bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Multi-Similarity Hashing with Spatial-Enhanced Learning for Remote Sensing Image Retrieval
Authors: Zhang Huihui , Qin Qibing , Ge Meiling , Huang Jianyong
Published: November 2024

Remote sensing image retrieval (RSIR) plays a crucial role in remote sensing applications, focusing on retrieving a collection of items that closely match a specified query image. Due to the advantages of low storage cost and fast search speed, deep hashing has been one of the most active research problems in remote sensing image retrieval. However, remote sensing images contain many content-irrelevant backgrounds or noises, and they often lack the ability to capture essential fine-grained features. In addition, existing hash learning often relies on random sampling or semi-hard negative mining strategies to form training batches, which could be overwhelmed by some redundant pairs that slow down the model convergence and compromise the retrieval performance. To solve these problems effectively, a novel Deep Multi-similarity Hashing with Spatial-enhanced Learning, termed DMsH-SL, is proposed to learn compact yet discriminative binary descriptors for remote sensing image retrieval. Specifically, to suppress interfering information and accurately localize the target location, by introducing a spatial enhancement learning mechanism, the spatial group-enhanced hierarchical network is firstly designed to learn the spatial distribution of different semantic sub-features, capturing the noise-robust semantic embedding representation. Furthermore, to fully explore the similarity relationships of data points in the embedding space, the multi-similarity loss is proposed to construct informative and representative training batches, which is based on pairwise mining and weighting to compute the self-similarity and relative similarity of the image pairs, effectively mitigating the effects of redundant and unbalanced pairs. Experimental results on three benchmark datasets validate the superior performance of our approach.
Assessment of Tree Species Classification by Decision Tree Algorithm Using Multiwavelength Airborne Polarimetric LiDAR Data
Authors: Hu Zhong , Tan Songxin
Published: November 2024

Polarimetric measurement has been proven to be of great importance in various applications, including remote sensing in agriculture and forest. Polarimetric full waveform LiDAR is a relatively new yet valuable active remote sensing tool. This instrument offers the full waveform data and polarimetric information simultaneously. Current studies have primarily used commercial non-polarimetric LiDAR for tree species classification, either at the dominant species level or at the individual tree level. Many classification approaches combine multiple features, such as tree height, stand width, and crown shape, without utilizing polarimetric information. In this work, a customized Multiwavelength Airborne Polarimetric LiDAR (MAPL) system was developed for field tree measurements. The MAPL is a unique system with unparalleled capabilities in vegetation remote sensing. It features four receiving channels at dual wavelengths and dual polarization: near infrared (NIR) co-polarization, NIR cross-polarization, green (GN) co-polarization, and GN cross-polarization, respectively. Data were collected from several tree species, including coniferous trees (blue spruce, ponderosa pine, and Austrian pine) and deciduous trees (ash and maple). The goal was to improve the target identification ability and detection accuracy. A machine learning (ML) approach, specifically a decision tree, was developed to classify tree species based on the peak reflectance values of the MAPL waveforms. The results indicate a re-substitution error of 3.23% and a k-fold loss error of 5.03% for the 2106 tree samples used in this study. The decision tree method proved to be both accurate and effective, and the classification of new observation data can be performed using the previously trained decision tree, as suggested by both error values. Future research will focus on incorporating additional LiDAR data features, exploring more advanced ML methods, and expanding to other vegetation classification applications. Furthermore, the MAPL data can be fused with data from other sensors to provide augmented reality applications, such as Simultaneous Localization and Mapping (SLAM) and Bird’s Eye View (BEV). Its polarimetric capability will enable target characterization beyond shape and distance.
6.5 kV SiC PiN and JBS Diodes’ Comparison in Hybrid and Full SiC Switch Topologies
Authors: Spejo Lucas Barroso , Knoll Lars , Minamisawa Renato Amaral
Published: November 2024

This work investigates the performance of state-of-the-art non-commercial 6.5 kV Silicon Carbide (SiC) PiN and Junction Barrier Schottky (JBS) diodes in hybrid (Si IGBT with SiC diode) and full SiC (SiC MOSFET with SiC diode) switch topologies. The static and dynamic performance has been systematically evaluated at distinct temperatures, gate resistances and currents for each configuration. The SiC PiN diode presented higher current density capability and lower leakage current density than the JBS diode. Moreover, in most cases, the SiC PiN diode-based topologies demonstrated slightly higher total switching losses compared to the SiC JBS diode-based equivalent configurations. A loadability analysis in a three-level NPC converter is presented to evaluate the potential of each configuration in a converter application. The SiC PiN technology presented a 25% power extension compared to the SiC JBS technology with similar efficiency at typical industrial drives switching frequency operation when comparing same-active-area diode technologies. Finally, a long-term reliability test (H3TRB) is presented to demonstrate the SiC PiN diode technology’s potential for operation in harsh environments. Such characteristics show the advantage of the 6.5 kV SiC PiN diode when a high current density (>100 A/cm2), high efficiency and reliability are required.
A Robust-Based Home Energy Management Model for Optimal Participation of Prosumers in Competitive P2P Platforms
Authors: Zetawi Alaa Al , Tostado-Véliz Marcos , Hasanien Hany M. , Jurado Francisco
Published: November 2024

Nowadays, advanced metering and communication infrastructures make it possible to enable decentralized control and market schemes. In this context, prosumers can interact with their neighbors in an active manner, thus sharing resources. This practice, known as peer-to-peer (P2P), can be put into practice under cooperative or competitive premises. This paper focuses on the second case, where the peers partaking in the P2P platform compete among themselves to improve their monetary balances. In such contexts, the domestic assets, such as on-site generators and storage systems, should be optimally scheduled to maximize participation in the P2P platform and thus enable the possibility of obtaining monetary incomes or exploiting surplus renewable energy from adjacent prosumers. This paper addresses this issue by developing a home energy management model for optimal participation of prosumers in competitive P2P platforms. The new proposal is cast in a three-stage procedure, in which the first and last stages are focused on domestic asset scheduling, while the second step decides the optimal offering/bidding strategy for the concerned prosumer. Moreover, uncertainties are introduced using interval notation and equivalent scenarios, resulting in an amicable computational framework that can be efficiently solved by average machines and off-the-shelf solvers. The new methodology is tested on a benchmark four-prosumer community. Results prove that the proposed procedure effectively maximizes the participation of prosumers in the P2P platform, thus increasing their monetary benefits. The role of storage systems is also discussed, in particular their capability of increasing exportable energy. Finally, the influence of uncertainties on the final results is illustrated.
A Strategy for Reliable Cargo Loading of Low-Pressure Liquid Carbon Dioxide Carriers
Authors: Hwang Soon-Kyu , Im Sang-Taek , Ahn Jong-Kap
Published: November 2024

This study addresses the control challenges associated with loading low-pressure liquid carbon dioxide carriers (LCO2Cs), which are crucial components of the carbon capture, utilization, and storage (CCUS) chain. It explores the need for stable pressure and temperature control to prevent dry ice formation and ensure efficient cargo handling. The research employed HYSYS dynamic simulations to assess three different control strategies. The simulations assessed each strategy’s effectiveness in maintaining stable operating conditions and preventing risks, such as dry ice formation and valve blockages. The study concluded by examining the necessity of pressurization for safe and efficient LCO2 loading and by determining which control strategy is most effective and reliable based on the simulation outcomes. Among the three scenarios examined, Case A, which utilized two control valves, exhibited initial instability due to significant flow coefficient differences, resulting in temperature drops below the CO2 triple point and increasing the risk of dry ice formation. Case C, operating without pressurization, experienced severe pressure fluctuations and prolonged exposure to temperatures below the triple point, posing risks of valve blockages. In contrast, Case B, which uses a remote pressure-reducing valve and a control valve, demonstrated the most stable performance, effectively avoiding dry ice formation and pressure fluctuations, making it the most reliable method for safe LCO2 cargo loading.
Investigation on Hydrodynamic Performance and Wall Temperature of Water-Cooled Wall in 1000 MW Boiler Under Low-Load Conditions
Authors: Chong Peian , Zhu Xiaolei , Li Jianning , Li Xiao , Deng Lei
Published: November 2024

To enhance the peak-shaving capability of a boiler, a mathematical model of hydrodynamic and wall temperature characteristics for the water-cooled wall of a 1000 MW boiler was established. Utilizing the component pressure method, the mass flow distribution, outlet working fluid temperature, pressure loss, and wall temperature distribution characteristics of the water-cooled walls at 30% of the boiler’s maximum continuous rating (BMCR) were calculated and analyzed. The findings suggest that, under the operation at 30% BMCR load, there is a substantial equilibrium in the flow distribution across the quartet of walls that constitute the water-cooled wall assembly. The maximum mass flow rate deviations in the helical and vertical sections are 1.95% and 3.47%, respectively, showing small flow deviations and reasonable distribution. The temperature deviation in the helical section is 0.3 °C, reflecting the characteristic low thermal deviation in helical tubes. While the temperature deviation at the outlet of the vertical section is higher, it remains within safe limits. The pressure loss across the water-cooled wall system amounts to 0.4 MPa. The peak wall temperature reaches 337.5 °C, remaining within the material’s permissible safety limits. Through an in-depth performance analysis, the hydrodynamic operational safety under 30% BMCR deep peak-shaving load is ensured.
Comprehensive Review of Lithium-Ion Battery State of Charge Estimation by Sliding Mode Observers
Authors: Behnamgol Vahid , Asadi Mohammad , Mohamed Mohamed A. A. , Aphale Sumeet S. , Faraji Niri Mona
Published: November 2024

The state of charge (SoC) is a critical parameter in lithium-ion batteries and their alternatives. It determines the battery’s remaining energy capacity and influences its performance longevity. Accurate SoC estimation is essential for making informed charging and discharging decisions, mitigating the risks of overcharging or deep discharge, and ensuring safety. Battery management systems rely on SoC estimation, utilising both hardware and software components to maintain safe and efficient battery operation. Existing SoC estimation methods are broadly classified into direct and indirect approaches. Direct methods (e.g., Coulumb counting) rely on current measurements. In contrast, indirect methods (often based on a filter or observer) utilise a model of a battery to incorporate voltage measurements besides the current. While the latter is more accurate, it faces challenges related to sensor drift, computational complexity, and model inaccuracies. The need for more precise and robust SoC estimation without increasing complexity is critical, particularly for real-time applications. Recently, sliding mode observers (SMOs) have gained prominence in this field for their robustness against model uncertainties and external disturbances, offering fast convergence and superior accuracy. Due to increased interest, this review focuses on various SMO approaches for SoC estimation, including first-order, adaptive, high-order, terminal, fractional-order, and advanced SMOs, along with hybrid methods integrating intelligent techniques. By evaluating these methodologies, their strengths, weaknesses, and modelling frameworks in the literature, this paper highlights the ongoing challenges and future directions in SoC estimation research. Unlike common review papers, this work also compares the performance of various existing methods via a comprehensive simulation study in MATLAB 2024b to quantify the difference and guide the users in selecting a suitable version for the applications.
Experimental Assessment of Hydrodynamic Behavior in a Gravitational Vortex Turbine with Different Inlet Channel and Discharge Basin Configurations
Authors: Velásquez Laura , Rengifo Juan Pablo , Urrego José , Rubio-Clemente Ainhoa , Chica Edwin
Published: November 2024

Gravitational vortex turbines can provide a sustainable and efficient solution for generating renewable energy from small watercourses, minimizing environmental impact, and contributing to the decentralization of energy production. Their design allows for high energy efficiency even under low flow conditions, thus benefiting rural communities and reducing their dependence on fossil fuels. This paper presents an experimental assessment of the hydrodynamic behavior of gravitational vortex turbines by examining various geometric configurations. The combinations of two types of inlet channels (spiral and tangential) and two types of discharge basins (conical and cylindrical) were investigated. Additionally, different geometries and placements of the runners were evaluated to determine their influence on the efficiency and performance of the turbine. The results indicate that the highest efficiency of 60.85% was achieved with a configuration that included a spiral inlet channel, cylindrical discharge, and a runner placement of 50%.
Application of the Integral Energy Criterion and Neural Network Model for Helicopter Turboshaft Engines’ Vibration Characteristics Analysis
Authors: Vladov Serhii , Bulakh Maryna , Baranovskyi Denys , Kisiliuk Eduard , Vysotska Victoria , Romanov Maksym , Czyżewski Jan
Published: November 2024

This article presents a vibration signal analysis method to diagnose helicopter turboshaft engine defects such as bearing imbalance and wear. The scientific novelty of the article lies in the development of a comprehensive approach to diagnosing helicopter turboshaft engine defects based on the vibration signals amplitude and frequency characteristics integral analysis combined with a neural network for probabilistic defect detection. Unlike existing methods, the proposed approach uses the energy criterion for the vibration characteristics. It averages the assessment of unique signal processing algorithms, which ensures reliable defect classification under flight vibration conditions. The method is based on representing vibration signals as a sum of harmonic oscillations supplemented by noise components, which helps to identify deviations from typical values. The developed method includes a state function in which the amplitudes and frequency characteristics from nominal parameters estimate deviations. When the critical threshold is exceeded, the function signals possible malfunctions. A multilayer neural network is used to classify defect types, providing high classification accuracy (from 0.985 to 0.994). Computer experiments on the developed seminaturalistic modeling stand confirm that the method can detect increased vibration levels, which is the potential failure indicator. Comparative analysis shows the proposed method’s accuracy and noise resistance superiority, emphasizing the importance of introducing modern technologies to improve aircraft operation reliability and safety.
Research on the Separation Technology of Kelp and Shellfish Box Based on Shellfish–Kelp Mixed Culture Mode
Authors: Wang Yanan , Zha Zehao , Wang Xian , Cui Yipeng , Wang Xinxin , Geng Duanyang , Zhou Hua , Sheng Tongfei
Published: November 2024

Aiming at the problem of floating shellfish boxes interfering with kelp harvesting when mechanized kelp harvesting is based on shellfish–kelp mixed culture mode, this paper combines the structural characteristics of the shellfish box itself, designs the kelp harvesting unit test bench and develops a shellfish box separator device. The key factors affecting the box separator’s separation effect were derived through the theoretical analysis. The process of separation of a shellfish box by the box separator is simulated and optimized under the derived boundary conditions. The single-factor test for the separating effect of the box separator was conducted with ADAMS kinematics simulation software. The test showed the optimal utility intervals for the key factors under consideration. Further orthogonal tests were conducted for the three key factors, which were ranked in descending order of importance as box separator separation angle θ, box separator taper angle β and box separator placement depth h. The optimal parameter combination is the box separator separation angle of 31.9°, the box separator taper angle of 30° and the box separator placement depth of 550 mm. Verification experiments have shown that both indicators, the farthest horizontal distance of the shellfish box and the angle of the shellfish box deviating from the box separator, meet the actual production requirements. In summary, the separator can effectively separate the shellfish box from the kelp, and the device is simple in design, quick in operation, and accomplished separation without disturbing shellfish. This study can provide a theoretical basis for the separation technology of kelp and shellfish box under shellfish–kelp mixed culture mode.
Mesh Sensitivity Analysis of Axisymmetric Models for Smooth–Turbulent Transient Flows
Authors: Ferreira Pedro Leite , Covas Dídia Isabel Cameira
Published: November 2024

The current paper focuses on the assessment of radial mesh influence on the description of the transient event obtained by an axisymmetric model. The objective is to reduce computational effort while accurately calculating hydraulic transients in smooth–turbulent pressurized pipes. The analyzed pipe system has a reservoir–pipe–valve configuration with an inner diameter of 0.02 m and a total length of 14.96 m, with the initial discharge being equal to 120 × 10−3 L/s (Re = 7638). An extensive study is carried out with 80 geometric sequence meshes by varying the total number of cylinders, the geometric common ratio, and the pipe axial discretization. The benefit of increasing the geometric common ratio is highlighted. A detailed comparison between two meshes is presented, in which the best mesh (i.e., the one with the lowest computational effort) has a three-fold higher value of the geometric common ratio. The two meshes show small differences for the instantaneous valve closure, limited to a time interval immediately after the arrival of the pressure surge and only during the first pressure wave. The dynamic characterization of the transient phenomenon demonstrates the in-depth consistency between the model results and the hydraulic transients’ phenomenon in terms of the piezometric head, the wall shear stress, and the mean velocity time-history, in comparison to the results obtained with the shear stress, lateral velocity, and axial velocity profiles.
Characterization of a Bacterium Isolated from Hydrolyzed Instant Sea Cucumber Apostichopus japonicus Using Whole-Genome Sequencing and Metabolomics
Authors: Luo Xin , Zhang Zhixuan , Zheng Zhangyi , Zhang Wenwen , Ming Tinghong , Jiao Lefei , Su Xiurong , Xu Jiajie , Kong Fei
Published: November 2024

Autolysis in the sea cucumber Apostichopus japonicus is typically triggered by degradation caused by microorganisms within their bodies. However, information on this topic remains limited. Recently, we isolated and purified a bacterial strain from hydrolyzed instant sea cucumber samples. To investigate its potential role in the autolysis process, this study employed whole-genome sequencing and metabolomics to explore its genetic and metabolic characteristics. The identified strain was classified as Lysinibacillus xylanilyticus and designated with the number XL-2024. Its genome size is 5,075,210 bp with a GC content of 37.33%, encoding 5275 genes. Functional database comparisons revealed that the protein-coding genes were distributed among glucose metabolism hydrolase, metal hydrolase, lysozyme, cell wall hydrolase, and CAZymes. Compared to 20 closely related strains, L. xylanilyticus XL-2024 shared 1502 core homologous genes and had 707 specific genes. These specific genes were mainly involved in the carbohydrate metabolism pathway and exhibited glycosyl bond hydrolase activity. Metabolomic analysis showed that L. xlanilyticus XL-2024 produced several metabolites related to polysaccharide degradation, including peptidase, glucanase, and pectinase. Additionally, the presence of antibacterial metabolites such as propionic acid and ginkgo acid among its metabolites may enhance the stability of the sea cucumber hydrolysate. In summary, L. xylanilyticus XL-2024 may play a pivotal role in the autolysis of A. japonicus. The results of this study provide a strong foundation for understanding how to prevent autolysis in A. japonicus and for better utilizing L. xylanilyticus XL-2024.
Development of a Whey Protein Recovery Process Using Sugar Kelp (Saccharina latissima) Extracts
Authors: Pierce Alex , Skonberg Denise , Calder Beth , Dumas Rob , Jin Qing
Published: November 2024

Whey is the largest waste product of the cheese-making industry and the current methods of extracting the nutrients from it are costly and inefficient. This study assessed the feasibility of using crude polysaccharides to flocculate proteins from liquid whey waste. The flocculants used were a sugar kelp (Saccharina latissima) extract, as well as commercial seaweed polysaccharides, alginate and k-carrageenan, to recover proteins from the liquid whey waste. Physicochemical and functional parameters including protein content, protein recovery efficiency, mineral content, total phenolic content (TPC), antioxidant capacity, color, water- and oil-holding capacity, gelling capacity, foaming activity and stability, and emulsifying activity and stability were tested on the resulting flocculates. The yield of the dried flocculates by use of alginate, the sugar kelp polysaccharide extract (SKPE), and carrageenan were 1.66, 0.98, and 1.22 g/100 g of liquid whey with protein contents of 27.4%, 45.5%, and 37.5%, respectively. The protein recovery efficiency from the whey was 57.5%, 56.2%, and 57.9% using alginate, SKPE, and carrageenan, respectively. The alginate flocculate had the highest oil-holding capacity and foaming abilities while the carrageenan flocculate had the best gelling ability and the highest emulsifying activity and stability. TPC and antioxidant activity were highest in the SKPE flocculate. All three flocculates presented slightly different compositional and functional qualities, which could be used for a variety of products. This study showed that seaweed polysaccharides present a simple and effective way to extract protein from liquid whey waste while creating a functional and high-protein ingredient.
A New Strategy for Enhancing Postharvest Quality of Sweet Cherry: High-Voltage Electrostatic Field Improves the Physicochemical Properties and Fungal Community
Authors: Liu Yanlong , Zhang Lulu , Hu Tan , Liu Qiongyin , Zhou Shuya , Zhao Yi , Jatt Abdul-Nabi , Zhang Caili , Gong Hansheng
Published: November 2024

Sweet cherry has a short shelf life due to the occurrence of senescence and fungal infection after harvest. This study aimed to study the effects of high-voltage electrostatic field (HVEF) on the physicochemical properties and fungal composition of sweet cherry during cold storage. The experiments were conducted at 4 °C for 28 days and the quality indicators were determined every 7 days during the period of storage. The fungal composition on sweet cherry was determined using high-throughput sequencing. The results showed that HVEF could better maintain the total soluble solids and inhibit the respiration of cherries. The decay incidence in sweet cherries was decreased by HVEF during cold storage. High-throughput sequencing revealed that HVEF could alter the fungal community and increase the fungal diversity on sweet cherries. Compared with the control group, HVEF decreased the abundance of Alternaria and Cladosporium on sweet cherries, while Aureobasidium, as a nonpathogenic fungus, increased and became the dominant strain at the end of the storage period. In summary, HVEF can improve the physicochemical properties of sweet cherry by inhibiting respiration and can reduce decay incidence by inhibiting specific pathogenic fungi. HVEF is expected to become an efficient and promising technology for the preservation of fruit.
Quality Change of Citri Reticulatae Pericarpium (Pericarps of Citrus reticulata ‘Chachi’) During Storage and Its Sex-Based In Vitro Digestive Performance
Authors: Yu Peirong , Zeng Yuying , Li Chunyu , Qiu Bixia , Shi Yuan , He Qixi , Lesmes Uri , Achmon Yigal
Published: November 2024

Citri Reticulatae Pericarpium (CRP), particularly including the pericarp of Citrus reticulata ‘Chachi’ (GCP), has been widely used as a food, a dietary supplement, and traditional Chinese medicine. Despite the widespread use of traditional foods, there is limited evidence regarding the precise relationships between storage conditions, aging duration, and the digestive performance of CRP. In this study, the aim was to investigate the impact of the storage conditions on the quality of aged GCP during shelf life and to evaluate the subsequent digestive performance of corresponding GCP decoctions. Respiration in GCP was monitored by measuring oxygen (O2), carbon dioxide (CO2), and methane (CH4) gases throughout the storage simulation, with O2 and CO2 validated as prospective safety measures. Five flavonoids (hesperidin, didymin, nobiletin, tangeretin, and 3,5,6,7,8,3′,4′-heptamethoxyflavone) were determined as quality indicators, and their contents were significantly affected by the duration of the storage simulation and the aging periods of GCP. Our study also found that temperature and humidity significantly affected the volatile organic compounds (VOCs) emission from GCP. Eighteen compounds were proposed to show potential as descriptive measures of aging periods while eight compounds were proposed as potential indicators to discriminate among the spoilage level. Furthermore, the bioaccessibility of hesperidin ranged from ~30% to ~50% and was not significantly affected by the GCP’s aging time nor the consumer’s sex (p < 0.05). This study presents evidence for the future control of the quality of GCP and its digestive performance in males and females.
A Combined Impact of Low-Voltage Electrostatic Field and Essential Oil on the Postharvest Properties of Chili Pepper: Insights into Related Molecular Mechanisms
Authors: Guo Xiaoqian , Liu Weihua , Zhang Liyong , Wang Xianghong , Mi Si
Published: November 2024

This research is intended to ascertain the impact of low-voltage electrostatic field (LVEF) together with chili pepper leaf essential oil (CLEO) on the storage quality of chili pepper. Four groups of samples were investigated, namely, control (CK), CLEO, LVEF, and CLEO + LVEF. Chili pepper from the CLEO + LVEF group reduced the weight loss and malondialdehyde content but improved the ascorbic acid contents, antioxidant potential, firmness, and color attributes. CLEO and LVEF could maintain the integral structure and stability of the cell wall by suppressing the activities of hydrolases of pectin, cellulose, and hemicellulose. The positive role of CLEO + LVEF on the color quality was explained by the significantly higher chlorophyll content and lower activities of chlorophyllase, pheophytinase, and Mg-dechelatase compared to the CK group. Taken together, all data provide supporting evidence for a synergistic effect of CLEO and LVEF on the enhancement of postharvest traits of chili peppers.
The Characterization and Stability of Powdered Oil Loaded with β-Carotene Prepared from a Sodium Caseinate–Carrageenan Complex: The Effect of Vacuum Freeze-Drying and Spray-Drying
Authors: Long Yue , Zhang Juan , Li Delong , Zhang Yanpeng , Cao Yang , Xu Wei , Hu Zhixiong , Hu Chun
Published: November 2024

β-carotene (BC) has various biological activities, such as anticancer properties, contributing to the prevention of cardiovascular diseases, etc., while the poor solubility and low bioavailability limit its further development in the food industry. Therefore, how to effectively encapsulate this unstable substance has become a hot topic. Here, different concentrations of sodium caseinate and ι-carrageenan (NaCas-CA) complex emulsions were used as wall materials, and the effect of spray-drying (SD) and vacuum freeze-drying (VFD) on the properties of BC powders loaded with NaCas-CA was investigated. The results showed that the characteristic peaks of BC disappeared in all powdered oils, indicating that BC could be effectively encapsulated. As the wall concentration increased, the surface oil of the powders decreased significantly. At the same concentration, the surface oil content of SD (minimum of 8.34%) was lower than that of VFD (minimum of 10.02%). However, the particle size of SD-reconstituted emulsions was larger than that of VFD. Furthermore, the SD-reconstituted emulsions were more stable than the VFD after storage at 25 °C for 3 h. This study reveals the effect of different drying methods on the structure and stability of powdered oils, providing valuable information for the research of functional active-loaded powdered oils and applications in the food industry.
DGGNets: Deep Gradient-Guidance Networks for Speckle Noise Reduction
Authors: Wang Li , Li Jinkai , Pu Yi-Fei , Yin Hao , Liu Paul
Published: November 2024

Speckle noise is a granular interference that degrades image quality in coherent imaging systems, including underwater sonar, Synthetic Aperture Radar (SAR), and medical ultrasound. This study aims to enhance speckle noise reduction through advanced deep learning techniques. We introduce the Deep Gradient-Guidance Network (DGGNet), which features an architecture comprising one encoder and two decoders—one dedicated to image recovery and the other to gradient preservation. Our approach integrates a gradient map and fractional-order total variation into the loss function to guide training. The gradient map provides structural guidance for edge preservation and directs the denoising branch to focus on sharp regions, thereby preventing over-smoothing. The fractional-order total variation mitigates detail ambiguity and excessive smoothing, ensuring rich textures and detailed information are retained. Extensive experiments yield an average Peak Signal-to-Noise Ratio (PSNR) of 31.52 dB and a Structural Similarity Index (SSIM) of 0.863 across various benchmark datasets, including McMaster, Kodak24, BSD68, Set12, and Urban100. DGGNet outperforms existing methods, such as RIDNet, which achieved a PSNR of 31.42 dB and an SSIM of 0.853, thereby establishing new benchmarks in speckle noise reduction.
Discovery of Intrinsic Ferromagnetism Induced by Memory Effects in Low-Dimensional System
Authors: Zeng Shaolong , Wan Xuejin , Hu Yangfan , Tan Shijing , Wang Biao
Published: November 2024

The impact of dynamic processes on equilibrium properties is a fundamental issue in condensed matter physics. This study investigates the intrinsic ferromagnetism generated by memory effects in the low-dimensional continuous symmetry Landau–Ginzburg model, demonstrating how memory effects can suppress fluctuations and stabilize long-range magnetic order. Our results provide compelling evidence that tuning dynamical processes can significantly alter the behavior of systems in equilibrium. We quantitatively evaluate how the emergence of the ferromagnetic phase depends on memory effects and confirm the presence of ferromagnetism through simulations of hysteresis loops, spontaneous magnetization, and magnetic domain structures in the 1D continuous symmetry Landau–Ginzburg model. This research offers both theoretical and numerical insights for identifying new phases of matter by dynamically modifying equilibrium properties.
Quantitative Analysis of the Fractional Fokker–Planck–Levy Equation via a Modified Physics-Informed Neural Network Architecture
Authors: Fazal Fazl Ullah , Sulaiman Muhammad , Bassir David , Alshammari Fahad Sameer , Laouini Ghaylen
Published: November 2024

An innovative approach is utilized in this paper to solve the fractional Fokker–Planck–Levy (FFPL) equation. A hybrid technique is designed by combining the finite difference method (FDM), Adams numerical technique, and physics-informed neural network (PINN) architecture, namely, the FDM-APINN, to solve the fractional Fokker–Planck–Levy (FFPL) equation numerically. Two scenarios of the FFPL equation are considered by varying the value of (i.e., 1.75, 1.85). Moreover, three cases of each scenario are numerically studied for different discretized domains with 100, 200, and 500 points in x∈[−1, 1] and t∈[0, 1]. For the FFPL equation, solutions are obtained via the FDM-APINN technique via 1000,  2000, and 5000 iterations. The errors, loss function graphs, and statistical tables are presented to validate our claim that the FDM-APINN is a better alternative intelligent technique for handling fractional-order partial differential equations with complex terms. The FDM-APINN can be extended by using nongradient-based bioinspired computing for higher-order fractional partial differential equations.
Integral Operators in b-Metric and Generalized b-Metric Spaces and Boundary Value Problems
Authors: Middlebrook Christopher , Feng Wenying
Published: November 2024

We study fixed-point theorems of contractive mappings in b-metric space, cone b-metric space, and the newly introduced extended b-metric space. To generalize an existence and uniqueness result for the so-called Φs functions in the b-metric space to the extended b-metric space and the cone b-metric space, we introduce the class of ΦM functions and apply the Hölder continuous condition in the extended b-metric space. The obtained results are applied to prove the existence and uniqueness of solutions and positive solutions for nonlinear integral equations and fractional boundary value problems. Examples and numerical simulation are given to illustrate the applications.
Exploring the Components of Cosmogenic UHECR, Neutrino, and Diffuse Gamma Ray from High-Energy Astrophysical Objects
Authors: Min Fangsheng , Lu Hong , Guo Yiqing
Published: November 2024

The development of multimessenger astrophysics allows us to probe various background particles from the distant early universe. Up to now, much effort has been made researching the emission and radiation of diverse steady or transient astrophysical sources. We review the potential accelerating, escaping, propagating, and radiation process of high-energy particles under specific circumstances for regular astrophysical sources and briefly discuss the underlying contribution from their emissions to the intensity of ultrahigh-energy cosmic ray, TeV-PeV cosmic neutrino, and the diffuse gamma-ray background, aiming to find a possible common origin.
Crosslinking by Click Chemistry of Hyaluronan Graft Copolymers Involving Resorcinol-Based Cinnamate Derivatives Leading to Gel-like Materials
Authors: Saletti Mario , Pepi Simone , Paolino Marco , Venditti Jacopo , Giuliani Germano , Bonechi Claudia , Leone Gemma , Magnani Agnese , Rossi Claudio , Cappelli Andrea
Published: November 2024

The well-known “click chemistry” reaction copper(I)-catalyzed azide-alkyne 1,3-dipolar cycloaddition (CuAAC) was used to transform under very mild conditions hyaluronan-based graft copolymers HA(270)-FA-Pg into the crosslinked derivatives HA(270)-FA-TEGERA-CL and HA(270)-FA-HEGERA-CL. In particular, medium molecular weight (i.e., 270 kDa) hyaluronic acid (HA) grafted at various extents (i.e., 10, 20, and 40%) with fluorogenic ferulic acid (FA) residue bonding propargyl groups were used in the CuAAC reaction with novel azido-terminated crosslinking agents Tri(Ethylene Glycol) Ethyl Resorcinol Acrylate (TEGERA) and Hexa(Ethylene Glycol) Ethyl Resorcinol Acrylate (HEGERA). The resulting HA(270)-FA-TEGERA-CL and HA(270)-FA-HEGERA-CL materials were characterized from the point of view of their structure by performing NMR studies. Moreover, the swelling behavior and rheological features were assessed employing TGA and DSC analysis to evaluate the potential gel-like properties of the resulting crosslinked materials. Despite the 3D crosslinked structure, HA(270)-FA-TEGERA-CL and HA(270)-FA-HEGERA-CL frameworks showed adequate swelling performance, the required shear thinning behavior, and coefficient of friction values close to those of the main commercial HA solutions used as viscosupplements (i.e., 0.20 at 10 mm/s). Furthermore, the presence of a crosslinked structure guaranteed a longer residence time. Indeed, HA(270)-FA-TEGERA-CL-40 and HA(270)-FA-HEGERA-CL-40 after 48 h showed a four times greater enzymatic resistance than the commercial viscosupplements. Based on the promising obtained results, the crosslinked materials are proposed for their potential applicability as novel viscosupplements.
Changes in Healthcare Utilization in Japan in the Aftermath of the COVID-19 Pandemic: A Time Series Analysis of Japanese National Data Through November 2023
Authors: Tanoue Yuta , Cao Alton , Koda Masahide , Harada Nahoko , Ghaznavi Cyrus , Nomura Shuhei
Published: November 2024

Introduction: The COVID-19 pandemic precipitated substantial disruptions in healthcare utilization globally. In Japan, reduced healthcare utilization during the pandemic’s early phases had been documented previously. However, few studies have investigated the impact of the pandemic’s later stages (2022–2023) on healthcare utilization rates, particularly in the Japanese context. Methods: We employed a quasi-Poisson regression model, adapted from the FluMOMO framework, to analyze temporal trends in Japanese healthcare utilization throughout the pandemic until November 2023. We estimated inpatient and outpatient volumes and hospital length of stay by bed type (general and psychiatric). Results: In general hospital beds, inpatient volumes remained significantly below pre-pandemic levels for every month until November 2023, with a reduction of 7.8 percent in 2023 compared to pre-pandemic levels. Psychiatric inpatient volumes, which had been declining before the pandemic, continued this downward trend, with the average occupancy rate decreasing by approximately 5.3% to 81.3% in 2023 compared to pre-pandemic levels. Significantly reduced outpatient volumes for both general and psychiatric care, in addition to prolonged lengths of hospital stay for psychiatric beds, were observed sporadically for several months in 2022 and 2023, persisting beyond the cessation of state of emergency and quasi-state of emergency declarations. Conclusion: The COVID-19 pandemic fundamentally altered healthcare utilization patterns in Japan. We observed a sustained reduction in general and psychiatric inpatient volumes relative to pre-pandemic baselines nationwide. The prolonged impact on healthcare utilization patterns, persisting beyond emergency measures, warrants continued monitoring of service delivery.
First Experience of Late Pruning on Kékfrankos Grapevine (Vitis vinifera L.) in Eger Wine Region (Hungary)
Authors: Villangó Szabolcs , Szekeres András , Végvári György , Ficzek Gitta , Simon Gergely , Zsófi Zsolt
Published: November 2024

Traditional winter pruning in dormancy (BBCH-00) as control (C) and three late pruning treatments, LP1 (wool stage—BBCH-05), LP2 (two leaves folded—BBCH-12), and LP3 (four leaves folded—BBCH-14), were applied on Kékfrankos grapevines. The evolution of the phenological growth stages, grape juice, wine analytical parameters, and phenolic composition were evaluated. The quantitative aspects of the grape berry, bunch, yield, and cane were also assessed. Our goal was to reach a decrease in sugar content and an increase in acidity. Delaying or postponing the phenological phases to bring technological and phenolic ripening closer together was also one of our objectives. These were accomplished, but the negative aspects of late pruning, which resulted in a reduction in the diameter and weight of the canes, should also be taken into account. We also found that, the later the late pruning, the more the yield was reduced. By postponing pruning, the phenological phases were also extended.
Integrated Assessment of Security Risk Considering Police Resources
Authors: Chen Jieying , Li Weihong , Li Yaxing , Chen Yebin
Published: November 2024

The existing research on security risk often focuses on specific types of crime, overlooking an integrated assessment of security risk by leveraging existing police resources. Thus, we draw on crime geography theories, integrating public security business data, socioeconomic data, and spatial analysis techniques, to identify integrated risk points and areas by examining the distribution of police resources and related factors and their influence on security risk. The findings indicate that security risk areas encompass high-incidence areas of public security issues, locations with concentrations of dangerous individuals and key facilities, and regions with a limited police presence, characterized by dense populations, diverse urban functions, high crime probabilities, and inadequate supervision. While both police resources and security risk are concentrated in urban areas, the latter exhibits a more scattered distribution on the urban periphery, suggesting opportunities to optimize resource allocation by extending police coverage to risk hotspots lacking patrol stations. Notably, Level 1 security risk areas often coincide with areas lacking a police presence, underscoring the need for strategic resource allocation. By comprehensively assessing the impact of police resources and public security data on spatial risk distribution, this study provides valuable insights for public security management and police operations.
Microbiome Shifts and Their Impact on Gut Physiology in Irritable Bowel Syndrome
Authors: Aggeletopoulou Ioanna , Triantos Christos
Published: November 2024

Irritable bowel syndrome (IBS) is one of the most prevalent functional gastrointestinal disorders characterized by recurrent abdominal pain and altered bowel habits. The exact pathophysiological mechanisms for IBS development are not completely understood. Several factors, including genetic predisposition, environmental and psychological influences, low-grade inflammation, alterations in gastrointestinal motility, and dietary habits, have been implicated in the pathophysiology of the disorder. Additionally, emerging evidence highlights the role of gut microbiota in the pathophysiology of IBS. This review aims to thoroughly investigate how alterations in the gut microbiota impact physiological functions such as the brain–gut axis, immune system activation, mucosal inflammation, gut permeability, and intestinal motility. Our research focuses on the dynamic “microbiome shifts”, emphasizing the enrichment or depletion of specific bacterial taxa in IBS and their profound impact on disease progression and pathology. The data indicated that specific bacterial populations are implicated in IBS, including reductions in beneficial species such as Lactobacillus and Bifidobacterium, along with increases in potentially harmful bacteria like Firmicutes and Proteobacteria. Emphasis is placed on the imperative need for further research to delineate the role of specific microbiome alterations and their potential as therapeutic targets, providing new insights into personalized treatments for IBS.
Molecular Structure of the Na+,K+-ATPase α4β1 Isoform in Its Ouabain-Bound Conformation
Authors: Abe Kazuhiro , McDermott Jeff , Valia Madapally Hridya , Marimuthu Parthiban , Gopalasingam Chai C. , Gerle Christoph , Shigematsu Hideki , Khandelia Himanshu , Blanco Gustavo
Published: November 2024

Na+,K+-ATPase is the active ion transport system that maintains the electrochemical gradients for Na+ and K+ across the plasma membrane of most animal cells. Na+,K+-ATPase is constituted by the association of two major subunits, a catalytic α and a glycosylated β subunit, both of which exist as different isoforms (in mammals known as α1, α2, α3, α4, β1, β2 and β3). Na+,K+-ATPase α and β isoforms assemble in different combinations to produce various isozymes with tissue specific expression and distinct biochemical properties. Na+,K+-ATPase α4β1 is only found in male germ cells of the testis and is mainly expressed in the sperm flagellum, where it plays a critical role in sperm motility and male fertility. Here, we report the molecular structure of Na+,K+-ATPase α4β1 at 2.37 Å resolution in the ouabain-bound state and in the presence of beryllium fluoride. Overall, Na+,K+-ATPase α4 structure exhibits the basic major domains of a P-Type ATPase, resembling Na+,K+-ATPase α1, but has differences specific to its distinct sequence. Dissimilarities include the site where the inhibitor ouabain binds. Molecular simulations indicate that glycosphingolipids can bind to a putative glycosphingolipid binding site, which could potentially modulate Na+,K+-ATPase α4 activity. This is the first experimental evidence for the structure of Na+,K+-ATPase α4β1. These data provide a template that will aid in better understanding the function Na+,K+-ATPase α4β1 and will be important for the design and development of compounds that can modulate Na+,K+-ATPase α4 activity for the purpose of improving male fertility or to achieve male contraception.