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Search Results (8,027)

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12 pages, 1712 KB  
Case Report
Refractory CMV Enteritis in Small Bowel Transplantation: A Case Highlighting the Challenges of Balancing Immunosuppression and Novel Antiviral Therapies
by Abdulrahman A. Al-Saud, Ehab H. Abufarhaneh, Madain S. Alsanea, Reem M. Alameer, Amani H. Yamani, Fatimah S. Alhamlan and Reem S. Almaghrabi
Viruses 2025, 17(10), 1379; https://doi.org/10.3390/v17101379 - 15 Oct 2025
Abstract
Background: Cytomegalovirus (CMV) remains a formidable complication in small bowel transplantation (SBT) due to the graft’s high immunogenicity and profound immunosuppression required, with refractory disease representing a particularly devastating challenge. Case: We report an 18-year-old male who underwent SBT, complicated by recurrent acute [...] Read more.
Background: Cytomegalovirus (CMV) remains a formidable complication in small bowel transplantation (SBT) due to the graft’s high immunogenicity and profound immunosuppression required, with refractory disease representing a particularly devastating challenge. Case: We report an 18-year-old male who underwent SBT, complicated by recurrent acute rejection episodes requiring intensive immunosuppression. He developed refractory CMV disease, marked by non-response to first line therapy with ganciclovir—despite the absence of genotypic resistance—necessitating sequential use of foscarnet, dual antivirals, CMV immunoglobulin, and novel agents (maribavir and letermovir). Discussion: This case illustrates the multifactorial drivers of refractory CMV disease in SBT recipients, including donor–recipient serostatus mismatch, profound immunosuppression through T-cell-depleting induction, corticosteroid exposure, and biologic therapy. It highlights the distinction between refractory and resistant CMV, and the role of combination antiviral strategies including novel agents to achieve disease control. Outcomes remain dismal despite aggressive and innovative therapies, underscoring the limited efficacy of interventions in the context of severe immunologic compromise. Conclusions: Refractory CMV enteritis in SBT exemplifies the extreme difficulty of balancing viral control with rejection management. Despite exhausting antiviral strategies, survival remains poor. Highlights: Refractory CMV enteritis is a significant challenge in small bowel transplant recipients due to intense immunosuppression. Persistent CMV disease may occur despite antiviral prophylaxis and the absence of resistant gene mutations. Combination antiviral strategies, including maribavir, demonstrated significant clinical improvement. Profound immunosuppression required to manage acute graft rejection episodes complicates antiviral management and disease clearance. Despite best efforts in CMV management in this population, outcomes may still be compromised by unrelated or compounding factors. Full article
15 pages, 878 KB  
Article
Development and Validation of the Eating Support for Healthcare Aides (ESHA) Questionnaire in Long-Term Care
by Chia-Hui Lin and Ming-Yi Liu
Nutrients 2025, 17(20), 3235; https://doi.org/10.3390/nu17203235 - 15 Oct 2025
Abstract
Background: Swallowing difficulties (dysphagia) are highly prevalent among older adults and significantly contribute to malnutrition, dehydration, and poor health outcomes. Healthcare aides (HCAs), as frontline caregivers in long-term care, play a pivotal role in supporting residents’ nutritional intake. However, validated tools to evaluate [...] Read more.
Background: Swallowing difficulties (dysphagia) are highly prevalent among older adults and significantly contribute to malnutrition, dehydration, and poor health outcomes. Healthcare aides (HCAs), as frontline caregivers in long-term care, play a pivotal role in supporting residents’ nutritional intake. However, validated tools to evaluate their competencies in nutrition-related eating support are lacking. Methods: A cross-sectional study was conducted to develop and validate a competency-based questionnaire assessing healthcare aides’ knowledge, attitudes, and behaviors toward nutrition-focused eating support. Core domains, including oral function care, safe feeding practices, food texture modification, and nutrition safety, were identified through a systematic literature review and refined using a two-round modified Delphi process involving 26 experts. A 47-item questionnaire was then administered to 202 HCAs in Taiwan. Psychometric testing included item analysis, KR-20, Cronbach’s α, confirmatory factor analysis (CFA), composite reliability (CR), and average variance extracted (AVE). Results: The final instrument demonstrated strong content validity. The knowledge domain achieved acceptable reliability (KR-20 = 0.61), while the attitude and behavior domains showed excellent internal consistency (Cronbach’s α = 0.98). CFA confirmed good structural validity (χ2/df = 3.86, CFI = 0.93). CR and AVE values further supported construct validity. Conclusions: This nutrition-centered questionnaire is a valid and reliable tool to assess HCAs’ competencies in providing eating support. It offers a foundation for identifying training needs and designing educational programs aimed at preventing malnutrition and enhancing person-centered mealtime care in long-term care facilities. Full article
(This article belongs to the Special Issue Advances in Technology for Dietary Assessment)
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21 pages, 1674 KB  
Article
Comparative Transcriptomics Provides Insight into the Neuroendocrine Regulation of Spawning in the Black-Lip Rock Oyster (Saccostrea echinata)
by Md Abu Zafar, Saowaros Suwansa-ard, Aiden Mellor, Max Wingfield, Karl Reiher, Abigail Elizur and Scott F. Cummins
Int. J. Mol. Sci. 2025, 26(20), 10032; https://doi.org/10.3390/ijms262010032 - 15 Oct 2025
Abstract
The black-lip rock oyster, Saccostrea echinata, is an emerging aquaculture species; however, difficulties in regulating their gonad conditioning to full maturation and spawning have impacted industry progress. Addressing this challenge requires a deeper understanding of the molecular mechanisms underlying reproduction, particularly the [...] Read more.
The black-lip rock oyster, Saccostrea echinata, is an emerging aquaculture species; however, difficulties in regulating their gonad conditioning to full maturation and spawning have impacted industry progress. Addressing this challenge requires a deeper understanding of the molecular mechanisms underlying reproduction, particularly the signalling molecules (e.g., neuroendocrine hormones) that regulate gonad development and spawning, which remains poorly understood in this species. Therefore, we investigated the molecular neuroendocrine regulation of gonad maturation in S. echinata through the analysis of gonad histological changes correlated with gene expression in the visceral ganglia and gonad (of male and female) at pre- and post-spawn stages. Our targeted analysis of neuropeptide genes demonstrated that only LASGLVamide showed significant differential expression, being upregulated in the pre-spawn female gonad. Of the 26 reproductive-related genes identified, four were significantly upregulated in female gonad (SOX9, Dax1, Nanos-like, and Piwi-like), while an insulin-like peptide receptor was elevated in male visceral ganglia at post-spawn. Untargeted investigation revealed numerous transmembrane receptors significantly upregulated in the pre-spawn ovary, such as receptors for thyrotropin-releasing hormone, metabotropic glutamate, and 5-hydroxytryptamine, while mesotocin and oxytocin receptors were upregulated in pre-spawn male gonads. At the post-spawn stage, the visceral ganglia displayed upregulation of genes encoding stress-related proteins such as superoxidase dismutase and DnaJ homologue subfamily A member 1. These findings provide important insights into the complexities of neuroendocrine signalling molecules and establish a molecular foundation to guide selective breeding and broodstock management strategies that will support sustainable aquaculture development of black-lip rock oyster. Full article
(This article belongs to the Section Molecular Biology)
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23 pages, 1091 KB  
Article
Proposing an Information Management Framework for Efficient Testing Strategies of Automotive Integration
by Wang Zhang, Meng Shi, Xinglong Liu and Linjie Ren
Processes 2025, 13(10), 3296; https://doi.org/10.3390/pr13103296 - 15 Oct 2025
Abstract
The increasing quantity and complexity of code in vehicles have imposed a heavy burden on traditional integration testing methods. However, applying new testing methods, such as eliminating redundant test cases, prioritizing based on risk, and optimizing test matching, requires the testing team to [...] Read more.
The increasing quantity and complexity of code in vehicles have imposed a heavy burden on traditional integration testing methods. However, applying new testing methods, such as eliminating redundant test cases, prioritizing based on risk, and optimizing test matching, requires the testing team to possess sufficient information, which entails communication and time costs. In this study, an information management framework is developed for the integration testing phase of automotive software to assess the importance and acquisition difficulty of specific information. The framework mainly includes three core parts: (1) classifying 37 types of test-related information into five hierarchical levels (requirement level, architecture level, function level, component level, and source code level) based on risk theory; (2) designing a scale to evaluate the difficulty of information usage from three dimensions (acquisition, transmission, and evaluation); (3) providing an operational guide for integration testing departments to match information with testing strategies. This framework assists enterprises in making wiser decisions regarding testing methods and provides guidance for future collaboration between original equipment manufacturers and suppliers. Full article
(This article belongs to the Special Issue Reliability and Engineering Applications (Volume II))
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26 pages, 7247 KB  
Article
DyslexiaNet: Examining the Viability and Efficacy of Eye Movement-Based Deep Learning for Dyslexia Detection
by Ramis İleri, Çiğdem Gülüzar Altıntop, Fatma Latifoğlu and Esra Demirci
J. Eye Mov. Res. 2025, 18(5), 56; https://doi.org/10.3390/jemr18050056 - 15 Oct 2025
Abstract
Dyslexia is a neurodevelopmental disorder that impairs reading, affecting 5–17.5% of children and representing the most common learning disability. Individuals with dyslexia experience decoding, reading fluency, and comprehension difficulties, hindering vocabulary development and learning. Early and accurate identification is essential for targeted interventions. [...] Read more.
Dyslexia is a neurodevelopmental disorder that impairs reading, affecting 5–17.5% of children and representing the most common learning disability. Individuals with dyslexia experience decoding, reading fluency, and comprehension difficulties, hindering vocabulary development and learning. Early and accurate identification is essential for targeted interventions. Traditional diagnostic methods rely on behavioral assessments and neuropsychological tests, which can be time-consuming and subjective. Recent studies suggest that physiological signals, such as electrooculography (EOG), can provide objective insights into reading-related cognitive and visual processes. Despite this potential, there is limited research on how typeface and font characteristics influence reading performance in dyslexic children using EOG measurements. To address this gap, we investigated the most suitable typefaces for Turkish-speaking children with dyslexia by analyzing EOG signals recorded during reading tasks. We developed a novel deep learning framework, DyslexiaNet, using scalogram images from horizontal and vertical EOG channels, and compared it with AlexNet, MobileNet, and ResNet. Reading performance indicators, including reading time, blink rate, regression rate, and EOG signal energy, were evaluated across multiple typefaces and font sizes. Results showed that typeface significantly affects reading efficiency in dyslexic children. The BonvenoCF font was associated with shorter reading times, fewer regressions, and lower cognitive load. DyslexiaNet achieved the highest classification accuracy (99.96% for horizontal channels) while requiring lower computational load than other networks. These findings demonstrate that EOG-based physiological measurements combined with deep learning offer a non-invasive, objective approach for dyslexia detection and personalized typeface selection. This method can provide practical guidance for designing educational materials and support clinicians in early diagnosis and individualized intervention strategies for children with dyslexia. Full article
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15 pages, 248 KB  
Article
Exploring the Experiences of Individuals Diagnosed with Metastatic Non-Small-Cell Lung Cancer: A Qualitative Study
by Sarah Scruton, Caroline Hovey, Cynthia Kendell and Robin Urquhart
Curr. Oncol. 2025, 32(10), 570; https://doi.org/10.3390/curroncol32100570 - 15 Oct 2025
Abstract
Advancements in targeted therapies and immunotherapies have improved survival for individuals with metastatic non-small-cell lung cancer (mNSCLC), creating a growing population of Canadians living long-term with the disease. These individuals face ongoing physical, emotional, and practical challenges, yet existing supportive care services are [...] Read more.
Advancements in targeted therapies and immunotherapies have improved survival for individuals with metastatic non-small-cell lung cancer (mNSCLC), creating a growing population of Canadians living long-term with the disease. These individuals face ongoing physical, emotional, and practical challenges, yet existing supportive care services are often designed for patients receiving curative intent treatment and may not adequately address the challenges of those undergoing continuous treatment. To explore these experiences and inform the development of supports tailored to their needs, eight participants with mNSCLC completed one-on-one virtual interviews. They described limited support for managing side effects and psychosocial concerns despite general satisfaction with oncology care. Fatigue and cognitive challenges impacted daily functioning, and emotional challenges (e.g., fear of progression, stigma, and difficulty finding meaning) impacted quality of life. Financial burden, including unexpected costs and loss of income, further affected their well-being. Existing supports, such as exercise programs, were viewed positively but were often difficult to access, were offered only short-term, and required patients to find them independently. Recommendations included improved coordination and communication across the healthcare system, alongside tailored interventions such as navigation services, resource directories, health promotion supports, and expanded peer support. Overall, people living long term with mNSCLC face distinct challenges and unmet supportive care needs, highlighting the importance of integrating supportive services into routine oncology care. Full article
9 pages, 1700 KB  
Proceeding Paper
Implementation of Industry 5.0 in SME: Scoping Review
by Zineb Bentassil, Anass Ben Abdelouahab and Aniss Moumen
Eng. Proc. 2025, 112(1), 14; https://doi.org/10.3390/engproc2025112014 - 15 Oct 2025
Abstract
Industry 5.0 (I5) represents a significant evolution in the trajectory of industrial development, emphasizing a human-centric approach that integrates advanced technologies with the goal of promoting sustainable growth, resilience, and enhanced human well-being. While Industry 4.0 already posed considerable challenges for industrial organizations, [...] Read more.
Industry 5.0 (I5) represents a significant evolution in the trajectory of industrial development, emphasizing a human-centric approach that integrates advanced technologies with the goal of promoting sustainable growth, resilience, and enhanced human well-being. While Industry 4.0 already posed considerable challenges for industrial organizations, particularly in terms of technological integration, workforce adaptation, and strategic realignment, the shift toward Industry 5.0 has introduced additional complexities. The accelerated pace of innovation and the evolving expectations for human–machine collaboration have intensified these challenges. Large manufacturing corporations are already facing difficulties in adapting to this new paradigm; thus, the question arises: how are Small and Medium-sized Enterprises (SMEs), which typically operate with limited resources, infrastructure, and financial capacity, managing this transition? This paper presents a scoping review of 17 research papers, chosen from an initial set of 37 publications sourced from Scopus, Web of Science and ScienceDirect on the implementation of Industry 5.0 in SMEs. A comprehensive synthesis of existing research was conducted to elucidate the current state of the topic, identify the research questions addressed, and outline future directions for this emerging paradigm. Full article
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0 pages, 423 KB  
Proceeding Paper
Virtual Laboratories in STEM Education: A Scoping Literature Review on E-Learning Innovation
by Hajar Hanine, Nouhaila Farajy and Aniss Moumen
Eng. Proc. 2025, 112(1), 17; https://doi.org/10.3390/engproc2025112017 - 14 Oct 2025
Abstract
As digital learning continues to expand, virtual laboratories have become increasingly prominent in STEM education. This scoping review explores the development and application of virtual labs within online and blended learning settings. It looks into how these resources encourage experiential learning, increase student [...] Read more.
As digital learning continues to expand, virtual laboratories have become increasingly prominent in STEM education. This scoping review explores the development and application of virtual labs within online and blended learning settings. It looks into how these resources encourage experiential learning, increase student interest, and offer substitutes for conventional laboratory limitations. The evaluation concentrates on important aspects such as learning objectives, instructional techniques, technology infrastructure, and real-world implementation difficulties. It also identifies recurring limitations in the current body of research, including the lack of adaptable virtual lab designs and limited empirical evaluation. The study highlights the essential role of virtual laboratories in advancing e-learning innovation and outlines future research directions aimed at maximizing their educational impact in STEM fields. Full article
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34 pages, 3248 KB  
Article
Playing Gebeta in Preschool: Informal Pathways to Early Numeracy Through Directionality and Bundling
by Oliver Thiel
Educ. Sci. 2025, 15(10), 1365; https://doi.org/10.3390/educsci15101365 - 14 Oct 2025
Abstract
Preschool children develop essential mathematical concepts through play, yet little is known about how traditional board games can support this process. This small-scale microgenetic case study investigates how children unfamiliar with the Ethiopian game Gebeta (a mancala-type game) learn to play the game [...] Read more.
Preschool children develop essential mathematical concepts through play, yet little is known about how traditional board games can support this process. This small-scale microgenetic case study investigates how children unfamiliar with the Ethiopian game Gebeta (a mancala-type game) learn to play the game and what mathematical competencies emerge. Video observations were conducted with 5-year-olds in Norway as they engaged in repeated play sessions. Event logs and transcripts were analysed with a focus on children’s developing strategies and difficulties. The results show that children quickly understood the basic rules but faced challenges with directionality (i.e., maintaining the correct direction of play) and differentiating between different types of game moves. Over time, they demonstrated evident progress in following the rules. They began to treat groups of counters as units, moving from one-by-one counting to bundling and unitising. These developments align with Bishop’s fundamental activities locating and counting. We conclude that Gebeta provides a playful context in which children can practice directionality and bundling, both of which are crucial for avoiding common errors in later school mathematics, such as off-by-one counting errors and misunderstandings of the number system. The study suggests that Gebeta can be introduced in early childhood settings without simplifying the rules, providing an engaging resource for early mathematics education. Full article
(This article belongs to the Special Issue Exploring Mathematical Thinking in Early Childhood Education)
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22 pages, 1922 KB  
Article
Real-Time Detection of LEO Satellite Orbit Maneuvers Based on Geometric Distance Difference
by Aoran Peng, Bobin Cui, Guanwen Huang, Le Wang, Haonan She, Dandan Song and Shi Du
Aerospace 2025, 12(10), 925; https://doi.org/10.3390/aerospace12100925 (registering DOI) - 14 Oct 2025
Abstract
Low Earth orbit (LEO) satellites, characterized by low altitudes, high velocities, and strong ground signal reception, have become an essential and dynamic component of modern global navigation satellite systems (GNSS). However, orbit decay induced by atmospheric drag poses persistent challenges to maintaining stable [...] Read more.
Low Earth orbit (LEO) satellites, characterized by low altitudes, high velocities, and strong ground signal reception, have become an essential and dynamic component of modern global navigation satellite systems (GNSS). However, orbit decay induced by atmospheric drag poses persistent challenges to maintaining stable trajectories. Frequent orbit maneuvers, though necessary to sustain nominal orbits, introduce significant difficulties for precise orbit determination (POD) and navigation augmentation, especially under complex operational conditions. Unlike most existing methods that rely on Two-Line Element (TLE) data—often affected by noise and limited accuracy—this study directly utilizes onboard GNSS observations in combination with real-time precise ephemerides. A novel time-series indicator is proposed, defined as the geometric root-mean-square (RMS) distance between reduced-dynamic and kinematic orbit solutions, which is highly responsive to orbit disturbances. To further enhance robustness, a sliding window-based adaptive thresholding mechanism is developed to dynamically adjust detection thresholds, maintaining sensitivity to maneuvers while suppressing false alarms. The proposed method was validated using eight representative maneuver events from the GRACE-FO satellites (May 2018–June 2022), successfully detecting seven of them. One extremely short-duration maneuver was missed due to the limited number of usable GNSS observations after quality-control filtering. To examine altitude-related applicability, two Sentinel-3A maneuvers were also analyzed, both successfully detected, confirming the method’s effectiveness at higher LEO altitudes. Since the thrust magnitudes and durations of the Sentinel-3A maneuvers are not publicly available, these cases primarily serve to verify applicability rather than to quantify sensitivity. Experimental results show that for GRACE-FO maneuvers, the proposed method achieves near-real-time responsiveness under long-duration, high-thrust conditions, with an average detection delay below 90 s. For Sentinel-3A, detections occurred approximately 7 s earlier than the reported maneuver epochs, a discrepancy attributed to the 30 s observation sampling interval rather than methodological bias. Comparative analysis with representative existing methods, presented in the discussion section, further demonstrates the advantages of the proposed approach in terms of sensitivity, timeliness, and adaptability. Overall, this study presents a practical, efficient, and scalable solution for real-time maneuver detection in LEO satellite missions, contributing to improved GNSS augmentation, space situational awareness, and autonomous orbit control. Full article
(This article belongs to the Special Issue Precise Orbit Determination of the Spacecraft)
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24 pages, 2306 KB  
Article
Dual-Path Short Text Classification with Data Optimization
by Wei Li, Guangying Lv and Yunling He
Appl. Sci. 2025, 15(20), 11015; https://doi.org/10.3390/app152011015 - 14 Oct 2025
Abstract
In order to solve problems of fragmented information, missing context and difficult-to-capture feature information in short texts, this paper proposes a dual-path classification model combining word-level and sentence-level feature information. Our method is developing the BERT pre-trained model for obtaining word vectors, and [...] Read more.
In order to solve problems of fragmented information, missing context and difficult-to-capture feature information in short texts, this paper proposes a dual-path classification model combining word-level and sentence-level feature information. Our method is developing the BERT pre-trained model for obtaining word vectors, and presenting attention mechanisms and the BiGRU model to extract local key information and global semantic information, respectively. To tackle the difficulties of models focusing more on hard-to-learn samples during training, a novel hybrid loss function is constructed as an optimization objective, and to address common quality issues in training data, a text data optimization method that integrates data filtering and augmentation techniques is proposed. This method aims to further enhance model performance by improving the quality of input data. Experimental results on three different short text datasets show that our proposed model outperforms existing models (such as Att + BiGRU, BERT + At), with an average F1 score exceeding 90%. Moreover, the performance metrics of the model improved on the datasets optimized with the proposed data optimization method compared to the original datasets, demonstrating the effectiveness of this method in enhancing training data quality and improving model performance. Full article
(This article belongs to the Special Issue Natural Language Processing in the Era of Artificial Intelligence)
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29 pages, 2033 KB  
Review
The Intelligentization Process of Agricultural Greenhouse: A Review of Control Strategies and Modeling Techniques
by Kangji Li, Jialu Shi, Chenglei Hu and Wenping Xue
Agriculture 2025, 15(20), 2135; https://doi.org/10.3390/agriculture15202135 - 14 Oct 2025
Abstract
With the increasing demand for sustainable food production, the facility agriculture is progressively developing towards automation and intelligence. Traditional control techniques such as PID, fuzzy logic, and model predictive control have been widely applied in greenhouse planting for years. Existing greenhouse management systems [...] Read more.
With the increasing demand for sustainable food production, the facility agriculture is progressively developing towards automation and intelligence. Traditional control techniques such as PID, fuzzy logic, and model predictive control have been widely applied in greenhouse planting for years. Existing greenhouse management systems still face challenges such as limited adaptability to fluctuating outdoor climates, and difficulties in maintaining both productivity and cost-effectiveness. Recently, with the development of greenhouse systems towards comprehensive environmental perception and intelligent decision-making, a large number of intelligent control and modeling technologies have provided new opportunities for the technological update of greenhouse management systems. This review systematically summarizes recent progress in greenhouse regulation and crop growth control technologies, emphasizing applications of intelligent techniques, involving adaptive strategies, neural networks, and reinforcement learning. Special attention is given to how these methods improve system robustness and control performance in terms of environmental stability, crop productivity, and energy efficiency, which are key performance indicators of greenhouse systems. Their advantages over conventional strategies in agricultural greenhouse systems are also analyzed in detail. Furthermore, the integration of intelligent technologies with greenhouse system modeling is examined, covering both greenhouse environmental models and crop growth models. The strengths and weaknesses of different techniques, such as mechanism, computational fluid dynamics (CFD), and data-driven models, are analyzed and discussed in terms of accuracy, computational cost, and applicability. Finally, future challenges and research opportunities are discussed, emphasizing the need for real-time adaptability, sustainability, and cluster intelligence. Full article
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9 pages, 902 KB  
Communication
A New Method for Calculating Dynamic Reserves of Fault-Controlled Condensate Gas Reservoir
by Quanhua Huang, Fengyuan Wang, Hong Xiao, Wenxue Zhang, Jie Liu, Wenliang Li and Cong Yang
Energies 2025, 18(20), 5402; https://doi.org/10.3390/en18205402 - 14 Oct 2025
Abstract
The SHB fault-controlled condensate gas reservoir is the largest ultra-deep carbonate gas reservoir in China, and the accuracy of dynamic reserve calculation is an important basis for developing the development plan. The fault-controlled condensate gas reservoir has some problems, such as “ultra-deep, ultra-high [...] Read more.
The SHB fault-controlled condensate gas reservoir is the largest ultra-deep carbonate gas reservoir in China, and the accuracy of dynamic reserve calculation is an important basis for developing the development plan. The fault-controlled condensate gas reservoir has some problems, such as “ultra-deep, ultra-high temperature, supercritical”, strong heterogeneity of reservoir space, and difficulty in obtaining real underground reservoir parameters, which seriously affect the results of dynamic reserve evaluation. Combining the quasi-steady flow equation and the flow resistance of a gas well, a new flow material balance method based on the original apparent formation pressure and daily production data is proposed to effectively calculate the dynamic reserves of a gas reservoir. By comparing the calculation results of various dynamic reserves calculation methods for the SHB condensate gas reservoir, it is proven that this method can effectively calculate the dynamic reserves of gas wells and has important guiding significance for the calculation of dynamic reserves of fault control body condensate gas reservoirs. Full article
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23 pages, 4375 KB  
Article
Association Between Neonicotinoids and Neurobehavioral Development in Preschool Children from South China: A Biomonitoring-Based Study
by Yixiang Zhou, Yong Wang, Zhan Huang, Wanting Xiao, Yujie He, Hui Guo, Wen Chen, Siqi Ai, Liecheng Hong, Lei Lu, Jianyong Lu, Chuanwen Li, Ziquan Lv and Qing Wang
Toxics 2025, 13(10), 872; https://doi.org/10.3390/toxics13100872 - 14 Oct 2025
Abstract
Neonicotinoid insecticides (NEOs), one of the most widely used pesticide classes worldwide, have raised concerns due to potential neurotoxic effects. Yet evidence on human exposure and health outcomes, particularly in preschool children, remains limited. In this study, 506 children aged 3–6 years from [...] Read more.
Neonicotinoid insecticides (NEOs), one of the most widely used pesticide classes worldwide, have raised concerns due to potential neurotoxic effects. Yet evidence on human exposure and health outcomes, particularly in preschool children, remains limited. In this study, 506 children aged 3–6 years from Shenzhen, China, were assessed. Neurobehavioral development was evaluated with the Strengths and Difficulties Questionnaire (SDQ), and urinary concentrations of 11 NEOs were measured, including imidacloprid (IMI), clothianidin (CLO), thiamethoxam (THM), dinotefuran (DNT), nitenpyram (NIT), sulfoxaflor (SFX), acetamiprid (ACE), thiacloprid (THD), flonicamid (FLO), 6-chloronicotinic acid (6-CINA), N-desmethyl-acetamiprid (NACE), and N-desmethyl-thiamethoxam (NTHM). Seven compounds showed high detection rates, including IMI (97.4%), CLO (100%), THM (100%), DNT (99.8%), NIT (99.8%), NACE (100%), and NTHM (99.8%). The mean urinary concentration was 234.145 μg/g creatinine, exceeding levels in earlier studies and indicating widespread exposure. IMI, NTHM, and NACE showed significant positive dose–response relationships with emotional symptoms, hyperactivity, and total difficulties and were major contributors in mixture models; sex-stratified analyses suggested effect modification for NTHM and NACE. These findings provide new epidemiological evidence to inform public health risk assessment and regulatory action on NEOs. Full article
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25 pages, 535 KB  
Article
Integrating Computer Science and Informatics Education in Primary Schools: Insights from a Slovenian Professional Development Initiative
by Andrej Flogie, Alenka Lipovec and Jakob Škrobar
Sustainability 2025, 17(20), 9068; https://doi.org/10.3390/su17209068 (registering DOI) - 13 Oct 2025
Abstract
In this study, we present a professional development programme for teachers launched to introduce Computer Science and Informatics (CSI) in primary education in Slovenia. The study aims to examine which CSI core concepts teachers most frequently choose to integrate into their lessons when [...] Read more.
In this study, we present a professional development programme for teachers launched to introduce Computer Science and Informatics (CSI) in primary education in Slovenia. The study aims to examine which CSI core concepts teachers most frequently choose to integrate into their lessons when given the freedom to select the topics within the framework, and to explore how students engage with and respond to these activities, as reported in teachers’ reflections. This study is based on reflective feedback from forty-seven teachers from seven primary schools who implemented interdisciplinary lessons that integrate CSI content into existing primary school curricula. Qualitative data from 152 reflections were used to support our research findings. The results show that teachers most frequently introduced the concepts from the content area of algorithms and programming. In contrast, content areas such as computing systems, networks and the internet, data and analysis, and impacts of computing received less attention. Teachers reported that students were motivated and engaged, although some challenges emerged, including difficulties in solving tasks or following instructions. As this pilot study reports on the first year of a two-year initiative, the findings provide preliminary insights into how a structured professional development programme for teachers can support interdisciplinary approaches in CSI education. Full article
(This article belongs to the Special Issue Creating an Innovative Learning Environment)
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