bluuebunny/crossref_metadata_2025 huggingface dataset:
Lubricant Viscosity Impact in Fuel Economy: Experimental Uncertainties Compensation
Authors: Rovai Fernando Fusco , Tomanik Eduardo
Published: January 2025

Climate constraints impose greenhouse gas emissions mitigation, and passenger cars have considerable contributions to contribute to this. To improve the engine efficiency of vehicles equipped with conventional powertrains, many technologies are available but with limited individual contribution. The experimental assessment of some technology regarding fuel economy measurement results is sometimes lower than test uncertainties. This study proposes a methodology to compensate the fuel economy for two test uncertainties: vehicle speed variations and battery recharging. The proposed method can be applied when investigating the effects of different vehicle design changes, including engine power cell design. In this work, the proposed method is demonstrated on the test of two oils: one 5W40, the other 5W20, both without FM. Applying the proposed methodology to experimental results, the expected higher influence of oil viscosity on urban conditions could be observed, and the experimental results presented a much better correlation with the vehicle numerical simulation. Applying the proposed compensation, fuel savings of using the 5W20 in comparison to the 5W40 oil was 3.5% under urban conditions and 2.0% on highways.
Isothermal and Thermomechanical Fatigue Behavior of 316LN Stainless Steel Under Torsional Loading
Authors: Zheng Yiming , Wang Fang , Xu Caijun
Published: January 2025

316LN austenitic stainless steel is extensively utilized within the domain of nuclear power, where its susceptibility to high-temperature fatigue and thermomechanical fatigue has emerged as a pivotal area of research for this material. Nevertheless, prior investigations have predominantly concentrated on axial loading outcomes, with a notable absence of studies examining its fatigue failure behavior under torsional loading conditions. The present study undertakes isothermal fatigue testing at temperatures of 450 °C, 550 °C, and 650 °C, along with thermomechanical fatigue testing across a temperature range of 350–550 °C, with strain amplitudes of 0.6%, 0.8%, and 1.2%. The findings reveal that secondary hardening observed under conditions of small deformation is primarily attributed to the enhancement of frictional stress, stemming from the accumulation of planar slip. Furthermore, as the temperature escalates, variations are observed in the intensity of the dynamic strain aging and the dislocation density within the material.
Analytical Bounds for Mixture Models in Cauchy–Stieltjes Kernel Families
Authors: Alsharari Fahad , Fakhfakh Raouf , Alshahrani Fatimah
Published: January 2025

Mixture models are widely used in mathematical statistics and theoretical probability. However, the mixture probability distribution is rarely explicit in its formula. One must then decide whether to keep the parent probability distribution or to obtain an approximation of the mixture probability distribution. In such cases, it is essential to estimate or evaluate the distance between a mixture probability distribution and its parent probability distribution. On the other hand, orthogonal polynomials offer a versatile mathematical tool for approximating, fitting, and analyzing mixture models, facilitating more accurate and efficient modeling in statistics and data science. This article considers mixture models in Cauchy–Stieltjes Kernel (CSK) families. Using a suitable basis of polynomials, we obtain an expression for the distance in the L2-norm between the mixed probability distribution and its parent probability distribution which belongs to a given CSK family. For the distance between the corresponding distribution functions, bounds are derived in L1-norm. The results are illustrated by some examples from quadratic CSK families.
The Graph Attention Recommendation Method for Enhancing User Features Based on Knowledge Graphs
Authors: Wang Hui , Li Qin , Luo Huilan , Tang Yanfei
Published: January 2025

Knowledge graphs have shown great potential in alleviating the data sparsity problem in recommendation systems. However, existing graph-attention-based recommendation methods primarily focus on user–item–entity interactions, overlooking potential relationships between users while introducing noisy entities and redundant high-order information. To address these challenges, this paper proposes a graph-attention-based recommendation method that enhances user features using knowledge graphs (KGAEUF). This method models user relationships through collaborative propagation, links entities via similar user entities, and filters highly relevant entities from both user–entity and user–relation perspectives to reduce noise interference. In multi-layer propagation, a distance-aware weight allocation mechanism is introduced to optimize high-order information aggregation. Experimental results demonstrate that KGAEUF outperforms existing methods on AUC and F1 metrics on the Last.FM and Book-Crossing datasets, validating the model’s effectiveness.
The Impact of Sodium-Glucose Co-Transporter-2 Inhibition on Insulin Resistance and Inflammation in Patients with Type 2 Diabetes: A Retrospective Study
Authors: Iordan Liana , Lazar Sandra , Timar Romulus , Popescu Simona , Sorescu Teodora , Albai Oana , Braha Adina , Timar Bogdan , Gaita Laura
Published: January 2025

Background and Objectives: Insulin resistance (IR) is a key factor involved in the development of type 2 diabetes (T2D). Besides its role in the pathogenesis of T2D, insulin resistance is associated with impairment of glycemic control, reduced achievement of glycemic targets, and increases in cardiovascular risk and diabetes complications, being thus a negative prognosis factor. Sodium-glucose co-transporter-2 inhibitors (SGLT2i) are therapies for T2D which demonstrated, besides glycemic control, improvements of biomarkers traditionally associated with IR and inflammation. This study aimed to evaluate the impact of SGLT2i treatment on IR and inflammation biomarkers in patients with T2D. Materials and Methods: In a retrospective study, 246 patients with T2D treated with SGLT2i for a median of 5 years were evaluated regarding IR (estimated glucose disposal rate—eGDR, triglyceride/glucose index, triglyceride/HDLc index) and inflammation biomarkers (neutrophils to lymphocyte ratio, platelets to lymphocytes ratio and C-reactive protein) before and after intervention with SGLT2i. Results: After a median 5 years of SGLT2i treatment, patients with T2D had a higher eGDR (6.07 vs. 5.24 mg/kg/min; p < 0.001), lower triglyceride/HDLc ratio (3.34 vs. 3.52, p < 0.001) and lower triglyceride/glucose index (9.23 vs. 9.58; p < 0.001). The inflammation biomarkers decreased after SGLT2i therapy: C-reactive protein (3.07 mg/L vs. 4.37 mg/L), NLR (0.68 vs. 0.72; p < 0.001), and PLR (115 vs. 122; p < 0.001). Intervention with SGLT2i also improved the biomarkers associated with diabetes complications and cardiovascular risk: HbA1c (7.1% vs. 8.4%; p < 0.001), body mass index (30.0 vs. 31.5 kg/m2; p < 0.001) and urinary albumin to creatinine ratio (4.75 vs. 11.00 mg/g; p < 0.001). Conclusions: Treatment with SGLT2i in patients with T2D leads to decreases in IR and inflammation. These mechanisms may partially explain the additional cardiovascular and renal risk reductions associated with SGLT2i therapy, alongside the improvements in glycemic control, in patients with T2D.
Integration of Arc and Microstructural Analysis for Anomaly Detection in Walls Manufactured by GMA-Based WAAM
Authors: Santos Lucas J. E. B. , Souto Joyce I. V. , Azevedo Igo J. S. , Castro Walman B. , Lima Jefferson S. , Delgado João M. P. Q. , Santana Renato A. C. , Gomez Ricardo S. , Bezerra André L. D. , Lima Antonio G. B.
Published: January 2025

Wire Arc Additive Manufacturing (WAAM) is a process for fabricating metal parts known for its high productivity and material flexibility. However, defects such as overheating, residual stresses, distortions, porosity, and a non-homogeneous microstructure limit its commercial applications. Therefore, the present study aims to analyze the correlation between electrical sensing anomalies in the Gas Metal Arc (GMA) during WAAM and the occurrence of microscopic defects caused by external contamination. To achieve this, experiments were conducted to fabricate walls using WAAM with controlled contaminant introduction. Simultaneously, electrical arc data, specifically voltage and current, were segmented and acquired during the wall deposition process. Metallographic analysis confirmed the presence of microscopic defects or changes in the solidification patterns in regions with contaminant inclusion, distinguishing them from other areas of the analyzed samples. Similarly, the contaminations were proven to cause anomalies in attributes associated with the electrical arc. Therefore, this approach confirms the criticality of electrical arc monitoring in WAAM, as it demonstrates that anomalies in the electrical arc could lead to microstructural consequences.
Decoration of Silver Nanoparticles on WS2-WO3 Nanosheets: Implications for Surface-Enhanced Resonance Raman Spectroscopy Detection and Material Characteristics
Authors: Al Youssef Khaled , Chauvin Adrien , Colomer Jean-François , Bittencourt Carla
Published: January 2025

This study investigates the chemical and structural modifications of vertically aligned tungsten disulfide–tungsten trioxide (WS2-WO3) nanosheets decorated with silver nanoparticles (Ag(NPs)) under nitrogen plasma conditions. The synthesized vertically aligned WS2-WO3 nanosheets were functionalized through direct-current (DC) magnetron sputtering, forming silver-decorated samples. Structural changes, as well as the size and distribution of Ag(NPs), were characterized using scanning electron microscopy (SEM). Chemical state analysis was conducted via X-ray photoelectron spectroscopy (XPS), while Raman spectroscopy was employed to investigate vibrational modes. The findings confirmed the successful decoration of Ag(NPs) and identified unexpected compound transformations that were dependent on the duration of functionalization. The synthesized and functionalized samples were evaluated for their sensing capabilities towards Rhodamine B (RhB) through surface-enhanced resonance Raman scattering (SERRS). This study discusses the impact of substrate morphology and the shape and size of nanoparticles on the enhancement of SERRS mechanisms, achieving an enhancement factor (EF) of approximately 1.6 × 106 and a limit of detection (LOD) of 10−9 M.
The Mediating Role of Self-Criticism in the Relationship Between Coaches’ Leadership Styles and Disordered Eating in Athletes
Authors: Coelho Carol , Oliveira Diane , Branco Catarina , Gomes António Rui , Conceição Eva , Machado Paulo P. P. , Gonçalves Sónia
Published: January 2025

Background/Objectives: Athletes are particularly vulnerable to developing eating disorders, which can negatively impact both health and athletic performance. The coach–athlete relationship plays a central role in athletes’ development and well-being. However, little is known about how coaches’ leadership styles relate to athletes’ self-criticism and disordered eating. Therefore, this study aimed to assess the relationship between athletes’ perceptions of their coach’s leadership style and their own self-criticism and disordered eating. Methods: A total of 150 athletes from team ball sports, aged 18 to 43 years (M = 25.0, SD = 6.0), completed self-report measures. Results: 27.3% of the participants were at heightened risk of developing eating disorders, and 38.7% lacked access to nutritional or psychological support within their clubs. Significant positive associations were found between coaches’ negative feedback style and athletes’ self-criticism and disordered eating, and between passive management style and athletes’ self-criticism and disordered eating. Moreover, athletes’ self-criticism fully mediated the relationship between these leadership styles and athletes’ disordered eating. Additionally, coaches’ vision, inspiration, and individualization styles were related to decreased self-criticism in athletes. Conclusions: Coaches’ leadership styles are significantly related to athletes’ psychological and nutritional health. This research has important implications for promoting healthier practices in sports settings.
Nutritional Screening Tools in the Pediatric Population: A Systematic Review
Authors: Fachal Carlos Veiga , Fernández-González Sara María , Moreno-Álvarez Ana , Solar-Boga Alfonso
Published: January 2025

Background/Objectives: Disease-related malnutrition (DRM) is the most common type of malnutrition in industrialized countries, and it has a high associated morbidity. Despite the existence of various screening tools for its detection, there is currently no consensus in the literature on which one is the most appropriate for clinical use. The aim of this systematic review is to update the available evidence on pediatric nutritional screening tools and to compare their validity and applicability. Methods: A systematic review of the literature was conducted using the MEDLINE (PubMed) database, selecting articles related to nutritional screening tools in the pediatric population. A quality assessment was carried out using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Results: A total of 200 articles were identified, of which 11 were included in the review. They include a total of 9,573 patients (mean age of 6.7 years and 49% female) from different countries. Eight screening tools were found, and three of them were the most employed: the Screening Tool for Risk on Nutritional Status and Growth (STRONGkids), the Screening Tool for the Assessment of Malnutrition in Pediatric (STAMP), and the Pediatric Yorkhill Malnutrition Score (PYMS). A high level of heterogeneity was observed among the selected studies without a gold standard for comparison. Conclusions: Despite the heterogeneity, the PYMS seems to have the greatest capacity to detect pediatric patients at nutritional risk and should therefore be considered when choosing a nutritional screening tool.
Addressing the Need for a Specialized Disconnection Device in Catheter Connection Management: A Case Study of User-Centered Medical Device Innovation
Authors: Cole Amy C. , Wiley Nicole , Dalton Kerri , Richardson Daniel R. , Allen Deborah , Havill Nancy , Mazur Lukasz
Published: January 2025

Background/Objectives: Improvements in catheter connection design intended to increase safety have resulted in connections that are difficult to release manually. No medical device exists to safely disconnect catheter connections. Nurses and other users have developed workarounds including use of hemostats, tourniquets, and wrenches. These workarounds are not always successful for performing this task and can break catheters and catheter connections. This study aimed to evaluate a disconnection device to safely disconnect catheter connections. Methods: This is a mixed-methods study using a user-centered design approach with triangulation of quantitative and qualitative data mapped to Valdez’s sociotechnical framework. Nurses (N = 139) from units across two academic medical centers encompassing diverse patient populations engaged in usability testing and surveys. Data about users’ past catheter disconnection experiences and usability of the specialized disconnection device were collected and analyzed. Triangulation of quantitative data and qualitative themes was mapped using Valdez’s socio-technical framework to complement and strengthen the final design generated for nurses’ user requirements. Results: Ninety-five percent of nurses reported previous difficulty with disconnecting luer connections; 93% of those reporting difficulty improvised with readily available medical devices or products to better grip the connected parts. Over 85% of nurses reported positive experiences using the specialized disconnection device; others suggested design improvements for better performance. Conclusions: The nurses who tested the developed disconnection device reported high acceptability, accessibility, ease of use, and improved task performance. Moreover, as workarounds develop at points of practice where no systematic solution exists, aiming product development activities at these points help close gaps in achieving and maintaining patient safety. This study was not registered.
Nurse Specialist in the Organ and Tissue Donation Process with Coordination Role: A Scoping Review
Authors: Longo Donato , Ramacciati Nicola , Giusti Gian Domenico
Published: January 2025

Background/Objectives: In recent years, the introduction of specialist nurses, such as donation coordinator nurses, has been proposed as a potentially effective strategy to increase the number of donations and improve the quality of the process. However, experiences in this field are still limited. The aim of this study was to evaluate the impact of the inclusion of this professional in health systems, both in quantitative and qualitative terms. Methods: A scoping review was performed. Studies published from 1990 to 2024 were included regardless of the study design. The bibliographic search was performed on the databases MedLine, Web of Science, Scopus, CINAHL, and PsycInfo and on the search engines EBSCOhost, ProQuest, and Google Scholar. The search strings included keywords such as organ donation, transplant, procurement, and nursing role. The extraction and selection of articles were conducted in accordance with the PRISMA-ScR guidelines and with the methodology of the Joanna Briggs Institute for scoping reviews. The protocol study was prospectively registered with the Open Science Framework database on 3 December 2023, with registration number osf.io/wzxr3. Results: From the included studies, it emerged that the involvement of a nurse coordinator in the donation process is significantly associated with an increase in the number of organ donors and higher rates of family consent to donation. Additionally, the studies highlighted enhanced effectiveness in identifying potential donors and improvements in the training and preparedness of healthcare staff. Conclusions: The nurse coordinator in the donation process can have positive effects both on the management of the process and on the increase in the number of organ and tissue donations.
Lebanese Medicinal Plants with Ophthalmic Properties
Authors: Andary Jeanne , El Ballouz Haitham , Abou-Khalil Rony
Published: January 2025

Lebanon benefits from a rich biodiversity, with medicinal and aromatic plants (MAPs) representing an important part of the country’s natural wealth; however, limited data are available documenting medicinal plants being employed in eye health. This review is the first to document Lebanese medicinal plants with ophthalmic characteristics and phytochemistry that might be beneficial in the development of new, accessible, and efficient ocular medications. In this study, we searched for studies on ocular therapeutic plants using known resources, including PubMed, ScienceDirect, and Google Scholar, and confirmed these plants’ presence within the Lebanese flora. The efficacy of 52 species from 28 families, including two endemic species (Crepis libanotica and Salvia libanotica), has been documented. Their Latin names, regional names, ocular medical applications, the plant parts used, and preparation forms are detailed below. The largest number of species belongs to the Lamiaceae family (21%), followed by Asteraceae (14%) and Solanaceae (7%). The most commonly used plant parts are the stems, leaves, and seeds. Ocular treatments fall into several categories: inflammation, infection, irritation, dry-eye, eyewash, the prevention or delay of cataracts, and general eye problems. A significant percentage (68%) of the medicinal plants target the anterior part of the eye. Some of the reported plants can be harmful to the eyes and should be handled with caution. The Lebanese medicinal plants listed, constituting a local heritage with global importance, could be used for treating ophthalmic ailments and require special screening and preservation.
Engineering Lipid Nanoparticles to Enhance Intracellular Delivery of Transforming Growth Factor-Beta siRNA (siTGF-β1) via Inhalation for Improving Pulmonary Fibrosis Post-Bleomycin Challenge
Authors: Deng Xu , Yang Yingjie , Gan Liming , Duan Xinliu , Wang Xiwei , Zhang Jingyan , Wang Aiping , Zhang Anan , Yuan Zhizhao , Chen Daquan , Zheng Aiping
Published: January 2025

Background/Objectives: Transforming Growth Factor-beta (TGFβ1) plays a core role in the process of pulmonary fibrosis (PF). The progression of pulmonary fibrosis can be alleviated by siRNA-based inhibiting TGF-β1. However, the limitations of naked siRNA lead to the failure of achieving therapeutic effect. This study aimed to design lipid nanoparticles (LNPs) that can deliver siTGF-β1 to the lungs for therapeutic purposes. Methods: The cytotoxicity and transfection assay in vitro were used to screen ionizable lipids (ILs). Design of Experiments (DOE) was used to obtain novel LNPs that can enhance resistance to atomization shear forces. Meanwhile, the impact of LNPs encapsulating siTGF-β1 (siTGFβ1-LNPs) on PF was investigated. Results: When DLin-DMA-MC3 (MC3) was used as the ILs, the lipid phase ratio was MC3:DSPC:DMG-PEG2000:cholesterol = 50:10:3:37, and N/P = 3.25; the siTGFβ1-LNPs could be stably delivered to the lungs via converting the siTGFβ1-LNPs solution into an aerosol (atomization). In vitro experiments have confirmed that siTGFβ1-LNPs have high safety, high encapsulation, and can promote cellular uptake and endosomal escape. In addition, siTGFβ1-LNPs significantly reduced inflammatory infiltration and attenuated deposition of extracellular matrix (ECM) and protected the lung tissue from the toxicity of bleomycin (BLM) without causing systemic toxicity. Conclusions: The siTGFβ1-LNPs can be effectively delivered to the lungs, resulting in the silencing of TGF-β1 mRNA and the inhibition of the epithelial–mesenchymal transition pathway, thereby delaying the process of PF, which provides a new method for the treatment and intervention of PF.
Advances in L-Lactic Acid Production from Lignocellulose Using Genetically Modified Microbial Systems
Authors: Díaz-Orozco Lucila , Moscosa Santillán Mario , Delgado Portales Rosa Elena , Rosales-Colunga Luis Manuel , Leyva-Porras César , Saavedra-Leos Zenaida
Published: January 2025

Lactic acid is a vital organic acid with a wide range of industrial applications, particularly in the food, pharmaceutical, cosmetic, and biomedical sectors. The conventional production of lactic acid from refined sugars poses high costs and significant environmental impacts, leading to the exploration of alternative raw materials and more sustainable processes. Lignocellulosic biomass, particularly agro-industrial residues such as agave bagasse, represents a promising substrate for lactic acid production. Agave bagasse, a by-product of the tequila and mezcal industries, is rich in fermentable carbohydrates, making it an ideal raw material for biotechnological processes. The use of lactic acid bacteria (LAB), particularly genetically modified microorganisms (GMMs), has been shown to enhance fermentation efficiency and lactic acid yield. This review explores the potential of lignocellulosic biomass as a substrate for microbial fermentation to produce lactic acid and other high-value products. It covers the composition and pretreatment of some agricultural residues, the selection of suitable microorganisms, and the optimization of fermentation conditions. The paper highlights the promising future of agro-industrial residue valorization through biotechnological processes and the sustainable production of lactic acid as an alternative to conventional methods.
Life Cycle Assessment of Waste Glass Geopolymerization for the Production of Sustainable Construction Materials
Authors: Manthos Georgios , Zagklis Dimitris , Georgopoulos Christos , Zafiri Constantina , Kornaros Michael
Published: January 2025

Replacing conventional materials with new recycled materials is one of the goals of sustainable development, as it promotes the creation of environmentally friendly products while reducing the amount of waste to be treated. A common recyclable waste stream associated with urban living is waste glass, which typically comes from packaging or product containers. Although most of this stream can be reused and/or recycled, it is worth exploring alternative uses, especially for areas with high fluctuations in waste glass production. An example would be the sudden increase in waste glass in tourist areas during the high season. To this end, the present work presents the results from the life cycle assessment of waste glass geopolymerization for the production of cement tiles. The methodology includes the estimation of mass and energy balances by dividing the whole process into several sub-processes (NaOH addition, energy consumption, etc.). The NaOH addition was found to be the most burden-intensive process, with a total damage of 9 × 10−5 DALY per ton of waste glass in the human health category, while a minor contribution in all damage categories was attributed to process electricity demands (7.7 to 19.4%). By comparing the geopolymerization process with conventional recycling, an environmental benefit of 20 mPt and 26 kg CO2 per ton of waste glass was demonstrated, indicating the process’s expediency. The present study is a valuable tool for the up-scaling of processes towards a circular economy.
Optimization of an Industrial Circulating Water System Based on Process Simulation and Machine Learning
Authors: Liu Yingjie , Shao Runjie , Ye Qing , Li Jinlong , Sun Ruiyu , Zhai Yifei
Published: January 2025

As an important part of industrial production, the optimization of circulating water systems is of great significance for improving energy efficiency and reducing operating costs. However, traditional optimization methods lack real-time and dynamic adjustment capabilities and often cannot fully cope with the complex and changeable industrial environment and energy demands. Advances in computer technology can enable people to use machine learning models to process information and data and ultimately help simplify simulation and optimization. In this paper, the circulating water system of a Fluid Catalytic Cracking (FCC) unit is optimized and evaluated based on process simulation and machine learning, adopting 284 sets of industrial operating data. The cooler network of the system is modified from a parallel structure to a series mode, and the effect is clarified using the ASPEN HYSYS software V12. Meanwhile, the fan power of the cooling tower is predicted by employing an optimized Gradient Boosting Regression (GBR) model, and the influence of the parallel-to-series transformation on the fan power is discussed. It is shown that the computer modeling results are in coincidence with the industrial data. Converting the parallel design to a series arrangement of the cooler network can significantly decrease the water consumption, with a reduction of 11%. The fan power of the cooling tower is also reduced by 8% after the optimization. Considering the changes in both water consumption and fan power, the saved total economic cost is 8.65%, and the decreased gas emission is 2142.06 kg/h. By building the optimization prediction system, the real-time sequencing and monitoring of equipment parameters are realized, which saves costs and improves process safety.
Multi-Source and Multitemporal Urban and Rural Settlement Mapping Under Spatial Constraint: Qinghai–Tibetan Plateau Case Study
Authors: Li Xiaopeng , Zhou Guangsheng , Zhou Li , Lv Xiaomin , He Xiaohui , Tian Zhihui
Published: January 2025

Accurately extracting long-term urban and rural settlement (URS) information is crucial for studying urbanization processes and their impacts on the ecological environment. However, existing remote sensing extraction methods often rely on independent classification strategies for each period, leading to error accumulation and increased uncertainty in long-term sequence extraction. To address this, this study proposed a data/model-constrained dynamic extraction method for URS information and validated it using the Qinghai–Tibetan Plateau at five-year intervals from 1985 to 2020. The area of URS extracted by this method had a matching degree of 97.79% with the reference, with an average overall accuracy of 93.25% and a kappa of 0.89 for the 1985–2020 confusion matrix sample. The urban and rural settlement boundary (URSB) extracted by this method were more accurate than the Global Urban Boundary (GUB) dataset, particularly in spatial completeness and boundary detail. The results provide technical support for uncovering urban development patterns and their environmental impacts.
Application of UAV Photogrammetry and Multispectral Image Analysis for Identifying Land Use and Vegetation Cover Succession in Former Mining Areas
Authors: Reinprecht Volker , Kieffer Daniel Scott
Published: January 2025

Variations in vegetation indices derived from multispectral images and digital terrain models from satellite imagery have been successfully used for reclamation and hazard management in former mining areas. However, low spatial resolution and the lack of sufficiently detailed information on surface morphology have restricted such studies to large sites. This study investigates the application of small, unmanned aerial vehicles (UAVs) equipped with multispectral sensors for land cover classification and vegetation monitoring. The application of UAVs bridges the gap between large-scale satellite remote sensing techniques and terrestrial surveys. Photogrammetric terrain models and orthoimages (RGB and multispectral) obtained from repeated mapping flights between November 2023 and May 2024 were combined with an ALS-based reference terrain model for object-based image classification. The collected data enabled differentiation between natural forests and areas affected by former mining activities, as well as the identification of variations in vegetation density and growth rates on former mining areas. The results confirm that small UAVs provide a versatile and efficient platform for classifying and monitoring mining areas and forested landslides.
Exploring the Effect of a Wavy Sea Surface on NLOS-UOWC Systems: A Novel Deterministic Approach
Authors: Samaniego-Rojas Paulo , Boluda-Ruiz Rubén , Garrido-Balsells José María , Castillo-Vázquez Beatriz , Puerta-Notario Antonio , García-Zambrana Antonio
Published: January 2025

This work presents a novel approach to modeling an underwater optical wireless communications (UOWC) channel based on a deterministic analysis specifically for non-line-of-sight (NLOS) configurations. The model considers the presence of a wavy ocean surface, providing a more accurate representation of realistic conditions. By expanding the possibilities for communication in complex underwater environments, our model offers a comprehensive analysis of the ocean waves’ impact. A significant achievement of this study is the capacity of the model to accurately compute the variable size of the width of the beam (footprint) on the receiver plane reflected by the sea surface and the time intervals during which the receiver remains illuminated. Additionally, the model determines the precise position of the reflected beam on the receiver plane and accurately identifies the time intervals during which communication is feasible, offering invaluable insight into the system performance under oceanic wave variability. The results confirmed that oceanic wave variability induces severe misalignment in optical links, creating intermittent opportunities for effective communication. The optical–geometric analysis contributed significantly to understanding the novel impact of ocean waves on NLOS-UOWC systems. These findings enhance the preliminary considerations in NLOS link design, particularly in scenarios with autonomous underwater vehicles in constant motion, aiding in the reduction of pointing errors.
Investigating the Effect of Vibration Signal Length on Bearing Fault Classification Using Wavelet Scattering Transform
Authors: Janjarasjitt Suparerk
Published: January 2025

Bearing condition monitoring and prognosis are crucial tasks for ensuring the proper operation of rotating machinery and mechanical systems. Vibration signal analysis is one of the most effective techniques for bearing condition monitoring and prognosis. In this study, the wavelet scattering transform, derived from wavelet transforms and incorporating concepts from scattering transform and convolutional network architectures, was utilized to extract quantitative features from vibration signals. The number of wavelet scattering coefficients obtained from vibration signals of different lengths varied due to the use of predefined wavelet and scaling filters in the wavelet scattering network. Additionally, these wavelet scattering coefficients are associated with different scattering paths within the corresponding wavelet scattering networks. Eight different lengths of vibration signals, associated with fifteen classes of rolling element bearing faults and conditions, were investigated using wavelet scattering feature extraction. The classes of rolling element bearing faults and conditions included normal bearings as well as ball and inner race faults with various fault diameters ranging from 0.007 inches to 0.028 inches. For the specific dataset validated, the computational results indicated that excellent bearing fault classification was achievable using wavelet scattering feature vectors derived from vibration signals with lengths of at least 6000 samples.
Wi-Filter: WiFi-Assisted Frame Filtering on the Edge for Scalable and Resource-Efficient Video Analytics
Authors: Lubwama Lawrence , Jang Jungik , Pyo Jisung , Yoo Joon , Choi Jaehyuk
Published: January 2025

With the growing prevalence of large-scale intelligent surveillance camera systems, the burden on real-time video analytics pipelines has significantly increased due to continuous video transmission from numerous cameras. To mitigate this strain, recent approaches focus on filtering irrelevant video frames early in the pipeline, at the camera or edge device level. In this paper, we propose Wi-Filter, an innovative filtering method that leverages Wi-Fi signals from wireless edge devices, such as Wi-Fi-enabled cameras, to optimize filtering decisions dynamically. Wi-Filter utilizes channel state information (CSI) readily available from these wireless cameras to detect human motion within the field of view, adjusting the filtering threshold accordingly. The motion-sensing models in Wi-Filter (Wi-Fi assisted Filter) are trained using a self-supervised approach, where CSI data are automatically annotated via synchronized camera feeds. We demonstrate the effectiveness of Wi-Filter through real-world experiments and prototype implementation. Wi-Filter achieves motion detection accuracy exceeding 97.2% and reduces false positive rates by up to 60% while maintaining a high detection rate, even in challenging environments, showing its potential to enhance the efficiency of video analytics pipelines.
An Underwater Polarization Imaging Technique Based on the Construction and Decomposition of the Low-Rank and Sparse Matrix in Stokes Space for Polarization State Imaging
Authors: Liu Pengfeng , Zhai Yuxiang , Zhu Hongjin , Ye Zijian , He Qinyu , Tang Zhilie , Tang Peijun
Published: January 2025

Traditional underwater polarization imaging methods can only provide clear degree of polarization (DOP) and intensity images of the object but cannot provide images of the polarization state of the object. This paper proposes a method to extract clear object information from turbid water in all four Stokes parameter (I, Q, U, and V) channels by using the full Stokes camera, enabling clear polarization state image reconstruction. The method utilizes multiple images from different angles to construct a low-rank and sparse matrix. Then, by decomposing this matrix into sparse and low-rank components, clear Q, U, and V images (i.e., the full polarization state) can be obtained. Unlike traditional methods that assume the circularly polarized component (V component) to be zero, this method retains V channel information, allowing for circular polarization component measurement. The study successfully reconstructed clear underwater images of samples with inhomogeneous DOP distribution and obtained the clear polarization states of polarizers and fish in the turbid water. The results show that the proposed method can visualize and analyze the object’s polarization state quantitatively with high accuracy in turbid water for the first time, potentially extending the applicability of polarization underwater imaging in ocean exploration.
Application of Discrete Exterior Calculus Methods for the Path Planning of a Manipulator Performing Thermal Plasma Spraying of Coatings
Authors: Kussaiyn-Murat Assel , Kadyroldina Albina , Krasavin Alexander , Tolykbayeva Maral , Orazova Arailym , Nazenova Gaukhar , Krak Iurii , Haidegger Tamás , Alontseva Darya
Published: January 2025

This paper presents a new method of path planning for an industrial robot manipulator that performs thermal plasma spraying of coatings. Path planning and automatic generation of the manipulator motion program are performed using preliminary 3D surface scanning data from a laser triangulation distance sensor installed on the same robot arm. The new path planning algorithm is based on constructing a function of the geodesic distance from the starting curve. A new method for constructing a geodesic distance function on a surface is proposed, based on the application of Discrete Exterior calculus methods, which is characterized by a high computational efficiency. The developed algorithms and their software implementation were experimentally tested with the robotic microplasma spraying of a protective coating on the surface of a jaw crusher plate, which was then successfully operated for crushing mineral-based raw materials.
Biochemical Oxygen Demand Prediction Based on Three-Dimensional Fluorescence Spectroscopy and Machine Learning
Authors: Zhang Xu , Zhang Yihao , Yang Xuanyi , Wang Zhiyun , Liu Xianhua
Published: January 2025

Biochemical oxygen demand (BOD) is an important indicator of the degree of organic pollution in water bodies. Traditional methods for BOD5 determination, although widely used, are complicated and dependent on accurate chemical measurements of dissolved oxygen. The aim of this study was to propose a facile method for predicting biochemical oxygen demand by fluorescence signals using three-dimensional fluorescence spectroscopy and parallel factor analysis in combination with a machine learning algorithm. The water samples were incubated for five days using the national standard method, during which the dissolved oxygen contents and three-dimensional fluorescence spectroscopy data were measured at eight-hour intervals. The maximum fluorescence intensity of three fluorescence components was decomposed and extracted by parallel factor analysis. The relationship between the maximum fluorescence of the three fluorescence components and the BOD5 values was established using a random forest model. The results showed that there was a good correlation between the fluorescence components and BOD values. The BOD5 values were effectively predicted by the random forest model with a high goodness of fit (R2 = 0.878) and low mean square error (MSE = 0.28). Although this method did not shorten the incubation time, successful BOD5 prediction was realized by the non-contact measurement of fluorescence signals. This avoids the complicated operation of DO determination, improves detection efficiency, and provides a convenient solution for analyzing large quantities of water samples and monitoring facile water quality.
A Review of Simultaneous Localization and Mapping for the Robotic-Based Nondestructive Evaluation of Infrastructures
Authors: Ghadimzadeh Alamdari Ali , Zade Farzad Azizi , Ebrahimkhanlou Arvin
Published: January 2025

The maturity of simultaneous localization and mapping (SLAM) methods has now reached a significant level that motivates in-depth and problem-specific reviews. The focus of this study is to investigate the evolution of vision-based, LiDAR-based, and a combination of these methods and evaluate their performance in enclosed and GPS-denied (EGD) conditions for infrastructure inspection. This paper categorizes and analyzes the SLAM methods in detail, considering the sensor fusion type and chronological order. The paper analyzes the performance of eleven open-source SLAM solutions, containing two visual (VINS-Mono, ORB-SLAM 2), eight LiDAR-based (LIO-SAM, Fast-LIO 2, SC-Fast-LIO 2, LeGO-LOAM, SC-LeGO-LOAM A-LOAM, LINS, F-LOAM) and one combination of the LiDAR and vision-based method (LVI-SAM). The benchmarking section analyzes accuracy and computational resource consumption using our collected dataset and a test dataset. According to the results, LiDAR-based methods performed well under EGD conditions. Contrary to common presumptions, some vision-based methods demonstrate acceptable performance in EGD environments. Additionally, combining vision-based techniques with LiDAR-based methods demonstrates superior performance compared to either vision-based or LiDAR-based methods individually.
Plant Sample Preparation for Metabolomics, Lipidomics, Ionomics, Fluxomics, and Peptidomics
Authors: da Silva Walace Breno , Hispagnol Gabriel Felipe , dos Santos Nunes Emanuel Victor , Castro-Gamboa Ian , Pilon Alan Cesar
Published: January 2025

Plant metabolomics, lipidomics, ionomics, fluxomics, and peptidomics are essential approaches for exploring how plants respond to epigenetic, pathological, and environmental stimuli through comprehensive chemical profiling. Over the past decades, significant progress has been made in protocols and methodologies to address the challenges in sample collection and extraction. Despite these advancements, sample preparation remains intricate, with ongoing debates about the most effective strategies. This review emphasizes the importance of clear research questions and well-designed experiments to minimize complexity, save time, and enhance reproducibility. It provides an overview of the key steps in these fields, including harvesting, drying, extraction, and data pre-acquisition for major analytical platforms. By discussing best practices and common challenges, this review aims to streamline methods and promote more consistent and reliable research outcomes.
German Translation and Psychometric Analysis of the SOLID-SD: A German Inventory for Assessing Security Culture in Software Companies
Authors: Glasauer Christina , Pearl Hollie N. , Alexandrowicz Rainer W.
Published: January 2025

The SOLID-S is an inventory assessing six dimensions of organizational (software) security culture, which is currently available in English. Here, we present the German version, SOLID-SD, along with its translation process and psychometric analysis. With a partial credit model based on a sample of N = 280 persons, we found, overall, highly satisfactory measurement properties for the instrument. There were no threshold permutations, no serious differential item functioning, and good item fits. The subscales’ internal consistencies and the inter-scale correlations show very high similarities between the SOLID-SD and the original English version, indicating a successful translation of the instrument.
Improving Chinese Transnational Enterprises’ Environmental Performance: Does Government’s Green Finance Support Matter?
Authors: Guo Liang , Jiang Feng
Published: January 2025

With the goal of promoting Chinese enterprises’ green development in overseas markets, China issued the Guidance on Promoting Green Belt and Road in 2017. The Guidance is the world’s first government document specifically designed to provide green finance support for domestic enterprises in overseas markets. Based on data on heavily polluting enterprises listed on the Shanghai and Shenzhen A-share markets from 2008 to 2021, this paper applies a Difference-in-Differences (DID) approach to explore the impact of this document on Chinese transnational enterprises’ environmental performance. Our empirical results reveal that government’s green finance support significantly improves Chinese transnational enterprises’ environmental performance by financing their overseas projects. Such effects are heterogeneous in enterprises with different natures, management levels, and profitability. From mechanism checks, we discovered that the Guidance impacts Chinese transnational enterprises’ green behaviors through both financial and institutional channels. Our study proposes corresponding policy suggestions and offers government policymakers insights into designing effective financial support for its enterprises’ green development in the global market.
RETRACTED: Di Paola et al. Environmental Risk Assessment of Dexamethasone Sodium Phosphate and Tocilizumab Mixture in Zebrafish Early Life Stage (Danio rerio). Toxics 2022, 10, 279
Authors: Di Paola Davide , Abbate Jessica Maria , Iaria Carmelo , Cordaro Marika , Crupi Rosalia , Siracusa Rosalba , D’Amico Ramona , Fusco Roberta , Impellizzeri Daniela , Cuzzocrea Salvatore , Spanò Nunziacarla , Gugliandolo Enrico , Peritore Alessio Filippo
Published: January 2025

The journal retracts the article “Environmental risk assessment of mixture of COVID-19 treating pharmaceutical drugs in zebrafish early life stage (Danio rerio)” [...]
Exploring the Ambient in Relation to Urban Life and AI
Authors: McKenna H. Patricia
Published: January 2025

The purpose of this paper is to explore the nature of the ambient in an era of artificial intelligence (AI), focusing on the urban context. As such, this paper explores evolving understandings of the ambient in everyday life encompassing a range of elements such as awareness, computing, experiences, information, and intelligence in relation to rapidly evolving and emerging applications of AI and generative AI in urban environments. A review of the research and practice literature for the ambient in relation to urban AI is provided in this paper enabling formulation of a conceptual framework to guide the exploration. A poll conducted online using the Whova platform during a hybrid (e.g., virtual and in person) conference event provides insight into the awareness element in the context of AI from the perspective of researchers, students, practitioners, and other conference participants and attendees (e.g., government business, etc.). Implications for urban life, smart cities, learning cities, and future cities are discussed, giving rise to challenges and opportunities for research and practice going forward. This work is significant in that a range of perspectives across a variety of domains emerge for the ambient in relation to everyday life and AI and to urban AI.
Risk Assessment and Prevention of Foot-and-Mouth Disease Transmission from Laos to China
Authors: Xin Jige , Lan Sixian , Ai Jun , Zeng Bangquan , Xin Aiguo , Ye Lingling , Zuo Weidong , Li Yanlin , Han Diangang
Published: January 2025

Foot-and-mouth disease (FMD) is classified as a Class I animal disease in China and listed as one of the notifiable animal diseases by the World Organization for Animal Health (WOAH). It significantly impacts the safe production of livestock and the trade of animals and related products. China’s Yunnan Province shares a 710 km border with Laos, with frequent cross-border trade, and the cross-border flow of animals and related products occurs from time to time. In order to prevent the introduction of FMD from the border areas of Laos into China, this study conducted an assessment of the entry, exposure, and consequences of FMD transmission. The findings revealed a “high” risk in terms of entry assessment, a “medium” risk in exposure assessment, and a “high” risk in the consequence assessment. Based on these assessments, the overall risk level for the introduction of FMD from Laos into China is determined to be “high”. Therefore, it is recommended that management measures are implemented, such as restricting animal movement across borders and strengthening inspection procedures for animals entering China, to effectively prevent FMD introduction from Laos.