bluuebunny/crossref_metadata_2025 huggingface dataset:
Satellite Selection Strategy and Method for Signals of Opportunity Navigation and Positioning with LEO Communication Satellites
Authors: Tao Yanhua , Guo Yang , Wang Shaobo , Yu Chuanqiang , Zhu Zimo
Published: January 2025

Experts and scholars from various nations have proposed studying low Earth orbit (LEO) satellite signals as the space-based signals of opportunity (SOPs) for navigation and positioning. This method serves as a robust alternative in environments where global navigation satellite systems (GNSS) are unavailable or compromised, providing users with high-precision, anti-interference, secure, and dependable backup navigation solutions. The rapid evolution of LEO communication constellations has spurred the development of SOPs positioning technology using LEO satellites. However, this has also led to a substantial increase in the number of LEO satellites, thereby reintroducing the traditional challenge of satellite selection. This research thoroughly examines three critical factors affecting positioning accuracy: satellite observable time, satellite elevation, and position dilution of precision (PDOP). It introduces a strategic approach for selecting satellites in LEO SOPs navigation and positioning. Simulation outcomes confirm that this satellite selection strategy effectively identifies visible satellites, ensuring precise positioning through LEO SOPs.
High-Temporal-Resolution Corrosion Monitoring in Fluctuating-Temperature Environments with an Improved Electrical Resistance Sensor
Authors: Takeyama Mao
Published: January 2025

The electrical resistance (ER) method is widely used for atmospheric corrosion measurements and can be used to measure the corrosion rate accurately. However, severe errors occur in environments with temperature fluctuations, such as areas exposed to solar radiation, preventing accurate temporal corrosion rate measurement. To decrease the error, we developed an improved sensor composed of a reference metal film and an overlaid sensor metal film to cancel temperature differences between them. The improved sensor was compared with an existing sensor product in outdoor monitoring experiments. The spike-like error during the daytime was successfully reduced. Furthermore, by utilizing a data-filtering process, we measured the corrosion rate every hour. Hourly corrosion rate measurements were difficult when the average daily corrosion rate was less than 50 µm/year under conditions of 0.05 g/m2 salt. Observations showed a strong correlation between corrosion rate and sensor surface humidity. In the future, this method will make it possible to study the relationship between the atmospheric corrosion rate and environmental changes over time.
An Inverse FEM for Structural Health Monitoring of a Containership: Sensor Network Optimization for Accurate Displacement, Strain, and Internal Force Reconstruction
Authors: Bardiani Jacopo , Oppezzo Christian , Manes Andrea , Sbarufatti Claudio
Published: January 2025

In naval engineering, particular attention has been given to containerships, as these structures are constantly exposed to potential damage during service hours and since they are essential for large-scale transportation. To assess the structural integrity of these ships and to ensure the safety of the crew and the cargo being transported, it is essential to adopt structural health monitoring (SHM) strategies that enable real-time evaluations of a ship’s status. To achieve this, this paper introduces an advancement in the field of smart sensing and SHM that improves ship monitoring and diagnostic capabilities. This is accomplished by a framework that combines the inverse finite element method (iFEM) with the definition of an optimal Fiber Bragg Gratings-based sensor network for the reconstruction of the full field of displacement; strain; and finally, cross-section internal forces. The optimization of the sensor network was performed by defining a multi-objective function that simultaneously considers the accuracy of the displacement field reconstruction and the associated cost of the sensor network. The framework was successfully applied to a mid-portion of a containership case, demonstrating its effective applicability in real and complex scenarios.
CANGuard: An Enhanced Approach to the Detection of Anomalies in CAN-Enabled Vehicles
Authors: Oladimeji Damilola , Jinad Razaq , Rasheed Amar , Baza Mohamed
Published: January 2025

As modern vehicles continue to evolve, advanced technologies are integrated to enhance the driving experience. A key enabler of this advancement is the Controller Area Network (CAN) bus, which facilitates seamless communication between vehicle components. Despite its widespread adoption, the CAN bus was not designed with security as a priority, making it vulnerable to various attacks. In this paper, we propose CANGuard, an Intrusion Detection System (IDS) designed to detect attacks on the CAN network and identify the originating node in real time. Using a simulated CAN-enabled system with four nodes representing diverse vehicle components, we generated a dataset featuring Denial-of-Service (DoS) attacks by exploiting the arbitration feature of the CAN bus, which prioritizes high-criticality messages (e.g., engine control) over lower-criticality ones (e.g., infotainment). We trained and evaluated several machine learning models for their ability to detect attacks and pinpoint the responsible node. Results indicate that Gradient Boosting outperformed other models, achieving high accuracy in both attack detection and node identification. While the Multi-Layer Perceptron (MLP) model demonstrated strong attack detection performance, it struggled with node identification, achieving less than 50% accuracy. These findings underscore the potential of tree-based models for real-time IDS applications in CAN-enabled vehicles.
Estimation of Forces and Powers in Ergometer and Scull Rowing Based on Long Short-Term Memory Neural Networks
Authors: Pitto Lorenzo , Simon Frédéric R. , Ertel Geoffrey N. , Gauchard Gérome C. , Mornieux Guillaume
Published: January 2025

Analyzing performance in rowing, e.g., analyzing force and power output profiles produced either on ergometer or on boat, is a priority for trainers and athletes. The current state-of-the-art methodologies for rowing performance analysis involve the installation of dedicated instrumented equipment, with the most commonly employed systems being PowerLine and BioRow. This procedure can be both expensive and time-consuming, thus limiting trainers’ ability to monitor athletes. In this study, we developed an easier-to-install and cheaper method for estimating rowers’ forces and powers based only on cable position sensors for ergometer rowing and inertial measurement units (IMUs) and GPS for scull rowing. We used data from 12 and 11 rowers on ergometer and on boat, respectively, to train a long short-term memory (LSTM) network. The LSTM was able to reconstruct the forces and power at the gate with an overall mean absolute error of less than 5%. The reconstructed forces and power were able to reveal inter-subject differences in technique, with an accuracy of 93%. Performing leave-one-out validation showed a significant increase in error, confirming that more subjects are needed in order to develop a tool that could be generalizable to external athletes.
An Open-Source Algorithm for Correcting Stress Wave Dispersion in Split-Hopkinson Pressure Bar Experiments
Authors: Van Lerberghe Arthur , Li Kin Shing O. , Barr Andrew D. , Clarke Sam D.
Published: January 2025

Stress wave dispersion can result in the loss or distortion of critical high-frequency data during high-strain-rate material tests or blast loading experiments. The purpose of this work is to demonstrate the benefits of correcting stress wave dispersion in split-Hopkinson pressure bar experiments under various testing situations. To do this, an innovative computational algorithm, SHPB_Processing.py, is created. Following the operational run through of SHPB_Processing.py’s capabilities, it is used to process test data acquired from split-Hopkinson pressure bar tests on aluminium, sand and kaolin clay samples, under various testing conditions. When comparing dispersion corrected and simple time shifting data obtained from SHPB experiments, accounting for dispersion removes spurious oscillations and improves the inferred measurement at the front of the specimen. The precision of the stress and strain results gathered from its application emphasises its importance through the striking contrast between its application and omission. This has a significant impact on the validity, accuracy and quality of the results. As a result, in the future, this tool can be utilised for any strain rate testing situation with cylindrical bars that necessitates dispersion correction, confinement, or stress equilibrium analysis.
Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer
Authors: Li Chaoyang , He Zhipeng , Lu Kai , Fang Chaoyang
Published: January 2025

Bird species detection is critical for applications such as the analysis of bird population dynamics and species diversity. However, this task remains challenging due to local structural similarities and class imbalances among bird species. Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information. However, this global information is essential for accurate bird species detection. To address this limitation, we propose BSD-Net, a bird species detection network. BSD-Net efficiently learns local and global information in pixels to accurately detect bird species. BSD-Net consists of two main components: a dual-branch feature mixer (DBFM) and a prediction balancing module (PBM). The dual-branch feature mixer extracts features from dichotomous feature segments using global attention and deep convolution, expanding the network’s receptive field and achieving a strong inductive bias, allowing the network to distinguish between similar local details. The prediction balance module balances the difference in feature space based on the pixel values of each category, thereby resolving category imbalances and improving the network’s detection accuracy. The experimental results using two public benchmarks and a self-constructed Poyang Lake Bird dataset demonstrate that BSD-Net outperforms existing methods, achieving 45.71% and 80.00% mAP50 with the CUB-200-2011 and Poyang Lake Bird datasets, respectively, and 66.03% AP with FBD-SV-2024, allowing for more accurate location and species information for bird detection tasks in video surveillance.
Bioremediation Potential of Sunflower-Derived Biosurfactants: A Bibliometric Description
Authors: Passos Wesley Araújo , Jesus Meirielly , Mata Fernando , Menezes Millena Souza , dos Santos Pablo Omar Lubarino , Santos Brenda Lohanny P. , Santana Hortência E. P. , Ruzene Denise Santos , Silva Daniel Pereira
Published: January 2025

Biosurfactants are amphiphilic molecules capable of reducing the surface tension of water and forming emulsions between immiscible liquids. These versatile molecules find applications in different industrial sectors, standing out in environmental applications, such as the bioremediation agents of contaminated environments. Bioremediation is an emerging sustainable method of controlling the degradation of waste. The present study carried out a bibliometric analysis, reviewing all research published in the SCOPUS database up to 2023, focused on producing biosurfactants from sunflowers with applications in this sustainable method of waste degradation. Using sunflowers to produce biosurfactants proved an ecological, sustainable, and economical alternative to conventional substrates. The results showed that only the seed husks, the oil derived from the seed, and the sunflower stems were used to produce biosurfactants, emphasizing oil as the most used raw material, probably due to its rich linoleic acid content. The preliminary selection detected only 12 articles that addressed the subject under analysis. According to these studies, the tested biosurfactants showed high potential for application in sustainable environmental bioremediation processes and were able to decontaminate soil, water, and liquid effluents. The bibliometric analysis was performed with the VOSviewer software to evaluate the quality of the publications and, above all, to show a more comprehensive scenario of the subject based on the following bibliometric indicators: the most productive journals, publications by country, the most cited articles, the most recurrent keywords, and most productive institutions. These insights will undoubtedly help scientists to develop new and sustainable practices of waste degradation and contribute to bioremediation research using biosurfactants from sunflowers. By showcasing the environmental benefits and practicality of sunflower-derived biosurfactants, this study contributes to the broader discourse on sustainable bioremediation, fostering innovative and eco-friendly waste management solutions.
Advances in Research on Desalination Technology for High-Sodium Wastewater
Authors: Li Zhucheng , Mao Chunchun , Zhang Jingwen , Hou Tianbao , Zhang Zixuan , Zhang Keqiang , Yang Peng , Yang Zengjun
Published: January 2025

Amidst escalating global water scarcity challenges, addressing industrial and agricultural wastewater treatment has emerged as a critical concern within environmental conservation efforts. Wastewater desalination technology not only mitigates salt pollution’s impact on ecosystems but also facilitates sustainable water resource management with significant economic and ecological advantages. This study delves into fundamental principles, methodologies, and application prospects in wastewater desalination technology by conducting a comprehensive assessment encompassing physical, chemical, and biological treatment approaches while scrutinizing their practical applicability through analysis of respective merits and drawbacks. Furthermore, this study illuminates specific operational impacts associated with diverse desalinization techniques employed in industrial or agricultural contexts based on prior research findings. The findings underscore that judicious selection of suitable desalinization methods along with optimization of operational parameters are pivotal factors influencing improved rates of sustainable wastewater desalinization. Finally, this paper proposes future directions and research focuses for wastewater desalination technology to provide a reference for related fields.
Navigating Research Frontiers in China’s Rural Planning: A Bibliometric Analysis of Sustainable Development
Authors: Xu Song , Gao Huichen
Published: January 2025

Since the onset of global industrialization, rural planning has evolved significantly in developed countries, establishing a comprehensive framework for sustainable development. However, China’s rural areas, rooted in longstanding agrarian traditions, face distinct challenges amid rapid urbanization and globalization, including land degradation, ecological degradation, and rural depopulation. This study examines the progression of rural planning in China, with a focus on Sustainable Development Goal 11 (SDG 11): “Sustainable Cities and Communities”. Employing a bibliometric approach, we analyzed the literature from the Web of Science database, concentrating on influential publications, collaborative patterns among research institutions, and emerging research themes. Findings reveal that Chinese rural planning research has expanded rapidly since 2004, characterized by interdisciplinary and cross-institutional collaborations. High-impact studies emphasize the transformation of rural settlements, land utilization, and urban–rural dynamics, reflecting an ongoing shift toward sustainable rural revitalization. Co-citation analysis identifies emerging themes such as resilience in rural development, land consolidation, and rural governance under environmental constraints. This study offers theoretical and empirical insights critical to advancing rural planning practices in China, proposing a framework for integrating sustainability into policy and guiding future research to optimize spatial layouts, preserve ecological resources, and support rural transformation aligned with China’s socioeconomic objectives.
Adaptive Cloud-Based Big Data Analytics Model for Sustainable Supply Chain Management
Authors: Stefanovic Nenad , Radenkovic Milos , Bogdanovic Zorica , Plasic Jelena , Gaborovic Andrijana
Published: January 2025

Due to uncertain business climate, fierce competition, environmental challenges, regulatory requirements, and the need for responsible business operations, organizations are forced to implement sustainable supply chains. This necessitates the use of proper data analytics methods and tools to monitor economic, environmental, and social performance, as well as to manage and optimize supply chain operations. This paper discusses issues, challenges, and the state of the art approaches in supply chain analytics and gives a systematic literature review of big data developments associated with supply chain management (SCM). Even though big data technologies promise many benefits and advantages, the prospective applications of big data technologies in sustainable SCM are still not achieved to a full extent. This necessitates work on several segments like research, the design of new models, architectures, services, and tools for big data analytics. The goal of the paper is to introduce a methodology covering the whole Business Intelligence (BI) lifecycle and a unified model for advanced supply chain big data analytics (BDA). The model is multi-layered, cloud-based, and adaptive in terms of specific big data scenarios. It comprises business process modeling, data ingestion, storage, processing, machine learning, and end-user intelligence and visualization. It enables the creation of next-generation BDA systems that improve supply chain performance and enable sustainable SCM. The proposed supply chain BDA methodology and the model have been successfully applied in practice for the purpose of supplier quality management. The solution based on the real-world dataset and the illustrative supply chain case are presented and discussed. The results demonstrate the effectiveness and applicability of the big data model for intelligent and insight-driven decision making and sustainable supply chain management.
Readiness for Industry 4.0 in a Medical Device Manufacturer as an Enabler for Sustainability, a Case Study
Authors: McDermott Olivia , Stam Dudley Luke , Duarte Susana , Sony Michael
Published: January 2025

This research aims to determine the state of Industry 4.0 readiness and to identify the best practices, challenges, and barriers to implementing Industry 4.0 technology in a medical device manufacturer, thus aiding in improving sustainability. Semi-structured interviews were completed with 12 senior executives representing a wide array of functions in a single large medical device manufacturer. Convenience sampling was used to analyse the interview transcripts to draw out themes that were then discussed and analysed with findings from the literature review. This research determined the state of Industry 4.0 readiness in the case study of medical device manufacturers. This research identified several best practices, challenges, and barriers to implementing Industry 4.0 technology. Currently, there are few case studies in the literature that have a medical device manufacturer as the case study for Industry 4.0 readiness. There are even fewer articles that tackle Industry 4.0 implementation across the entire medical device industry. There is currently no published literature that analyses the best practices for implementing Industry 4.0 in a medical device manufacturer. The best practices for Industry 4.0 implementation identified in this study can be beneficial to stakeholders in the medical device industry and within the healthcare sector, help them plan current and future Industry 4.0 programmes, improve sustainability in their companies, as well as optimise patient treatment and approaches.
Sustainable Intensification of the Montado Ecosystem: Evaluation of Sheep Stocking Methods and Dolomitic Limestone Application
Authors: Carreira Emanuel , Serrano João , Shahidian Shakib , Infante Paulo , Paniagua Luís L. , Moral Francisco , Paixão Luís , Gomes Carlos Pinto , de Castro José Lopes , de Carvalho Mário , Pereira Alfredo F.
Published: January 2025

The objective of this study was to determine how application of dolomitic limestone and stocking methods (continuous stocking or deferred stocking) affect the soil compaction, sheep grazing location, height, and nutritional value of pastures when the pasture growth rate is at its maximum. A 4 ha field at Mitra farm—University of Évora—was divided into four plots: P1 and P2—without application of dolomitic limestone, continuous stocking (CS), and deferred stocking (DS), respectively—and P3 and P4—with application of dolomitic limestone, DS (2.3 AUE), and CS (1 AUE), respectively. In DS, animals were placed and removed from the plots depending on the height of the pasture (entry ≥ 10 cm; removal ≤ 5 cm). Throughout the pasture’s vegetative cycle, several measurements of pasture height and cut were carried out. From the beginning of March to the beginning of June, animal behavior was observed (animals’ activity grazing and location) by trained observers through binoculars on six dates. The results show the following: (i) the application of dolomitic limestone combined with CS provided higher values of pasture height; (ii) there were no significant differences in pasture quality between treatments; (iii) DS led to 50% more sheep grazing days that CS; (iv) there were no significant differences in soil compaction between CS and DS; and (v) the stocking methods and the application of dolomitic limestone did not seem to change the grazing pattern between treatments. This study constitutes a basis to support more informed decisions by agricultural managers and may also contribute to maintaining balance in the Montado ecosystem, as well as increasing the efficiency of livestock production systems based on rainfed pastures.
Spillover Effects of Currency Interactions Across Economic Cycles: A Quantile-VAR Analysis
Authors: Liang Zhuqin , Ismail Mohd Tahir
Published: January 2025

This study employs Markov-Switching Regression (MS-Regression) to model four macroeconomic indicators—US GDP, CPI, interest rate, and unemployment rate—to identify economic crisis cycles, while all indicators provide some level of insight into these cycles, the unemployment rate offers the closest alignment with the actual patterns of economic cycles. Based on the regime identification derived from the unemployment rate, we delineate the time series for expansion and recession periods. Subsequently, we apply the Quantile Vector Autoregression (Quantile-VAR) model to analyze three sets of time series: the entire dataset, the expansion period, and the recession period. Our findings reveal that, under normal conditions, the US dollar exerts the greatest influence on and is most influenced by other currencies, whereas the Australian dollar has the least impact on others. In the extreme lower and upper tails, the mutual influence among the currencies of different countries intensifies, concurrently diminishing the relative influence of the US dollar. Notably, the spillover effects under extreme lower and upper tail conditions are not consistent, as the occurrence of extreme values does not coincide, suggesting an asymmetry in the spillover effects at these quantiles.
The Limits of Riemann Solutions for Chaplygin Gas Magnetohydrodynamics Euler Equations with Active Terms
Authors: Yu Kangning , Xu Wenxia , Yang Jibin , Li Shuo , Li Guodong
Published: January 2025

Chaplygin gas magnetohydrodynamics Euler equations with active terms are often used to study physical phenomena in the universe, which is of great significance for exploring unknown fields. This article mainly studies the limited behavior of Riemann solutions of Chaplygin gas magnetohydrodynamics Euler equations with active terms using methods such as the characteristic line method and the Lax–Friedrichs method. In cases where only the magnetic field disappears, it was found, using the characteristic line method, that the solution converges to Chaplygin gas magnetohydrodynamics Euler equations with active terms. Additionally, we have identified the cause of the generation of δ shock waves. When pressure and magnetic induction disappear simultaneously, the reasons for the generation of δ shock waves and vacuum solutions are found. In the Discussion section, the Lax–Friedrichs method was used for numerical experiments to simulate the occurrence of phenomena such as mass concentration and vacuum. The innovation of this article lies in the construction of the Riemann problem for Chaplygin gas MHD Euler equations with active terms, as well as the study of the scenario where the magnetic field and pressure gradually weaken and approach zero. Finally, numerical experiments are used to verify the theoretical results. Compared with previous work, this article not only focuses on theoretical derivation, but also applies numerical simulation, especially simulating the characteristic lines of physical planes. This achievement provides a powerful tool for studying more complex Riemann problems.
Coordinated Development of Urban Transportation Structure Optimization and Energy Conservation, and Emission Reduction Under the Low-Carbon Background in Lanzhou, China
Authors: Shi Zheming , Qian Yongsheng , Zeng Junwei , Wei Xu , Yang Minan
Published: January 2025

Under the context of low-carbon travel, promoting the green and environmentally friendly upgrade of urban transportation and optimizing urban transportation structures are of great significance in reducing carbon emissions. Exploring the pathways and methods to achieve green and low-carbon goals in urban transportation is a key research objective. Accordingly, this study constructs a multi-objective optimization model to optimize the transportation structure of Lanzhou City and quantitatively verifies the optimization effects through carbon emission calculations and coordination evaluations. The results indicate that (1) optimizing urban transportation structures can reduce energy consumption and emission levels but cannot achieve the “carbon peaking” goal; (2) developing urban rail transit has a significant positive impact on energy saving and emission reduction; (3) the development of green transportation is closely integrated with and mutually influenced by slow-moving transportation, showing both synergy and constraints; and (4) under the comprehensive restriction scenario, despite higher energy consumption and emission values, better coordination is achieved, making it the most suitable optimization plan aligned with the green transportation development concept.
Balancing E-Commerce Platform and Manufacturer Goals in Sustainable Supply Chains: The Impact of Eco-Friendly Private Labels
Authors: Liu Zhiheng , Cui Xiangcheng , Ji Yuanyuan
Published: January 2025

This paper analyzes how consumer preferences for eco-friendly private labels affect platform selling formats and manufacturer channel strategies. We construct a game-theoretic model that encompasses both an e-commerce platform and a manufacturer. In this model, the platform chooses its selling format—either wholesale or agency—while the manufacturer determines whether to launch an online direct channel. Our analysis takes into account consumer preferences for both product brands and sales channels. We compare and analyze the equilibrium outcomes across four different scenarios, leading to the following conclusions: (1) When the platform utilizes the wholesale selling format, the manufacturer is consistently motivated to launch the direct channel if the costs associated with it are low. Conversely, when the platform employs the agency selling format, the manufacturer’s decision to establish an online direct marketing channel depends on the relative strength of consumers’ eco-friendly and channel preferences. (2) The platform’s choice of selling format is affected by the manufacturer’s channel strategy, leading the platform to modify its selling format based on varying manufacturer channel approaches. (3) The choices of the platform’s selling format and the manufacturer’s channel strategy are not always in conflict. When consumer preferences for the manufacturer’s direct channel are strong and the cost of introducing it is moderate, the platform’s decision to adopt the agency selling format can create a win-win outcome for both the platform and the manufacturer. And the establishment of online channels by manufacturers further enhances the sustainable growth of eco-friendly products.
Aromaticity as a Useful Descriptor of Pharmacological Activity: A Case Study of Quinoline-Based Antimalarial Agents
Authors: Behzadi Hadi , Zborowski Krzysztof K.
Published: January 2025

Aromatic properties of two series of quinoline derivatives were studied theoretically using the Density Functional Theory (DFT) approach. One series of compounds possesses antimalarial activity while the other does not have such properties. The B3LYP functional and the 6-311++G** basis set were employed in the study. The optimized geometries of the studied compounds were used for aromaticity level determination using several aromaticity indices, like HOMA, NICS, PDI, I6, FLU, and PLR. It was shown that the level of aromaticity seems to be a feature that differentiates these two series of compounds. This is reasonable because it has been presented, previously in the literature, that this type of drug acts as an antimalarial drug through the formation of the π-π complex with ferriprotoporphyrin. There are two types of rings in the quinoline system, a benzene type, and a pyridine type. The aromaticity of the benzene-type ring in both series of studied compounds is similar while the aromaticity of the pyridine-type ring is lower for compounds that have antimalarial properties. It is derived on the basis of performed research that the properties of the pyridine-type ring are more important for the drug activity of studied compounds.
Improvement in XIa Selectivity of Snake Venom Peptide Analogue BF9-N17K Using P2′ Amino Acid Replacements
Authors: Ding Li , Zhai Zhiping , Qin Tianxiang , Lin Yuexi , Shuang Zhicheng , Sun Fang , Qin Chenhu , Luo Hongyi , Zhu Wen , Ye Xiangdong , Chen Zongyun , Luo Xudong
Published: January 2025

Coagulation factor XIa is a new serine-protease family drug target for next-generation anticoagulants. With the snake venom Kunitz-type peptide BF9 as the scaffold, we obtained a highly active XIa inhibitor BF9-N17K in our previous work, but it also inhibited the hemostatic target plasmin. Here, in order to enhance the selectivity of BF9-N17K toward XIa, four mutants, BF9-N17K-L19A, BF9-N17K-L19S, BF9-N17K-L19D, and BF9-N17K-L19K, were further designed using the P2′ amino acid classification scanning strategy. The anticoagulation assay showed that the four P2′ single-point mutants still had apparent inhibitory anticoagulation activity that selectively inhibited the human intrinsic coagulation pathway and had no influence on the extrinsic coagulation pathway or common coagulation pathway, which indicated that the single-point mutants had minimal effects on the anticoagulation activity of BF9-N17K. Interestingly, the enzyme inhibitor assay experiments showed that the XIa and plasmin inhibitory activities were significantly changed by the P2′ amino acid replacements. The XIa inhibitory activity of BF9-N17K-L19D was apparently enhanced, with an IC50 of 19.28 ± 2.53 nM, and its plasmin inhibitory was significantly weakened, with an IC50 of 459.33 ± 337.40 nM. BF9-N17K-L19K was the opposite to BF9-N17K-L19D, which had enhanced plasmin inhibitory activity and reduced XIa inhibitory activity. For BF9-N17K-L19A and BF9-N17K-L19S, no apparent changes were found in the serine protease inhibitory activity, and they had similar XIa and plasmin inhibitory activities to the template peptide BF9-N17K. These results suggested that the characteristics of the charge of the P2′ site might be associated with the drug selectivity between the anticoagulant target XIa and hemostatic target plasmin. In addition, according to the molecular diversity and sequence conservation, a common motif GR/PCR/KA/SXIP-XYGGC is proposed in the XIa-inhibitory Kunitz-type peptides, which might provide a new clue for further peptide engineering. In conclusion, through P2′ amino acid classification scanning with the snake venom Kunitz-type peptide scaffold, a new potent and selective XIa inhibitor, BF9-N17K-L19D, was discovered, which provides a new XIa-targeting lead drug template for the treatment of thrombotic-related diseases.
Impact of COVID-19 on Ocular Surface Health: Infection Mechanisms, Immune Modulation, and Inflammatory Responses
Authors: Huang Duliurui , Xuan Weixia , Li Zhijie
Published: January 2025

COVID-19, caused by SARS-CoV-2, has presented formidable challenges to global health since its emergence in late 2019. While primarily known for respiratory symptoms, it can also affect the ocular surface. This review summarizes the effects of SARS-CoV-2 on ocular surface immunity and inflammation, focusing on infection mechanisms, immune responses, and clinical manifestations. Ocular symptoms, though uncommon, include conjunctivitis, dry eye, and blurred vision. SARS-CoV-2 binds to ACE2 receptors in ocular surface epithelial cells, facilitating viral entry, replication, and local dissemination. The innate immune responses involving corneal epithelial cells and immune cells are discussed, alongside mechanisms of antigen presentation and adaptive immunity. The review also examines the roles of cytokines and chemokines in mediating ocular surface inflammation and explores the impact of cytokine storms and chronic inflammation on ocular health. Additionally, the interplay between systemic and ocular immune responses is highlighted, analyzing how systemic COVID-19 inflammation influences ocular surface health. These insights underscore the broader implications of COVID-19 beyond localized ocular infection. By consolidating current findings, this review aims to guide preventive and therapeutic strategies while identifying directions for future research to mitigate the ocular consequences of COVID-19.
Conserved Nuclear Localization Signal in NS2 Protein of Bombyx Mori Bidensovirus: A Potential Invertebrate ssDNA Virus Trait
Authors: Yu Qian , Yan Jiaxin , Chen Ying , Zhang Jinfeng , Tang Qi , Zhu Feifei , Sun Lindan , Ma Shangshang , Liu Xiaoyong , Chen Keping , Yao Qin
Published: January 2025

Bombyx mori bidensovirus (BmBDV), a significant pathogen in the sericulture industry, holds a unique taxonomic position due to its distinct segmented single-stranded DNA (ssDNA) genome and the presence of a self-encoding DNA polymerase. However, the functions of viral non-structural proteins, such as NS2, remain unknown. This protein is hypothesized to play a role in viral replication and pathogenesis. To investigate its structure and function, we employed phylogenetic analysis, subcellular localization, mutational analysis, and a dual-luciferase reporter system to characterize the nuclear localization signal (NLS) within NS2 and its effect on viral promoter activity. Additionally, co-immunoprecipitation and mass spectrometry were utilized to identify host proteins interacting with NS2. We identified a functional bipartite NLS in NS2, validated the combination pattern of key amino acids, and demonstrated its role in regulating viral promoter activity. Furthermore, we identified potential NLSs in NS2 homologs in other invertebrate ssDNA viruses based on sequence analysis. We also revealed interactions between NS2 and host nuclear transport proteins, suggesting that it plays a role in nuclear transport and viral replication. This research underscores the importance of NS2’s NLS in BmBDV’s life cycle and its potential conservation across invertebrate ssDNA viruses, providing insights into virus–host interactions and avenues for antiviral strategy development.
Development of a Recombinant Fusion Vaccine Candidate Against Lethal Clostridium botulinum Neurotoxin Types A and B
Authors: Choi Eun-Sun , Pyo Seong-Wook , Kim So-Hyeon , Jeon Jun-Ho , Rhie Gi-Eun , Yun Mi-Ran , Yi Hwajung , Chung Yoon-Seok
Published: January 2025

Background: Botulinum neurotoxins (BoNTs), produced by Clostridium botulinum, are potent protein toxins that can cause botulism, which leads to death or neuroparalysis in humans by targeting the nervous system. BoNTs comprise three functional domains: a light-chain enzymatic domain (LC), a heavy-chain translocation domain (HCN), and a heavy-chain receptor-binding domain (HCC). The HCC domain is critical for binding to neuronal cell membrane receptors and facilitating BoNT internalization via endocytosis. Accordingly, it may serve as a vaccine candidate, inducing anti-BoNT-neutralizing antibodies in animals. Here, we aimed to develop a vaccine capable of simultaneously defending against both BoNT/A and B. Methods: We combined the HCC domains of botulinum neurotoxin type A (BoNT/A) and botulinum neurotoxin type B (BoNT/B) in Escherichia coli to produce a recombinant protein (rHCCB-L-HCCArHCcB) that offers dual protection against both toxins by inhibiting their receptor binding. To evaluate the efficacy of the vaccine, mice were immunized intramuscularly with rHCCB-L-HCCA plus alum thrice at 2-week intervals, followed by the assessment of immunogenicity and protective efficacy. Results: The antibody titer in mice immunized with rHCCB-L-HCCA was significantly higher than that in mice immunized with alum alone, protecting them from the lethal challenges of BoNT/A (105 50% lethal dose, LD50) and B (103 LD50). Conclusion: These findings suggest that rHCCB-L-HCCA may simultaneously be an effective vaccine candidate against BoNT/A and B.
Parental Attitudes, Motivators and Barriers Toward Children’s Vaccination in Poland: A Scoping Review
Authors: Szalast Krystyna , Nowicki Grzegorz Józef , Pietrzak Mariola , Mastalerz-Migas Agnieszka , Biesiada Aleksander , Grochans Elżbieta , Ślusarska Barbara
Published: January 2025

Background: Vaccination is one of the most effective ways of protecting individuals against serious infectious diseases and their fatal consequences. Objectives: The aim of this scoping review was to synthesize data on parental attitudes toward vaccination and identify factors influencing the motivators and barriers to children’s vaccination based on Polish studies. Methods: The scoping review process and reporting were based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScRs) checklist. In the period between January 2014 and July 2024, the following databases were searched for publications: PubMed, Web of Science, Cochrane, Ebsco, and Scholar Google. Results: A total of 1531 potentially relevant records were reviewed, and 30 original publications from research samples collected in Poland were selected. According to the findings, vaccination rates varied between 100% and 70%, with parental acceptance levels for mandatory vaccination ranging from 99% to 65%. Parents most commonly cited the physician, the nurse, and the Internet as their primary sources of vaccination-related information. Moreover, parental primary motivators for vaccinating their children were prevention against infectious diseases, the opinion that vaccines are safe, and the belief that childhood vaccination is right and effective. The major barriers to vaccination were fear of vaccine side effects and the belief that vaccines are ineffective. Parents that were better educated, were of younger age, lived in cities, and had a higher income were much more likely to vaccinate their children. Conclusions: Understanding parental attitudes toward vaccination may help develop an educational program aimed at combating misinformation and increasing childhood vaccination coverage rates.
Enhancing the Fluoride Adsorption Efficiency of Diatomaceous Earth Through Modification with Ce/Al/Fe Metal Oxides
Authors: Budeli Tshilidzi L. , Gitari Wilson M. , Mudzielwana Rabelani
Published: January 2025

Sustainable Development Goal 6.1 calls for the development of technologies to improve water quality for human consumption to ensure that there is clean drinking water for everyone by 2030. This study aims to contribute to the goal by synthesizing Ce/Al/Fe metal oxide-modified diatomaceous earth for the adsorption of fluoride from drinking water. Adsorption experiments were performed to determine the effectiveness of the Ce/Al/Fe metal oxide-modified diatomaceous earth in regard to fluoride adsorption. About 98% fluoride removal efficiency was obtained from an initial fluoride concentration of 5 mg/L, using a 0.6 g/100 mL adsorbent dosage, at an initial pH range from 4 to 10, after 50 min agitation time. The adsorption kinetics models revealed that fluoride adsorption occurred via chemisorption, while the isotherm models confirmed both monolayer and multilayer adsorption. Thermodynamic studies showed that the adsorption process was spontaneous, endothermic, and random, as denoted by the negative ΔG°, positive ΔH°, and positive ΔS°, respectively. Regeneration studies showed that Ce/Al/Fe metal oxide-modified diatomaceous earth can be reused for eight successive regeneration–reuse cycles. This study revealed that the modification of diatomaceous earth with Ce/Al/Fe metal oxides enhances its fluoride adsorption capacity and that it is suitable for use in the defluoridation of groundwater.
Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision
Authors: Xu Yueda , Xing Yanfeng , Zhao Hongbo , Lin Yufang , Ren Lijia , Zhou Zhihan
Published: January 2025

The positioning of lithium battery tabs in electric vehicles is a crucial aspect of the power battery assembly process. During the pre-tightening process of the lithium battery stack assembly, cells and foams undergo different deformations, leading to varying displacements of cells at different levels. Consequently, determining tab positions poses numerous challenges during the pre-tightening process of the stack assembly. To address these challenges, this paper proposes a method for detecting feature points and calculating the displacement of lithium battery stack tabs based on the MicKey method. This research focuses on the cell tab, utilizing the hue, saturation, and value (HSV) color space for image segmentation to adaptively extract the cell tab region and further obtain the ROI of the cell tab. In order to enhance the accuracy of tab displacement calculation, a novel method for feature point detection and displacement calculation of lithium battery stacks based on the MicKey (Metric Keypoints) method is introduced. MicKey can predict the coordinates of corresponding keypoints in the 3D camera space through keypoint matching based on neural networks, and it can acquire feature point pairs of the subject to be measured through its unique depth reduction characteristics. Results demonstrate that the average displacement error and root mean square error of this method are 0.03 mm and 0.04 mm, respectively. Compared to other feature matching algorithms, this method can more consistently and accurately detect feature points and calculate displacements, meeting the positioning accuracy requirements for the stack pole ear in the actual assembly process. It provides a theoretical foundation for subsequent procedures.
EFEITO DA BIOAUMENTAÇÃO DE BACTÉRIAS NITRIFICANTES AUTÓCTONES EM CULTIVO INTENSIVO DE CAMARÃO MARINHO LITOPENAEUS VANNAMEI EM SISTEMA DE BIOFLOCOS EM BAIXA SALINIDADE
Authors: Da Silva Jéssica Lucinda Saldanha , Rodríguez Marina Teresa Torres , Soares Danyela Carla Elias , Marques Ricardo Rios , De Sousa Oscarina Viana
Published: January 2025

A pesquisa teve como objetivo avaliar os efeitos da bioaumentação com estirpes nitritifcantes autoctónes de sistemas de bioflocos (BFT) sobre os parâmetros qualidade de água e desempenho zootécnico do camarão marinho Litoenaeus vannamei em um sistema de produção intensivo. O experimento foi conduzido com a avaliação de dois grupos experimentais: suplementado com probiótico comercial (BF-PC) e suplementado com bactérias probióticas autóctones (BF-PA). Nos resultados obtidos, os camarões cultivados com o tratamento BF-PA apresentaram maior taxa de sobrevivência, crescimento em peso médio, biomassa final e produtividade em comparação com os animais do tratamento BF-PC. As variáveis ambientais da água de cultivo (pH, oxigênio dissolvido e temperatura) apresentaram o mesmo comportamento nos tratamentos. O uso de estirpes bacterianas autóctones com potencial probiótico, empregado no tratamento BF-PA, promoveu a formação e o desenvolvimento mais estável da comunidade microbiana nos sistemas de bioflocos, tendo efeito bioaumentador, contribuindo para uma maior estabilidade dos sistemas de cultivo, o que levou a uma melhoria do desempenho zootécnico dos animais.
Interactive effects of some coastal metal contaminant and environmental variables in the performance of the tropical winged pearl oyster Pteria colymbus (Mollusca: Bivalvia), in hanging culture
Authors: Pinto Rafael , Ramírez Enmary , Núñez Maximiano , Narvaéz Mariela , Dale Andrew W. , Freites Valbuena Luis Felipe
Published: January 2025

| The present study aimed to evaluate the interactive effect between the concentration of several pollutants metals (Zn, Cd, Mn, and Cu) detected in the soft tissue of the winged oyster Pteria colymbus and the environmental variables that occurred during the culture period. Quantification of contaminants was performed by inductively coupled plasma optical emission spectrophotometry. Monthly sampling of environmental variables in the water column included total particulate matter (TPM), organic fractions (POM) and inorganic fractions (PIM), temperature, dissolved oxygen, chlorophyll a (Chl-a), and the upwelling index. The results showed a decreasing order in the levels of Zn > Cd > Mn > Cu. The principal components analysis showed a significant and direct relationship between the upwelling index and Zn, Cd, and Cu, and an inverse and significant relationship with Mn. On the other hand, this analysis also showed an inverse and significant relationship between Zn, Cu, and Cd with the temperature (cold waters), suggesting that the source of the availability of these contaminants is not local and that it depends more on the transport of water masses caused probably by the action of upwelling. Due to the high concentration levels of Zn and Cd, the consumption of P. colymbus cannot be considered safe according to the tolerable limits of these contaminants, which exceeded the allowed levels. However, interest in the cultivation of members of the Pteriidae family does not decay due to the great benefit of their potential to produce round and mabé pearls.