAPS Forecast System. The results indicated that the variability in the optimized parameters closely mirrored the variability in the rainfall events, demonstrating a consistent pattern. Comparison with previous blending results, which employed event-type-based weighting functions, showed significant deviation in the average AUC (0.076) and the least deviation (0.029). The optimized temporal weighting function effectively mitigated the limitations associated with varying forecast lead times in individual datasets, with RMSE values of 0.884 for the 1 h lead time of KLFS and 2.295 for the 4–6 h lead time of MAPLE. This blending methodology, incorporating temporal weighting functions, considers the temporal patterns in various forecast datasets, markedly reducing computational cost while addressing the temporal challenges of existing forecast data.
LARS: Remote Sensing Small Object Detection Network Based on Adaptive Channel Attention and Large Kernel Adaptation
Authors: Li Yuanyuan , Yang Yajun , An Yiyao , Sun Yudong , Zhu Zhiqin
Published: August 2024

In the field of object detection, small object detection in remote sensing images is an important and challenging task. Due to limitations in size and resolution, most existing methods often suffer from localization blurring. To address the above problem, this paper proposes a remote sensing small object detection network based on adaptive channel attention and large kernel adaptation. This approach aims to enhance multi-channel information mining and multi-scale feature extraction to alleviate the problem of localization blurring. To enhance the model’s focus on the features of small objects in remote sensing at varying scales, this paper introduces an adaptive channel attention block. This block applies adaptive attention weighting based on the input feature dimensions, guiding the model to better focus on local information. To mitigate the loss of local information by large kernel convolutions, a large kernel adaptive block is designed. The block dynamically adjusts the surrounding spatial receptive field based on the context around the detection area, improving the model’s ability to extract information around remote sensing small objects. To address the recognition confusion during the sample classification process, a layer batch normalization method is proposed. This method enhances the consistency analysis capabilities of adaptive learning, thereby reducing the decline in the model’s classification accuracy caused by sample misclassification. Experiments on the DOTA-v2.0, SODA-A and VisDrone datasets show that the proposed method achieves state-of-the-art performance.
Dual-Band Antenna Array Fed by Ridge Gap Waveguide with Dual-Periodic Interdigital-Pin Bed of Nails
Authors: Chen Boju , Chen Xiaoming , Cheng Xin , Da Yiran , Liu Xiaobo , Gao Steven , Kishk Ahmed A.
Published: August 2024

A dual-band (K-/Ka-band) antenna array is presented. An ultra-wideband antenna element in the shape of a double-ridged waveguide is used as a radiation slot, and a novel dual-periodic ridge gap waveguide (RGW) with an interdigital-pin bed of nails (serving as a filter) is used to realize dual-band operation. By periodically arranging the pins of two different heights in two dimensions, the proposed RGW with interdigital-pin bed of nails is able to realize and flexibly adjust two passbands. The widely used GW-based back cavity boosts the realized gain and simplifies the feed network design. A 4 × 4 prototype array was designed, fabricated, and measured. The results show that the array has two operating bands at 24.5–26.4 GHz and 30.3–31.5 GHz, and the realized gain can reach 19.2 dBi and 20.4 dBi, respectively. Meanwhile, there is a very significant gain attenuation at stopband.
Detection Strategies for COM, WMI, and ALPC-Based Multi-Process Malware
Authors: Portase Radu Marian , Muntea Andrei Marius , Mermeze Andrei , Colesa Adrian , Sebestyen Gheorghe
Published: August 2024

Behavioral malware detection is based on attributing malicious actions to processes. Malicious processes may try to hide by changing the behavior of other benign processes to achieve their goals. We showcase how Component Object Model (COM) and Windows Management Instrumentation (WMI) can be used to create such spoofing attacks. We discuss the internals of COM and WMI and Asynchronous Local Procedure Call (ALPC). We present multiple functional monitoring techniques to identify the spoofing and discuss the strong and weak points of each technique. We create a robust process monitoring system that can correctly identify the source of malicious actions spoofed via COM, WMI and ALPC with a low performance impact. Finally, we discuss how malicious actors use COM, WMI and ALPC by examining real-world malware detected by our monitoring system.
Impact of Multi-Scattered LiDAR Returns in Fog
Authors: Hevisov David , Liemert André , Reitzle Dominik , Kienle Alwin
Published: August 2024

In the context of autonomous driving, the augmentation of existing data through simulations provides an elegant solution to the challenge of capturing the full range of adverse weather conditions in training datasets. However, existing physics-based augmentation models typically rely on single scattering approximations to predict light propagation under unfavorable conditions, such as fog. This can prevent the reproduction of important signal characteristics encountered in a real-world environment. Consequently, in this work, Monte Carlo simulations are employed to assess the relevance of multiple-scattered light to the detected LiDAR signal in different types of fog, with scattering phase functions calculated from Mie theory considering real particle size distributions. Bidirectional path tracing is used within the self-developed GPU-accelerated Monte Carlo software to compensate for the unfavorable photon statistics associated with the limited detection aperture of the LiDAR geometry. To validate the Monte Carlo software, an analytical solution of the radiative transfer equation for the time-resolved radiance in terms of scattering orders is derived, thereby providing an explicit representation of the double-scattered contributions. The results of the simulations demonstrate that the shape of the detected signal can be significantly impacted by multiple-scattered light, depending on LiDAR geometry and visibility. In particular, double-scattered light can dominate the overall signal at low visibilities. This indicates that considering higher scattering orders is essential for improving AI-based perception models.
Compact Chromatic Confocal Lens with Large Measurement Range
Authors: He Ning , Hu Huiqin , Cui Zhiying , Xu Xinjun , Zhou Dakai , Chen Yunbo , Gong Puyin , Chen Youhua , Kuang Cuifang
Published: August 2024

Spectral confocal sensors are effective for measuring displacements. The core of the spectral confocal measurement system is a dispersive objective lens that uses optical dispersion to establish a one-to-one correspondence between the focusing position and wavelength, achieving high-resolution measurements in the longitudinal direction. Despite significant progress in dispersive objective lenses for spectral confocal sensor systems, challenges such as a limited dispersion range, high cost, and insufficient measurement accuracy persist. To expand the measurement range and improve the accuracy of the spectral confocal sensor, we designed a compact, long-axial dispersion objective lens. This lens has a simple structure that requires only six lens elements, two of which form cemented doublets. The system length is 58 mm, with a working distance of 46 ± 6 mm and a dispersion range of 12 mm within the wavelength range of 450–656 nm. The lens has an object-side numerical aperture (NA) of 0.22 and an image-side NA between 0.198 and 0.24, ensuring high light energy utilization. Finally, a spectral confocal measurement system was constructed based on the designed dispersive objective lens, and performance evaluation tests were conducted. The test results showed that the system achieved a resolution of 0.15 μm and a maximum linear error of ±0.7 μm, demonstrating high-precision measurement capabilities. The proposed lens design enables the development of more portable and cost-effective spectral confocal sensors.
Temperature Compensation Method Based on Bilinear Interpolation for Downhole High-Temperature Pressure Sensors
Authors: Shu Yizhan , Hua Chenquan , Zhao Zerun , Wang Pengcheng , Zhang Haocheng , Yu Wenxin , Yu Haobo
Published: August 2024

Due to their high accuracy, excellent stability, minor size, and low cost, silicon piezoresistive pressure sensors are used to monitor downhole pressure under high-temperature, high-pressure conditions. However, due to silicon’s temperature sensitivity, high and very varied downhole temperatures cause a significant bias in pressure measurement by the pressure sensor. The temperature coefficients differ from manufacturer to manufacturer and even vary from batch to batch within the same manufacturer. To ensure high accuracy and long-term stability for downhole pressure monitoring at high temperatures, this study proposes a temperature compensation method based on bilinear interpolation for piezoresistive pressure sensors under downhole high-temperature and high-pressure environments. A number of calibrations were performed with high-temperature co-calibration equipment to obtain the individual temperature characteristics of each sensor. Through the calibration, it was found that the output of the tested pressure measurement system is positively linear with pressure at the same temperatures and nearly negatively linear with temperature at the same pressures, which serves as the bias correction for the subsequent bilinear interpolation temperature compensation method. Based on this result, after least squares fitting and interpolating, a bilinear interpolation approach was introduced to compensate for temperature-induced pressure bias, which is easier to implement in a microcontroller (MCU). The test results show that the proposed method significantly improves the overall measurement accuracy of the tested sensor from 21.2% F.S. to 0.1% F.S. In addition, it reduces the MCU computational complexity of the compensation model, meeting the high accuracy demand for downhole pressure monitoring at high temperatures and pressures.
Machine Learning-Based Classification of Soil Parent Materials Using Elemental Concentration and Vis-NIR Data
Authors: İnci Yüsra , Bilgili Ali Volkan , Gündoğan Recep , Gözükara Gafur , Karadağ Kerim , Tenekeci Mehmet Emin
Published: August 2024

In soil science, the allocation of soil samples to their respective origins holds paramount significance, as it serves as a crucial investigative tool. In recent times, with the increasing use of proximal sensing and advancements in machine-learning techniques, new approaches have accompanied these developments, enhancing the effectiveness of soil utilization in soil science. This study investigates soil classification based on four parent materials. For this purpose, a total of 59 soil samples were collected from 12 profiles and the vicinity of each profile at a depth of 0–30 cm. Surface soil samples were analyzed for elemental concentrations using X-Ray fluorescence (XRF) and inductively coupled plasma–optical emission spectrometry (ICP-OES) and soil spectra using a visible near-infrared (Vis-NIR) spectrometer. Soil samples collected from soil profiles (12 soil samples) and surface (47 soil samples) were used to classify parent materials using machine learning-based algorithms such as Support Vector Machine (SVM), Ensemble Subspace k-Near Neighbor (ESKNN), and Ensemble Bagged Trees (EBTs). Additionally, as a validation of the classification techniques, the dataset was subjected to five-fold cross-validation and independent sample set splitting (80% calibration and 20% validation). Evaluation metrics such as accuracy, F score, and G mean were used to evaluate prediction performance. Depending on the dataset and algorithm used, the classification success rates varied between 70% and 100%. Overall, the ESKNN (99%) produced better results than other classification methods. Additionally, Relief algorithms were employed to identify key variables for each dataset (ICP-OES: CaO, Fe2O3, Al2O3, MgO, and MnO; XRF: SiO2, CaO, Fe2O3, Al2O, and MnO; Vis-NIR: 567, 571, 572, 573, and 574 nm). Subsequent soil reclassification using these reduced variables revealed reduced accuracies using Vis-NIR data, with ESKNN still yielding the best results.
Secure Triggering Frame-Based Dynamic Power Saving Mechanism against Battery Draining Attack in Wi-Fi-Enabled Sensor Networks
Authors: Kim So-Yeon , Park So-Hyun , Lee Jung-Hoon , Lee Il-Gu
Published: August 2024

Wireless local area networks (WLANs) have recently evolved into technologies featuring extremely high throughput and ultra-high reliability. As WLANs are predominantly utilized in Internet of Things (IoT) and Wi-Fi-enabled sensor applications powered by coin cell batteries, these high-efficiency, high-performance technologies often cause significant battery depletion. The introduction of the trigger frame-based uplink transmission method, designed to enhance network throughput, lacks adequate security measures, enabling attackers to manipulate trigger frames. Devices receiving such frames must respond immediately; however, if a device receives a fake trigger frame, it fails to enter sleep mode, continuously sending response signals and thereby increasing power consumption. This problem is specifically acute in next-generation devices that support multi-link operation (MLO), capable of simultaneous transmission and reception across multiple links, rendering them more susceptible to battery draining attacks than conventional single-link devices. To address this, this paper introduces a Secure Triggering Frame-Based Dynamic Power Saving Mechanism (STF-DPSM) specifically designed for multi-link environments. Experimental results indicate that even in a multi-link environment with only two links, the STF-DPSM improves energy efficiency by an average of approximately 55.69% over conventional methods and reduces delay times by an average of approximately 44.7% compared with methods that consistently utilize encryption/decryption and integrity checks.
Polyphenols Extraction from Different Grape Pomaces Using Natural Deep Eutectic Solvents
Authors: Frontini Alessandro , Luvisi Andrea , Negro Carmine , Apollonio Massimiliano , Accogli Rita , De Pascali Mariarosaria , De Bellis Luigi
Published: August 2024

Exploiting by-products from the oenological industry to extract antioxidant chemicals is a shared goal that combines the need to reduce the wine sector’s environmental impact with the need to improve the availability of these biomolecules, according to a circular economy approach. Natural deep eutectic solvents (NaDES) have recently captured researchers’ interest as a safer and more environmentally friendly alternative to traditional solvents due to their effectiveness, low toxicity, and stability. In this work, we set out to investigate several NaDES for the extraction of phenolic chemicals from local monovarietal grape pomace resulting from different vinification procedures (including both red and rosé vinification of Negroamaro and Primitivo grapes; rosé vinification of Susumaniello grapes and white vinification of Chardonnay, Fiano and Malvasia bianca grapes), with the additional goal of generalizing the use of NaDES to extract chemicals of interest from organisms selected from the wide plant biodiversity. Three binary choline chloride-based NaDES (DES-Lac, DES-Tar, and DES-Gly, with lactic acid, tartaric acid, and glycerol as hydrogen bond donors, respectively) were compared to ethanol as a conventional solvent, and the extracts were evaluated using HPLC/MS and colorimetric techniques. The results revealed that each NaDES produces a substantially higher total phenolic yield than ethanol (up to 127.8 mg/g DW from Primitivo rosé grape pomace). DES-Lac and DES-Tar were more effective for anthocyanins extraction; the most abundant compound was malvidin 3-O-glucoside (highest extraction yield with DES-Lac from Susumaniello pomace: 29.4 mg/g DW). Regarding phenolic compounds, DES-Gly was the most effective NaDES producing results comparable to ethanol. Unexpectedly, Chardonnay pomace has the greatest content of astilbin. In most cases, grape pomace extracts obtained by rosé and white vinification provided the maximum yield. As a result, NaDES have emerged as a viable alternative to traditional organic solvent extraction techniques, allowing for higher (or equal) yields while significantly lowering costs, hazards, and environmental impact.
Psychosexual Health and Well-Being of Trans and Gender-Diverse Individuals in Portugal
Authors: Henriques Mariana , Pereira Henrique
Published: August 2024

This study aimed to explore and describe the perceptions of trans and gender-diverse individuals (TGD) in Portugal regarding the implications on their psychological, social, and psychosexual health. A qualitative investigation was conducted using an electronic interview answered by 32 participants. The data were examined through a thematic analysis, and the following themes were identified: experiences with healthcare services, social interaction, discrimination experiences, mental health, social support systems, self-esteem, social identity, sex and sexual health, quality of life, and sociopolitical enhancement strategy proposals. The analysis of these themes provides information on the perceptions and experiences of the participants and suggests factors that impact the well-being and quality of life of the individuals in the current sample.
Is There a Single Profile of a Victim of Workplace Bullying? The Prevalence of Workplace Bullying in the Educational Sector in Spain and Its Consequences for Teachers’ Health
Authors: López-Vílchez Jorge J. , Grau-Alberola Ester , Gil-Monte Pedro R.
Published: August 2024

Dysfunctional work environments are characterized by the presence of psycho-social risks, such as workplace bullying (WB): hostile, systematic, and planned behaviors toward other workers in order to get them to leave the organization they work for. The aims of this study are (1) to analyze the prevalence of WB in a sample of teachers and (2) to determine the relationship between socio-demographic and socio-labor variables in relation to three study groups: teacher victims of WB, violent behaviors, and null or low violence. The sample consists of 3442 teachers working in publicly regulated educational centers located in the province of Valencia (Spain). Estimated frequencies, cross-tabulations, and effect sizes were analyzed using SPSS 24. The following results were obtained: (1) 12.26% were potential WB cases, and (2) potential victims of WB were not influenced by the socio-demographic and socio-labor variables proposed. The results obtained did not make it possible to determine a single profile of a teacher victim of WB. It is recommended that training protocols be developed to help teachers recognize and manage WB more effectively. This will improve their health, well-being, and performance in educational centers.
Evolution of the Behavioural Strategies of Stakeholders in Green Supply within Government Compensation Mechanisms
Authors: Sun Wenyuan , Ye Xingyi , Wang Bo , Wang Jianxin
Published: August 2024

Since economic development and environmental protection constitute a multidimensional and complex interaction process, government regulatory mechanisms, as policy tools for green development, have become significant means for environmental conservation. The motivation of this paper is to reveal the government’s promotion mechanism for the green development of the supply chain. To achieve this objective, an evolutionary game model (EGM) method is applied in this paper. The specific steps of this method include the following: a unified theoretical analysis framework was first developed in which integrated suppliers (ISs), government agencies (GAs), and financial institutions (FIs) were integrated into the EGM. Second, on the basis of dynamic evolution and differential equations, the evolution and stabilisation strategies of the stakeholders were examined separately. Finally, adopting a supply chain that includes ISs, GAs, and FIs as a case study, stability strategies under changes in various parameters were investigated. The research results indicated that the behavioural strategies of GAs could serve as a weathervane for ISs and FIs. Within a certain range, government compensation mechanisms could positively impact product R&D, as well as IS green development, while the government subsidy phase-out system could be more suitable at the maturity stage. The contribution of this paper is to provide methodological support for the operational decision-making of GAs, FIs, and ISs.
A Short-Term Wind Speed Forecasting Framework Coupling a Maximum Information Coefficient, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, Shared Weight Gated Memory Network with Improved Northern Goshawk Optimization for Numerical Weather Prediction Correction
Authors: Liu Yanghe , Zhang Hairong , Wu Chuanfeng , Shao Mengxin , Zhou Liting , Fu Wenlong
Published: August 2024

In line with global carbon-neutral policies, wind power generation has received widespread public attention, which can enhance the security of supply and social sustainability. Since wind with non-stationarity and randomness makes power systems unstable, precise wind speed forecasting is an integral part of wind farm scheduling and management. Therefore, a compound short-term wind speed forecasting framework based on numerical weather prediction (NWP) is proposed coupling a maximum information coefficient (MIC), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), shared weight gated memory network (SWGMN) with improved northern goshawk optimization (INGO). Firstly, numerical weather prediction is adopted to acquire the predicted variables with different domains, including the predicted wind speed and other predicted meteorological variables, after which the error is calculated using the predicted and actual wind speeds. Then, the correlation between the predicted variables and the error is obtained using the MIC to select the correlation factors. Subsequently, CEEMDAN is employed to decompose the correlation factors, corresponding the actual factors and the error into a series of subsequences, which are regarded as the input series. After that, the input series is fed into the proposed SWGMN to forecast each subsequent error, respectively, in which the shared gate is proposed to replace the input gate, the forgetting gate and the output gate. Meanwhile, the proposed INGO based on northern goshawk optimization (NGO), the levy flight disturbance strategy and the nonlinear contraction strategy is applied to calibrate the parameters of the SWGMN. Finally, the forecasting values are acquired by summing the forecasted error and the predicted wind speed from the NWP. The experimental results depict that the errors are small among all the models. Compared with the traditional method, the proposed framework achieves higher prediction accuracy and efficiency. The application of this framework not only assists in optimizing the operation and management of wind farms, but also reduces the dependence on fossil fuels, thereby promoting environmental protection and the sustainable use of resources.