bluuebunny/crossref_metadata_2025 huggingface dataset:
Waning neutralizing antibodies through 180 days after homologous and heterologous boosters of inactivated COVID-19 vaccine
Authors: Chen Zhifei , Xie Fangqin , Zhang Hairong , Li Dong , Zhang Suhan , Zhang Mengping , Li Junrong , Xie Jianfeng , Zhang Lina , Yang Xiuhui , Zhang Dongjuan
Published: January 2025

To enhance the personal immunity to COVID-19, a third booster dose of inactivated COVID-19 vaccines program campaign was implemented in China. Our study endeavored to compare the dynamics of neutralizing antibodies generated by four distinct booster vaccines against three kinds of live SARS-CoV-2 virus (wild-type, Delta AY.23, and Omicron BA5.2). This cohort study involved 320 healthy individuals, who were randomly assigned to four groups, to receive boosters with inactivated vaccine (COVac and BIBP), the adenovirus type-5-vectored vaccine (Convidecia), and the recombinant protein-based vaccine (Zifivax), respectively, all the vaccines studied had the Wuhan variant as their parental variant. Participants were recruited from December 2021 to June 2022, with a follow-up period of 180 days. We evaluated humoral immune responses and their longevity by measuring the geometric mean titers (GMTs) of neutralizing antibodies against the SARS-CoV-2 virus at various time points post-boost. After 180 days of follow-up, 310 participants completed the study. Across all booster groups, neutralizing antibodies against the wild-type virus declined sharply within the first 90 days, accounting for an 81.24 to 92.34% reduction, then slowed down with gradually decreasing decay rates. By day 14 of post-boost, the ability to neutralize the Delta variant slightly diminished compared to the wild-type, whereas neutralizing antibodies against the Omicron variant exhibited a more pronounced decline, ranging from 10.78 to 19.88 times lower than those against the wild-type. Notably, heterologous boosting with the Convidecia vaccine maintained higher GMTs of neutralizing antibodies against both Delta and Omicron variants compared to the other boosters. At 180 days of post-boost, GMTs of neutralizing antibodies against SARS-CoV-2 had substantially decreased, yet individuals who received the Convidecia vaccine still exhibited higher titers than those who received other boosters. In summary, neutralizing antibody levels significantly waned 180 days after the third vaccine dose, with the most pronounced decline occurring within the initial 90 days. Heterologous boosting with Convidecia demonstrated a more robust, durable, and broad humoral immune response compared to boosting with inactivated vaccines or Zifivax, suggesting that adenovirus vector vaccines possess a special advantage in the realm of vaccine development for preventing infectious diseases.
Best practice portals in health promotion and disease prevention: approaches, definitions, and intervention evaluation criteria
Authors: Piotrowicz Maria , Gajewska Małgorzata , Lewtak Katarzyna , Urban Ewa , Rutyna Anna , Nitsch-Osuch Aneta
Published: January 2025

Introduction

The evaluation of practices is a valuable source of evidence in the context of an evidence-based approach to public health. Best practice portals (BPPs) are promising tools for facilitating access to recommended programmes, monitoring and improving the quality of interventions. There are several such portals in Europe, but there is little work in the scientific literature on the subject. The study aimed to identify and characterise BPPs in health promotion and disease prevention and analyse the approaches, definitions, and criteria for evaluating interventions.

Methods

To identify portals, websites of public health institutions and organisations, the PubMed database and grey literature were searched. The material consisted of elements of each portal’s design, information available on their websites, and collected publications. The study applied a qualitative analysis with a descriptive approach and covered a detailed description of the four selected portals.

Results

Among the analysed BPPs, three were from the European region, and one was from Canada (pioneer in developing best practice tools). The dates of launching the portals ranged from the year 2003 to 2016. The number of interventions collected in the databases ranged from 120 to 337. Portals were useful, well-designed, and developed tools. BPPs differed in terms of their objectives and roles, adopted standards and criteria for assessing practices, and other operational factors. In each portal, interventions underwent a rigorous and multilevel assessment process conducted by independent experts in the field and based on intervention evaluation criteria. Generally, the analysed catalogues described similar issues, e.g., Selection of the issue addressed by the practice, Description of a particular element of the practice, Theoretical foundation, or Evaluation/Effectiveness. However, we identified both similarities and differences in the adopted terms (names of criteria) and their definitions. It was shown that sometimes the same criterion had different names depending on the catalogue. On the other hand, criteria with identical or similar names could be defined differently within the detailed thematic scope.

Conclusion

The similarities and differences presented in this work can serve as a valuable starting point for designing such tools to support practice-based and evidence-based decision-making in health promotion and disease prevention.
Why individuals with trait anger and revenge motivation are more likely to engage in cyberbullying perpetration? The online disinhibition effect
Authors: Ding Jin-liang , Lin Yan , Chen I-Hua
Published: January 2025

Background

Trait anger has been identified as a significant risk factor in cyberbullying perpetration; however, the mechanisms underlying this relationship remain underexplored. This study aims to elucidate the connection between trait anger and cyberbullying perpetration among adolescents, with a focus on the mediating role of revenge motivation and the moderating effect of online disinhibition.

Methods

A sample of 1,574 Chinese adolescents (46.1% female, mean age 16.89 years, SD = 0.34) participated in the study. Participants completed measures assessing trait anger, revenge motivation, online disinhibition, and cyberbullying perpetration.

Results

Revenge motivation partially mediated the association between trait anger and cyberbullying perpetration. Furthermore, the relationship between revenge motivation and cyberbullying perpetration, as well as the relationship between trait anger and cyberbullying perpetration, were moderated by online disinhibition, with a significant association observed only among adolescents exhibiting higher levels of toxic disinhibition.

Conclusion

These findings extend the current understanding of cyberbullying perpetration among adolescents and offer valuable insights for intervention strategies targeting this antisocial online behavior.
Gender and antimicrobial resistance: a conceptual framework for researchers working in livestock systems
Authors: Emdin Fiona , Galiè Alessandra , Moodley Arshnee , Rogers Van Katwyk Susan
Published: January 2025

Background

To promote gender mainstreaming in future AMR research projects and policy implementation within livestock and other systems, researchers need to embrace gender-responsive research methodologies. Ignoring gender considerations can lead to unsustainable interventions and exacerbate existing equity gaps. Incorporating gender analysis is crucial for identifying data collection needs and opportunities to develop gender-responsive research programs and policies.

Objectives

We have developed a conceptual framework and a set of research questions designed to enhance the gender-responsiveness of AMR research in livestock systems.

Methods

A narrative review previously identified three key entry points for gender dynamic impacting AMR in agricultural systems: gendered antimicrobial resistance exposure, gendered antimicrobial use and gendered outcomes of antimicrobial resistance infections. This information was then analyzed using a health system gender framework. Combining these insights, we developed a comprehensive list of research questions.

Results

We developed comprehensive list of gender-related questions. Given the limited understanding of how gender dynamics and norms influence AMR, we have primarily proposed qualitative, exploratory questions. These questions are categorized into two types: integrated and strategic. Integrated questions offer a deeper understanding of gender dynamics and norms in livestock systems with the aim of improving them, while strategic questions focus on gender-related issues in livestock as entry points, highlighting some of the mechanisms behind these gender issues to progress towards gender equality.

Conclusion

As gender-analysis in livestock research gains prominence, there is an increasing expectation for AMR researchers to integrate gender considerations into their work. This framework provides a starting point for researchers aiming to enhance gender inclusivity and considerations in AMR research within livestock systems. The next phase of our project will involve applying this framework in the field, where a real-life application will enable its validation and further refinement.
An Analysis of the Generational Succession Procedures for Retaining Organizational Knowledge in Companies Within the Basque Autonomous Community (Spain)
Authors: Igoa-Iraola Elene , Díez Ruiz Fernando , Campos Granados José Antonio
Published: January 2025

The retention of organizational knowledge is increasingly challenging for companies giventhe aging workforce, high turnover rates, and declining birth rates. This study explores the knowledge transfer processes during generational transitions and examines how digital transformation facilitates business model innovation. Specifically, it examines theknowledge transfer procedures implemented in companies in the Autonomous Community of the Basque Country, a competitive industrial region in Europe. Using a quantitative approach, 168 individuals in key leadership positions were surveyed on the mechanisms used for knowledge retention and their effectiveness. The results reveal that while companies prioritize knowledge transfer, most lack effective protocols. Organizations employing both digital and analog strategies are perceived as more efficient in retaining knowledge. Only half of the companies integrate knowledge transfer processes into their management strategies, with no observed differences in employee knowledge-sharing behaviors based on company size. This study concludes that a lack of structured procedures may harm long-term competitiveness, recommending that companies invest more in developing formal generational handover protocols. This research underscores the vital importance of knowledge retention for organizational sustainability and highlights the need for further exploration to address this issue.
Research on the Generation Technology of Declared Airport Capacity Thresholds Based on Profit Maximization
Authors: Liu Ying , Zhao Zheng , Peng Ying
Published: January 2025

Declared airport capacity is a key parameter in flight scheduling. The evaluation method for airport capacity primarily relies on computer simulation, and the capacity assessment results are dependent on the determination of the acceptable delay level. However, applying the same acceptable delay level across airports with different characteristics is unreasonable. To reasonably evaluate the acceptable delay level in simulations, this paper takes the flight profit of airport operations as the research object, conducting a marginal analysis of flight profit under various simulated delay levels. This approach identifies the simulated acceptable delay level that corresponds to maximum flight profit, serving as the threshold for assessing declared airport capacity. An empirical study is conducted using typical coordinated airports nationwide, aiming to determine acceptable delay level thresholds that align with declared airport capacity from an economic perspective. The experimental results indicate that the reasonable simulated acceptable delay levels for Shanghai, Nanjing, Shenyang, and Urumqi airports are 8.67 min, 6.18 min, 3.98 min, and 7.02 min, respectively. These levels demonstrate significant flight profit growth, validating the model’s positive role in enhancing the potential of declared airport capacity and in scientifically evaluating the supply-side capability of civil aviation.
Normal Shock Waves in Chemically Reacting Flows with Exothermic and Endothermic Reactions Under High-Temperature Conditions
Authors: Avramenko Andriy A. , Shevchuk Igor V. , Kovetskaya Margarita M. , Kovetska Yulia Y. , Tyrinov Andrii I. , Anastasiev Dmytro V.
Published: January 2025

This article theoretically investigates the interaction of a normal shock wave in a flow with chemical reactions under high-temperature conditions. The main novelty of the work is that the thermal effect of chemical reactions is modeled as a function of the temperature. A modified Rankine–Hugoniot model for a shock wave in a flow with chemical reactions has been developed. It is shown that for an exothermic reaction the pressure jump increases with increasing Arrhenius numbers. This is due to the additional energy introduced into the flow as heat is released during the chemical reaction. For endothermic reactions, the opposite trend is observed. The change in the speed of the adiabatic gas flow as it passes through a normal shock wave depending on the type of chemical reaction is clarified. The study provides comparisons between the results of the analytical and numerical solutions of the modified Hugoniot adiabatic equations.
Identifying the Garlic and Grain Mixture with the Highest Allithiamine Content
Authors: Lee Chang-Dae , Chae Jiheong , Kim Minju , Jang Minah , Ye Eunju , Kim Jungwook , Lee Sanghyun
Published: January 2025

Garlic (Allium sativum L.) has been extensively studied for its therapeutic and culinary applications, owing to its sulfur-containing bioactive compounds, including allicin and its derivatives. This study identified garlic varieties with high allicin content from different regions of Korea. It explores the synthesis of allithiamine, a lipid-soluble derivative of thiamine with enhanced bioavailability, by combining garlic with various grains. High-performance liquid chromatography (HPLC) analysis revealed significant regional variations in the allicin content, with Jeju garlic exhibiting the highest levels (1.04 mg/g). Among the grains tested, Avena sativa showed the most effective interaction with garlic, yielding the highest allithiamine levels (14.93 mg/g). These findings underscore the importance of grain matrix properties in optimizing the synthesis of allithiamine. This study provides valuable insights into the development of functional foods that leverage the bioactive compounds in garlic to enhance metabolic health and thiamine bioavailability.
Distribution of Trachelospermum jasminoides Under the Influence of Different Environmental Factors
Authors: Yu Huan , Zhuo Zhihang , He Zhipeng , Liu Quanwei , Deng Xinqi , Xu Danping
Published: January 2025

Trachelospermum jasminoides (Lindl.) Lem. is a well-known herb with important medicinal and economic values. It is widely used in the treatment of inflammations in China. As global climate change intensifies, the ecological niche of plants has correspondingly shifted. Therefore, understanding the distribution of suitable habitats for T. jasminoides under different climate conditions is of great significance for its cultivation, introduction, and conservation. This research utilizes the MaxEnt model in combination with the Geographic Information System (ArcGIS) to analyze the present and future potential habitat distributions of T. jasminoides. Based on 227 documented occurrence points and 15 ecological variables, the results emphasize that the key environmental limitations influencing the optimal habitats of T. jasminoides are the precipitation during the coldest quarter, the mean temperature of the driest quarter, precipitation in the warmest quarter, temperature seasonality (standard deviation × 100), and the human impact index. At present, the combined area of suitable and highly suitable habitats for T. jasminoides amounts to 15.76 × 104 km2, with the highly suitable habitats predominantly situated in East and Central China. Based on climate scenario forecasts, within the SSP1-2.6 climate scenario, the total suitable habitat area for T. jasminoides is projected to increase relative to the current situation. Nevertheless, in the SSP2-4.5 and SSP5-8.5 climate scenarios, the suitable habitat area is anticipated to initially rise and then decline. The distribution center is mainly concentrated in the provinces of Hunan and Jiangxi, with the centroid shifting southeastward compared to the current situation. The findings of this research offer valuable insights for the effective cultivation, preservation, and sustainable use of T. jasminoides resources.
Effects of Lameness on Milk Yield, Milk Quality Indicators, and Rumination Behaviour in Dairy Cows
Authors: Džermeikaitė Karina , Krištolaitytė Justina , Anskienė Lina , Šertvytytė Greta , Lembovičiūtė Gabija , Arlauskaitė Samanta , Girdauskaitė Akvilė , Rutkauskas Arūnas , Baumgartner Walter , Antanaitis Ramūnas
Published: January 2025

This study investigates the relationship between lameness, milk composition, and rumination behaviour in dairy cows by leveraging sensor-based data for automated monitoring. Lameness was found to significantly impact both rumination and milk production. Lameness was assessed in 24 multiparous Holstein dairy cows throughout early lactation (up to 100 days postpartum), utilising a 1-to-5 scale. Lameness was found to significantly impact both rumination and milk production. On the day of diagnosis, rumination time decreased by 26.64% compared to the pre-diagnosis period (p < 0.01) and by 26.06% compared to healthy cows, indicating the potential of rumination as an early health indicator. The milk yield on the day of diagnosis was 28.10% lower compared to pre-diagnosis levels (p < 0.01) and 40.46% lower than healthy cows (p < 0.05). These findings suggest that lameness manifests prior to clinical signs, affecting productivity and welfare. Milk composition was also influenced, with lame cows exhibiting altered fat (+0.68%, p < 0.05) and lactose (−2.15%, p < 0.05) content compared to healthy cows. Positive correlations were identified between rumination time and milk yield (r = 0.491, p < 0.001), while negative correlations were observed between milk yield and milk fat, protein, and the fat-to-protein ratio (p < 0.001). Additionally, lameness was associated with elevated somatic cell counts in the milk, although sample size limitations necessitate further validation. This study highlights the critical role of rumination and milk performance metrics in identifying subclinical lameness, emphasising the utility of automated systems in advancing dairy cow welfare and productivity. The findings underscore the importance of early detection and management strategies to mitigate the economic and welfare impacts of lameness in dairy farming.
Tracking Long-Distance Systematic Trajectories of Different Robot Mower Patterns with Enhanced Custom-Built Software
Authors: Luglio Sofia Matilde , Frasconi Christian , Gagliardi Lorenzo , Raffaelli Michele , Peruzzi Andrea , Pieri Stefano , Volterrani Marco , Magni Simone , Fontanelli Marco
Published: January 2025

Sustainable turfgrass management is essential for maintaining healthy and visually appealing green spaces. Autonomous mowers have emerged as an innovative solution, but the efficiency and quality of mowing operations depend on several factors. This study investigates the impact of mowing patterns and cutting heights on the performance of an autonomous mower through updated custom-built software. Three different mowing patterns (vertical, diagonal, and horizontal) and two cutting heights (3 cm and 6 cm) were analyzed to analyze mowing efficiency, coverage, and cutting uniformity. The vertical pattern emerged as the most effective, maximizing speed (0.52 m/s) and efficiency (0.77), while minimizing overlap (4.27 cm) and uncut areas (0.014 m2). In contrast, the horizontal and diagonal patterns showed lower efficiency (0.71 and 0.76) and less coverage percentage (97.05% and 96.71%) compared to the vertical pattern (98.57%). Cutting height influenced performance, with higher heights sometimes requiring adjustments to prevent inefficiencies. The interaction between the mowing pattern and cutting height was critical for optimizing both operational efficiency and cutting quality. These findings highlight the importance of selecting an appropriate mowing pattern and cutting height tailored to the specific operational goals.
Frass and Furious: Unfolding the Potential of Insect Frass as Soil Fertilizer
Authors: Athanassiou Christos G. , Rumbos Christos I.
Published: January 2025

Over the past decade, insect farming has garnered significant scientific and commercial attention due to its potential as a sustainable and efficient alternative nutrient source for both animal feed [...]
Remote Sensing-Assisted Estimation of Water Use in Apple Orchards with Permanent Living Mulch
Authors: Ferreira Susana , Sánchez Juan Manuel , Gonçalves José Manuel , Eugénio Rui , Damásio Henrique
Published: January 2025

Orchards are complex agricultural systems with various characteristics that influence crop evapotranspiration (ETc), such as variety, tree height, planting density, irrigation methods, and inter-row management. The preservation of biodiversity and improvement of soil fertility have become important goals in modern orchard management. Consequently, the traditional approach to weed control between rows, which relies on herbicides and soil mobilization, has gradually been replaced by the use of permanent living mulch (LM). This study explored the potential of a remote sensing (RS)-assisted method to monitor water use and water productivity in apple orchards with permanent mulch. The experimental data were obtained in the Lis Valley Irrigation District, on the Central Coast of Portugal, where the “Maçã de Alcobaça” (Alcobaça apple) is produced. The methodology was applied over three growing seasons (2019–2021), combining ground observations with RS tools, including drone flights and satellite images. The estimation of ETa followed a modified version of the Food and Agriculture Organization of the United Nations (FAO) single crop coefficient approach, in which the crop coefficient (Kc) was derived from the normalized difference vegetation index (NDVI) calculated from satellite images and incorporated into a daily soil water balance. The average seasonal ETa (FAO-56) was 824 ± 14 mm, and the water productivity (WP) was 3.99 ± 0.7 kg m−3. Good correlations were found between the Kc’s proposed by FAO and the NDVI evolution in the experimental plot, with an R2 of 0.75 for the entire growing season. The results from the derived RS-assisted method were compared to the ETa values obtained from the Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) surface energy balance model, showing a root mean square (RMSE) of ±0.3 mm day−1 and a low bias of 0.6 mm day−1. This study provided insights into mulch management, including cutting intensity, and its role in maintaining the health of the main crop. RS data can be used in this management to adjust cutting schedules, determine Kc, and monitor canopy management practices such as pruning, health monitoring, and irrigation warnings.
Genomic Prediction and Genome-Wide Association Study for Growth-Related Traits in Taiwan Country Chicken
Authors: Tu Tsung-Che , Lin Chen-Jyuan , Liu Ming-Che , Hsu Zhi-Ting , Chen Chih-Feng
Published: January 2025

Taiwan Country chickens are integral to Taiwanese culture and the poultry industry. By establishing a crossbreeding system, breeders must consider the growth-related traits of the dam line to achieve acceptable traits in commercial meat-type chickens. This study compared the accuracy of genomic estimated breeding values (GEBVs) predicted using the pedigree-based best linear unbiased prediction (PBLUP) model and the single-step genomic BLUP (ssGBLUP) model. Additionally, we conducted a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNPs) associated with growth, shank, and body conformation traits to support marker-assisted selection (MAS). The results showed that the ssGBLUP model achieved 4.3% to 16.4% higher prediction accuracy than the PBLUP model. GWAS identified four missense SNPs and four significant SNPs associated with body weight, shank length, and shank width at 12 weeks. These findings highlight the potential of integrating the ssGBLUP model with identified SNPs to improve genetic gain and breeding efficiency and provide preliminary results to assess the feasibility of genomic prediction and MAS in Taiwan Country chicken breeding programs. Further research is necessary to validate these findings and explore their mechanisms and broader application across different breeding programs, particularly for the NCHU-G101 breed of Taiwan Country chickens.
Artificial Afterimage Algorithm: A New Bio-Inspired Metaheuristic Algorithm and Its Clustering Application
Authors: Demir Murat
Published: January 2025

Metaheuristic methods are optimization methods that look for different ways to converge to a solution to a problem where it is difficult to find a solution analytically. Their difference from known optimization methods is that they imitate living things or systems in nature. Each metaheuristic method has its equations, and the solution is found using these equations. In this study, a new, metaheuristic method called the afterimage algorithm is proposed. The proposed method was developed inspired by the fact that when we close our eyes after looking at a luminous image for a while, the vision still occurs in our minds. This is called an afterimage. The proposed method first pre-processes with the operator called afterimage and calculates the best and worst solution values. The visual angle value is then calculated, and new solutions are produced around this value. Three different datasets were used in experimental studies on data clustering. Accuracies of 96.66% for the iris plant dataset, 92% for the Wisconsin breast cancer dataset, and 95% for the occupancy detection dataset were obtained.
Research on Intelligent Optimization of Wellbore Trajectory in Complex Formation
Authors: Gu Haipeng , Yan Tie , Wu Yang
Published: January 2025

Borehole trajectory optimization is a key issue in oil and gas drilling engineering. The traditional wellbore trajectory design method faces great challenges in optimizing the trajectory length and complexity, and it is difficult to meet the actual engineering requirements. In this paper, the three-stage wellbore trajectory optimization problem is studied, and a multi-objective optimization model including two objective functions of trajectory length and trajectory complexity is constructed. In this paper, an improved multi-objective particle swarm optimization algorithm is proposed, which combines the clustering strategy to improve the diversity of solutions, and enhances the local search ability and global convergence performance of the algorithm through the elite learning strategy. In order to verify the performance of the algorithm, comparative experiments were carried out using classical multi-objective benchmark functions. The results showed that the improved algorithm is superior to the traditional method in terms of diversity and convergence of solutions. Finally, the proposed algorithm was applied to the actual three-stage wellbore trajectory optimization problem. In summary, the research results of this paper provide theoretical support and engineering practice methods for wellbore trajectory optimization, and serve as an important reference for further improving the efficiency and quality of wellbore trajectory design.
Impact of Road Gradient on Fuel Consumption of Light-Duty Diesel Vehicles
Authors: Jiang Bigang , Yang Dongyang , Yu Haisheng , Wang Jiguang , He Chao , Li Jiaqiang , Chen Yanlin
Published: January 2025

The geometric alignment of highways directly affects the fuel consumption of motor vehicles. To analyze the impact of the road gradient on fuel consumption, actual road tests were conducted in plateau and mountainous areas. Geographic Information Systems (GISs) were used to calculate road gradients, and Vehicle Specific Power (VSP) distributions were obtained through testing, serving as inputs for the motor vehicle emission simulator (MOVES) model. Finally, the simulation results were verified against the experimental results. The findings indicate a strong positive correlation between road gradients ranging from −5% to +5%, the VSP, and fuel consumption. At a constant gradient, the fuel consumption rate increases with the vehicle speed; the fuel consumption factor is lowest at 60 km/h and highest at 40 km/h. Under both constant and actual driving speeds, when the absolute values of uphill and downhill gradients are the same, the average fuel consumption for both uphill and downhill driving shows that, at gradients of 1% to 3%, the fuel savings from downhill driving can offset the additional fuel consumption on uphill driving. At gradients of 4% to 6%, the increase in fuel consumption on uphill driving surpasses the savings from downhill driving. During uphill climbs, lower speeds within the mid-to-low range result in lower fuel consumption and greater reserve power. The MOVES model demonstrates good adaptability in plateau and mountainous areas.
Spatiotemporal Analysis of Drought and Its Driving Factors in the Yellow River Basin Based on a Standardized Precipitation Evapotranspiration Index
Authors: Wei Chong , Su Danning , Zhao Dongbao , Li Yixuan , He Junwei , Wang Zhiguo , Cao Lianhai , Jia Huicong
Published: January 2025

As a natural disaster, drought can endanger global ecology, socio-economic systems, and sustainable development. To address sudden droughts in the future, assess drought disasters, and propose mitigation measures, in-depth research on the spatiotemporal variations in and driving factors of meteorological drought is essential. To study drought in the Yellow River Basin, we calculated the multi-scale Standardized Precipitation Evapotranspiration Index (SPEI), derived from monthly meteorological data recorded at weather stations from 1968 to 2019. We examined the features of drought and its driving factors using the trend-free pre-whitening Mann–Kendall (TFPW-MK) test and Sen’s slope estimator, as well as a drought frequency analysis, center of gravity migration model, standard deviation ellipse model, and geographic detector. Our analysis shows that (1) from 1968 to 2019, the Yellow River Basin exhibited a shift from aridity to increased moisture on an annual basis, with the smallest SPEI of −1.47 in 2002 indicating a moderate drought; SPEI3 showed a growing tendency in all seasons, particularly in winter (0.00388/year), followed by spring (0.00214/year), summer (0.00232/year), and fall (0.00196/year). The SPEI3 exhibited higher fluctuations in frequency compared to the annual-scale SPEI12; (2) in terms of spatial variability, there was no significant change in drought conditions at any scale, with the probability of a drought event being greater in the eastern and northwestern portions of the watershed. The epicenter of the drought exhibited a tendency to migrate southwestward; (3) among the seven driving factors, land use and night lighting were the dominant factors affecting drought conditions, with driving force values of 0.75 and 0.63, respectively.
On the Axiomatic of GV-Fuzzy Metric Spaces and Its Completion
Authors: Gregori Valentín , Miñana Juan-José , Roig Bernardino , Sapena Almanzor
Published: January 2025

The concept of fuzzy metric space introduced by Kramosil and Michalek was later slightly modified by George and Veeramani who imposed three additional restrictions on it. A significant difference between these two concepts of fuzzy metrics is that fuzzy metric spaces in the sense of George and Veeramani do not admit completion, in general. This paper is devoted to go into detail on completable fuzzy metric spaces by means of the study of the impact on the completion of each one of the restrictions imposed by George and Veeramani in their definition of fuzzy metric. In this direction, we characterize those completable fuzzy metric spaces, in which just one of the three restrictions imposed by George and Veeramani is required. Various examples illustrate and justify the main results.
Exploring Star Filters of Almost Distributive Lattices
Authors: Khabyah Ali Al , Rafi Noorbhasha , Ansari Moin A.
Published: January 2025

In an almost distributive lattice (ADL), we have presented and explored the notions of star filters and starlets. Further, we have characterized star filters through their starlets. A set of equivalent conditions is established for a filter in an ADL to become a star filter. Additionally, this paper investigates the topological properties of the prime spectrum associated with star filters in an ADL.
Efficient Tensor Robust Principal Analysis via Right-Invertible Matrix-Based Tensor Products
Authors: Huang Zhang , Feng Jun , Li Wei
Published: January 2025

In this paper, we extend the definition of tensor products from using an invertible matrix to utilising right-invertible matrices, exploring the algebraic properties of these new tensor products. Based on this novel definition, we define the concepts of tensor rank and tensor nuclear norm, ensuring consistency with their matrix counterparts, and derive a singular value thresholding (∗L,R SVT) formula to approximately solve the subproblems in the alternating direction method of multipliers (ADMM), which is integral to our proposed tensor robust principal component analysis (∗LR TRPCA) algorithm. The computational complexity of the ∗LR TRPCA algorithm is O(k·(n1n2n3+p·min(n12n2,n1n22))) for k iterations. According to this complexity analysis, by using a right-invertible matrix that selects p rows from the n3 rows of the invertible matrix used in the tensor product with an invertible matrix, the computational load is approximately reduced to p/n3 of what it would be with an invertible matrix, highlighting the efficiency gain in terms of computational resources. We apply this efficient algorithm to grayscale video denoising and motion detection problems, where it demonstrates significant improvements in processing speed while maintaining comparable quality levels to existing methods, thereby providing a promising approach for handling multi-linear data and offering valuable insights for advanced data analysis tasks.
Sustainable Extraction of Critical Minerals from Waste Batteries: A Green Solvent Approach in Resource Recovery
Authors: Dar Afzal Ahmed , Chen Zhi , Zhang Gaixia , Hu Jinguang , Zaghib Karim , Deng Sixu , Wang Xiaolei , Haghighat Fariborz , Mulligan Catherine N. , An Chunjiang , Ramirez Antonio Avalos , Sun Shuhui
Published: January 2025

This strategic review examines the pivotal role of sustainable methodologies in battery recycling and the recovery of critical minerals from waste batteries, emphasizing the need to address existing technical and environmental challenges. Through a systematic analysis, it explores the application of green organic solvents in mineral processing, advocating for establishing eco-friendly techniques aimed at clipping waste and boosting resource utilization. The escalating demand for and shortage of essential minerals including copper, cobalt, lithium, and nickel are comprehensively analyzed and forecasted for 2023, 2030, and 2040. Traditional extraction techniques, including hydrometallurgical, pyrometallurgical, and bio-metallurgical processes, are efficient but pose substantial environmental hazards and contribute to resource scarcity. The concept of green extraction arises as a crucial step towards ecological conservation, integrating sustainable practices to lessen the environmental footprint of mineral extraction. The advancement of green organic solvents, notably ionic liquids and deep eutectic solvents, is examined, highlighting their attributes of minimal toxicity, biodegradability, and superior efficacy, thus presenting great potential in transforming the sector. The emergence of organic solvents such as palm oil, 1-octanol, and Span 80 is recognized, with advantageous low solubility and adaptability to varying temperatures. Kinetic (mainly temperature) data of different deep eutectic solvents are extracted from previous studies and computed with machine learning techniques. The coefficient of determination and mean squared error reveal the accuracy of experimental and computed data. In essence, this study seeks to inspire ongoing efforts to navigate impediments, embrace technological advancements including artificial intelligence, and foster an ethos of environmental stewardship in the sustainable extraction and recycling of critical metals from waste batteries.
Fluorination Strategies for Mn₃O₄ Nanoparticles: Enhancing Reversibility and Capacity in Li-Ion Batteries
Authors: Porhiel Régis , Clavier Batiste , Karakoç Taylan , Pronkin Sergey , Foix Dominique , Petit Elodie , El-Ghozzi Malika , Guérin Katia
Published: January 2025

Transition metal oxides (TMOs) occupy an increasing share in the search for new electrode materials for Li-Ion batteries. Despite promising electrochemical performances (up to 1000 mAh g−1 in the case of conversion), these materials have poor cyclability linked primarily to hysteresis phenomena. To improve their electrochemical performance, one strategy consists of reducing the particle size. A second strategy relies on the incorporation of fluorine directly into electrode materials to limit the solid–electrolyte interface (SEI). Our study focuses on the impact of fluorination on the electrochemical performance of manganese oxide obtained by solid combustion synthesis (SCS). Two fluorinating agents were used: pure gaseous molecular fluorine F2 and radical fluorine F• through xenon difluoride XeF2 decomposition. The use of F2 results in strong fluorination localized primarily at the particle surface while XeF2 diffuses deeper into the particle, resulting in the removal of residual carbon from the synthesis by combustion. The electrochemical performance of the oxide fluorinated with XeF2 reaches more than 750 mAh g−1 after 160 cycles, whereas that of the oxide fluorinated by F2 barely exceeds that of the non-fluorinated oxide, less than 200 mAh g−1 after 200 cycles.
Relationship Between Renal Resistive Index and Retinal Vascular Density in Individuals with Hypertension
Authors: Carollo Caterina , Vadalà Maria , Sorce Alessandra , Sinatra Nicola , Orlando Emanuele , Cirafici Emanuele , Bennici Miriam , Polosa Riccardo , Bonfiglio Vincenza Maria Elena , Mulè Giuseppe , Geraci Giulio
Published: January 2025

Background/Objectives: Considering the physiological analogies between the eye and the kidney, this study aimed to investigate the potential relationship between retinal vascular density, assessed using Optical Coherence Tomography Angiography (OCT-A), and the renal resistive index (RRI) in patients with arterial hypertension. Methods: A total of 82 hypertensive patients (mean age 48 ± 13) were enrolled in the study. Participants underwent routine biochemical evaluations, office-based blood pressure measurement, 24 h ambulatory blood pressure monitoring, OCT-A imaging, and renal Doppler ultrasound examinations. Results: The mean RRI in the study population was 0.616 ± 0.06. Participants were divided into two groups based on the 75th percentile threshold of the RRI distribution (0.66, 95% CI 0.64–0.68). The group with RRI > 75th percentile, which appeared to have a higher number of smokers, exhibited significantly higher mean triglyceride and urinary albumin excretion (UAE) levels and a significantly reduced estimated glomerular filtration rate (eGFR) as compared to the group with RRI < 75th percentile. Among the hemodynamic parameters, 24 h pulse pressure (PP), daytime and nighttime PP, and nighttime systolic blood pressure (SBP) were significantly higher in the group with RRI > 75th percentile. Regarding retinal vascular density indices, the only significant difference was observed in the deep foveal vascular plexus, which displayed a reduced density in the group with RRI > 75th percentile. Logistic regression analysis revealed that RRI > 75th percentile was independently associated with increased nighttime mean pulse pressure (OR = 1.13, 95% CI: 1.049–1.221, p = 0.0014) and reduced deep foveal vascular density (OR = −0.5026, 95% CI: 1.0493–1.2211, p = 0.0044). Conclusions: Our findings demonstrate that ocular microvascular alterations are associated with RRI, a marker with a well-established prognostic value for renal disease progression and systemic macrovascular dysfunction. These results further substantiate the close relationship between renal and ocular microcirculation.
Clarity Amidst Ambiguity: Towards Precise Definitions in Biological-Informed Disciplines for Enhanced Communication
Authors: Huber Tim , Müssig Jörg
Published: January 2025

This study conducts a meta-analysis of over 1000 abstracts to examine the use and consistency of the terminology in biomimetics, bioinspiration, biomimicry, and bionics, focusing on how these terms impact biological study design. Despite the increasing research in these areas, the ambiguous definitions of key terms complicate study design and interdisciplinary collaboration. The primary aim of this work is to analyse how biological studies in these fields are conceptualised and evaluated, particularly concerning the inconsistent use of terminology. By identifying discrepancies in term usage, we offer refined definitions and practical examples to improve the clarity of study design and research methodologies. Our findings underscore the importance of standardised terminology for ensuring that biological research is accurately designed and executed, leading to more rigorous experimental frameworks and better alignment across disciplines. This meta-analysis reveals how clearer, more consistent terminology can enhance study design in biologically inspired research fields.
Biomechanical Optimization of the Human Bite Using Numerical Analysis Based on the Finite Element Method
Authors: González-Martín Maribel , Hermida-Cabrera Paula , Gutiérrez-Corrales Aida , Torres-Carranza Eusebio , Ruiz-de-León Gonzalo , García-Mira Berta , Martínez-González Álvaro-José , Torres-Lagares Daniel , Serrera-Figallo María-Ángeles , Gutiérrez-Pérez José-Luis , Baus-Domínguez María
Published: January 2025

Biomechanical bite analysis is essential for understanding occlusal forces and their distribution, especially in the design and validation of dental prostheses. Although the finite element method (FEM) has been widely used to evaluate these forces, the existing models often lack accuracy due to simplified geometries and limited material properties. Methods: A detailed finite element model was developed using Abaqus Standard 2023 software (Dassault Systemes, Vélizy-Villacoublay, France), incorporating scanned 3D geometries of mandibular and maxillary bones. The model included cortical and cancellous bones (Young’s modulus: 5.5 GPa and 13.7 GPa, respectively) and was adjusted to simulate bite forces of 220.7 N based on experimental data. Occlusal forces were evaluated using flexible connectors that replicate molar-to-molar interactions, and the stress state was analyzed in the maxillary and mandibular bones. Results: The FEM model consisted of 1.68 million elements, with mesh sizes of 1–1.5 mm in critical areas. Bite forces on the molars were consistent with clinical trials: first molar (59.3 N), second molar (34.4 N), and third molar (16.7 N). The results showed that the maximum principal stresses in the maxillary bones did not exceed ±5 MPa, validating the robustness of the model for biomechanical predictions. Conclusion: The developed model provides an accurate and validated framework for analyzing the distribution of occlusal forces in intact dentures. This approach allows the evaluation of complex prosthetic configurations and their biomechanical impact, optimizing future designs to reduce clinical complications and improve long-term outcomes. The integration of high-resolution FEM models with clinical data establishes a solid foundation for the development of predictive tools in restorative dentistry.
German Version of the Child Sexual Abuse Myth Scale (CSAMS-G): Translation, Expansion, and Construct Validation
Authors: Bayer Lennart , Cigelski Maike , Eilfgang Justine , Kraus Elisabeth Barbara , Mensing Frieda , Pülschen Simone
Published: January 2025

Research is needed on the myths regarding child sexual abuse in order to address commonly held misconceptions in persons training for professional careers in relevant fields for child protection. We present our translated, validated, and expanded Child Sexual Abuse Myth Scale (CSAMS-G). It was tested on a sample of 569 students studying either education, social work, law, or policing. Results of confirmatory factor analysis revealed a good model fit for our assumed factorial structure. Acceptable results on internal consistency were confirmed with McDonald’s ω. We also present the first results on the acceptance of child sexual abuse myths in our sample. Overall, myth acceptance was low, but a few exceptions were found, especially for the newly added items. We found group differences in factor scores for gender as well as between survivors and non-survivors of child sexual abuse.
Automating Dataset Generation for Object Detection in the Construction Industry with AI and Robotic Process Automation (RPA)
Authors: Araya-Aliaga Erik , Atencio Edison , Lozano Fidel , Lozano-Galant José
Published: January 2025

The construction industry is increasingly adopting artificial intelligence (AI) to enhance productivity and safety, with object detection in visual data serving as a vital tool. However, developing robust object detection models demands extensive, high-quality datasets, which are often difficult to generate and maintain in construction due to the dynamic and complex nature of job sites. This paper presents an innovative approach to automating dataset generation using robotic process automation (RPA) and generative AI techniques, specifically, DALL-E 2. This approach not only accelerates dataset creation but also improves model performance by delivering balanced, high-quality inputs. To validate the proposed methodology, a case study of a building construction site is conducted. In this study, three commonly used convolutional neural network architectures—RetinaNet, Faster R-CNN, and YOLOv5—are trained with the artificially generated dataset to automate the identification of formworks and rebars during construction.