bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling the Effect of Milk Vetch–Rice Rotation on N Runoff Loss in the Middle and Lower Reaches of the Yangtze River
Authors: Zhou Guodong , Wei Cuilan , Li Penghui , Liang Hao
Published: November 2024

The winter planting of green manure (GM) is widely used in South China to reduce chemical nitrogen (N) fertilizer use, improve soil fertility, and maintain rice yields, but its effect on N runoff loss in paddy fields remains unclear. This study combines multi-site field experiments with a process model (WHCNS-Rice) to assess how GM with reduced N fertilizer impacts N runoff loss and its forms in the Yangtze River’s middle and lower reaches, considering different rainfall years. The network field experiments included four treatments: conventional fertilization (FR), conventional fertilization plus straw return (FRS), GM with a 40% N reduction (MR), and GM-straw combined return with a 40% N reduction (MRS). Monitoring the results showed that compared to the winter fallow treatment, the GM treatments reduced the peak and average total N (TN) concentrations by 11.1–57.9% (average 26.9%) and 17.1–27.3% (average 22.3%), respectively. The TN runoff loss under the GM treatment decreased by 3.50–10.61 kg N ha−1 (22.5–42.1%). GM primarily reduced the runoff loss of dissolved inorganic N (DIN), with reductions at different sites ranging from 0.22 to 9.66 kg N ha−1 (8.4–43.4%), indicating GM effectively decreases N runoff by reducing DIN. Model simulations of ponding water depth, runoff, TN concentration in surface water, and TN loss in paddy fields produced the consistency indices and simulation efficiencies of 0.738–0.985, 0.737–0.986, 0.912–0.986, and 0.674–0.972, respectively, indicating that the model can be used to evaluate water consumption and N runoff loss in the GM-paddy system. The simulations showed that GM with a 40% N fertilizer significantly reduced N runoff loss under all rainfall conditions, with the greatest reductions in wet years. Under wet, normal, and dry conditions, the GM treatments significantly reduced average TN loss by 0.37–5.53 kg N ha−1 (12.77–29.17%), 0.21–5.32 kg N ha−1 (9.95–24.51%), and 0.02–3.2 kg N ha−1 (1.78–23.19%), respectively, compared to the winter fallow treatment. These results indicate that the combination of GM and a 40% reduction in N fertilizer can significantly reduce N runoff loss from paddy fields, demonstrating good effectiveness under various rainfall conditions, making it a green production model worth promoting.
The Effect of Vegetation Ecological Restoration by Integrating Multispectral Remote Sensing and Laser Point Cloud Monitoring Technology
Authors: Shi Mengxi , Xing Shuhan , Bai He , Xu Dawei , Shi Lei
Published: November 2024

This research aims to evaluate and monitor the effectiveness of vegetation ecological restoration by integrating Multispectral Remote Sensing (MRS) and laser point cloud (LPC) monitoring technologies. Traditional vegetation restoration monitoring methods often face challenges of inaccurate data and insufficient coverage, and the use of MRS or LPC techniques alone has its limitations. Therefore, to more accurately monitor the vegetation restoration status, this study proposes a new monitoring method that combines the advantages of the large-scale coverage of MRS technology and the high-precision three-dimensional structural data analysis capability of LPC technology. This new method was applied in the Daqing oilfield area of China, aiming to provide effective ecological restoration assessment methods through the precise monitoring and analysis of regional vegetation growth and coverage. The results showed that there was a negative correlation between the vegetation humidity index and vegetation growth in the Daqing oilfield in 2023. The estimated monitoring effect of the research method could reach over 90%, and the coverage area of hydrangea restoration in the monitoring year increased by 7509 km2. The research technology was closer to the actual coverage situation. The simulation image showed that the vegetation coverage in the area has significantly improved after returning farmland to forests. Therefore, the technical methods used can effectively monitor the ecological restoration of vegetation, which has great research significance for both vegetation restoration and monitoring.
Effects of Temperature, Precipitation, and Sunshine on Cold-Tolerant Wheat Yield Under Warming Trends: A 20-Year Study in Hokkaido, Japan
Authors: Nishio Zenta , Kurushima Masatomo , Suzuki Takeshi , Shimoda Seiji , Hirota Tomoyoshi
Published: November 2024

To clarify the adaptation strategies of cold-tolerant wheat against global warming, this study examined the effects of daily temperature, precipitation, and sunshine duration on wheat yield in Hokkaido, Japan, over 13 years (2011–2023). Yield components were also analyzed over 20 years (2004–2023). The number of snow-cover days decreased by about 24 days over the 20-year period. As a result, the growth of overwintered wheat accelerated, with the heading and maturity of plants advancing by about 8 and 5 days, respectively, and the grain-filling period extending from about 44 to about 48 days. Multiple regression analysis was conducted using wheat yield as the objective variable and weather conditions as explanatory variables. Three weather conditions were selected: precipitation for 8 days from 27 March, sunshine hours for 8 days from 21 March, and sunshine hours for 12 days from 13 June, which yielded a coefficient of determination of 0.953. Despite the highest mean summer temperatures on record being registered in 2023, high yields were ensured by the number of sunshine hours, which were approximately 1.5 times the normally recorded hours. This highlights the importance of this parameter in mitigating the impact of high summer temperatures.
Double Hydrophilic Hyperbranched Copolymer-Based Lipomer Nanoparticles: Copolymer Synthesis and Co-Assembly Studies
Authors: Gerardos Angelica Maria , Pispas Stergios
Published: November 2024

Double hydrophilic, random, hyperbranched copolymers were synthesized via reversible addition–fragmentation chain transfer (RAFT) polymerization of oligo(ethylene glycol) methyl ether methacrylate (OEGMA) and 2-(dimethylamino)ethyl methacrylate (DMAEMA) utilizing ethylene glycol dimethacrylate (EGDMA) as the branching agent. The resulting copolymers were characterized in terms of their molecular weight and dispersity using size exclusion chromatography (SEC), and their chemical structure was confirmed using FT-IR and 1H-NMR spectroscopy techniques. The choice of the two hydrophilic blocks and the design of the macromolecular structure allowed the formation of self-assembled nanoparticles, partially due to the pH-responsive character of the DMAEMA segments and their interaction with -COOH end groups remaining from the chain transfer agent. The copolymers showed pH-responsive properties, mainly due to the protonation–deprotonation equilibria of the DMAEMA segments. Subsequently, a nanoscopic polymer–lipid (lipomer) mixed system was formulated by complexing the synthesized copolymers with cosmetic amphiphilic emulsifiers, specifically glyceryl stearate (GS) and glyceryl stearate citrate (GSC). This study aims to show that developing lipid–polymer hybrid nanoparticles can effectively address the limitations of both liposomes and polymeric nanoparticles. The effects of varying the ionic strength and pH on stimuli-sensitive polymeric and mixed polymer–lipid nanostructures were thoroughly investigated. To achieve this, the structural properties of the hybrid nanoparticles were comprehensively characterized using physicochemical techniques providing insights into their size distribution and stability.
Optimization of Tensile Strength and Cost-Effectiveness of Polyethylene Terephthalate Glycol in Fused Deposition Modeling Using the Taguchi Method and Analysis of Variance
Authors: Chen Dyi-Cheng , Zheng Quan-De , Chen Chih-Hao
Published: November 2024

This paper investigates the optimization of tensile strength, tensile strength per unit weight, and tensile strength per unit time of polyethylene terephthalate glycol (PETG) material in fused deposition modeling (FDM) technology using the Taguchi method and analysis of variance (ANOVA). Unlike previous studies that typically focused on optimizing a single mechanical property, our research offers a multi-dimensional evaluation by simultaneously optimizing three critical quality characteristics: tensile strength, tensile strength per unit weight, and tensile strength per unit time. This comprehensive approach provides a broader perspective on both the mechanical performance and production efficiency, contributing new insights into the optimization of PETG in FDM. The Taguchi method (L16 45) was designed and executed, with the layer height, infill density, print temperature, print speed, and infill line direction as the control factors. Sixteen tensile tests were conducted, and ANOVA was employed to identify the main influencing factors for each quality characteristic. For the tensile strength, the infill density was found to have the greatest impact (48.45%), while the print temperature had the least impact (0.78%). The optimal parameter combination reduced the quality loss to 31.28% and standard deviation to 55.93%. For tensile strength per unit weight, the infill line direction had the greatest impact (87.22%), whereas the print temperature had the least impact (0.77%). The optimal parameter combination reduced the quality loss to 54.09% and standard deviation to 73.54%. Regarding the tensile strength per unit time, the layer height had the greatest impact (82.12%), while the print temperature had the least impact (0.08%). The optimal parameter combination reduced the quality loss to 10.81% and standard deviation to 32.87%.
High-Strength and Conductive Electrospun Nanofiber Yarns
Authors: Shao Qingqing , Xing Bo , Du Zhaoqun , Yu Weidong
Published: November 2024

In electrospinning, nanofibers are frequently produced in nonwoven web form. Their poor mechanical properties (below 100 MPa) and difficulty in tailoring the fibrous structure have restricted their applications. However, advanced materials must be highly resistant to both deformation and fracture. By combining electrospinning technology with stretching, we have overcome this disadvantage and demonstrated a polyacrylonitrile nanofiber yarn with a tensile strength of 743 ± 20 MPa. The nearly perfect uniaxial orientation of the fibrils under the stretching process is crucial for the remarkable mechanical properties of the yarn. Additionally, the nanofiber yarn was functionalized by a dip-coating process with silver nanowires (AgNWs), imparting conductive properties. This conductive, high-strength nanofiber yarn demonstrates practical applications in flexible and wearable devices. The presented strategy is versatile and can be adapted to create other high-performance nanofiber yarns, with potential uses in fields such as biomedicine and smart textiles.
Facile Synthesis of Polypyrrole-Decorated RGO-CuS Nanocomposite for Efficient Nickel Removal from Wastewater
Authors: Mashkoor Fouzia , Shoeb Mohd , Khan Mohmmad Naved , Jeong Changyoon
Published: November 2024

Efficient wastewater treatment, particularly the removal of heavy metal ions, remains a challenging priority in environmental remediation. This study introduces a novel sandwich-structured nanocomposite, RGO-CuS-PPy, composed of reduced graphene oxide (RGO), copper sulfide (CuS), and polypyrrole (PPy), synthesized via a straightforward hydrothermal method. The unique combination of RGO, CuS, and PPy offers enhanced adsorption capacity for Ni(II) ions due to RGO’s high surface area and CuS’s active binding sites, supported by PPy’s structural stability contributions. This study is among the first to explore this specific nanocomposite architecture for Ni(II) removal, achieving an adsorption capacity of 166.67 mg/g and a high removal efficiency of 94.9% within 210 min for 55 mg/L of Ni(II) concentration at pH 6 and adsorbent dose of 3 mg/15 mL. The kinetic analysis shows the best fitted time-dependent experimental data with the pseudo-second-order model, indicating chemisorption. Isotherm studies confirmed the Langmuir model as the best fit, yielding a high monolayer adsorption capacity of 166.67 mg/g. Thermodynamic analysis shows the adsorption process was endothermic (ΔH° = 80.23 kJ/mol) and spontaneous (ΔG° ranging from −6.985 to −14.399 kJ/mol). Additionally, reusability tests using 0.1 M HCl for desorption demonstrated good reusability, emphasizing the RGO-CuS-PPy nanocomposite’s potential as a sustainable adsorbent for Ni(II) removal in wastewater treatment applications.
A Review of the Measurement of the Multiphase Slug Frequency
Authors: Höhn Ronaldo Luís , Arabi Abderraouf , Stiriba Youssef , Pallares Jordi
Published: November 2024

The slug frequency (SF), which refers to the number of liquid slugs passing through a pipe during a specific time, is an important parameter for characterizing the multiphase intermittent flows and monitoring some process involving this kind of flow. The simplicity of the definition of SF contrasts with the difficulty of correctly measuring it. This manuscript aims to review and discuss the various techniques and methods developed to determine the slug frequency experimentally. This review significantly reveals the absence of a universal measurement method applicable to a wide range of operating conditions. Thus, the recourse to recording videos with high-speed cameras, which can be used only at a laboratory scale, remains often necessary. From the summarized state-of-the-art, it appears that correctly defining the threshold values for detecting the liquid slugs/elongated bubbles interface from physical parameters time series, increasing the applicability of instrumentations at industrial scales, and properly estimating the uncertainties are the challenges that have to be faced to advance in the measurement of SF.
DC-Mamba: A Novel Network for Enhanced Remote Sensing Change Detection in Difficult Cases
Authors: Zhang Junyi , Chen Renwen , Liu Fei , Liu Hao , Zheng Boyu , Hu Chenyu
Published: November 2024

Remote sensing change detection (RSCD) aims to utilize paired temporal remote sensing images to detect surface changes in the same area. Traditional CNN-based methods are limited by the size of the receptive field, making it difficult to capture the global features of remote sensing images. In contrast, Transformer-based methods address this issue with their powerful modeling capabilities. However, applying the Transformer architecture to image processing introduces a quadratic complexity problem, significantly increasing computational costs. Recently, the Mamba architecture based on state-space models has gained widespread application in the field of RSCD due to its excellent global feature extraction capabilities and linear complexity characteristics. Nevertheless, existing Mamba-based methods lack optimization for complex change areas, making it easy to lose shallow features or local features, which leads to poor performance on challenging detection cases and high-difficulty datasets. In this paper, we propose a Mamba-based RSCD network for difficult cases (DC-Mamba), which effectively improves the model’s detection capability in complex change areas. Specifically, we introduce the edge-feature enhancement (EFE) block and the dual-flow state-space (DFSS) block, which enhance the details of change edges and local features while maintaining the model’s global feature extraction capability. We propose a dynamic loss function to address the issue of sample imbalance, giving more attention to difficult samples during training. Extensive experiments on three change detection datasets demonstrate that our proposed DC-Mamba outperforms existing state-of-the-art methods overall and exhibits significant performance improvements in detecting difficult cases.
Long-Term Ground Deformation Monitoring and Quantitative Interpretation in Shanghai Using Multi-Platform TS-InSAR, PCA, and K-Means Clustering
Authors: Chong Yahui , Zeng Qiming
Published: November 2024

Ground subsidence in urban areas is mainly due to natural or anthropogenic activities, and it seriously threatens the healthy and sustainable development of the city and the security of individuals’ lives and assets. Shanghai is a megacity of China, and it has a long history of ground subsidence due to the overexploitation of groundwater and urban expansion. Time Series Synthetic Aperture Radar Interferometry (TS-InSAR) is a highly effective and widely used approach for monitoring urban ground deformation. However, it is difficult to obtain long-term (such as over 10 years) deformation results using single-platform SAR satellite in general. To acquire long-term surface deformation monitoring results, it is necessary to integrate data from multi-platform SAR satellites. Furthermore, the deformations are the result of multiple factors that are superimposed, and relevant studies that quantitatively separate the contributions from different driving factors to subsidence are rare. Moreover, the time series cumulative deformation results of massive measurement points also bring difficulties to the deformation interpretation. In this study, we have proposed a long-term surface deformation monitoring and quantitative interpretation method that integrates multi-platform TS-InSAR, PCA, and K-means clustering. SAR images from three SAR datasets, i.e., 19 L-band ALOS-1 PALSAR, 22 C-band ENVISAT ASAR, and 20 C-band Sentinel-1A, were used to retrieve annual deformation rates and time series deformations in Shanghai from 2007 to 2018. The monitoring results indicate that there is serious uneven settlement in Shanghai, with a spatial pattern of stability in the northwest and settlement in the southeast of the study area. Then, we selected Pudong International Airport as the area of interest and quantitatively analyzed the driving factors of land subsidence in this area by using PCA results, combining groundwater exploitation and groundwater level change, precipitation, temperature, and engineering geological and human activities. Finally, the study area was divided into four sub-regions with similar time series deformation patterns using the K-means clustering. This study helps to understand the spatiotemporal evolution of surface deformation and its driving factors in Shanghai, and provides a scientific basis for the formulation and implementation of precise prevention and control strategies for land subsidence disasters, and it can also provide reference for monitoring in other urban areas.
Assessment of Vegetation Drought Loss and Recovery in Central Asia Considering a Comprehensive Vegetation Index
Authors: Han Wanqiang , Zheng Jianghua , Guan Jingyun , Liu Yujia , Liu Liang , Han Chuqiao , Li Jianhao , Li Congren , Mao Xurui , Tian Ruikang
Published: November 2024

In the context of drought events caused by global warming, there is limited understanding of vegetation loss caused by drought and the subsequent recovery of vegetation after drought ends. However, employing a single index representing a specific vegetation characteristic to explore drought’s impact on vegetation may overlook vegetation features and introduce increased uncertainty. We applied the enhanced vegetation index (EVI), fraction of vegetation cover (FVC), gross primary production (GPP), leaf area index (LAI), and our constructed remote sensing vegetation index (RSVI) to assess vegetation drought in Central Asia. We analyzed the differences in drought experiences for different climatic regions and vegetation types and vegetation loss and recovery following drought events. The results indicate that during drought years (2012 and 2019), the differences in vegetation drought across climatic regions were considerable. The vegetation in arid, semiarid, and Mediterranean climate regions was more susceptible to drought. The different indices used to assess vegetation loss exhibited varying degrees of dynamic changes, with vegetation in a state of mild drought experiencing more significantly during drought events. The different vegetation assessment indices exhibited significant variations during the drought recovery periods (with a recovery period of 16 days: EVI of 85%, FVC of 50%, GPP of 84%, LAI of 61%, and RSVI of 44%). Moreover, the required recovery periods tended to decrease from arid to humid climates, influenced by both climate regions and vegetation types. Sensitivity analysis indicated that the primary climatic factors leading to vegetation loss varied depending on the assessment indices used. The proposed RSVI demonstrates high sensitivity, correlation, and interpretability to dry–wet variations and can be used to assess the impact of drought on vegetation. These findings are essential for water resource management and the implementation of measures that mitigate vegetation drought.
FA-HRNet: A New Fusion Attention Approach for Vegetation Semantic Segmentation and Analysis
Authors: He Bingnan , Wu Dongyang , Wang Li , Xu Sheng
Published: November 2024

Semantic segmentation of vegetation in aerial remote sensing images is a critical aspect of vegetation mapping. Accurate vegetation segmentation effectively informs real-world production and construction activities. However, the presence of species heterogeneity, seasonal variations, and feature disparities within remote sensing images poses significant challenges for vision tasks. Traditional machine learning-based methods often struggle to capture deep-level features for the segmentation. This work proposes a novel deep learning network named FA-HRNet that leverages the fusion of attention mechanism and a multi-branch network structure for vegetation detection and segmentation. Quantitative analysis from multiple datasets reveals that our method outperforms existing approaches, with improvements in MIoU and PA by 2.17% and 4.85%, respectively, compared with the baseline network. Our approach exhibits significant advantages over the other methods regarding cross-region and cross-scale capabilities, providing a reliable vegetation coverage ratio for ecological analysis.
Review of Recent Advances in Remote Sensing and Machine Learning Methods for Lake Water Quality Management
Authors: Deng Ying , Zhang Yue , Pan Daiwei , Yang Simon X. , Gharabaghi Bahram
Published: November 2024

This review examines the integration of remote sensing technologies and machine learning models for efficient monitoring and management of lake water quality. It critically evaluates the performance of various satellite platforms, including Landsat, Sentinel-2, MODIS, RapidEye, and Hyperion, in assessing key water quality parameters including chlorophyll-a (Chl-a), turbidity, and colored dissolved organic matter (CDOM). This review highlights the specific advantages of each satellite platform, considering factors like spatial and temporal resolution, spectral coverage, and the suitability of these platforms for different lake sizes and characteristics. In addition to remote sensing platforms, this paper explores the application of a wide range of machine learning models, from traditional linear and tree-based methods to more advanced deep learning techniques like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). These models are analyzed for their ability to handle the complexities inherent in remote sensing data, including high dimensionality, non-linear relationships, and the integration of multispectral and hyperspectral data. This review also discusses the effectiveness of these models in predicting various water quality parameters, offering insights into the most appropriate model–satellite combinations for different monitoring scenarios. Moreover, this paper identifies and discusses the key challenges associated with data quality, model interpretability, and integrating remote sensing imagery with machine learning models. It emphasizes the need for advancements in data fusion techniques, improved model generalizability, and the developing robust frameworks for integrating multi-source data. This review concludes by offering targeted recommendations for future research, highlighting the potential of interdisciplinary collaborations to enhance the application of these technologies in sustainable lake water quality management.
Feasibility of a Non-Anticipatory, Random-Action Target System to Improve Shooting Performance: A Brief Field Trial
Authors: Smith Matthew Lee , Boolani Ali
Published: November 2024

Firearm shooting performance training rightfully focuses on shooting accuracy; however, additional foci should include decision processing speed and reaction time associated with decision making to avoid reaction-only based shooting responses. While advancements in realistic training environments attempt to mimic “real-world” situations, many remain largely anticipatory or subject to a speed–accuracy trade-off (SAT). The purpose of this brief field trial was to demonstrate the feasibility of a random-action target system (RATS) on participants’ shooting performance (i.e., accuracy, omission, and commission rates) among a convenience sample of six retired police officers and competitive shooters (age range: 45–58 years, mean age = 52.5 ± 5.89). Observational data were gathered from a single-day, three-round trial to test shooting accuracy and shooting errors when shooters were unable to anticipate target appearance location and target exposure speed. In Trial 1, the target exposure time was 0.5 s, which increased to 0.7 s in Trial 2, and decreased back to 0.5 s in Trial 3. Shooting accuracy generally increased, while omission and commission generally decreased, when shooters were presented with targets exposed for longer durations. From Trial 1 to Trial 3 (both trials with 0.5 s target exposures), shooters showed higher median accuracy rates, lower median omission rates, and lower median commission rates. Findings suggest that a non-anticipatory, RATS holds promise for improving shooting performance and offset SAT among shooters with firearm experience. However, additional trials are needed with the RATS to replicate these findings among a larger and more diverse set of participants, who train with the RATS consistently, over longer durations.
Geometric Analysis of Black Hole with Primary Scalar Hair
Authors: Liu Haotian
Published: November 2024

Within the novel context of primary scalar hair black holes, this article explores the fascinating subject of black hole thermal stability. Thermodynamic stability is the main subject of our investigation, which involves measuring the bound points, divergence points, black hole mass, thermal temperature, and specific heat capacity. In addition, we determine the scalar curvatures of thermodynamic geometries like Ruppeiner, Weinhold, Hendi-Panahiyah-Eslam-Momennia, and geometrothermodynamics formulations inside the framework of primary scalar hair black holes and delve into their complexities. Improving our knowledge of fundamental scalar hair black holes, this study sheds light on the intricate thermal geometric properties of these objects.
Symmetry and Complexity in Gene Association Networks Using the Generalized Correlation Coefficient
Authors: Ospina Raydonal , Xavier Cleber M. , Esteves Gustavo H. , Espinheira Patrícia L. , Castro Cecilia , Leiva Víctor
Published: November 2024

High-dimensional gene expression data cause challenges for traditional statistical tools, particularly when dealing with non-linear relationships and outliers. The present study addresses these challenges by employing a generalized correlation coefficient (GCC) that incorporates a flexibility parameter, allowing it to adapt to varying levels of symmetry and asymmetry in the data distribution. This adaptability is crucial for analyzing gene association networks, where the GCC demonstrates advantages over traditional measures such as Kendall, Pearson, and Spearman coefficients. We introduce two novel adaptations of this metric, enhancing its precision and broadening its applicability in the context of complex gene interactions. By applying the GCC to relevance networks, we show how different levels of the flexibility parameter reveal distinct patterns in gene interactions, capturing both linear and non-linear relationships. The maximum likelihood and Spearman-based estimators of the GCC offer a refined approach for disentangling the complexity of biological networks, with potential implications for precision medicine. Our methodology provides a powerful tool for constructing and interpreting relevance networks in biomedicine, supporting advancements in the understanding of biological interactions and healthcare research.
Optimized Energy Management Strategy for an Autonomous DC Microgrid Integrating PV/Wind/Battery/Diesel-Based Hybrid PSO-GA-LADRC Through SAPF
Authors: Ibrahim AL-Wesabi , Xu Jiazhu , Al-Shamma’a Abdullrahman A. , Farh Hassan M. Hussein , Aboudrar Imad , Oubail Youssef , Alaql Fahad , Alfraidi Walied
Published: November 2024

This study focuses on microgrid systems incorporating hybrid renewable energy sources (HRESs) with battery energy storage (BES), both essential for ensuring reliable and consistent operation in off-grid standalone systems. The proposed system includes solar energy, a wind energy source with a synchronous turbine, and BES. Hybrid particle swarm optimizer (PSO) and a genetic algorithm (GA) combined with active disturbance rejection control (ADRC) (PSO-GA-ADRC) are developed to regulate both the frequency and amplitude of the AC bus voltage via a load-side converter (LSC) under various operating conditions. This approach further enables efficient management of accessible generation and general consumption through a bidirectional battery-side converter (BSC). Additionally, the proposed method also enhances power quality across the AC link via mentoring the photovoltaic (PV) inverter to function as shunt active power filter (SAPF), providing the desired harmonic-current element to nonlinear local loads as well. Equipped with an extended state observer (ESO), the hybrid PSO-GA-ADRC provides efficient estimation of and compensation for disturbances such as modeling errors and parameter fluctuations, providing a stable control solution for interior voltage and current control loops. The positive results from hardware-in-the-loop (HIL) experimental results confirm the effectiveness and robustness of this control strategy in maintaining stable voltage and current in real-world scenarios.
Ochratoxin A in Poultry Supply Chain: Overview of Feed Occurrence, Carry-Over, and Pathognomonic Lesions in Target Organs to Promote Food Safety
Authors: Bonerba Elisabetta , Manfredi Alessio , Dimuccio Michela Maria , Lorusso Patrizio , Pandiscia Annamaria , Terio Valentina , Di Pinto Angela , Panseri Sara , Ceci Edmondo , Bozzo Giancarlo
Published: November 2024

Ochratoxin A (OTA) is a mycotoxin produced by fungi species belonging to the genera Aspergillus spp. and Penicillium spp. The proliferation of OTA-producing fungal species may occur due to inadequate practices during both the pre-harvest and post-harvest stages of feed. Consequently, poultry species may be exposed to high concentrations of this mycotoxin that can be transferred to animal tissues due to its carry-over, reaching dangerous concentrations in meat and meat products. Therefore, this review aims to propose a comprehensive overview of the effects of OTA on human health, along with data from global studies on the prevalence and concentrations of this mycotoxin in avian feeds, as well as in poultry meat, edible offal, and eggs. Moreover, the review examines significant gross and histopathological lesions in the kidneys and livers of poultry linked to OTA exposure. Finally, the key methods for OTA prevention and decontamination of feed are described.
Complete Improvement of Severe Forearm Complex Regional Pain Syndrome with Six High-Dose Incobotulinumtoxin A Injections: Clinical Implications with Respect to the Literature
Authors: Hefter Harald , Moll Marek , Samadzadeh Sara
Published: November 2024

There is some evidence that injections of botulinum neurotoxin effectively reduce pain in complex regional pain syndromes (CRPSs). But no or little experience appears to exist for the application of incobotulinum neurotoxin type A (incoBoNT/A) in complex pain disorders. Here, a case of CRPS type I, characterized by severe symptoms in the left forearm is presented, showed significant continuous improvement following a series of six repetitive (painful) injections into the finger, hand, and forearm muscles of incoBoNT/A every 3 months, administered at declining doses varying between 500 and 100 U. Remarkably, this treatment regimen led to the complete resolution of pain, vaso- and sudomotor symptoms, and hand dystonia. This highlights the possible efficacy of incoBoNT/A in the treatment of CRPS and encourages the further exploration of incoBoNT/A’s role in the successful management of complex pain disorders.
Why an Integrated Approach to Tick-Borne Pathogens (Bacterial, Viral, and Parasitic) Is Important in the Diagnosis of Clinical Cases
Authors: Contreras-Ferro Raúl , Trueba Jorge Martín , Sánchez-Mora Patricia , Escudero Raquel , Sánchez-Seco María Paz , Montero Estrella , Negredo Anabel , González Luis Miguel , Dashti Alejandro , Llorente María Teresa , Gil-Zamorano Judit , Vázquez Ana , Jado Isabel , González-Barrio David
Published: November 2024

Tick-borne diseases have emerged as a major global public health problem in recent decades. The increasing incidence and geographical dissemination of these diseases requires the implementation of robust surveillance systems to monitor their prevalence, distribution, and public health impact. It is therefore not unexpected that tick-borne pathogens coexist in the same vectors, but the interactions of these agents between vectors and vertebrate hosts, including humans, remain poorly understood. The impact of infection in humans extends to the diagnostic challenges that arise when the same symptomatology can be associated with any tick-borne pathogen, and therapeutic recommendations only focus on the major or best-known tick-borne diseases, ignoring other lesser-known or less prevalent infections. Both surveillance systems and the holistic diagnosis of tick-borne pathogens are necessary tools to address the emergence of vector-borne diseases. In this study, we will focus on the main tick-borne viral, bacterial, and parasitic diseases in Spain to reflect the need to establish syndromic diagnostics in samples from patients with a history of tick bites and symptomatology compatible with them. On the other hand, and highlighting this need, innovations in molecular techniques, syndromic surveillance, and surveillance programs for ticks and tick-borne pathogens with public health implications are expected to be developed.
Knowledge, Attitude, and Practice of Healthcare Providers Towards Preventive Chemotherapy Neglected Tropical Diseases in the Forécariah Health District, Guinea, 2022
Authors: Diallo Fatoumata Diaraye , Millimouno Tamba Mina , Manet Hawa , Kamano Armand Saloum , Camara Emmanuel , Camara Bienvenu Salim , Delamou Alexandre
Published: November 2024

Background: Neglected tropical diseases (NTDs) are a diverse group of twenty diseases that occur in tropical and subtropical regions that particularly affect vulnerable and often marginalised populations. Five of these are classified as “preventive chemotherapy” (PC) diseases such as trachoma, onchocerciasis, geo-helminthiasis, lymphatic filariasis, and schistosomiasis. This study aimed to describe the knowledge, attitudes, and practices of healthcare providers in the Forecariah health district with respect to PC-NTDs in Guinea in 2022. Methods: A descriptive cross-sectional study was conducted from 7 to 22 November 2022 among healthcare providers in the health district of Forécariah in Guinea. Data on participants’ socio-demographic characteristics and knowledge of and attitudes and practices regarding PC-NTDs were collected using an electronic (KoboToolbox) semi-structured questionnaire and analysed using descriptive statistics. Results: Among the 86 healthcare providers who participated in this study, nurses (44.2%) and young adults aged between 25 and 49 years (81.4%) were mostly represented. The majority of respondents declared having already heard about onchocerciasis (70.7%) and lymphatic filariasis (60.0%) but only the minority declared having already heard about geo-helminthiasis (30.7%), schistosomiasis (21.3%), and trachoma (9.3%). Only a few respondents knew how to prevent PC-NTDs (onchocerciasis 26.7%, lymphatic filariasis 26.7%, geo-helminthiasis 29.3%, and schistosomiasis 17.3%). Many healthcare providers reported they would refer cases of onchocerciasis (50.6%), lymphatic filariasis (58.7%), and schistosomiasis (46.7%) to a management centre. Conclusions: This study highlights the varying levels of knowledge, attitudes, and practices among healthcare providers in dealing with PC-NTDs, suggesting areas for improvement in training and resource allocation.
Characterization of HTLV-1 Infectious Molecular Clone Isolated from Patient with HAM/TSP and Immortalization of Human Primary T-Cell Lines
Authors: Bellon Marcia , Jain Pooja , Nicot Christophe
Published: November 2024

Human T-cell leukemia virus (HTLV-1) is the etiological agent of lymphoproliferative diseases such as adult T-cell leukemia and T-cell lymphoma (ATL) and a neurodegenerative disease known as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). While several molecular clones of HTLV-1 have been published, all were isolated from samples derived from patients with adult T-cell leukemia. Here, we report the characterization of an HTLV-1 infectious molecular clone isolated from a sample of a patient with HAM/TSP disease. Genetic comparative analyses of the HAM/TSP molecular clone (pBST) revealed unique genetic alterations and specific viral mRNA expression patterns. Interestingly, our clone also harbors characteristics previously published to favor the development of HAM/TSP disease. The molecular clone is capable of infection and immortalization of human primary T cells in vitro. Our studies further demonstrate that the HTLV-1 virus produced from primary T cells transfected with pBST or ACH molecular clones cannot sustain long-term expansion, and cells cease to proliferate after 3–4 months in culture. In contrast, long-term proliferation and immortalization were achieved if the virus was transmitted from dendritic cells to primary T cells, and secondary infection of 729B cells in vitro was demonstrated. In both primary T cells and 729B cells, pBST and ACH were latent, and only hbz viral RNA was detected. This study suggests that HTLV-1 transmission from DC to T cells favors the immortalization of latently infected cells.
The Emergence of Saliva as a Diagnostic and Prognostic Tool for Viral Infections
Authors: Oliveira Neto Nilson Ferreira de , Caixeta Rafael Antônio Velôso , Zerbinati Rodrigo Melim , Zarpellon Amanda Caroline , Caetano Matheus Willian , Pallos Debora , Junges Roger , Costa André Luiz Ferreira , Aitken-Saavedra Juan , Giannecchini Simone , Braz-Silva Paulo Henrique
Published: November 2024

Saliva has emerged as a promising diagnostic fluid for viral infections, enabling the direct analysis of viral genetic material and the detection of infection markers such as proteins, metabolites, microRNAs, and immunoglobulins. This comprehensive review aimed to explore the use of saliva as a diagnostic tool for viral infections, emphasizing its advantages and limitations. Saliva stands out due to its simplicity and safety in collection, along with the convenience of self-collection without the need for healthcare supervision, while potentially being comparable to urine and blood in terms of effectiveness. Herein, we highlighted the significant potential of saliva in assessing viral loads and diagnosing viral infections, such as herpesviruses, HPV, PyV, TTV, SARS-CoV-2, and MPXV. The detection of viral shedding in saliva underscores its utility in early diagnosis, the monitoring of infection progression, and evaluating treatment responses. The non-invasive nature of saliva collection makes it an appealing alternative to more invasive methods, promoting better patient compliance and facilitating large-scale screening and surveillance. As such, we further highlight current evidence on the use of saliva as a prognostic tool. Although a significant amount of data is already available, further investigations are warranted to more comprehensively assess the added benefit from the utilization of salivary biomarkers in the clinics. Salivary biomarkers show great promise for the early detection and prevention of viral infection complications, potentially improving disease management and control at the population level. Integrating these non-invasive tools into routine clinical practice could enhance personalized healthcare strategies and patient outcomes. Future studies should focus on establishing standardization protocols, validating the accuracy of salivary diagnostics, and expanding clinical research to enhance the diagnostic and monitoring capabilities of salivary biomarkers.
Efficacy of Feed-Based Genome-Free Bacterial Vaccine Against Aeromonas hydrophila Infection in Red Tilapia (Oreochromis sp.)
Authors: Ali Nur Shidaa Mohd , Ngalimat Mohamad Syazwan , Lim Boon Chuan , Hsu Chia-Chen , Salleh Annas , Nazarudin Muhammad Farhan , Yasin Ina Salwany Md , Azmai Mohammad Noor Amal
Published: November 2024

Aeromonas hydrophila causes motile Aeromonas septicemia (MAS), a disease with a high mortality rate in tilapia culture. Feed-based vaccines with the incorporation of inactivated whole-cell bacteria into the feed offer promising tools to control MAS. Currently, the incorporation of genome-free bacteria as bacterial vaccine through the implementation of SimCells® technology into the feed has become a particular interest. Background/Objectives: This study investigates the efficacy of a feed-based vaccine incorporating genome-free A. hydrophila (FBV-GFAH) against MAS infection in red tilapia. Methods: The vaccine was prepared and delivered at 5% fish body weight for three consecutive days in weeks 0 (prime vaccination) and 2 (first booster vaccination), orally. Throughout a five-week experimental period, the immune-related genes (IL-1β, MHC-II, CD4, IgT, and IgM) expression in the hindgut and head kidney of the fish was determined using RT-qPCR assay. Lysozyme (serum) and overall IgM (serum, gut lavage, and skin mucus) productions were also detected. Results: Fish vaccinated with FBV-GFAH showed a significant (p ≤ 0.05) improvement in relative percent survival compared with unvaccinated fish following bacterial challenge. FBV-GFAH induced the expression of immune-related genes in the hindgut and head kidney, especially after booster vaccination. Furthermore, serum lysozyme activity and overall IgM production in serum, skin mucus, and gut lavage were also significantly (p ≤ 0.05) improved in the FBV-GFAH vaccinated fish than the unvaccinated fish. Conclusions: This study showed that FBV-GFAH is a promising feed-based vaccine technology to control MAS in cultured tilapia.
An Outbreak of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) in a German Boar Stud: A Retrospective Analysis of PRRSV Shedding in Boar Semen
Authors: Aundrup Jakob , Lüken Caroline , Heenemann Kristin , Vahlenkamp Thomas W. , Hennig-Pauka Isabel
Published: November 2024

The porcine reproductive and respiratory syndrome virus (PRRSV) causes high economical costs due to reduced productivity and losses in pig production. The virus can infect sow herds through various routes. One possible risk factor is the transmission of PRRSV through artificial insemination with infected boar semen. For these reasons, conventional boar studs should be closely monitored to detect an outbreak of PRRSV at an early stage. In the presented retrospective study, 2184 fresh semen samples from 336 boars were investigated (RT-qPCR) after an accidental PRRSV introduction to the herd. Hence, the different shedding profiles of PRRSV via semen resulted in 42.2% where no virus was detected, 2.0% intermittent shedding, and 8.4% permanent shedding. The duration of viral shedding varies from 2 days to 83 days post outbreak (on average 33 days). A significant impact of breed on PRRSV shedding duration could not be shown. Also, the distribution of the shedding profile does not follow a consistent mode, indicating that not every boar is shedding the virus via semen.
Evaluation of the Impact of Recycled Distillery Effluent on the Cultivation of Wheat and Sorghum
Authors: Huang Chi-Hsuan , Chiang Li-Chi , Liao Ci-Jyun , Chen Feng-Wen
Published: November 2024

With increasing global water scarcity, the reuse of treated wastewater for agricultural irrigation offers a promising solution, particularly in arid regions. This study evaluates the impact of distillery wastewater from Kinmen Kaoliang Liquor Inc. (KKL) on the growth of wheat and sorghum in the Kinmen region. The field experiment applied varying proportions of KKL wastewater to assess its effects on soil properties, nutrient distribution, and crop performance. The results showed that wastewater irrigation increased soil concentrations of key nutrients, such as potassium (K), sodium (Na), magnesium (Mg), and phosphorus (P), but also raised the electrical conductivity (EC) and sodium adsorption ratio (SAR) beyond acceptable irrigation standards. K, Mg, Ca, and P primarily accumulated in the stems and grains, while Na was concentrated in the roots. However, higher wastewater concentrations negatively affected soil permeability due to Na accumulation, and elevated salinity levels led to reduced plant biomass. This study concludes that although wastewater irrigation improves nutrient availability, careful management is essential to mitigate salinity risks and ensure sustainable agricultural practices. These findings offer valuable insights into the potential of wastewater reuse in water-scarce regions and provide practical recommendations for managing associated risks.