bluuebunny/crossref_metadata_2025 huggingface dataset:
Barriers to the adoption of open-pollinated varieties in the organic farming sector: a case study of small-scale vegetable production in France
Authors: Antier Clémentine , Baret Philippe V.
Published: February 2025

Seeds are a critical, influential element of agricultural production and sustainability. The European organic farming sector has specific standards and targets regarding its seed supply. Ideally, seeds should be grown organically, participate in the conservation of biodiversity, contribute to the autonomy of farmers, and be bred into reproducible cultivars. Inbred lines and open-pollinated varieties, along with organic heterogeneous material, fit with this criterion. In a case study of small-scale vegetable production in the South-East of France, we analyze the gap between the organic sector’s seed standards regarding reproducibility and their actual implementation when farmers buy seeds. The data were collected through a focus group and interviews of 15 farmers and seven other actors of the organic vegetable value chain. While all farmers of the sample consider open-pollinated varieties more aligned with the principles of organic agriculture and peasant farming, their perception of the operational relevance of the OP varieties currently available in seed companies’ catalogues varies and leads to contrasted varietal choices. Perceived advantages of OP varieties over hybrids include ethical and hedonic aspects along with context-specific technical advantages. On the other hand, the listed advantages of hybrid varieties are mostly about productivity, disease resistance and access to technical recommendations. This paper discusses how the technical, economic, educational, and social contexts influence farmers’ seed choices of hybrids versus open-pollinated varieties. We highlight 11 barriers to the adoption and use of open-pollinated varieties. These barriers are present in the seed market, at the farm level, as well as in the education and extension sectors. Our findings suggest that activating various levers is needed to make it more feasible for organic farmers to choose open-pollinated varieties. These findings call for further assessment of the conditions required for the adoption of reproducible varieties in a wider range of organic farming contexts across Europe.
Characterization and Effects of Floor Impact Sound in Residential Buildings: A Systematic Review
Authors: Zou Yuying , Liu Mengjin , Ma Hui
Published: February 2025

The lightweight development trend of modern residential structures reduces sound attenuation in buildings and makes sound propagation paths more complex. Neighbor-induced impact sound has become a significant source of residents’ dissatisfaction with the acoustic environment. To gain a deeper understanding of the characteristics of residential impact sound, reduce its impact on users, and improve the quality of residential buildings, a systematic review of existing research based on PRISMA2020 was carried out. Articles indexed in the Web of Science core dataset and Scopus were searched, with a cutoff date of October 2024. After screening and reviewing, 132 articles were systematically analyzed, categorizing the research on floor impact sound into four aspects, namely impact sound sources, evaluation indicators, prediction methods, and improvement measures. The results show that due to the diversity of real sound sources and differences in living habits, the standard impact sound sources in different countries or regions still need further study. Both subjective and objective evaluations indicate that heavyweight impact sound, particularly low-frequency sound, has the greatest impact on occupants and is the most difficult to eliminate. The physical characteristics of floor impact sound can be predicted using methods such as finite element analysis. However, there are fewer prediction methods for subjective evaluations due to the poor correlation between subjective and objective evaluation indicators. Though different soundproofing measures significantly improve the sound insulation of impact sound, they are still not widely applied due to materials, construction techniques, and time and economic costs. This study provides a reference for research on residential impact sound in China and offers an outlook for future research directions.
Numerical Simulation of Self-Sustained Roll Oscillations of an 80-Degree Delta Wing Caused by Leading-Edge Vortices
Authors: Sereez Mohamed , Goman Mikhail , Abramov Nikolay , Lambert Caroline
Published: February 2025

Numerical simulations of an 80-degree delta wing in free-to-roll motion are performed by applying the dynamic fluid–body interaction (DFBI) model and the overlap/chimera method using the URANS equations. The capabilities of modern computational fluid dynamics methods for predicting wing-rock phenomena over a wide range of angles of attack at low Mach numbers and strong wing–vortex interaction, including the vortex breakdown phenomenon, were investigated by comparing simulation results with wind tunnel test data. At low angles of attack, delays in the strength and position of the leading-edge vortices above the wing have a destabilizing effect on it, leading to the emergence of self-sustained limit-cycle oscillations. At high angles of attack, where vortex breakdown occurs, the available wind tunnel data show that there are two modes of wing self-oscillations in free-to-roll motion, namely, regular large-amplitude oscillations and irregular small-amplitude oscillations, where the excitation of the latter mode depends on the angle of attack and the initial roll angle of the wing motion. The performed numerical simulation also shows the existence of these two self-oscillatory modes in roll, qualitatively and quantitatively matching the experimental data.
Finite-Time Control for Satellite Formation Reconfiguration and Maintenance in LEO: A Nonlinear Lyapunov-Based SDDRE Approach
Authors: Bakhtiari Majid , Panahyazdan Amirhossein , Abbasali Ehsan
Published: February 2025

This paper introduces a nonlinear Lyapunov-based Finite-Time State-Dependent Differential Riccati Equation (FT-SDDRE) control scheme, considering actuator saturation constraints and ensuring that the control system operates within safe operational limits designed for satellite reconfiguration and formation-keeping in low Earth orbit (LEO) missions. This control approach addresses the challenges of reaching the relative position and velocity vectors within a defined timeframe amid various orbital perturbations. The proposed approach guarantees precise formation control by utilizing a high-fidelity relative motion model that incorporates all zonal harmonics and atmospheric drag, which are the primary environmental disturbances in LEO. Additionally, the article presents an optimization methodology to determine the most efficient State-Dependent Coefficient (SDC) form regarding fuel consumption. This optimization process minimizes energy usage through a hybrid genetic algorithm and simulated annealing (HGASA), resulting in improved performance. In addition, this paper includes a sensitivity analysis to identify the optimized SDC parameterization for different satellite reconfiguration maneuvers. These maneuvers encompass radial, along-track, and cross-track adjustments, each with varying baseline distances. The analysis provides insights into how different parameterizations affect reconfiguration performance, ensuring precise and efficient control for each type of maneuver. The finite-time controller proposed here is benchmarked against other forms of SDRE controllers, showing reduced error margins. To further assess the control system’s effectiveness, an input saturation constraint is integrated, ensuring that the control system operates within safe operational limits, ultimately leading to the successful execution of the mission.
Model Predictive Control of Adaptive Irrigation Decisions Incorporating Rainfall Intensity and Soil Properties
Authors: Liu Ao , Zhao Dongbao , Wei Yichang
Published: February 2025

To mitigate the loss of surface runoff and deep percolation in the water-scarce area and enhance the utilization of rainfall resources, this study adaptively determines the soil water content threshold triggering such losses by incorporating rainfall intensity (RI) and soil properties (SP) based on the model predictive control (MPC) framework. These thresholds then serve as the target soil water content before rainfall, and a model predictive control incorporating RI and SP (RISPMPC) irrigation decision-making is proposed. We conducted irrigation simulation experiments in Ya’an City, Sichuan Province, across four RI levels and six soil texture types. The results were compared with those obtained from conventional model predictive control (CMPC), rule-based closed-loop irrigation decision (RBC), and a newly developed zone-based model predictive control (ZMPC). Results demonstrate that RISPMPC enhances the utilization of rainfall resources across different scenarios. In soils with strong infiltration capabilities, such as loamy sand, loam, and clay loam, RISPMPC reduces irrigation water use by 26%, 5%, and 3% compared to RBC, CMPC, and ZMPC, respectively. In contrast, for soils with poor infiltration capabilities, including silty soil, clay A, and clay B, RISPMPC’s water-saving efficiency strongly correlates with rainfall intensity levels, achieving maximum savings of 61%, 36%, and 34% compared to the same three methods. Furthermore, in all cases, RISPMPC demonstrates the highest maximum effective rainfall utilization rate (MERU). As soil infiltration capability decreases and rainfall intensity increases, the MERU gap between RISPMPC and the other three methods widens significantly, underscoring RISPMPC’s robustness in environments where rainwater utilization is challenging. Therefore, RISPMPC can improve the utilization efficiency of rainwater resources and effectively alleviate agricultural water scarcity issues.
Agricultural Non-Point Source Pollution: Comprehensive Analysis of Sources and Assessment Methods
Authors: Hussain Fida , Ahmed Shakeel , Muhammad Zaigham Abbas Naqvi Syed , Awais Muhammad , Zhang Yanyan , Zhang Hao , Raghavan Vijaya , Zang Yiheng , Zhao Guoqing , Hu Jiandong
Published: February 2025

Agricultural non-point source pollution (ANPSP) significantly affects worldwide water quality, soil integrity, and ecosystems. Primary factors are nutrient runoff, pesticide leaching, and inadequate livestock waste management. Nonetheless, a thorough assessment of ANPSP sources and efficient control techniques is still lacking. This research delineates the origins and present state of ANPSP, emphasizing its influence on agricultural practices, livestock, and rural waste management. It assesses current evaluation models, encompassing field- and watershed-scale methodologies, and investigates novel technologies such as Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) that possess the potential to enhance pollution monitoring and predictive precision. The research examines strategies designed to alleviate ANPSP, such as sustainable agricultural practices, fertilizer reduction, and waste management technology, highlighting the necessity for integrated, real-time monitoring systems. This report presents a comprehensive analysis of current tactics, finds significant gaps, and offers recommendations for enhancing both research and policy initiatives to tackle ANPSP and foster sustainable farming practices.
Projected Bioclimatic Changes in Portugal: Assessing Maize Future Suitability
Authors: Soares Daniela , Paredes Paula , Paço Teresa A. , Rolim João
Published: February 2025

In Portugal, maize is a major crop, occupying about 40% of the cereals area. The present study aimed to assess future bioclimatic conditions that could affect maize production in Portugal. For this purpose, a set of indicators was selected including dry spells (DSs) and the aridity index (AI). Two additional indicators were included, one related to the soil water reservoir available for maize (RAW) and the other related to the maize thermal unit (MTU), which were designed to assess the suitability of land for growing different varieties of maize. The analysis focused on historical (1971–2000) and future (2011–2070; 2041–2070; 2071–2100) climate scenarios (RCP4.5 and RCP8.5) using a four-member ensemble of global climate models. The results for the more distant and severe scenario suggest that there will be an overall increasing tendency in the AI, i.e., higher aridity, namely in the southern part of Portugal compared to the north (0.65 vs. 0.45). The soils in the south are characterized by a lower average RAW (<35 mm) than in the north (>50 mm), which leads to a lower irrigation frequency requirement in the north. As a result of the increased MTU, maize production will shift, allowing for varieties with higher thermal requirements and the conversion of areas traditionally used for silage maize to grain maize production areas. Adaptation measures to improve the climate resilience of maize are discussed.
Phytoremediation of Total Petroleum Hydrocarbons-Contaminated Soils: Case Study of Jerusalem Artichokes with Cost Analysis and Biomass Conversion
Authors: Rubežius Mantas , Kidikas Žygimantas , Kick Christopher , Kasiulienė Alfreda
Published: February 2025

The application of environmentally friendly technologies, such as phytoremediation, for contaminated soil remediation and biofuel generation should be one of the goals of sustainable development. Phytoremediation is based on the use of plants and their associated microorganisms to clean contaminated soils, resulting in a positive impact on the environment and the production of biomass that can be utilized for biofuel production. Combining phytoremediation with advanced thermochemical conversion technologies like thermo-catalytic reforming process (TCR) allows for the production of high-quality biochar, bio-oil comparable to fossil crude oil, and hydrogen-rich syngas. This study presents a full-scale phytoremediation experiment conducted at a former oil storage site using energy crops like Jerusalem artichokes (Helianthus tuberosus), where the biomass was later converted into biofuel and other by-products using lab-scale technology. Significant and promising results were obtained: (i) within two years, the initial total petroleum hydrocarbons (TPH) contamination level (698 mg/kg) was reduced to a permissible level (146 mg/kg); (ii) the yield of the harvested Jerusalem artichoke biomass reached 18.3 t/ha dry weight; (iii) the thermochemical conversion produced high-quality products, such as a thermally stable oil a higher heating value (HHV) of 33.85 MJ/kg; (iv) the two-year phytoremediation costs for the rejuvenated soil amounted to3.75 EUR/t.
A Preliminary Study on the Use of Remote Sensing Techniques to Determine the Nutritional Status and Productivity of Oats on Spatially Variable Sandy Soils
Authors: Franz Aleksandra , Sowiński Józef , Głogowski Arkadiusz , Fiałkiewicz Wieslaw
Published: February 2025

Field studies and satellite imagery were conducted on an oat cultivation field located on sandy soil with significant spatial heterogeneity in southwestern Poland. Observations and field measurements were carried out during the BBCH growth stages 12, 31, 49, 77, and 99 at 40 points each. Satellite images were acquired at specific intervals, and selected remote sensing indices (NDVI, GNDVI, SAVI, EVI, NDMI, MCARI) were calculated to investigate possibility of early detection of nitrogen demand at the early stage of oat development. The results of this study confirmed that sandy soils, characterized by limited water and nutrient capacity, require a specialized approach to resource management. The selected remote sensing indices provided an effective method for monitoring oat canopy variability in real time. At BBCH 12 growing stage, the highest correlations with plant density were shown by NDVI, SAVI, GNDVI, and EVI. The correlation coefficients ranged from 0.38 to 0.56, with a significance level of ≤0.01, which indicates their usefulness for monitoring crop emergency and early development. At early growing stage (BBCH 31–34), GNDVI was significantly correlated with the final nitrogen uptake (r = 0.44, p < 0.01) and biomass yield of oat (r = 0.39, p = 0.01). This suggests that the GNDVI index is particularly useful for predicting the final nitrogen uptake and biomass yield of oat. It offers a reliable estimation of the plant’s nitrogen status and its potential for nitrogen absorption, allowing for fertilization management at this critical stage.
Histochemical and Immunohistochemical Evaluation of the Effects of a Low-Input Diet on Different Chicken Breeds
Authors: Fonsatti Elisa , Bortoletti Martina , Birolo Marco , Bordignon Francesco , Xiccato Gerolamo , Trocino Angela , Bertotto Daniela , Vascellari Marta , Radaelli Giuseppe , Ballarin Cristina
Published: February 2025

Reducing the environmental impact of poultry farming aligns with the European Green Deal’s goal of climate neutrality and sustainable food production. Local chicken breeds and low-input diets are promising strategies to achieve this goal. This study evaluated the effects of diet (standard vs. low-input, formulated with reduced soybean meal in favour of local ingredients) on the morphological characteristics of the jejunum in fast-growing chickens (Ross 308), local breeds (Bionda piemontese, BP; Robusta maculata, RM), and their crosses with Sasso (SA) hens (BP × SA, RM × SA). Histological samples from the jejunum were collected at slaughter (47 days for Ross 308, 105 days for others). Jejunal morphology was assessed focusing on villi height, crypt depth, goblet cell density, and immune markers (CD3+ and CD45+ cells). Local breeds, particularly RM, exhibited superior villus height-to-crypt depth ratios, related to better nutrient absorption compared to fast-growing genotypes. Ross chickens had higher goblet cell densities, reflecting greater sensitivity to environmental stress. Although the low-input diet reduced villi height and villus-to-crypt ratio, it tended to increase CD3+ cell density. These effects may be ascribed to the replacement of soybeans with fava beans and their antinutritional factors. These findings highlight the resilience of local breeds to dietary changes, supporting their suitability for alternative poultry production systems.
Immunohistochemical Characterization of Feline Giant Cell Tumor of Bone (GCTb): What We Know and What We Can Learn from the Human Counterpart
Authors: Porcellato Ilaria , Giglia Giuseppe , Leonardi Leonardo
Published: February 2025

Giant cell tumor of bone (GCTb), formerly also known as osteoclastoma, is a pathological entity that in veterinary medicine is still undefined and, probably, underdiagnosed. In humans, GCTb is recognized as a primary benign bone tumor, locally aggressive, with high local recurrence rates, with controversial histogenesis that can rarely progress or present as a malignant form. In pets, this tumor is still considered rare, though the possibility of underdiagnosis is significant. Hence, the aim of the present study is to provide a histological and immunohistochemical characterization of a small case series of presumptive feline GCTb, comparing our results to the data reported for the human counterpart. Searching our archive, we found, from 2010 to 2023, only three diagnosed cases of GCTb from domestic cats (felis catus). After diagnosis revision, the samples were submitted to immunohistochemistry for Iba1, TRAP, SATB2, RUNX2, RANK, karyopherin α2 (KPNA-2), and osteocalcin. Ki-67 index was also evaluated. Results showed that the multinucleated giant cells were positive for Iba1, TRAP, and RANK, accounting for their osteoclastic origin. On the other side, mononuclear cells were mostly positive for osteoblast markers such as RUNX2, SATB2, and KPNA-2, whereas tumor-associated macrophages showed positivity for Iba1. Hence, results on the cell types characterizing the feline GCTb were comparable to those described in the human form of the tumor. Currently, diagnostic criteria for GCTBs in cats and, in domestic animals more broadly, are still lacking. This study provides valuable data into the immunohistochemical characteristics of the cell populations in feline GCTBs, enhancing veterinarians’ and pathologists’ knowledge for its diagnosis, ultimately improving patient care. Larger case series, complete with follow-up information, molecular analyses for specific mutations, and imaging of both tumors and patients, are needed to improve identification and achieve greater sensitivity in diagnosing this unique tumor.
The Impact of SGLT-2 Inhibitors on Hydroxyl Radical Markers and Diabetic Neuropathy: A Short-Term Clinical Study
Authors: Klabuzai Ágnes , Bekő Viktória , Sütő Zsófia , Horváth Marcell , Wágner Zoltán , Vágási Katalin , Pfeil Veronika , Süle Miklós , Grosz György , Wittmann István , Kun Szilárd
Published: February 2025

Beyond their metabolic effect, sodium–glucose cotransporter-2 (SGLT-2) inhibitors reduce the risk of heart failure and have cardiovascular and nephroprotective effects, yet their exact mechanism of action remains unclear. This prospective study included 40 patients with type 2 diabetes whose physician initiated SGLT-2 inhibitor therapy. Prior to and 4 weeks after the initiation of SGLT-2 inhibitors, in addition to routine clinical and laboratory measurements, hydroxyl free radical and neuropathic evaluations were performed. Body weight, body mass index (BMI), fasting glucose, fructosamine, and albuminuria decreased significantly, whereas red blood cell (RBC) count, hemoglobin, hematocrit, mean corpuscular volume (MCV), and platelet count increased significantly. Urinary o-tyrosine/p-tyrosine and (m-tyrosine+o-tyrosine)/p-tyrosine ratios were significantly reduced, suggesting diminished hydroxyl free radical production. Patients with neuropathy, identified by abnormal baseline current perception threshold (CPT) values, showed significant improvements. Significant correlations between RBCs, platelet parameters, albuminuria, and hydroxyl free radical markers disappeared after SGLT-2 treatment and changes in hydroxyl free radical markers correlated positively with CPT changes. Our results suggest that short-term SGLT-2 inhibition recalibrates metabolic, hematologic, renal, and neuropathic endpoints simultaneously, presumably through attenuating abnormal ortho- and meta-tyrosine incorporation into signaling proteins. Further studies are required to confirm long-term durability and examine whether additional strategies, such as supplementation of the physiological p-tyrosine, could amplify these benefits.
diAcCA, a Pro-Drug for Carnosic Acid That Activates the Nrf2 Transcriptional Pathway, Shows Efficacy in the 5xFAD Transgenic Mouse Model of Alzheimer’s Disease
Authors: Banerjee Piu , Wang Yubo , Carnevale Lauren N. , Patel Parth , Raspur Charlene K , Tran Nancy , Zhang Xu , Natarajan Ravi , Roberts Amanda J. , Baran Phil S. , Lipton Stuart A.
Published: February 2025

The antioxidant/anti-inflammatory compound carnosic acid (CA) is a phenolic diterpene found in the herbs rosemary and sage. Upon activation, CA manifests electrophilic properties to stimulate the Nrf2 transcriptional pathway via reaction with Keap1. However, purified CA is readily oxidized and thus highly unstable. To develop CA as an Alzheimer’s disease (AD) therapeutic, we synthesized pro-drug derivatives, among which the di-acetylated form (diAcCA) showed excellent drug-like properties. diAcCA converted to CA in the stomach prior to absorption into the bloodstream, and exhibited improved stability and bioavailability as well as comparable pharmacokinetics (PK) and efficacy to CA. To test the efficacy of diAcCA in AD transgenic mice, 5xFAD mice (or littermate controls) received the drug for 3 months, followed by behavioral and immunohistochemical studies. Notably, in addition to amyloid plaques and tau tangles, a hallmark of human AD is synapse loss, a major correlate to cognitive decline. The 5xFAD animals receiving diAcCA displayed synaptic rescue on immunohistochemical analysis accompanied by improved learning and memory in the water maze test. Treatment with diAcCA reduced astrocytic and microglial inflammation, amyloid plaque formation, and phospho-tau neuritic aggregates. In toxicity studies, diAcCA was as safe or safer than CA, which is listed by the FDA as “generally regarded as safe”, indicating diAcCA is suitable for human clinical trials in AD.
Modeling and Reliability Evaluation of the Motion and Fluid Flow Characteristics of Spark Bubbles in a Tube
Authors: Gou Yuxin , Shi Dongyan , Wang Jiuqiang
Published: February 2025

Bubbles in pipes are widely present in marine engineering, transmission, and fluid systems with complex environments. This paper divides tubes into short, longer, and long tubes due to different lengths. In short tubes, the formation, development, and stability of spark bubbles are deeply analyzed through numerical simulation and experimental measurement, and the morphology and period of vortex rings generated in the surrounding fluid are studied. The results show that bubbles in tubes are significantly elongated compared with those in free fields. Changing the parameters of tubes can affect the size and oscillation speed of vortex rings. Secondary cavitation is found in asymmetric positions in longer tubes. The conditions, positions, and periods of multiple secondary cavitations are summarized in a series of experiments on long tubes. It is found that bubbles in tubes are related to the γt and γL tube parameters. More secondary cavitation is easily generated in thinner and longer tubes. In addition, the pumping effect brought about by the movement of bubbles in tubes is studied. By designing reasonable tube parameters, the life cycle of bubbles can be changed, and the pumping efficiency can be improved. This study provides important theoretical support for the reliability of the movement of bubbles and surrounding fluid in tubes and lays a foundation for the optimization and promotion of this technology in practical applications.
Human Health Risk Associated with As, Cu, Pb, and Zn in Soils of the Aconcagua and Casablanca River Basins, Valparaíso Region, Chile
Authors: Bech Jaume , Pradenas Daniela , Tume Pedro , Cornejo Óscar , Pedreros Javiera , Toledo Sofía , Correa Claudio , Sepúlveda Bernardo , Roca Núria
Published: February 2025

Chile is an important producer of copper, and it has serious soil contamination problems, mainly related to mining activities. A typical example is the Aconcagua River basin, which has been the scene of large-scale mining operations throughout history, making it critical to analyze due to the high concentrations of heavy metals in its soils. The objectives of this study are (1) to assess the level of As, Cu, Pb, and Zn contamination in the surface soil ecosystem based on different environmental indexes and (2) to determine the health risks of adults and children located in watersheds of the Aconcagua and Casablanca Rivers. A database of the Aconcagua River and Casablanca River basins is used to achieve the objectives. From the Aconcagua River basin, 20 topsoil samples from agricultural sectors without mining activity and 127 topsoil samples from sectors with mining activity were selected. On the other hand, thirty-five topsoil samples of the Casablanca River basin, without mining activity, were analyzed. The evaluation of soil contamination was done using environmental indexes. Finally, carcinogenic and noncarcinogenic risks to humans were calculated using the USEPA model. The mean concentration of chemical elements in the Aconcagua River basin for samples without mining presence was As 10.55 mg kg−1, Cu 85.75 mg kg−1, Pb 26.65 mg kg−1, and Zn 139.5 mg kg−1. The correlations show that the elements As, Cu, Pb, and Zn come from anthropogenic sources, which are also enhanced by the geogenic origin of Cu and Zn. The spatial distribution of the analyzed elements shows a spatial pattern that extends across industrial areas and emission sources, with higher concentrations of As, Cu, Pb, and Zn identified near mining areas of the Aconcagua River basin. The upper limit of the geogenic values determined by the MAD (median absolute deviation) method for the Aconcagua River basin without mining presence was 14.5 mg kg−1 for As, 94 mg kg−1 for Cu, 37.5 mg kg−1 for Pb, and 194 mg kg−1 for Zn. Finally, the geoaccumulation index, contamination factor, integrated contamination index, and potential ecological risk registered exceptionally high contamination in some soil samples, especially in areas with mining influence. It is essential to highlight that there are non-carcinogenic risks related to As, Cu, and Pb, a hazard quotient (HQ) higher than 1, and acceptable carcinogenic risks between 1.0 × 10−6 and 1.0 × 10−4 to As and Pb in children and adults in the Aconcagua River basin.
Characteristics Evaluation and Coordinated Control Strategy of Power-Electronics-Based MMC-HVDC Systems Connected with Wind Farms
Authors: Xu Lin , Liu Chang , Zhang Jingyi , Tian Zhen , Feng Pan , Huang Meng
Published: February 2025

Modular multilevel converter–high-voltage direct current (MMC-HVDC) systems are a key technology for integrating large-scale offshore wind farms due to their flexibility, controllability, and decoupled active and reactive power characteristics. However, offshore wind farms rely on power electronic converters, resulting in low inertia, which can worsen frequency fluctuations and affect system stability during major disturbances. Additionally, the decoupled power control of MMC-HVDC systems limits wind farms’ inertia contribution to the AC grid, exacerbating inertia deficiency. To address this, a coordinated inertia support strategy is proposed, utilizing a DC voltage–frequency mapping method that enables wind farms to perceive frequency variations without communication and rapidly provide inertia response. This strategy coordinates wind farms and MMC-HVDC systems to enhance frequency support. Simulations demonstrate that the proposed strategy overcomes MMC-HVDC’s decoupling effect, accelerates frequency recovery, and improves the inertia response speed, achieving faster power support and higher peak power output, thereby enhancing frequency stability. Furthermore, PSCAD/EMTDC simulations were conducted to analyze the transient characteristics of MMC-HVDC under AC-side faults, verifying that braking resistors (BRs) effectively suppress DC overvoltage, reducing wind farm power curtailment and improving system security. This study provides a new approach for frequency stability control in MMC-HVDC-based offshore wind integration and serves as a reference for further optimization of inertia support and fault protection strategies.
Intelligent Scheduling of a Pulsating Assembly Flow Shop Considering a Multifunctional Automated Guided Vehicle
Authors: Song Hailong , Yang Shengluo , Yin Shuoxin , Wang Junyi , Xu Zhigang
Published: February 2025

The pulsating assembly line is widely used in modern manufacturing, particularly in high-precision industries such as aerospace, where it greatly enhances production efficiency. To achieve overall optimization, both product scheduling and Automated Guided Vehicle (AGV) scheduling must be simultaneously optimized. However, existing research predominantly focuses on product scheduling, with limited attention given to AGV scheduling. This paper proposes an optimized solution for the pulsating assembly line scheduling problem, incorporating multifunctional AGV scheduling. A mathematical model is developed and three AGV selection strategies and three AGV standby strategies are designed to optimize AGV scheduling and control. To improve scheduling efficiency, nine heuristic strategies are introduced, along with the Variable Neighborhood Descent (VND) algorithm as a metaheuristic method for product scheduling. The VND algorithm refines the solution through multiple neighborhood searches, enhancing both the precision and efficiency of product scheduling. Our experimental results demonstrate that the proposed strategies significantly improve the production efficiency of pulsating assembly workshops, reduce AGV scheduling costs, and optimize overall production workflows. This study offers novel methods for intelligent scheduling in pulsating assembly workshops, contributing to the advancement of manufacturing toward “multiple varieties, small batches, and customization”.
Design of the Converter Prototype for Powering the Hydrogen Electrolyzer
Authors: Paulec Tomáš , Špánik Pavol , Tvarožek Juraj , Praženica Michal
Published: February 2025

Electrolysis, which uses direct current, is the most common way to produce hydrogen gas. However, its efficiency is very low, about 70%. The method used when current pulses are used by electrolysis is called pulse electrolysis. According to other studies, this method can increase the efficiency of the production of hydrogen gas by the electrolysis of water. The main objective of this paper is to present a prototype of a converter that provides current pulses with specific parameters. This converter can produce positive and negative pulse-modulated current pulses of defined amplitude and duty. Also, the number of positive and negative pulses in one working cycle is adjustable. This converter’s design enables us to research pulse water electrolysis, its electrical behavior, and the possibilities of increasing the efficiency of the electrolysis process. While this paper focuses on the development of the prototype for future research, the technology could be extended to other applications requiring precise current pulse control.
Optimal Placement of Leakage Sensors in Urban Gas Networks Based on an Ant Colony Algorithm and System Clustering
Authors: Sui Zhewen , Yuan Xiaobing , Cai Baoping , Ye Fangqi , Duan Qingqing , Zhao Zhiqiang , Shao Xiaoyan , Zhou Xin , Hu Zhiming
Published: February 2025

In urban gas network leakage monitoring, the optimized placement of sensors plays a pivotal role in ensuring public safety and minimizing system maintenance costs. This study introduces an innovative approach that integrates hierarchical clustering with ant colony optimization (ACO) to optimize sensor layouts in urban gas networks. The hierarchical clustering technique is first employed to evaluate the strategic importance of each monitoring node, which subsequently influences the pheromone importance parameter in the ACO algorithm. Furthermore, the proposed method accounts for soil types and gas diffusion characteristics, which affect the pheromone concentration gradient, as well as the physical distances between nodes, which determine the heuristic factors in the algorithm. By finely tuning these parameters, the method achieves a significant reduction in the number of sensors required while ensuring comprehensive network coverage, thereby improving economic and operational efficiency. The optimized sensor layout not only accelerates the response to gas leaks but also enhances the system’s adaptability to complex urban environments. Simulation and field test results validate the effectiveness of this optimization approach, demonstrating its practical value in advancing the safety management of urban gas networks.
Binary or Integer Chromosome: Which Is the Best Structure for Supervised Machine Learning Using Genetic Algorithms?
Authors: Alves Alexandre Henrick da Silva , Neto Guilherme Antonio Coelho , Gomes Matheus de Souza , Santos Líbia Diniz , Bertarini Pedro Luiz Lima , do Amaral Laurence Rodrigues
Published: February 2025

Supervised machine learning is widely researched nowadays. Several works have already been developed using genetic algorithms (GAs) for classification tasks evolving IF-THEN classification rules. Oftentimes, these methods are built using integers and real values from one’s chromosome structure. In this paper, new and important improvements are proposed to Non-linear Computation Evolutionary Environment (NLCEE), a GA-based rule-set generator proposed by Amaral and Hruschka. The proposed GA, called BIN-NLCEE, uses binary representation in its chromosome structure to simplify its mutation and also produce a higher search space. The main goal is to have a rule-set generator that produces simple and interpretable classification rules with good accuracy values and better converge rates. The BIN-NLCEE performance was compared with other GAs-based and four traditional classifiers in five medical domain datasets. The results showed a better convergence rate and higher fitness values for BIN-NLCEE when compared with the GA-based CEE and NLCEE. In 20 comparisons, BIN-NLCEE achieved better results in 9 (45%), and, according to the confidence interval, equivalent results were obtained in 11 (55%). In this way, BIN-NLCEE was better or equal to NLCEE and CEE in 100% of the comparisons. Also, BIN-NLCEE outperformed all traditional classifiers’ results, i.e., achieved better results in 100% of comparisons.
A Vision-Guided Deep Learning Framework for Dexterous Robotic Grasping Using Gaussian Processes and Transformers
Authors: Kadalagere Sampath Suhas , Wang Ning , Yang Chenguang , Wu Howard , Liu Cunjia , Pearson Martin
Published: February 2025

Robotic manipulation of objects with diverse shapes, sizes, and properties, especially deformable ones, remains a significant challenge in automation, necessitating human-like dexterity through the integration of perception, learning, and control. This study enhances a previous framework combining YOLOv8 for object detection and LSTM networks for adaptive grasping by introducing Gaussian Processes (GPs) for robust grasp predictions and Transformer models for efficient multi-modal sensory data integration. A Random Forest classifier also selects optimal grasp configurations based on object-specific features like geometry and stability. The proposed grasping framework achieved a 95.6% grasp success rate using Transformer-based force modulation, surpassing LSTM (91.3%) and GP (91.3%) models. Evaluation of a diverse dataset showed significant improvements in grasp force modulation, adaptability, and robustness for two- and three-finger grasps. However, limitations were observed in five-finger grasps for certain objects, and some classification failures occurred in the vision system. Overall, this combination of vision-based detection and advanced learning techniques offers a scalable solution for flexible robotic manipulation.
Design of a Lung Lesion Target Detection Algorithm Based on a Domain-Adaptive Neural Network Model
Authors: Liu Xiaochen , Liu Wenjian , Wu Anqi
Published: February 2025

This study developed a novel domain-adaptive neural network framework, CNDAD—Net, for addressing the challenges of lung lesion detection in cross-domain medical image analysis. The proposed framework integrates domain adaptation techniques into a classical encoding–decoding structure to align feature distributions between source and target domains. Specifically, a “Generative Adversarial Network” GAN-based domain discriminator is utilized for the iterative refinement of feature representations to minimize cross-domain discrepancies and improve the generalization capability of the model. In addition, a novel Cross-Fusion Block (CFB) is proposed to implement multi-scale feature fusion that facilitates the deep integration of 2D, 3D, and domain-adapted features. The CFB achieves bidirectional feature flow across dimensions, thereby improving the model’s capability to detect diverse lesion morphologies while minimizing false positives and missed detections. For better detection, coarse-grained domain adaptation is implemented by MMD for further optimization. It integrates a module inspired by a CycleGAN for the process to generate high-resolution images on low-quality data. Using the Lung Nodule Analysis (LUNA16) dataset, the test was conducted and its experimental result was compared with that of previous standard methods such as Faster R-CNN and YOLO, yielding mAP 0.889, recall at 0.845 and the F1-score at 0.886. This work, with a novel CNDAD—Net model, lays down a solid and scalable framework for the precise detection of lung lesions, which is extremely critical for early diagnosis and treatment. The model has prospects and is capable of being extended in future to multimodal imaging data ad real-time diagnostic scenarios, and can help in further developing intelligent medical image analysis systems.
Sensitivity Analysis of 3D Printing Parameters on Mechanical Properties of Fused Deposition Modeling-Printed Polylactic Acid Parts
Authors: Mencarelli Marta , Sisella Mattia , Puggelli Luca , Innocenti Bernardo , Volpe Yary
Published: February 2025

This study investigates the influence of various printing parameters on the tensile, compressive, and bending stiffness of fused deposition modeling (FDM)-printed polylactic acid (PLA) parts through a comprehensive full factorial design of experiment. Key factors, including infill percentage, infill pattern, number of outer shells, and part orientation, were systematically varied to quantify their impact on mechanical performance. A total of 36 parameter combinations, selected based on a literature review and experimental feasibility, were tested using standardized specimens: beams for bending, cylinders for compression, and dogbones for tensile testing. Mechanical tests were performed according to ISO 5893:2019, employing a 1 kN load cell to determine stiffness and elastic modulus. The results indicate that the number of outer shells and infill density are the most influential parameters, whereas infill pattern and part orientation have a minor effect, depending on the loading condition. This study provides a novel and robust evaluation of the interactions between key printing parameters, offering new insights into optimizing the mechanical properties of FDM-printed parts. These findings establish a foundation for further optimization and material selection in future additive manufacturing research.
Fuzzy Delphi Evaluation on Long-Term Care Nurse Aide Platform: Socio-Technical Approach for Job Satisfaction and Work Effectiveness
Authors: Chiu Jun-Zhi , Hsieh Chao-Chen
Published: February 2025

This study adopted a socio-technical approach to optimizing key factors for implementing the ETHICS (Effective Technical and Human Implementation of Computer-based Systems) framework in long-term care. Accurate record-keeping by nurse aides is essential, and deploying suitable information technology solutions can greatly improve operational efficiency. To achieve a comprehensive understanding of system requirements and information needs, the researchers combined the Fuzzy Delphi method, FAHP (Fuzzy Analytic Hierarchy Process), and TISM (Total Interpretive Structural Modeling), addressing both human and technical dimensions. The findings highlighted that the efficient allocation of human resources, a consultative and participative work environment, and adequate time to deliver high-quality care are crucial for enhancing record-keeping practices and overall operational efficiency. This improvement will ultimately lead to a higher care quality, cost savings, and better resource utilization. Additionally, adapting to changes in technology, regulations, economic conditions, demographics, industry standards, and organizational practices remains critical. By promoting a balanced integration of technical capabilities with human factors, this approach supports the effective design of socio-technical systems in long-term care settings.
Enhanced Hybrid Algorithms for Inverse Problem Solutions in Computed Tomography
Authors: Brociek Rafał , Pleszczyński Mariusz , Miarka Jakub , Goik Mateusz
Published: February 2025

This article presents a method for solving the inverse problem of computed tomography using an incomplete dataset. The problem focuses on reconstructing spatial objects based on the data collected from transmitters and receivers (referred to as projection vectors). The novelty of the proposed approach lies in combining two types of algorithms, namely heuristic and deterministic. Specifically, Artificial Bee Colony (ABC) and Jellyfish Search (JS) algorithms were utilized and compared as heuristic methods, while the deterministic methods were based on the Hooke–Jeeves (HJ) and Nelder–Mead (NM) approaches. By merging these techniques, a hybrid algorithm was developed, integrating the strengths of both heuristic and deterministic algorithms. The proposed hybrid algorithm proved to be approximately five to six times faster than an approach relying solely on metaheuristics while also providing more accurate results. In the worst-case test, the fitness function value for the hybrid algorithm was approximately 22% lower than that of the purely metaheuristic-based approach. Experimental tests further demonstrated that the hybrid algorithm, whether based on Hooke–Jeeves or Nelder–Mead, was stable and well suited for solving the considered problem. The article includes experimental results that confirm the effectiveness, accuracy, and efficiency of the proposed method.
Deciphering the Electron Spectral Hardening in AMS-02
Authors: Evoli Carmelo
Published: February 2025

We analyze the electron cosmic-ray spectrum from AMS-02, focusing on the spectral hardening around 42 GeV. Our findings confirm that this feature is intrinsic to the primary electron component rather than a byproduct of contamination from primary positron sources. Even under conservative assumptions, its significance remains at about 7σ, strongly indicating a genuine spectral break. Accordingly, we introduce a new, more realistic parametric fit, which we recommend for the next round of AMS-02 analyses. Once the sources of systematic uncertainties are better constrained, this refined approach can either reinforce or refute our conclusions, providing a clearer understanding of the observed electron spectrum. If confirmed, we propose that this hardening most likely arises from interstellar transport or acceleration effects.
Optimizing PPP-AR with BDS-3 and GPS: Positioning Performance Across Diverse Geographical Regions Under Mostly Quiet Space Weather Conditions
Authors: Bilgen Burhaneddin
Published: February 2025

The integration of Global Navigation Satellite Systems (GNSS) has revolutionized geodetic positioning, with techniques like Precise Point Positioning with Ambiguity Resolution (PPP-AR) offering highly accurate results with reduced convergence times. The full deployment of the BeiDou Navigation Satellite System-3 (BDS-3) has spurred interest in assessing its standalone and combined performance with GPS in PPP-AR applications. This study evaluates the performance of BDS-3-based PPP-AR across diverse geographical regions considering space weather conditions (SWCs) for the first time. GNSS data from six International GNSS Service (IGS) stations located in the Asia–Pacific, Europe, Africa, and the Americas were processed for 15 consecutive days. The three scenarios (BDS-3 only, GPS only, and BDS-3 + GPS) were analyzed using the open-source raPPPid v2.3 software developed in 2023. The estimated coordinates were statistically compared to the IGS-derived coordinates to assess accuracy. Results demonstrate that BDS-3 PPP-AR can independently deliver reliable positioning for many applications and that the accuracy of BDS-3-based PPP-AR is relatively low in the Americas. However, combining BDS-3 with GPS significantly enhances horizontal and vertical accuracies, especially in the Americas, achieving improvements of up to 86% and 82%, respectively. These findings highlight the potential of BDS-3 for complementing GPS for precise geodetic applications.