bluuebunny/crossref_metadata_2025 huggingface dataset:
Processed Food Consumption and Sleep Quality in School-Aged Children: Insights from a Cross-Sectional Study
Authors: Sousa Gomes Matilde , Martins Juliana , Duarte Ana , Augusto Cláudia , Silva Maria José , Padrão Patrícia , Moreira Pedro , Rosário Rafaela
Published: January 2025

Objective: This cross-sectional study aimed to investigate the association between processed food consumption and sleep quality among school-aged children. Methods: Our sample consisted of 137 children, with 52.6% being girls with a mean age of 7.9 ± 1.2 years. Moreover, 40.2% of children had overweight and 35.9% had experienced sleep problems. Dietary intake was evaluated using two non-consecutive 24 h recalls, and foods were categorized according to the NOVA classification system. The amount of sweet snacks consumed, in grams, was recorded for each meal and throughout the day. Sleep quality was assessed using the Portuguese Children’s Sleep Habits Questionnaire (CSHQ-PT). Results: The study found a significant and positive association between the sleep habits score and daily sweet snack consumption (B = 0.035; 95% CI: 0.011, 0.059). Additionally, there were higher odds of experiencing sleep problems in those children who consumed a higher percentage of energy from ultra-processed foods (OR: 1.043; 95% CI: 1.004, 1.084), higher total daily consumption of sweet snacks (OR: 1.016; 95% CI: 1.006, 1.026), particularly during morning and afternoon snack times (OR: 1.018; 95% CI: 1.002, 1.033). Conclusions: These findings underscore the importance of addressing dietary patterns on children’s sleep quality. Future interventions should account for reducing NOVA 4 and sweet snack consumption in order to improve sleep quality.
Does Creatine Supplementation Enhance Performance in Active Females? A Systematic Review
Authors: Tam Ryan , Mitchell Lachlan , Forsyth Adrienne
Published: January 2025

The use of creatine as a dietary supplement is widespread. However, its reported performance benefit has been largely demonstrated in male populations. The aim was to evaluate the effectiveness of creatine supplementation in improving exercise performance in active females. A secondary aim was to appraise the quality of research in this area. Five databases were searched from the earliest record to July 2024. Eligible studies used supplemental creatine as an intervention with physically active female participants and reported an exercise performance-related outcome. Study quality was appraised using the Critical Appraisal Skills Program randomised controlled trials checklist with four additional items related to methodological considerations for research with active females. Performance outcomes were categorised as strength/power, anaerobic, or aerobic. Of the 10,563 records identified, 27 studies were included. Participant calibre ranged from recreationally active to elite. Creatine interventions ranged from five days to 12 weeks and included a range of dosage strategies. Compared to placebo, 3/11 studies showed an improvement in strength/power outcomes, 4/17 showed an improvement in anaerobic outcomes, and 1/5 showed an improvement in aerobic outcomes. Study quality varied, but methodological considerations for research with female athletes were poorly addressed by most studies. Although some benefits were reported, most studies showed no improvement in performance compared to placebo. The heterogeneity in participant characteristics, performance tests, creatine intervention, insufficient consideration of the unique physiological characteristics of females, and an overall small evidence base limits our understanding of how creatine supplementation influences physical performance in active females.
Interdisciplinary Oral Nutrition Support and Supplementation After Hip Fracture Surgery in Older Adult Inpatients: A Global Cross-Sectional Survey (ONS-STUDY)
Authors: Bell Jack , Turabi Ruqayyah , Olsen Sissel Urke , Sheehan Katie Jane , Geirsdóttir Ólöf Guðný
Published: January 2025

Background: Malnutrition predicts poor outcomes following hip fracture, affecting patient recovery, healthcare performance, and costs. Evidence-based guidelines recommend multicomponent, interdisciplinary nutrition care to improve intake, reduce complications, and enhance outcomes. This study examines global variation in oral nutrition support for older (65+ years) hip fracture inpatients. Methods: A global survey was conducted as part of a broader program to improve interdisciplinary nutrition care. The protocol was based on evidence-based guidelines, reviewed by experts, and piloted for validity. Recruitment used snowball sampling to achieve diversity across income levels, countries, and healthcare roles. Results: The survey (July–September 2023) recruited 308 participants from 46 countries across five global regions. Respondents primarily worked in acute teaching (57.5%) and non-teaching (17.5%) hospitals, representing medical (48.4%), nursing (28.2%), and allied health (17.9%) roles. Findings revealed a global knowledge-to-practice gap in multicomponent nutrition care, across providing high-protein/energy food and fluids (median: “half the time”), post-operative provision of oral nutritional supplements (median: “half the time”) and continuation for one month with assessment (median: “not very often”), and nutritional education (median: “not very often”). Only 17.9% of respondents reported routine provision (“often” and “nearly always or always”) of high-protein/energy food, supplements, and education. Substantial regional variation showed Western Pacific respondents perceiving the lowest provision across multicomponent processes. Interdisciplinary, multicomponent interventions were seen as a potential opportunity requiring further exploration. Conclusions: Major gaps persist in implementing evidence-based, interdisciplinary, multicomponent nutrition care for older adults with hip fractures. A targeted implementation approach is the next step to addressing the knowledge-to-practice gap.
Diversity of the Amoebozoa and Ciliophora Groups in Non-Human Primates Kept Ex Situ and in Their Handlers in Different Institutions in Brazil
Authors: Dib Laís , da Silva Breno , Correa Lais , Pissinatti Alcides , Moreira Silvia , Tavares Maria Clotilde , Teixeira Rodrigo , da Costa André Luíz , Muniz José Augusto , Junglos Amauri , Hirano Zelinda Maria , Dada Aline , da Silva Sidnei , Amendoeira Maria Regina , Barbosa Alynne
Published: January 2025

Parasitic infections in non-human primates (NHPs) kept ex situ can be caused by zoonotic protists like Balantioides coli and Entamoeba histolytica. In Brazil, little is known about these infections in neotropical species. This study aimed to identify Amoebozoa and Ciliophora groups in fecal samples through in vitro isolation and molecular analysis, mapping their distribution in Brazil. Among 511 NHP and 74 handler’s fecal samples, Amoebozoa were found in 61 (11.9%) NHP samples, and Ciliophora in 6 (1.2%). Amoebic cysts were present in 12 (16.2%) human samples. Iodamoeba sp. from S. xanthosternos, E. coli from a handler, and B. coli from P. troglodytes and A. guariba were isolated in vitro. Molecular techniques identified E. dispar (34.2%), E. histolytica (5.1%), E. hartmanni (26.6%), E. coli (15.2%), Iodamoeba sp. (12.6%), E. nana (8.9%), and B. coli (7.6%). Greater protist diversity occurred in northern and southeastern regions, with E. histolytica and B. coli detected in endangered species, such as Saguinus bicolor and Alouatta guariba. Protist overlap between humans and NHPs underscores zoonotic risks. This study presents the first molecular characterization of Amoebozoa and Ciliophora in neotropical NHPs kept ex situ in Brazil, highlighting the need for improved hygiene and management protocols in primate institutions.
Eicosapentaenoic Acid and Docosahexaenoic Acid as an Antimicrobial Agent in Orthopedics—An In Vitro Study About the Race for Surface
Authors: Spiegel Christopher , Ünalan Burak , Kaserbacher Andreas , Arora Rohit , Coraça-Huber Débora C.
Published: January 2025

Background: The burden of prosthetic joint infection in combination with antibiotic-resistant bacterial strains is a rising dilemma for patients experiencing total joint replacements. Around 0.8–2% of patients experience prosthetic joint infections, while up to 21% of patients are considered fatal cases after 5 years. Staphylococcus aureus is one of the main reasons for prosthetic joint infections. Its capability of forming biofilms and developing mechanisms against antibiotics is one of the most dangerous clinical topics being currently discussed. Previous studies have shown the promising results of omega-3 fatty acids as an antimicrobial agent against Staphylococcus aureus. Though an antimicrobial effect has been examined, the influence of polyunsaturated fatty acids on Staphylococcus aureus in the presence of human osteoblasts has not been reported yet. In this study, we aimed to investigate the influence of omega-3 fatty acids on the biofilm formation of Staphylococcus aureus ATCC 29213 in the presence of hFOB 1.19 cells. The co-culture setup helped to examine the influence of omega-3 fatty acids on the race for surface to simulate prosthetic joint infections. Methods: In this study, we tested Staphylococcus aureus ATCC 29213 co-cultured with human fetal osteoblasts hFOB 1.19 in the presence of sub-MIC and MIC concentrations of docosahexaenoic acid (1.25 mg/L, 2.5 mg/L) and eicosapentaenoic acid (0.15 mg/L, 0.3 mg/L) after 1, 6 and 24 h of incubation. After establishing the co-culture, cell culture and biofilm, we performed colony-forming unit counting and cell counting to examine cell survivability. In addition, we carried out scanning electron microscopy to study the race for surface behaviour of the cells. Results: We found a protective influence of omega-3 fatty acids on osteoblasts when present in co-culture with Staphylococcus aureus after 6 h of incubation. Omega-3 fatty acids increase the cell survival of osteoblasts after 6 h in a co-culture with bacteria and are able to influence the race for surface. In this study, the strain of Staphylcoccus aureus ATCC 29213 showed signs of growth inhibition within the first 6 h. Conclusions: Omega-3 fatty acids can be a valuable antimicrobial agent in terms of decreasing the risk of on-site infection during surgery. Omega-3 fatty acids were shown to decrease the bacterial load within the first 6 h of incubation and increase the survivability of osteoblasts.
Positive Correlation Between Serum Limonene Levels and Muscle Health in a Representative Adult Population in the United States
Authors: Wu Chang-Chin , Fang Yu-Wei , Wang Chikang , Lin Chien-Yu
Published: January 2025

Background/Objectives: Monoterpenes, a class of organic compounds with the molecular formula C10H16, have garnered significant attention for their potential medicinal benefits. Emerging evidence suggests they may positively influence skeletal muscle function. However, the impact of monoterpene exposure on muscle strength and mass in humans remains unclear. Methods: To explore this relationship, we analyzed data from 1202 adults (aged ≥ 18 years) who participated in the 2013–2014 National Health and Nutrition Examination Survey (NHANES), focusing on serum levels of three specific monoterpenes—α-pinene, β-pinene, and limonene—and their association with hand grip strength and lean muscle mass. Results: Our analysis revealed that, except for test 2 of hand 1, all grip strength measures showed a positive correlation with ln-limonene levels. The β coefficient for combined grip strength was 2.409 (S.E. = 0.891, p = 0.015). Positive associations were also found between serum limonene levels and lean muscle mass. The β coefficient for the Appendicular Skeletal Muscle Mass Index (ASMI) was 0.138 (S.E. = 0.041, p = 0.004). Furthermore, combined grip strength and ASMI significantly increased across limonene quintiles (p for trend = 0.005 and 0.006, respectively). However, none of the three monoterpene levels showed a significant association with clinically defined low muscle mass or low muscle strength. Conclusions: Our findings suggest a plausible association between exposure to limonene, hand grip strength, and lean muscle mass among adults in the United States. Further investigation is needed to fully understand the underlying mechanisms and medical significance of this association.
Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance
Authors: Sabit Hussein , Arneth Borros , Pawlik Timothy M. , Abdel-Ghany Shaimaa , Ghazy Aysha , Abdelazeem Rawan M. , Alqosaibi Amany , Al-Dhuayan Ibtesam S. , Almulhim Jawaher , Alrabiah Noof A. , Hashash Ahmed
Published: January 2025

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of the tumor microenvironment (TME), leading to important advancements toward a much deeper understanding of how tumor microenvironment heterogeneity contributes to cancer progression and therapeutic resistance. These technologies are able to integrate data from molecular genomic, transcriptomic, proteomics, and metabolomics studies of cells at a single-cell resolution scale that give rise to the full cellular and molecular complexity in the TME. Understanding the complex and sometimes reciprocal relationships among cancer cells, CAFs, immune cells, and ECs has led to novel insights into their immense heterogeneity in functions, which can have important consequences on tumor behavior. In-depth studies have uncovered immune evasion mechanisms, including the exhaustion of T cells and metabolic reprogramming in response to hypoxia from cancer cells. Single-cell multi-omics also revealed resistance mechanisms, such as stromal cell-secreted factors and physical barriers in the extracellular matrix. Future studies examining specific metabolic pathways and targeting approaches to reduce the heterogeneity in the TME will likely lead to better outcomes with immunotherapies, drug delivery, etc., for cancer treatments. Future studies will incorporate multi-omics data, spatial relationships in tumor micro-environments, and their translation into personalized cancer therapies. This review emphasizes how single-cell multi-omics can provide insights into the cellular and molecular heterogeneity of the TME, revealing immune evasion mechanisms, metabolic reprogramming, and stromal cell influences. These insights aim to guide the development of personalized and targeted cancer therapies, highlighting the role of TME diversity in shaping tumor behavior and treatment outcomes.
Real-Time Pharmacovigilance: Transforming Population-Based Monitoring of Post-Approval Vaccine Safety Through Rapid Cycle Analysis (RCA)—A Review of the Published Literature
Authors: Gandhi Sampada , Iannacone Michelle R. , Leapley Andrea , Wang Li , Mtenga Mwedusasa , Younus Muhammad , Wu Joanne
Published: January 2025

Background/Objectives: Rapid cycle analysis (RCA) is an established and efficient methodology that has been traditionally utilized by United States health authorities to monitor post-approval vaccine safety. Initially developed in the Vaccine Safety Datalink (VSD) in early 2000s, RCA has evolved into a valuable approach for timely post-approval signal detection. Due to the availability of additional near real-time data sources and enhanced analytic approaches, the use of RCA has expanded. This narrative review provides an in-depth assessment of studies that utilized RCA for safety surveillance to detect and evaluate safety signals in post-approval vaccine monitoring. Methods: Embase and Medline were searched on 8 August 2024 to identify post-approval non-interventional vaccine safety studies using RCA or other near real-time surveillance methods published from 1 January 2018 to 31 July 2024. Data on study characteristics (e.g., study population, data source, outcomes) and RCA methodological characteristics (e.g., type of comparator, sequential testing method, confounding control method) were extracted from the eligible RCA studies. Results: Of 1128 articles screened, 18 RCA vaccine safety studies were included, of which 17 (94.4%) were conducted in the United States (US). Twelve (67%) aimed at signal detection and six (33%) conducted further signal evaluation. Over 60% examined COVID-19 vaccine safety, with half using VSD. Over 80% conducted the RCA weekly or monthly and about 78% of the studies used a database-specific historical comparator group. Conclusions: This review indicates that most of the published articles on the application of the RCA methodology in vaccine safety studies are based on research conducted in the US. With increasing availability of near real-time data sources and advanced analytic methods capabilities, RCA is expected to be more widely deployed as an active surveillance tool to complement traditional pharmacovigilance. Future studies should explore the extension of vaccine RCA methodology for non-vaccine medicinal products.
Polymer Materials for U-Shaped Optic Fiber Sensors: A Review
Authors: Sokołowski Patryk , Łubiński Jacek , Wierzba Paweł , Czubek Jakub , Miluski Piotr , Janiak Filip , Guan Shanyue , Szczerska Małgorzata
Published: January 2025

Fiber optic sensors have gained popularity over the last few decades. This is due to their numerous advantages, such as good metrological parameters, biocompatibility and resistance to magnetic and electric fields and environmental pollution. However, those built from glass fiber have one main disadvantage—they are fragile, meaning they can be easily damaged, even by the presence of vibration. Due to the great progress made by material research recently, it is possible to build such a sensor with polymer fibers instead. Although those fibers have worse transmission parameters compared to telecommunication fibers, they provide the possibility to realize flexible fiber optic sensors. Taking into consideration other advantages of such fibers, including biocompatibility, electromagnetic resistance and even, biodegradation characteristics, as well as there being a variety of materials we can use, it can be seen that those materials are beneficial to produce fiber optic sensors. This paper aims to provide researchers with guidelines on the factors to consider when choosing a material for bent fiber optic sensors, depending on the application.
Correction: Zandberg et al. The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics. Plants 2022, 11, 2740
Authors: Zandberg Jaco D. , Fernandez Cassandria T. , Danilevicz Monica F. , Thomas William J. W. , Edwards David , Batley Jacqueline
Published: January 2025

There was an error in the original publication [...]
Development of Molecularly Imprinted Photonic Crystals Sensor for High-Sensitivity, Rapid Detection of Sulfamethazine in Food Samples
Authors: He Jinxing , Wu Mengke , Wang Xin , Xu Ruoxuan , Zhang Shuting , Zhao Xiaolei
Published: January 2025

As a veterinary drug, sulfamethazine is frequently used to control animal diseases. In this study, a novel molecularly imprinted photonic crystal sensor for the fast visual detection of sulfamethazine in milk and chicken has been developed. Under optimum preparation conditions, a molecularly imprinted, photonic crystal with an anti-opal structure and a clear bright color was prepared and characterized. The adsorption conditions, including adsorption solvent, solvent pH, and detection time, were studied in detailed. Based on its excellent selectivity and fast response, a photonic crystal sensor detection method for the quantitative analysis of sulfamethazine was established, which achieved good linearity, ranging from 10−4 mg/L to 10 mg/L, a limit detection of 1.16 μg/L, and spiked recoveries of 80.56% to 103.59%, with a relative standard deviation (RSD) <6.41%. More importantly, the detection process could be completed within 3 min. This method provides an alternative for the rapid screening of sulfamethazine in food samples.
Plasma Treatment of Metal Surfaces for Enhanced Bonding Strength of Metal–Polymer Hybrid Structures
Authors: Kim Dong Hyun , Kim Han Su , Jung Yunki , Hong Jin-Yong , Jeon Young-Pyo , Lee Jea Uk
Published: January 2025

The adhesion between metals and polymers plays a pivotal role in numerous industrial applications, especially within the automotive and aerospace sectors, where there is a growing demand for materials that are both lightweight and durable. This study introduces an innovative technique to improve the adhesion between a metal and a polymer in hybrid structures through the synergistic use of anodization and plasma treatment. By forming a nanoporous oxide layer on aluminum surfaces, anodization enhances the interface for polymer binding. Plasma treatment further augments the surface properties by increasing the concentration of functional groups, thus allowing better polymer infiltration during the 3D printing process. Comprehensive analyses, including X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, and contact angle measurements confirm the substantial enhancement in the bonding strength achieved through this method. Additionally, cross-sectional analysis via focused ion-beam etching provides a detailed view of polymer integration into the treated layers. The findings suggest significant potential for these surface modification strategies to advance the development of lightweight, robust composites suitable for use in sectors such as automotive, aerospace, and consumer electronics.
Preparation of Heat and Salt Resistant Foam Composite System Based on Weathered Coal Particle Strengthening and a Study on Foam Stabilization Mechanism
Authors: Xu Yanyan , Xi Linghui , Wu Yajun , Shi Xin , Kang Zhi , Wu Beibei , Zhang Chao
Published: January 2025

Nitrogen foam is a promising enhanced oil recovery (EOR) technique with significant potential for tertiary oil recovery. This improves the efficiency of the oil displacement during the gas drive processes while expanding the swept volume. However, in the high-temperature, high-salinity reservoirs of the Tahe Oilfield, conventional N2 foam systems show suboptimal performance, as their effectiveness is heavily limited by temperature and salinity. Consequently, enhancing the foam stability under these harsh conditions is crucial for unlocking new opportunities for the development of Tahe fracture-vuggy reservoirs. In this study, the Waring–Blender method was used to prepare weathered coal particles as a foam stabilizer. Compared to conventional foam stabilizers, weathered coal particles were found to enhance the stability of the liquid film under high-temperature and high-salinity conditions. Firstly, the foaming properties of the six foaming agents were comprehensively evaluated and their foaming properties were observed at different concentrations. YL-3J with a mass concentration of 0.7% was selected. The foaming stabilization performance of four types of solid particles was evaluated and weathered coal solid particles with a mass concentration of 15% and particle size of 300 mesh were selected. Therefore, the particle-reinforced foam system was determined to consist of “foaming agent YL-3J (0.7%) + weathered coal (15.0%) + nitrogen”. This system exhibited a foaming volume of 310 mL at 150 °C and salinity of 210,000 mg/L, with a half-life of 1920 s. Finally, through interfacial tension and viscoelastic modulus tests, the synergistic mechanism between weathered coal particles and surfactants was demonstrated. The incorporation of weathered coal particles reduced the interfacial tension of the system. The formation of a skeleton at the foam interface increased the apparent viscosity and viscoelastic modulus, reduced the liquid drainage rate from the foam, and mitigated the disproportionation effect. These effects enhanced the temperature, salinity resistance, and stability of the foam. Consequently, they contributed to the stable flow of foam under high-temperature and high-salinity conditions in the reservoir, thereby improving the oil displacement efficiency of the system.
God’s Forgotten Garden: The Role of Missionary Botany in Sino-European Exchanges
Authors: Hong Jooyoung
Published: January 2025

This study explores how European botanical science, introduced by foreign missionaries, transformed the intellectual and environmental landscape of premodern China. By examining the transnational exchange of scientific ideas, the paper highlights the role of missionaries, particularly Jesuits and Protestants, in promoting Western botany within a highly sophisticated Chinese intellectual framework. Despite cultural barriers, missionaries sought to integrate a Christian understanding of nature into Chinese episteme, using botanical studies as a conduit for proselytization. The research focuses on key historical moments, including the Treaty of Nanking, which opened China to Western religious and scientific influences. Findings show that missionaries’ botanical studies, driven by both religious and scientific interests, contributed to cross-cultural intellectual collaboration, leading to ideological–environmental changes. The research reveals that botanical exchange was not limited to science but also intertwined with political, economic, and religious interests. Furthermore, the introduction of experimental science reshaped Chinese approaches to nature, blending European and Chinese intellect systems. Ultimately, this paper argues that foreign missionaries played a crucial role in shaping both modern Chinese botany and global episteme, illustrating how scientific ideas transcended cultural boundaries to create lasting environmental impacts.
Mom Knows More than a Little Ghost: Children’s Attributions of Beliefs to God, the Living, and the Dead
Authors: Jung Dawoon , Kim Euisun , Kim Sung-Ho
Published: January 2025

The growing body of research on children’s understanding of extraordinary minds has demonstrated that children believe in the persistence of mental functioning after death. However, beyond the continuity of mind, the supernatural conception of death often involves the concept of the disembodied mind, which transcends the constraints of the physical body, possessing supernatural mental capacities. The current study investigated whether children differentiate between a dead agent’s mind and ordinary minds in terms of their perceptual and information-updating capacities. In a location-change false-belief task, which involved a story of a mouse protagonist that was either eaten by an alligator or not, 4- to 6-year-old Korean children (N = 114) were asked about the mental states of the protagonist, an ordinary adult (mom), and God. The results showed (1) older children’s tendency to respond in a way that differentiated (the living) mom from the dead protagonist, (2) an increasing trend of differentiating God’s super-knowingness from ordinary minds with age, and (3) inconclusive evidence regarding children’s differential responses to the dead versus living protagonist. This study suggests that children are not predisposed to view dead agents as possessing a disembodied and supernatural mind, highlighting the importance of cultural learning in the development of such religious concepts.
Applying the Dempster–Shafer Fusion Theory to Combine Independent Land-Use Maps: A Case Study on the Mapping of Oil Palm Plantations in Sumatra, Indonesia
Authors: Bethuel Carl , Arvor Damien , Corpetti Thomas , Hélie Julia , Descals Adrià , Gaveau David , Chéron-Bessou Cécile , Gignoux Jérémie , Corgne Samuel
Published: January 2025

The remote sensing community benefits from new sensors and easier access to Earth Observation data to frequently released new land-cover maps. The propagation of such independent and heterogeneous products offers promising perspectives for various scientific domains and for the implementation and monitoring of land-use policies. Yet, it may also confuse the end-users when it comes to identifying the most appropriate product to address their requirements. Data fusion methods can help to combine competing and/or complementary maps in order to capitalize on their strengths while overcoming their limitations. We assessed the potential of the Dempster–Shafer Theory (DST) to enhance oil palm mapping in Sumatra (Indonesia) by combining four land-cover maps, hereafter named DESCALS, IIASA, XU, and MAPBIOMAS, according to the first author’s name or the research group that published it. The application of DST relied on four steps: (1) a discernment framework, (2) the assignment of mass functions, (3) the DST fusion rule, and (4) the DST decision rule. Our results showed that the DST decision map achieved significantly higher accuracy (Kappa = 0.78) than the most accurate input product (Kappa = 0.724). The best result was reached by considering the probabilities of pixels to belong to the OP class associated with DESCALS map. In addition, the belief (i.e., confidence) and conflict (i.e., uncertainty) maps produced by DST evidenced that industrial plantations were detected with higher confidence than smallholder plantations. Consequently, Kappa values computed locally were lower in areas dominated by smallholder plantations. Combining land-use products with DST contributes to producing state-of-the-art maps and continuous information for enhanced land-cover analysis.
Identifying Optimal Variables to Predict Soil Organic Carbon in Sandy, Saline, and Black Soil Regions: Remote Sensing, Terrain, or Climate Factors?
Authors: Wang Liping , Liu Huanjun , Wang Xiang , Xu Xiaofeng , He Liyuan , Luo Chong , Li Yong , Zhang Xinle , Zang Deqiang , Zheng Shufeng , Mei Xiaodan
Published: January 2025

Environmental variables have a substantial effect on the reliability of soil organic carbon (SOC) mapping. However, it is still challenging to identify which environmental variables are effective in cropland SOC prediction in sandy, saline, and black soil regions. To address this issue, we used the principal component analysis (PCA) method for the feature selection of bands, spectral indexes, and terrain factors for each region. Based on the selection feature, we used global RF and local RF for SOC prediction for these three regions. Our results indicated that (1) climate factors, particularly mean annual precipitation and mean annual temperature, were the most effective predictors in SOC mapping across sandy, saline, and black soil regions, as indicated by their significant contribution to RF model performance (R2 > 0.63); (2) followed by climate factors, the Transformed Vegetation Index (TVI) was consistently identified as the most influential variable for SOC prediction among spectral indexes in all three regions; (3) a local regression method based on RF models showed good performance compared to a global model; (4) desertification and salinization were the main reasons for the spatial differences in AH and DM&LD, respectively. The SOC of HL in black soil regions was consistent with the climate change trend because of the latitude difference. This study provides valuable information for constructing a more precise soil prediction strategy for cultivated land in sandy, saline, and black soil regions.
Delay-Sensitive Multi-Sensor Routing Scheduling Method for Underground IoT in Mines
Authors: Zhang Yinghui , Liu Mingli , Tan Aiping
Published: January 2025

Recently, there has been a growing interest in underground construction safety, during activities such as subway construction, underground mining, and tunnel excavation. While Internet of Things (IoT) sensors help to monitor these conditions, large-scale deployment is limited by high power needs and complex tunnel layouts, making real-time response a critical challenge. A delay-sensitive multi-sensor multi-base-station routing scheduling method is proposed for the IoT in underground mining. First, a mixed network topology of wireless and wired networks is formed based on the irregular distribution characteristics of multiple tunnels in the mine construction environment. Based on this topology, a multi-sensor and multi-base-station real-time routing scheduling problem is proposed, proving that the problem is NP-hard. Secondly, the corresponding solving algorithms are designed based on the greedy strategy and the heuristic strategy. Finally, an experimental platform is built, and the performance of the proposed algorithm is compared and analyzed.
Evaluation of Semantic Segmentation Performance for a Multimodal Roadside Vehicle Detection System on the Edge
Authors: Ervin Lauren , Eastepp Max , McVicker Mason , Ricks Kenneth
Published: January 2025

Discretely monitoring traffic systems and tracking payloads on vehicle targets can be challenging when traversal occurs off main roads where overhead traffic cameras are not present. This work proposes a portable roadside vehicle detection system as part of a solution for tracking traffic along any path. Training semantic segmentation networks to automatically detect specific types of vehicles while ignoring others will allow the user to track payloads present only on certain vehicles of interest, such as train cars or semi-trucks. Different vision sensors offer varying advantages for detecting targets in changing environments and weather conditions. To analyze the benefits of both, corresponding LiDAR and camera data were collected at multiple roadside sites and then trained on separate semantic segmentation networks for object detection. A custom CNN architecture was built to handle highly asymmetric LiDAR data, and a network inspired by DeepLabV3+ was used for camera data. The performance of both networks was evaluated, and showed comparable accuracy. Inferences run on embedded platforms showed real-time execution matching the performance on the training hardware for edge deployments anywhere. Both camera and LiDAR semantic segmentation networks were successful in identifying vehicles of interest from the proposed viewpoint. These highly accurate vehicle detection networks can pair with a tracking mechanism to establish a non-intrusive roadside detection system.
Classroom Behavior Recognition Using Computer Vision: A Systematic Review
Authors: Liu Qingtang , Jiang Xinyu , Jiang Ruyi
Published: January 2025

Behavioral computing based on visual cues has become increasingly important, as it can capture and annotate teachers’ and students’ classroom states on a large scale and in real time. However, there is a lack of consensus on the research status and future trends of computer vision-based classroom behavior recognition. The present study conducted a systematic literature review of 80 peer-reviewed journal articles following the Preferred Reporting Items for Systematic Assessment and Meta-Analysis (PRISMA) guidelines. Three research questions were addressed concerning goal orientation, recognition techniques, and research challenges. Results showed that: (1) computer vision-supported classroom behavior recognition focused on four categories: physical action, learning engagement, attention, and emotion. Physical actions and learning engagement have been the primary recognition targets; (2) behavioral categorizations have been defined in various ways and lack connections to instructional content and events; (3) existing studies have focused on college students, especially in a natural classical classroom; (4) deep learning was the main recognition method, and the YOLO series was applicable for multiple behavioral purposes; (5) moreover, we identified challenges in experimental design, recognition methods, practical applications, and pedagogical research in computer vision. This review will not only inform the recognition and application of computer vision to classroom behavior but also provide insights for future research.
Smartphone-Based Experimental Analysis of Rainfall Effects on LTE Signal Indicators
Authors: Xu Yiyi , Wu Kai , Zhang J. Andrew , Wang Zhongqin , Jayawickrama Beeshanga A. , Guo Y. Jay
Published: January 2025

This work investigates the impact of rainfall on cellular communication links, leveraging smartphone-collected measurements. While existing studies primarily focus on line-of-sight (LoS) microwave propagation environments, this work explores the impact of rainfall on typical signal metrics over cellular links when the LoS path is not guaranteed. We examine both small-scale and large-scale variations in signal measurements across dry and rainy days, considering diverse locations and time windows. Through statistical and spectral analysis of a large dataset, we uncover novel insights into how rainfall influences cellular communication links. Specifically, we observe a consistent daily fluctuation pattern in key cellular metrics, such as the reference signal received quality. Additionally, spectral features of key mobile metrics show noticeable changes during rainfall events. These findings, consistent across three distinct locations, highlight the significant impact of rainfall on everyday cellular links. They also suggest that the widely available by-product signals from mobile phones could be leveraged for innovative rainfall-sensing applications.
An Ultra-Wide Range D-Shaped Fiber SPR Sensor with a Nanostructure of Gold–MoS2 and Sodium for the Simultaneous Measurement of Refractive Index and Temperature
Authors: Lu Xinglian , Yu Xiantong , Zhou Jun , Chang Min , Lu Dunke
Published: January 2025

Refractive index (RI) and temperature (T) are both critical environmental parameters for environmental monitoring, food production, and medical testing. The paper develops a D-shaped photonic crystal fiber (PCF) sensor to measure RI and T simultaneously. Its cross-sectional structure encompasses a hexagonal-hole lattice, with one hole selectively filled with toluene for temperature sensing. By coating the D-shaped surface of the PCF with a metal film and a MoS2 film, the refractive index-detection channel is formed. Numerical results demonstrate that RI and T can be reflected in the same spectrum, without any interference caused by the two parameters with each other. At an environmental RI of 1.26–1.38, its maximum RI sensitivity is up to 5400 nm/RIU. At a temperature of 20–80 °C, its temperature sensitivity reaches −1.2 nm/°C. This design allows for a broad operational spectrum and an extensive measurement range, which makes it particularly suitable for applications requiring low-RI detection. Moreover, the resonance strength of the sensor is significantly enhanced by introducing a two-dimensional material MoS2 on the D-surface. Specifically, it reaches 195,149 dB/m when RI = 1.34 at 30 °C. This is much higher than that of most previous studies, and the requirements for inspection equipment can be lowered in this case. These results are essential for progress in simultaneously detecting RI and T.
Rapid and Simultaneous Detection of Petroleum Hydrocarbons and Organic Pesticides in Soil Based on Electronic Nose
Authors: Kong Cheng , Sun Lin , Li Xiaodan , Yan Yu , Chang Zhiyong , Li Mo , Gou Fuyan , Rong Baojun
Published: January 2025

The rapid detection of petroleum hydrocarbons and organic pesticides is an important prerequisite for precise soil management. It is also a guarantee for soil quality, environmental safety, and human health. However, the current rapid detection methods are prone to sample matrix interference, complex development processes, short lifespan, and low detection accuracy. Moreover, they face difficulties in achieving simultaneous detection of petroleum hydrocarbons and organic pesticides. In this paper, we developed an electronic nose system for the simultaneous detection of petroleum hydrocarbons and organic pesticides in soil based on gas technology, which includes a sampling module and recognition model. The developed sampling module can simultaneously acquire the odor signals of petroleum hydrocarbons and organic pesticides in soil. The established recognition model can quickly distinguish between healthy soil, soil contaminated by petroleum hydrocarbons, and soil contaminated by organic pesticides. It can also achieve specific recognition of pesticide types and petroleum types. The performance of the developed electronic nose system was verified for real soil, petroleum products, and organic pesticides. The experiment shows that the developed electronic nose system has an accuracy of 100% for three tasks: soil conditions identification, pesticide types identification, and petroleum types identification.
Research on a Novel Unsupervised-Learning-Based Pipeline Leak Detection Method Based on Temporal Kolmogorov–Arnold Network with Autoencoder Integration
Authors: Wu Hengyu , Jiang Zhu , Zhang Xiang , Cheng Jian
Published: January 2025

Artificial intelligence (AI) technologies have been widely applied to the automated detection of pipeline leaks. However, traditional AI methods still face significant challenges in effectively detecting the complete leak process. Furthermore, the deployment cost of such models has increased substantially due to the use of GPU-trained neural networks in recent years. In this study, we propose a novel leak detector, which includes a new model and a sequence labeling method that integrates prior knowledge with traditional reconstruction error theory. The proposed model combines the Kolmogorov–Arnold Network (KAN) with an autoencoder (AE). This model combines the Kolmogorov–Arnold Network (KAN) with an autoencoder (AE), forming a hybrid framework that effectively captures complex temporal dependencies in the data while exhibiting strong pattern modeling and reconstruction capabilities. To improve leak detection, we developed a novel unsupervised anomaly sequence labeling method based on traditional reconstruction error theory, which incorporates an in-depth analysis of the reconstruction error curve along with prior knowledge. This method significantly enhances the interpretability and accuracy of the detection process. Field experiments were conducted on real urban water supply pipelines, and a benchmark dataset was established to evaluate the proposed model and method against commonly used models and methods. The experimental results demonstrate that the proposed model and method achieved a high segment-wise precision of 93.1%. Overall, this study presents a transparent and robust solution for automated pipeline leak detection, facilitating the large-scale, cost-effective development of digital twin systems for urban pipeline leak emergency management.
Deep Reinforcemnet Learning for Robust Beamforming in Integrated Sensing, Communication and Power Transmission Systems
Authors: Xie Chenfei , Xiu Yue , Yang Songjie , Miao Qilong , Chen Lu , Gao Yong , Zhang Zhongpei
Published: January 2025

A communication network integrating multiple modes can effectively support the sustainable development of next-generation wireless communications. Integrated sensing, communication, and power transfer (ISCPT) represents an emerging technological paradigm that not only facilitates information transmission but also enables environmental sensing and wireless power transfer. To achieve optimal beamforming in transmission, it is crucial to satisfy multiple constraints, including quality of service (QoS), radar sensing accuracy, and power transfer efficiency, while ensuring fundamental system performance. The presence of multiple parametric constraints makes the problem a non-convex optimization challenge, underscoring the need for a solution that balances low computational complexity with high precision. Additionally, the accuracy of channel state information (CSI) is pivotal in determining the achievable rate, as imperfect or incomplete CSI can significantly degrade system performance and beamforming efficiency. Deep reinforcement learning (DRL), a machine learning technique where an agent learns by interacting with its environment, offers a promising approach that can dynamically optimize system performance through adaptive decision-making strategies. In this paper, we propose a DRL-based ISCPT framework, which effectively manages complex environmental states and continuously adjusts variables related to sensing, communication, and energy harvesting to enhance overall system efficiency and reliability. The achievable rate upper bound can be inferred through robust, learnable beamforming in the ISCPT system. Our results demonstrate that DRL-based algorithms significantly improve resource allocation, power management, and information transmission, particularly in dynamic and uncertain environments with imperfect CSI.
Application of Additive Manufacturing and Deep Learning in Exercise State Discrimination
Authors: Zhao Zhilong , Yang Jiaxi , Liu Jiahao , Soong Shijie , Wang Yiming , Zhang Juan
Published: January 2025

With the rapid development of sports technology, smart wearable devices play a crucial role in athletic training and health management. Sports fatigue is a key factor affecting athletic performance. Using smart wearable devices to detect the onset of fatigue can optimize training, prevent excessive fatigue and resultant injury, and increase efficiency and safety. However, current wearable sensing devices are often uncomfortable and imprecise. Furthermore, stable methods for fatigue detection are not yet established. To address these challenges, this paper introduces 3D printing and deep learning to design a smart wearable sensing device to detect different states of sports fatigue. First, to meet the need for comfort and improved accuracy in data collection, we utilized reverse engineering and additive manufacturing technologies. Second, we designed a prototype based on the long short-term memory (LSTM) neural network to analyze the collected bioelectrical signals for the identification of sports fatigue states and the extraction of related indicators. Finally, we conducted a large number of numerical experiments. The results demonstrated that our prototype and related equipment could collect signals and mine information as well as identify indicators associated with sports fatigue in the signals, thereby improving accuracy in the classification of fatigue states.
Fathers’ Experiences of Relationship Breakdown Including Post-Separation Abuse and Parental Alienating Behaviours
Authors: Hine Benjamin , Roy Eilish Mairi , Huang Ching-Yu , Bates Elizabeth
Published: January 2025

Background: Family breakdown, separation, and divorce (FBSD) are often traumatic events, particularly for fathers who face unique challenges. These include emotional, psychological, and financial struggles, often exacerbated by abusive behaviours from ex-partners. This study explores fathers’ experiences of FBSD, focusing on both the breakdown event itself and any abuse, including coercive control and parental alienation, before and after the separation. Methods: A mixed-methods approach was employed, including a survey of 141 men and follow-up interviews with 30 participants. Data were analysed using reflexive thematic analysis to identify key themes related to FBSD and associated abuse. Results: Fathers reported significant emotional, psychological, and financial distress, with many experiencing ongoing abuse and coercive control after separation. Abuse often continued through legal processes and manipulation of child access. Parental alienation emerged as a prominent form of post-separation abuse, with fathers describing attempts by ex-partners to undermine their relationships with their children. Conclusions: The findings highlight the need for gender-inclusive services that address the specific challenges fathers face during and after FBSD, particularly in relation to post-separation abuse. Targeted interventions are necessary to support fathers’ well-being and ensure their continued involvement in their children’s lives.