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25 pages, 5770 KiB

Open AccessArticle

Comparative Transcriptome Analysis Reveals the Mechanism by Ethylene and 1-Methylcyclopropene Treatment on the Vase Life of Cut Oncidium hybridum ‘Honey Angle’

by Jingjing Kou, Xueqian Zang, Zirui Mo, Guangwei Wu, Bei Wang and Guopeng Zhu

Horticulturae 2025, 11(4), 386; https://doi.org/10.3390/horticulturae11040386 (registering DOI) - 4 Apr 2025

Abstract

The cut flowers of the Oncidium hybridum cultivar ‘Honey Angle’ are highly regarded for their vibrant floral display, excellent flower quality, and broad commercial applications. However, its postharvest vase life is significantly challenged by wilting, water loss, and color fading, primarily [...] Read more.

The cut flowers of the Oncidium hybridum cultivar ‘Honey Angle’ are highly regarded for their vibrant floral display, excellent flower quality, and broad commercial applications. However, its postharvest vase life is significantly challenged by wilting, water loss, and color fading, primarily due to ethylene exposure. To clarify the underlying mechanism, we performed treatments with ethylene and ethylene action inhibitor 1-Methylcyclopropene (1-MCP). The petal changes, vase life, and transcriptomic analysis after treatments were investigated. The results revealed that the 1-MCP treatment significantly extended the vase life by upregulating the genes involved in carotenoid synthesis, suppressing the genes related to cell wall degradation and the ethylene signaling pathways. In contrast, the ethylene treatment accelerated senescence by activating the senescence-related genes and increasing ethylene production. Transcriptome analysis identified 960 transcription factors, predominantly from the NAC, WRKY, ERF, bHLH, and MYB families, which were crucial in regulating quality changes during the vase life. A total of 5203 differentially expressed genes (DEGs) were assigned to 19 KEGG pathways including carbohydrate and energy metabolism as well as plant hormone signal transduction. Weighted gene co-expression network analysis (WGCNA) indicated that these DEGs were primarily associated with weight loss, flowering ratio, lightness, maximum petal diameter, and respiration intensity. This research provided valuable insights into the molecular mechanisms of floral senescence and practical guidance for extending the vase life of ‘Honey Angle’ cut flowers. Full article

(This article belongs to the Section Postharvest Biology, Quality, Safety, and Technology)

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20 pages, 17221 KiB

Open AccessArticle

Big Data-Driven 3D Visualization Analysis System for Promoting Regional-Scale Digital Geological Exploration

by Yiping Tian, Jiongqi Wu, Genshen Chen, Gang Liu and Xialin Zhang

Appl. Sci. 2025, 15(7), 4003; https://doi.org/10.3390/app15074003 (registering DOI) - 4 Apr 2025

Abstract

As geological exploration technology advances, geoscience relies on digitization and intelligence to address challenges such as data fragmentation, multi-source heterogeneity, and visual analysis. This study develops a big data-driven 3D visual analysis system for regional-scale applications. The system integrates three core technological components: [...] Read more.

As geological exploration technology advances, geoscience relies on digitization and intelligence to address challenges such as data fragmentation, multi-source heterogeneity, and visual analysis. This study develops a big data-driven 3D visual analysis system for regional-scale applications. The system integrates three core technological components: (1) a heterogeneous cloud resource scheduling method employing an optimized CMMN algorithm with unified cloud API standardization to enhance task distribution efficiency; (2) a block model-based dynamic data aggregation approach utilizing semantic unification and attribute mapping for multi-source geological data integration; (3) a GPU-accelerated rendering framework implementing occlusion culling and batch processing to optimize 3D visualization performance. Experimental validation shows the improved CMMN algorithm reduces cloud task completion time by 2.37% while increasing resource utilization by 0.652% compared with conventional methods. The dynamic data model integrates 12 geological data types across eight categories through semantic mapping. Rendering optimizations achieve a 93.7% memory reduction and 60.6% faster visualization compared with baseline approaches. This system provides robust decision support and reliable tools for the digital transformation of geoscience work. Full article

(This article belongs to the Special Issue Technologies and Methods for Exploitation of Geological Resources)

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22 pages, 1904 KiB

Open AccessArticle

The Full Lifecycle Evolution Model of Accidents: A Case Study of Underground Metal Mines in China

by Xingbang Qiang, Guoqing Li, Chunchao Fan, Wei Zhao and Qiuling Wang

Appl. Sci. 2025, 15(7), 4004; https://doi.org/10.3390/app15074004 (registering DOI) - 4 Apr 2025

Abstract

Analyzing the mechanisms of accidents is essential for clarifying the accident evolution process, devising preventive measures, and achieving proactive accident management. To address the potential issues in existing accident causation theories, such as the unclear distinction between direct causes and incomplete accident evolution [...] Read more.

Analyzing the mechanisms of accidents is essential for clarifying the accident evolution process, devising preventive measures, and achieving proactive accident management. To address the potential issues in existing accident causation theories, such as the unclear distinction between direct causes and incomplete accident evolution pathways in enterprise-level accident prevention analysis, this study systematically reviewed the elements involved in safety management activities and their interrelationships. We identified the central role of human factors in the accident evolution process and developed a full lifecycle evolution model for industrial accidents, which begins with hazard identification and follows a safety management logic as its primary framework. This model provides a clear pathway for constructing enterprise-level risk control lists and accident prevention schemes. The model’s effectiveness was validated through its application to China’s underground metal mining industry. Drawing on Chinese laws and regulations as well as accident investigation reports, this study identifies 11 common types of accidents in underground metal mines and maps their evolution pathways from a complex systems perspective. Quantitative data from 61 accident reports were used to pinpoint the core factors and critical pathways leading to these various accidents. The study also analyzes prevention strategies and proposes new countermeasures to control the propagation of accident risks. Practical applications of the model demonstrate that emphasizing human factors enhances the effectiveness and accuracy of enterprise-level accident analysis and risk management. Full article

(This article belongs to the Special Issue Safety and Risk Analysis in Underground Engineering)

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23 pages, 1930 KiB

Open AccessArticle

A Study on Chatbot Development Using No-Code Platforms by People with Disabilities for Their Peers at a Sheltered Workshop

by Sara Hamideh Kerdar, Britta Marleen Kirchhoff, Lars Adolph and Liane Bächler

Technologies 2025, 13(4), 146; https://doi.org/10.3390/technologies13040146 (registering DOI) - 4 Apr 2025

Abstract

No-code (NC) platforms empower individuals without IT experience to create tailored applications and websites. While these platforms are accessible to a broader audience, their usability for people with disabilities remains underexplored. This study investigated whether, with targeted training, people with disabilities could effectively [...] Read more.

No-code (NC) platforms empower individuals without IT experience to create tailored applications and websites. While these platforms are accessible to a broader audience, their usability for people with disabilities remains underexplored. This study investigated whether, with targeted training, people with disabilities could effectively use NC platforms to develop customized tools for their workplace, and whether these tools would be adopted by their peers. Conducted in collaboration with a sheltered workshop in Germany, the study had three phases. Phase I involved a brainstorming session with employees, which shaped the study design and product development. In Phase II, six participants with disabilities received a one-week training to develop chatbots. Phase III implemented the chatbots in the workshop. In Phase II, each participant successfully developed four chatbots, which increased the participants’ skills and motivation. Based on the phase III results, users rated the developed chatbots highly (the System Usability Scale (SUS) questionnaire was delivered in the form of a chatbot), indicating their user-friendliness (M = 88.9, SD = 11.2). This study suggests that with appropriate training, individuals with disabilities can use NC platforms to create impactful, customized tools that are user-friendly and accessible to their peers. Full article

(This article belongs to the Special Issue Assistive Technologies in Care and Rehabilitation: Research, Developments, and International Initiatives)

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16 pages, 864 KiB

Open AccessArticle

Development of a Scale for Measuring Cognitive Biases Related to Risk-Taking Among Firefighters: The Five Cognitive Bias Risk Scale (5 CBR-S)

by Sébastien Lhardy, Emma Guillet-Descas and Guillaume Martinent

Fire 2025, 8(4), 147; https://doi.org/10.3390/fire8040147 (registering DOI) - 4 Apr 2025

Abstract

This study aimed to develop the Five Cognitive Biases in Risk-Taking Scale (5 CBR-S) to measure five cognitive biases associated with risk-taking: overconfidence, illusion of control, belief in the law of small numbers, escalation of commitment, and optimism. Firefighters completed a series of [...] Read more.

This study aimed to develop the Five Cognitive Biases in Risk-Taking Scale (5 CBR-S) to measure five cognitive biases associated with risk-taking: overconfidence, illusion of control, belief in the law of small numbers, escalation of commitment, and optimism. Firefighters completed a series of five questionnaires: cognitive biases related to risk-taking, emotional intelligence, self-regulation behaviors, personality traits, and mental toughness. Data were collected from two distinct samples, each consisting of 202 firefighters. A series of exploratory and confirmatory factor analyses conducted on an initial version of the 5 CBR-S with 50 items provided structural evidence supporting a 5-factor, 19-item solution. Evidence of validity and reliability for the 5 CBR-S scores was provided by examining correlations with emotional intelligence, personality traits, and mental toughness. Overall, despite certain limitations, the 5 CBR-S constitutes a robust measure, offering the advantage of highlighting the five main cognitive biases related to risk-taking. It can be used both among firefighters and in other professional contexts involving high-intensity emergency decision-making. Full article

(This article belongs to the Section Fire Social Science)

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27 pages, 1480 KiB

Open AccessArticle

Ethical Decision-Making in Education: A Comparative Study of Teachers and Artificial Intelligence in Ethical Dilemmas

by Neslihan Karakuş, Kerim Gedik and Semin Kazazoğlu

Behav. Sci. 2025, 15(4), 469; https://doi.org/10.3390/bs15040469 (registering DOI) - 4 Apr 2025

Abstract

The use of artificial intelligence (AI) in education supports long-term educational goals. AI enables learners to engage with ethical issues through simulations and virtual environments, allowing them to experience responsible decision-making in practice. Additionally, it assists administrators and educators in making data-driven decisions, [...] Read more.

The use of artificial intelligence (AI) in education supports long-term educational goals. AI enables learners to engage with ethical issues through simulations and virtual environments, allowing them to experience responsible decision-making in practice. Additionally, it assists administrators and educators in making data-driven decisions, contributing to the more effective formulation of educational policies. This study examines how teachers and AI address ethical educational dilemmas, comparing their decisions based on gender, experience, and education level. A total of 141 public school teachers in Turkey participated in the study, and their responses were compared with AI-generated decisions using Yin’s nested multiple-case design. The scenarios were analyzed within the framework of five ethical perspectives: virtue ethics, deontological ethics, utilitarianism, social justice ethics, and situation ethics. AI aligned with teachers in five out of eight ethical dilemmas but differed in three cases, adopting a more analytical and outcome-oriented approach. In contrast, teachers placed greater emphasis on empathy and adherence to ethical principles. These findings highlight the differences in ethical decision-making between AI and teachers, emphasizing the role of AI in fostering ethical responsibility and awareness in education. Full article

(This article belongs to the Section Educational Psychology)

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47 pages, 1870 KiB

Open AccessSystematic Review

Immersive Extended Reality (I-XR) in Medical and Nursing for Skill Competency and Knowledge Acquisition: A Systematic Review and Implications for Pedagogical Practices

by Jennifer M. B. Fugate, Michaela J. Tonsager and Sheila L. Macrine

Behav. Sci. 2025, 15(4), 468; https://doi.org/10.3390/bs15040468 (registering DOI) - 4 Apr 2025

Abstract

Simulation has evolved from basic practice to Immersive Extended Reality (I-XR). This systematic review examined 56 published studies on the impact of I-XR, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), on the education of medical and nursing students, specifically [...] Read more.

Simulation has evolved from basic practice to Immersive Extended Reality (I-XR). This systematic review examined 56 published studies on the impact of I-XR, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), on the education of medical and nursing students, specifically their skill competency, and knowledge acquisition. The results demonstrate the significant potential of I-XR in healthcare education, with 42.5% of VR studies, 42.9% of AR studies, and the single MR study also demonstrating greater improvements in clinical skills and knowledge acquisition compared to non-immersive (non-I-XR) training conditions. In contrast, only 2.5% of VR studies and 7.14% of AR studies favored non-I-XR methods. It is important, however, to acknowledge the 26.8% of studies that showed mixed results (some evidence for the I-XR methods on some outcomes, but also some evidence for the non-I-XR methods, on other outcomes). Notably, the review also identified a critical gap in the theoretical foundations of I-XR learning, highlighting the urgent need for research to inform the effective pedagogical implementation of these powerful tools. We offer a preliminary framework to address the lack of learning theory in healthcare I-XR training, with implications for pedagogical practices. Full article

(This article belongs to the Special Issue Neurocognitive Foundations of Embodied Learning)

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14 pages, 1248 KiB

Open AccessArticle

Smallholder Cattle Farmers’ Knowledge, Attitudes, and Practices Toward Rabies: A Regional Survey in Kazakhstan

by Nurbek Ginayatov, Zukhra Aitpayeva, Izimgali Zhubantayev, Leila Kassymbekova, Assylbek Zhanabayev, Gulmira Abulgazimova, Raikhan Arynova, Alim Bizhanov, Assiya Mussayeva, Maxat Berdikulov, Marat Aisin, Zaure Sayakova, Spandiyar Tursunkulov, Nurkuisa Rametov, Ainur Akhmadiyeva, Aigul Bulasheva, Nurgul Jussupbekova, Olzhas Yeskhojayev, Gulnara Baikadamova, Kaissar Kushaliyev, Nadezhda Burambayeva and Arman Issimov Show full author list Hide full author list

Vet. Sci. 2025, 12(4), 335; https://doi.org/10.3390/vetsci12040335 (registering DOI) - 4 Apr 2025

Abstract

Rabies remains a significant public health and economic concern in Kazakhstan, particularly in rural livestock-farming communities. This study aimed to assess the knowledge, attitudes, and practices (KAPs) related to rabies among livestock farmers in the Aktobe and Oral regions of West Kazakhstan. A [...] Read more.

Rabies remains a significant public health and economic concern in Kazakhstan, particularly in rural livestock-farming communities. This study aimed to assess the knowledge, attitudes, and practices (KAPs) related to rabies among livestock farmers in the Aktobe and Oral regions of West Kazakhstan. A cross-sectional survey was conducted between April and August 2022, involving 688 randomly selected participants. The data were collected through structured interviews and analyzed using descriptive and inferential statistics. The findings revealed that 89% of respondents were aware of rabies, yet significant knowledge gaps existed regarding clinical signs, transmission, and prevention. While 87% recognized the importance of rabies vaccination in dogs, 81% were unaware of pre-exposure prophylaxis (PrEP) for cattle, and 72% lacked knowledge of PrEP for humans. Awareness of the post-exposure prophylaxis (PEP) regimen was significantly higher in the Aktobe region (p < 0.002). Attitudinal differences were observed, with the Oral region participants exhibiting more favorable perceptions of rabies control programs (p < 0.01). Additionally, the χ² test revealed that the proportion of female respondents (p < 0.02), those with school-aged dependents (p < 0.003), respondents owning both exotic and indigenous cattle breeds (p < 0.002), and those possessing more than five cattle (p < 0.025) was statistically different in the Oral region. Practices such as free grazing, lack of protective equipment use, and improper carcass disposal were identified as potential risk factors for rabies transmission. This study highlights the need for targeted educational initiatives to improve rabies awareness and promote safer livestock management practices. Enhancing veterinary surveillance, strengthening community engagement, and expanding vaccination efforts could mitigate rabies transmission risks. Full article

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14 pages, 1395 KiB

Open AccessSystematic Review

Electrocardiographic Changes in Patients with Type 2 Diabetes Mellitus—A Meta-Analysis

by Teodora-Gabriela Alexescu, Antonia Nechita, Paula Alexander, Mirela-Georgiana Perné, Mircea-Vasile Milaciu, George Ciulei, Ioana Para, Vasile Negrean, Ana-Florica Chiș, Doina-Adina Todea, Dan Vălean, Simina-Felicia Țărmure and Olga-Hilda Orășan

J. Mind Med. Sci. 2025, 12(1), 14; https://doi.org/10.3390/jmms12010014 - 4 Apr 2025

Abstract

Background: Diabetes mellitus (DM) is a chronic metabolic disorder significantly associated with cardiovascular complications. Electrocardiographic (ECG) abnormalities are common in patients with type 2 diabetes (T2DM) and can serve as early markers for cardiovascular risk. Objective: This meta-analysis aims to evaluate the impact [...] Read more.

Background: Diabetes mellitus (DM) is a chronic metabolic disorder significantly associated with cardiovascular complications. Electrocardiographic (ECG) abnormalities are common in patients with type 2 diabetes (T2DM) and can serve as early markers for cardiovascular risk. Objective: This meta-analysis aims to evaluate the impact of T2DM on electrocardiographic changes, focusing on major ECG abnormalities, fragmented QRS (fQRS) complexes, and prolonged corrected QT (QTc) intervals. Materials and Methods: A systematic review of observational studies published between 2017 and 2022 was conducted using databases such as PubMed, Web of Science, Cochrane Library, Embase, and ClinicalTrials.gov. The inclusion criteria required studies to focus on patients with T2DM and report ECG changes. A total of 13 studies comprising 25,530 participants met the criteria and were included in the meta-analysis. The statistical analysis was performed using RevMan 5.4 with a random-effects model. Results: T2DM patients were 1.74 times more likely to develop major ECG abnormalities than non-diabetic individuals (crude OR = 1.74, 95% CI = 1.17–2.57, p = 0.006). The prevalence of fQRS complexes was significantly higher among T2DM patients (crude OR = 2.48, 95% CI = 2.09–2.957, p < 0.00001). Additionally, T2DM patients exhibited a higher likelihood of QTc interval prolongation (crude OR = 1.38, 95% CI = 1.09–1.74, p = 0.008). Conclusions: This meta-analysis demonstrates that T2DM patients have a significantly higher risk of ECG abnormalities, including major changes, fQRS complexes, and prolonged QTc intervals. Regular ECG monitoring is essential for early detection and management of cardiovascular risks in T2DM patients. Full article

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11 pages, 2249 KiB

Open AccessArticle

Synergistic Antinociceptive Effects of Ketorolac and Ascorbic Acid in a Formalin-Induced Pain Model

by Josué Vidal Espinosa-Juárez, Erika Florecita Hoover-Lazo, Sergio de Jesús Rubio-Trujillo, Citlaly Natali de la Torre-Sosa, Nereida Violeta Vega-Cabrera, Josselin Carolina Corzo-Gómez, Refugio Cruz-Trujillo and Osmar Antonio Jaramillo-Morales

Future Pharmacol. 2025, 5(2), 15; https://doi.org/10.3390/futurepharmacol5020015 - 4 Apr 2025

Abstract

Pain is a widespread global issue and one of the most common disabling conditions in daily life. A wide range of medications are available to reduce or eliminate pain, with nonsteroidal anti-inflammatory drugs (NSAIDs) being among those most commonly used. Additionally, new analgesic [...] Read more.

Pain is a widespread global issue and one of the most common disabling conditions in daily life. A wide range of medications are available to reduce or eliminate pain, with nonsteroidal anti-inflammatory drugs (NSAIDs) being among those most commonly used. Additionally, new analgesic approaches, such as antioxidants (Ascorbic Acid), have been explored for their potential to relieve acute pain after surgery, cancer-related pain, and chronic pain not related to cancer with fewer adverse effects. Furthermore, the use of pharmacological combinations is an alternative treatment strategy to obtain a higher efficacy using lower drug concentrations, at which side effects are minimal. Background/Objectives: The aim of this study was to evaluate the pharmacological synergism of ketorolac and ascorbic acid in an inflammatory pain model. Methods: The individual and combined effects of ketorolac and ascorbic acid were evaluated in a formalin-induced pain model in mice. Four experimental groups were established: control (vehicle), ketorolac (KET), ascorbic acid (AA), and combination (KET/AA). Results: The combination of ketorolac and ascorbic acid produced a greater antinociceptive effect compared to the vehicle and individual treatments in the formalin model. Notably, even the lowest dose of the combination (KET 6.26/AA 3.21 µg/paw) exhibited a stronger effect than the maximum doses of each individual treatment KET (100 µg/paw) and AA (100 µg/paw). The effective concentration that produced 30% of antinociception (EC₃₀) for the tested treatments were determined, and an isobologram analysis confirmed the presence of a synergistic interaction in these combinations. Conclusions: These findings suggest that the combination of ketorolac and ascorbic acid produces a synergistic antinociceptive effect in the formalin-induced pain model. The enhanced efficacy of the combination indicates a potential therapeutic advantage in pain management by reducing the required dosage of each compound while maintaining or improving analgesic effects. Full article

(This article belongs to the Special Issue Novel Therapeutic Approach to Inflammation and Pain)

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25 pages, 975 KiB

Open AccessArticle

Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory

by Anshumitra Baul, Herbert Fotso, Hanna Terletska, Ka-Ming Tam and Juana Moreno

Quantum Rep. 2025, 7(2), 18; https://doi.org/10.3390/quantum7020018 - 4 Apr 2025

Abstract

Modeling many-body quantum systems is widely regarded as one of the most promising applications for near-term noisy quantum computers. However, in the near term, system size limitation will remain a severe barrier for applications in materials science or strongly correlated systems. A promising [...] Read more.

Modeling many-body quantum systems is widely regarded as one of the most promising applications for near-term noisy quantum computers. However, in the near term, system size limitation will remain a severe barrier for applications in materials science or strongly correlated systems. A promising avenue of research is to combine many-body physics with machine learning for the classification of distinct phases. We present a workflow that synergizes quantum computing, many-body theory, and quantum machine learning (QML) for studying strongly correlated systems. In particular, it can capture a putative quantum phase transition of the stereotypical strongly correlated system, the Hubbard model. Following the recent proposal of the hybrid quantum-classical algorithm for the two-site dynamical mean-field theory (DMFT), we present a modification that allows the self-consistent solution of the single bath site DMFT. The modified algorithm can be generalized for multiple bath sites. This approach is used to generate a database of zero-temperature wavefunctions of the Hubbard model within the DMFT approximation. We then use a QML algorithm to distinguish between the metallic phase and the Mott insulator phase to capture the metal-to-Mott insulator phase transition. We train a recently proposed quantum convolutional neural network (QCNN) and then utilize the QCNN as a quantum classifier to capture the phase transition region. This work provides a recipe for application to other phase transitions in strongly correlated systems and represents an exciting application of small-scale quantum devices realizable with near-term technology. Full article

(This article belongs to the Topic Theoretical, Quantum and Computational Chemistry—2nd Edition)

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19 pages, 3752 KiB

Open AccessReview

Artificial Intelligence Driving Innovation in Textile Defect Detection

by Ahmet Ozek, Mine Seckin, Pinar Demircioglu and Ismail Bogrekci

Textiles 2025, 5(2), 12; https://doi.org/10.3390/textiles5020012 - 4 Apr 2025

Abstract

The cornerstone of textile manufacturing lies in quality control, with the early detection of defects being crucial to ensuring product quality and sustaining a competitive edge. Traditional inspection methods, which predominantly depend on manual processes, are limited by human error and scalability challenges. [...] Read more.

The cornerstone of textile manufacturing lies in quality control, with the early detection of defects being crucial to ensuring product quality and sustaining a competitive edge. Traditional inspection methods, which predominantly depend on manual processes, are limited by human error and scalability challenges. Recent advancements in artificial intelligence (AI)—encompassing computer vision, image processing, and machine learning—have transformed defect detection, delivering improved accuracy, speed, and reliability. This article critically examines the evolution of defect detection methods in the textile industry, transitioning from traditional manual inspections to AI-driven automated systems. It delves into the types of defects occurring at various production stages, assesses the strengths and weaknesses of conventional and automated approaches, and underscores the pivotal role of deep learning models, especially Convolutional Neural Networks (CNNs), in achieving high precision in defect identification. Additionally, the integration of cutting-edge technologies, such as high-resolution cameras and real-time monitoring systems, into quality control processes is explored, highlighting their contributions to sustainability and cost-effectiveness. By addressing the challenges and opportunities these advancements present, this study serves as a comprehensive resource for researchers and industry professionals seeking to harness AI in optimizing textile production and quality assurance amidst the ongoing digital transformation. Full article

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28 pages, 320 KiB

Open AccessArticle

Situating Place and Wellbeing Within Heritage Interactions for Older Adults

by Jessica Bowden, Ryan Woolrych and Craig J. Kennedy

Heritage 2025, 8(4), 131; https://doi.org/10.3390/heritage8040131 - 4 Apr 2025

Abstract

As the global population ages, more older adults are engaging with the historic environment than ever before. However, the needs of this population may not always be met by local and national heritage sites and organizations. Here, eight professionals working in the UK [...] Read more.

As the global population ages, more older adults are engaging with the historic environment than ever before. However, the needs of this population may not always be met by local and national heritage sites and organizations. Here, eight professionals working in the UK heritage, health and well-being and aging sectors were interviewed to gather their views on how older adults interact with the historic environment. Three key themes emerged from these interviews: barriers to accessing the historic environment; positive well-being implications of engaging with the historic environment; and the need to develop a wider knowledge base. Barriers to accessing the historic environment include physiological barriers, such as mobility issues, psychological barriers, and financial barriers. Positive well-being derived from engaging with the historic environment are explored in two key themes: communal well-being, and personal well-being. Attention is drawn to activities developed by heritage organizations to engage with older adults, and how these can be better coordinated and implemented to maximize the benefits the historic environment can offer, and minimize the barriers. Full article

(This article belongs to the Section Cultural Heritage)

26 pages, 17793 KiB

Open AccessArticle

Study on the Spatial and Temporal Evolution of Hydrogen-Blended Natural Gas Leakage and Flare-Up in the Typical Semi-Open Space

by Xu Wang, Saitao Hu, Shengzhu Zhang, Yingquan Duo, Jinhuai Xu and Tong Zhao

Fire 2025, 8(4), 146; https://doi.org/10.3390/fire8040146 - 4 Apr 2025

Abstract

Numerical simulations reveal the combustion dynamics of hydrogen-blended natural gas (H-BNG) in semi-open spaces. In the typical semi-open space scenario, increasing the hydrogen blending ratio from 0% to 60% elevates peak internal pressure by 107% (259.3 kPa → 526.0 kPa) while reducing pressure [...] Read more.

Numerical simulations reveal the combustion dynamics of hydrogen-blended natural gas (H-BNG) in semi-open spaces. In the typical semi-open space scenario, increasing the hydrogen blending ratio from 0% to 60% elevates peak internal pressure by 107% (259.3 kPa → 526.0 kPa) while reducing pressure rise time by 56.5% (95.8 ms → 41.7 ms). A vent size paradox emerges: 0.5 m openings generate 574.6 kPa internal overpressure, whereas 2 m openings produce 36.7 kPa external overpressure. Flame propagation exhibits stabilized velocity decay (836 m/s → 154 m/s, 81.6% reduction) at hydrogen concentrations ≥30% within 2–8 m distances. In street-front restaurant scenarios, 80% H-BNG leaks reach alarm concentration (0.8 m height) within 120 s, with sensor response times ranging from 21.6 s (proximal) to 40.2 s (distal). Forced ventilation reduces hazard duration by 8.6% (151 s → 138 s), while door status shows negligible impact on deflagration consequences (412 kPa closed vs. 409 kPa open), maintaining consistent 20.5 m hazard radius at 20 kPa overpressure threshold. These findings provide crucial theoretical insights and practical guidance for the prevention and management of H-BNG leakage and explosion incidents. Full article

(This article belongs to the Special Issue Hydrogen Safety: Challenges and Opportunities)

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22 pages, 5710 KiB

Open AccessArticle

Experimental Characterization of Cast Explosive Charges Used in Studies of Blast Effects on Structures

by Anselmo S. Augusto, Girum Urgessa, Caio B. Amorim, Robison E. Lopes Júnior, Fausto B. Mendonça, José A. F. F. Rocco and Koshun Iha

CivilEng 2025, 6(2), 20; https://doi.org/10.3390/civileng6020020 - 4 Apr 2025

Abstract

Structural research teams face significant challenges when conducting studies with explosives, including the costs and inherent risks associated with field detonation tests. This study presents a replicable method for loading spherical and bare TNT-based cast explosive charges, offering reduced costs and minimal risks. [...] Read more.

Structural research teams face significant challenges when conducting studies with explosives, including the costs and inherent risks associated with field detonation tests. This study presents a replicable method for loading spherical and bare TNT-based cast explosive charges, offering reduced costs and minimal risks. Over eighty TNT and Composition B charges (comprising 60% RDX, 39% TNT, and 1% wax) were prepared using spherical molds made of thin aluminum, which are low-cost, off-the-shelf solutions. The charges were bare, meaning they lacked any casing, as the molds were designed to be easily removed after casting. The resulting charges were safer due to their smaller dimensions and the absence of hazardous metallic debris. Composition B charges demonstrated promising results, with their performance characterized through blast and thermochemical experiments. Comprehensive data are provided for Composition B charges, including TNT equivalence, pressures, velocity of detonation, DSC/TGA curves at four different heating rates, activation energy, peak decomposition temperatures, X-ray analysis, and statistics on masses and densities. A comparison between detonation and deflagration processes, captured in high-speed footage, is also presented. This explosive characterization is crucial for structural teams to precisely understand the blast loads produced, ensuring a clear and accurate knowledge of the forces acting on structures. Full article

(This article belongs to the Section Structural and Earthquake Engineering)

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16 pages, 2325 KiB

Open AccessReview

Central and Peripheral Immunity Responses in Parkinson’s Disease: An Overview and Update

by Ghaidaa Ebrahim, Hunter Hutchinson, Melanie Gonzalez and Abeer Dagra

Neuroglia 2025, 6(2), 17; https://doi.org/10.3390/neuroglia6020017 - 4 Apr 2025

Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms, with increasing evidence supporting the role of immune dysregulation in its pathophysiology. Neuroinflammation, mediated by microglial activation, pro-inflammatory cytokine production, and blood–brain barrier dysfunction, plays a crucial role in [...] Read more.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms, with increasing evidence supporting the role of immune dysregulation in its pathophysiology. Neuroinflammation, mediated by microglial activation, pro-inflammatory cytokine production, and blood–brain barrier dysfunction, plays a crucial role in dopaminergic neuronal degeneration. Furthermore, peripheral immune changes, including T cell infiltration, gut microbiota dysbiosis, and systemic inflammation, contribute to disease progression. The bidirectional interaction between the central and peripheral immune systems suggests that immune-based interventions may hold therapeutic potential. While dopaminergic treatments remain the standard of care, immunomodulatory therapies, monoclonal antibodies targeting α-synuclein, and deep brain stimulation (DBS) have demonstrated immunological effects, though clinical efficacy remains uncertain. Advances in immune phenotyping offer new avenues for personalized treatment approaches, optimizing therapeutic responses by stratifying patients based on inflammatory biomarkers. This review highlights the complexities of immune involvement in PD and discusses emerging strategies targeting immune pathways to develop disease-modifying treatments. Full article

(This article belongs to the Special Issue The Multifaceted Roles of Glia: From Cellular Functions to Neurological Implications)

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16 pages, 4912 KiB

Open AccessArticle

Characterization of Laser-Ablated Bound Metal Deposition (laBMD)

by Alexander Watson, Masoud Rais-Rohani, John Belding, Jasper McGill and Brett D. Ellis

J. Manuf. Mater. Process. 2025, 9(4), 119; https://doi.org/10.3390/jmmp9040119 - 4 Apr 2025

Abstract

Additive manufacturing of metals is limited by a fundamental tradeoff between deposition rates and manufacturability of fine-scale features. To overcome this problem, a laser-ablated bound metal deposition (laBMD) process is demonstrated in which 3D-printed green-state bound metal deposition (BMD) parts are post-processed via [...] Read more.

Additive manufacturing of metals is limited by a fundamental tradeoff between deposition rates and manufacturability of fine-scale features. To overcome this problem, a laser-ablated bound metal deposition (laBMD) process is demonstrated in which 3D-printed green-state bound metal deposition (BMD) parts are post-processed via laser ablation prior to conventional BMD debinding and sintering. The laBMD process is experimentally characterized via a full-factorial design of experiments to determine the effect of five factors—number of laser passes (one pass, three passes), laser power (25%, 75%), scanning speed (50%, 100%), direction of laser travel (perpendicular, parallel), and laser resolution (600 dpi, 1200 dpi)—on as-sintered ablated depth, surface roughness, width, and angle between ablated and non-ablated regions. The as-sintered ablation depth/pass ranged from 3 to 122 µm/pass, the ablated surface roughness ranged from 3 to 79 µm, the angle between ablated and non-ablated regions ranged from 1° to 68°, and ablated bottom widths ranged from 729 to 1254 µm. This study provides novel insights into as-manufactured ablated geometries and surface finishes produced via laser ablation of polymer–metallic composites. The ability to inexpensively and accurately manufacture fine-scale features with tailorable geometric tolerances and surface finishes is important to a variety of applications, such as manufacturing molds for microfluidic devices. Full article

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21 pages, 370 KiB

Open AccessArticle

A Study of a Nonlocal Coupled Integral Boundary Value Problem for Nonlinear Hilfer–Hadamard-Type Fractional Langevin Equations

by Bashir Ahmad, Hafed A. Saeed and Sotiris K. Ntouyas

Fractal Fract. 2025, 9(4), 229; https://doi.org/10.3390/fractalfract9040229 - 4 Apr 2025

Abstract

We discuss the existence criteria and Ulam–Hyers stability for solutions to a nonlocal integral boundary value problem of nonlinear coupled Hilfer–Hadamard-type fractional Langevin equations. Our results rely on the Leray–Schauder alternative and Banach’s fixed point theorem. Examples are included to illustrate the results [...] Read more.

We discuss the existence criteria and Ulam–Hyers stability for solutions to a nonlocal integral boundary value problem of nonlinear coupled Hilfer–Hadamard-type fractional Langevin equations. Our results rely on the Leray–Schauder alternative and Banach’s fixed point theorem. Examples are included to illustrate the results obtained. Full article

(This article belongs to the Special Issue Advances in Fractional Initial and Boundary Value Problems)

15 pages, 734 KiB

Open AccessSystematic Review

Utilizing VR Visual Novels Incorporating Social Stories for Learning in Children with Autism Spectrum Disorder: A Systematic Literature Review

by Katerina Atsalaki and Ioannis Kazanidis

Multimodal Technol. Interact. 2025, 9(4), 32; https://doi.org/10.3390/mti9040032 - 4 Apr 2025

Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that impacts social, communication, and emotional skills, presenting significant challenges in learning and social interaction. Traditional teaching approaches often fail to engage children with ASD, highlighting the need for innovative solutions. This study investigates the [...] Read more.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that impacts social, communication, and emotional skills, presenting significant challenges in learning and social interaction. Traditional teaching approaches often fail to engage children with ASD, highlighting the need for innovative solutions. This study investigates the potential of virtual reality (VR) visual novels, incorporating social stories, as a tool to enhance social skills in children with ASD Level 1. Through a comprehensive literature review, the research evaluates VR environments that blend the interactive, choice-based structure of visual novels with immersive social narratives. Key aspects such as empathy, communication, and emotional regulation are analyzed to assess whether VR-based social stories provide better learning outcomes compared to conventional 2D methods. The findings aim to inform about the application of VR technologies in educational interventions, demonstrating how immersive learning experiences can promote essential social competencies in children with ASD. Full article

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17 pages, 24696 KiB

Open AccessArticle

Energy Transition and Heritage in Anthropocene Era—Proposal for a Methodological Analysis at Local Scale

by Belén Pérez-Pérez and Eva Chacón-Linares

Urban Sci. 2025, 9(4), 112; https://doi.org/10.3390/urbansci9040112 - 4 Apr 2025

Abstract

In the Anthropocene era, climate change highlights the need to abandon the centralized energy generation model using large installations located far from consumption centers, and to move towards an urban energy transition based on decentralized self-consumption models—both individual and collective—and local energy communities. [...] Read more.

In the Anthropocene era, climate change highlights the need to abandon the centralized energy generation model using large installations located far from consumption centers, and to move towards an urban energy transition based on decentralized self-consumption models—both individual and collective—and local energy communities. These approaches reduce emissions and external dependency, strengthening resilience, urban sustainability, and promoting energy justice and citizen participation. This work aims to develop a model for integrating photovoltaic solar systems in urban centers of high heritage value, combining the protection of cultural legacy with climate change adaptation strategies. A methodology is designed to integrate solar energy into urban areas while respecting cultural heritage in the most reasonable way possible. The proposed methodology consists of carrying out a characterization of the municipalities under study, considering legal, demographic, energy, and heritage aspects. Next, a territorial zoning is proposed that differentiates between protected and unprotected areas in each municipality. Visibility maps are developed to assess the impact of the installations by sector from the main visual consumption points, facilitating differentiated decisions to protect the most sensitive environments. In addition, specific measures are proposed, such as locating the installations in non-visible areas and using materials and techniques adapted to the construction typology, to preserve areas of higher cultural value and to implement energy communities and collective self-consumption outside culturally protected zones. This methodology is applied to two urban areas in the province of Jaén (South of Andalusia): Alcalá la Real and Cazorla, which, due to their different characteristics, demonstrate its versatility and adaptability. It is concluded that the transition toward decentralized models is an effective way to adapt cities to climate change, reinforcing social cohesion, contributing to the fight against energy vulnerability, and protecting historical heritage. Full article

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26 pages, 1985 KiB

Open AccessArticle

Inter- and Intra-Estuarine Comparison of the Feeding Ecology of Keystone Fish Species in the Elbe and Odra Estuaries

by Jesse Theilen, Sarah Storz, Sofía Amieva-Mau, Jessica Dohr, Elena Hauten, Raphael Koll, Christian Möllmann, Andrej Fabrizius and Ralf Thiel

Fishes 2025, 10(4), 161; https://doi.org/10.3390/fishes10040161 - 4 Apr 2025

Abstract

Food webs in estuarine ecosystems serve as important biological indicators. The feeding ecology of four keystone fish species, pikeperch (Sander lucioperca L.), smelt (Osmerus eperlanus L.), ruffe (Gymnocephalus cernua L.) and flounder (Platichthys flesus L.), in the Elbe and [...] Read more.

Food webs in estuarine ecosystems serve as important biological indicators. The feeding ecology of four keystone fish species, pikeperch (Sander lucioperca L.), smelt (Osmerus eperlanus L.), ruffe (Gymnocephalus cernua L.) and flounder (Platichthys flesus L.), in the Elbe and Odra estuaries was analyzed using stomach content analyses. Important prey of pikeperch were fishes and mysids in both estuaries. Amphipods were especially important as prey for smelt in the Elbe estuary, whereas smelt caught in the Odra estuary mainly consumed mysids. Ruffe fed mainly on amphipods in the Elbe estuary, while annelids (lower section) and insect larvae (upper section) were the most important prey in the Odra estuary. Flounder favored copepods as prey in the Elbe estuary, while bivalves were preferred in the Odra estuary. Higher dietary overlaps were found in the Elbe estuary between smelt vs. ruffe, pikeperch vs. ruffe, and pikeperch vs. smelt. In the Elbe estuary, a shift in the diet composition of pikeperch, smelt, and ruffe was observed from 2021 to 2022 compared to food analyses from the 1990s. These shifts included an increased consumption of amphipods, while mysids and copepods had recently decreased in their diets. These changes indicate a restructuring of the food web, potentially linked to environmental changes, which highlights the sensitivity of estuarine ecosystems. Full article

20 pages, 980 KiB

Open AccessArticle

Age, Growth, and Mortality of the Common Pandora (Pagellus erythrinus, L. 1758) in the Central Aegean Sea: Insights into Population Dynamics

by Alexandros Theocharis, Sofia Vardali and Dimitris Klaoudatos

Fishes 2025, 10(4), 160; https://doi.org/10.3390/fishes10040160 - 4 Apr 2025

Abstract

This study investigates the age, growth, and mortality of the common pandora (Pagellus erythrinus) in the Central Aegean Sea, providing critical insights into its population dynamics and sustainability. A total of 589 specimens were analyzed, identifying nine age cohorts with mean [...] Read more.

This study investigates the age, growth, and mortality of the common pandora (Pagellus erythrinus) in the Central Aegean Sea, providing critical insights into its population dynamics and sustainability. A total of 589 specimens were analyzed, identifying nine age cohorts with mean total lengths ranging from 13.18 cm to 32.94 cm. Growth parameters, estimated using the von Bertalanffy growth model, yielded an asymptotic length (L∞) of 39.53 cm and a growth coefficient (k) of 0.16 year⁻¹, indicating moderate growth rates. The population exhibited non-isomorphic growth (b = 2.49, R² = 98.4), suggesting slower weight gain relative to length. Mortality estimates indicated natural mortality (M) at 0.321 year⁻¹, total mortality (Z) at 0.52 year⁻¹, and fishing mortality (F) at 0.2 year⁻¹, resulting in an exploitation rate (E) of 0.38. The fishing mortality at maximum sustainable yield (FMSY) was estimated at 0.33, with an exploitation rate at MSY (EMSY) of 0.51, suggesting that the population is currently harvested sustainably but close to the threshold of overexploitation. These findings provide essential reference points for fisheries management and highlight the need for continuous monitoring to ensure the long-term sustainability of P. erythrinus in Greek waters. Full article

28 pages, 4886 KiB

Open AccessArticle

The Aesthetic Appreciation of Multi-Stable Images

by Levin Saracbasi and Heiko Hecht

J. Imaging 2025, 11(4), 111; https://doi.org/10.3390/jimaging11040111 - 4 Apr 2025

Abstract

Does the quality that renders multi-stable images fascinating, the sudden perceptual reorganization, the switching from one interpretation into another, also make these images appear beautiful? Or is the aesthetic quality of multi-stable figures unrelated to the ease with which they switch? Across two [...] Read more.

Does the quality that renders multi-stable images fascinating, the sudden perceptual reorganization, the switching from one interpretation into another, also make these images appear beautiful? Or is the aesthetic quality of multi-stable figures unrelated to the ease with which they switch? Across two experiments, we presented multi-stable images and manipulated their perceptual stability. We also presented their unambiguous components in isolation. In the first experiment, this manipulation targeted the inherent stimulus stability through properties like figural size and composition. The second experiment added an instruction for observers to actively control the stability, by attempting to either enhance or prevent perceptual switches as best they could. We found that higher stability was associated with higher liking, positive valence, and lower arousal. This increase in appreciation was mainly driven by inherent stimulus properties. The stability instruction only increased the liking of figures that had been comparatively stable to begin with. We conclude that the fascinating feature of multi-stable images does not contribute to their aesthetic liking. In fact, perceptual switching is detrimental to it. Processing fluency can explain this counterintuitive finding. We also discuss the role of ambiguity in the aesthetic quality of multi-stable images. Full article

(This article belongs to the Special Issue Next-Gen Visual Stimulators: Smart Human-Machine Interfaces for Visual Perception Assessment)

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37 pages, 23423 KiB

Open AccessReview

Thermally Stable Carbon Materials from Polybenzoxazines: Structure, Properties, and Supercapacitor Potential

by Thirukumaran Periyasamy, Shakila Parveen Asrafali and Jaewoong Lee

Batteries 2025, 11(4), 140; https://doi.org/10.3390/batteries11040140 - 4 Apr 2025

Abstract

This review explores the structural and electrochemical characteristics of carbon materials derived from polybenzoxazines, emphasizing their potential in supercapacitors. A detailed analysis of thermal degradation by-products during carbonization reveals distinct competing mechanisms, underscoring the exceptional thermal stability of benzoxazines. These materials exhibit significant [...] Read more.

This review explores the structural and electrochemical characteristics of carbon materials derived from polybenzoxazines, emphasizing their potential in supercapacitors. A detailed analysis of thermal degradation by-products during carbonization reveals distinct competing mechanisms, underscoring the exceptional thermal stability of benzoxazines. These materials exhibit significant pseudocapacitive behavior and excellent charge retention, making them strong candidates for energy storage applications. The versatility of polybenzoxazine-based carbons enables the formation of diverse morphologies—nanospheres, foams, films, nanofibers, and aerogels—each tailored for specific functionalities. Advanced synthesis techniques allow for precise control over porosity at the nanoscale, optimizing performance for supercapacitors and beyond. Their exceptional thermal stability, electrical conductivity, and tunable porosity extend their utility to gas adsorption, catalysis, and electromagnetic shielding. Additionally, their intumescent properties (unique ability to expand when exposed to high heat) make them promising candidates for flame-retardant coatings. The combination of customizable architecture, superior electrochemical performance, and high thermal resistance highlights their transformative potential in sustainable energy solutions and advanced protective applications. Full article

(This article belongs to the Special Issue High-Performance Supercapacitors: Advancements & Challenges)

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15 pages, 1291 KiB

Open AccessArticle

Optimizing Silage Efficiency: The Role of Ryegrass Varieties, Harvest Time, and Additives in Enhancing Perennial Ryegrass (Lolium perenne) Fermentation

by Tianyi Guo, Tong Niu, Katrin Kuka and Nils Tippkötter

Fermentation 2025, 11(4), 192; https://doi.org/10.3390/fermentation11040192 - 4 Apr 2025

Abstract

The increasing demand for bio-based chemicals and sustainable materials has placed biomass-derived lactic acid in the spotlight as a key building block for biodegradable polylactic acid (PLA). Perennial ryegrass (Lolium perenne) is a promising feedstock due to its high dry matter [...] Read more.

The increasing demand for bio-based chemicals and sustainable materials has placed biomass-derived lactic acid in the spotlight as a key building block for biodegradable polylactic acid (PLA). Perennial ryegrass (Lolium perenne) is a promising feedstock due to its high dry matter (DM) yield, adaptability, and widespread agricultural use. This study investigates an integrated lactic acid–silage cascade process, focusing on how pH regulation, harvest timing, and biomass characteristics influence lactic acid production while maintaining agronomic efficiency. The results highlighted the crucial role of pH management and silage duration in optimizing lactic acid production. A silage period of 21 days was found to be optimal, as peak lactic acid yields were consistently observed at this stage. Maintaining a pH range of 4.5 to 6 proved essential for stabilizing fermentation, with citrate buffering at pH 6 leading to the highest lactic acid yields and minimizing undesirable by-products. Harvest timing also significantly affected lactic acid yield per hectare. While later harvesting increased total DM yield, it led to a decline in lactic acid concentration per kg DM. Tetraploid ryegrass (Explosion) maintained stable lactic acid yields due to higher biomass accumulation, whereas diploid varieties (Honroso) experienced a net reduction. From an agronomic perspective, optimizing harvest timing and variety selection is key to balancing biomass yield and fermentation efficiency. While tetraploid varieties offer greater flexibility, diploid varieties require precise harvest timing to avoid losses. These findings contribute to sustainable forage management, improving lactic acid production, silage efficiency, and agricultural resource use. Full article

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