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Recent Articles  

42 pages, 551 KiB  
Article
AI Reasoning in Deep Learning Era: From Symbolic AI to Neural–Symbolic AI
by Baoyu Liang, Yuchen Wang and Chao Tong
Mathematics 2025, 13(11), 1707; https://doi.org/10.3390/math13111707 (registering DOI) - 23 May 2025
Abstract
The pursuit of Artificial General Intelligence (AGI) demands AI systems that not only perceive but also reason in a human-like manner. While symbolic systems pioneered early breakthroughs in logic-based reasoning, such as MYCIN and DENDRAL, they suffered from brittleness and poor scalability. Conversely, [...] Read more.
The pursuit of Artificial General Intelligence (AGI) demands AI systems that not only perceive but also reason in a human-like manner. While symbolic systems pioneered early breakthroughs in logic-based reasoning, such as MYCIN and DENDRAL, they suffered from brittleness and poor scalability. Conversely, modern deep learning architectures have achieved remarkable success in perception tasks, yet continue to fall short in interpretable and structured reasoning. This dichotomy has motivated growing interest in Neural–Symbolic AI, a paradigm that integrates symbolic logic with neural computation to unify reasoning and learning. This survey provides a comprehensive and technically grounded overview of AI reasoning in the deep learning era, with a particular focus on Neural–Symbolic AI. Beyond a historical narrative, we introduce a formal definition of AI reasoning and propose a novel three-dimensional taxonomy that organizes reasoning paradigms by representation form, task structure, and application context. We then systematically review recent advances—including Differentiable Logic Programming, abductive learning, program induction, logic-aware Transformers, and LLM-based symbolic planning—highlighting their technical mechanisms, capabilities, and limitations. In contrast to prior surveys, this work bridges symbolic logic, neural computation, and emergent generative reasoning, offering a unified framework to understand and compare diverse approaches. We conclude by identifying key open challenges such as symbolic–continuous alignment, dynamic rule learning, and unified architectures, and we aim to provide a conceptual foundation for future developments in general-purpose reasoning systems. Full article
(This article belongs to the Special Issue Advanced Applications of Deep Learning Methods: Interdisciplinary Perspectives)
21 pages, 5910 KiB  
Article
Applying Structure Exchange to Battery Charging to Enhance Light-Load Efficiency
by Kuo-Ing Hwu, Pei-Ching Tseng and Jenn-Jong Shieh
Energies 2025, 18(11), 2699; https://doi.org/10.3390/en18112699 (registering DOI) - 23 May 2025
Abstract
A full-bridge DC–DC converter with structure exchange is proposed to simulate battery charging based on an electronic load. The full-bridge phase-shift converter (FBPSC) uses an external resonant inductor and phase-shift control on the primary side to realize zero voltage switching (ZVS) above medium [...] Read more.
A full-bridge DC–DC converter with structure exchange is proposed to simulate battery charging based on an electronic load. The full-bridge phase-shift converter (FBPSC) uses an external resonant inductor and phase-shift control on the primary side to realize zero voltage switching (ZVS) above medium load. However, the energy of the resonant inductor is not enough to carry away the energy of the parasitic capacitance on the switch at light load, leading to the inability of ZVS as well as the circulating current problem due to the long duration of the primary-side circulating current. Consequently, in order to conquer such problems mentioned above, the structure exchange, with only the control strategy changed from the phase-shift control to the two-transistor forward control, is presented to increase the light-load efficiency remarkably. Furthermore, the number of inductors is reduced by using the center-tap structure on the secondary side compared to the current-doubler structure. In addition, the synchronous rectifier on the secondary side is used to further improve the overall efficiency of the converter. Full article
(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)
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15 pages, 5448 KiB  
Article
Modeling and Testing of 3D Wound Core Loss of Amorphous Alloy Transformer for Photovoltaic Inverter
by Peng Chen, Jianwei Han, Xinglong Yao, Xiaohui Wang, Yunfei Yan, Zhe Zhao, Lisong Zhang, Zhanyang Yu and Hao Li
Energies 2025, 18(11), 2698; https://doi.org/10.3390/en18112698 (registering DOI) - 23 May 2025
Abstract
The harmonic content of transformers used in the field of new energy is significantly higher than that of conventional transformers, leading to an abnormal increase in transformer loss during operation. Therefore, the loss characteristics of amorphous alloy transformers are investigated in this paper. [...] Read more.
The harmonic content of transformers used in the field of new energy is significantly higher than that of conventional transformers, leading to an abnormal increase in transformer loss during operation. Therefore, the loss characteristics of amorphous alloy transformers are investigated in this paper. First, a measurement platform for the magnetic property of transformer cores under sinusoidal excitation is developed. The magnetization characteristics, loss characteristics and loss composition of the amorphous alloy core under sinusoidal excitation are measured and analyzed. On this basis, the traditional Steinmetz loss calculation formula is modified, and the loss calculation formula is further refined by improving its coefficients to accommodate various frequencies. Secondly, using a field-circuit coupling method, a 3D model of the transformer core is established by finite element simulation. The magnetic flux distribution and core losses are computed under both sinusoidal excitation and non-sinusoidal excitation. Finally, the impact of core rotation magnetization on the magnetic flux density is considered, and experimental errors are minimized by applying an empirical formula. The numerical model validity and accuracy are verified by comparing the simulation results with experimental data. Full article
(This article belongs to the Section F: Electrical Engineering)
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20 pages, 6761 KiB  
Article
Spatiotemporal Analysis of Soil Moisture Variability and Precipitation Response Across Soil Texture Classes in East Kazakhstan
by Dmitry Chernykh, Roman Biryukov, Andrey Bondarovich, Lilia Lubenets, Anatoly Pavlenko, Kamilla Rakhymbek, Denis Revenko and Zheniskul Zhantassova
Land 2025, 14(6), 1136; https://doi.org/10.3390/land14061136 (registering DOI) - 23 May 2025
Abstract
The study of the hydrological regimes of rivers in different regions of the globe has revealed the need to include the soil moisture content in flood prediction models. This paper investigates the nature of the dependence of soil moisture content on soil texture [...] Read more.
The study of the hydrological regimes of rivers in different regions of the globe has revealed the need to include the soil moisture content in flood prediction models. This paper investigates the nature of the dependence of soil moisture content on soil texture in the East Kazakhstan region. Data from ERA-5-land reanalysis, soil maps, hydrogeological maps, and the meteorological data of Kazhydromet were used. The years for analysis were selected due to their different moisture conditions. This study analyzed soil moisture within the root zone (0–28 cm depth). A JavaScript-based algorithm was developed in Google Earth Engine to analyze soil moisture and total precipitation across five Soil Texture Index categories during the growing seasons (April–September) of 2013, 2022, and 2023. Final cartographic processing and spatial distribution analysis were conducted using ESRI ArcGIS Pro 3.3. The study of soil moisture’s relationship with different soil textures in the East Kazakhstan region has revealed several key trends. The maximum values of soil moisture for each texture class change very slightly from year to year. The minimum soil moisture values fluctuate more strongly from year to year. The regression analysis demonstrates a statistically significant relationship between precipitation and soil moisture. The best performance is achieved when using a 1-day lag for 2013 and varying optimal lags for 2022 and 2023 (ranging from 1 to 3 days) during the high-precipitation period (months 6–9), with filtering applied to remove days with negligible rainfall. Full article
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19 pages, 3205 KiB  
Article
MSTN Regulates Bovine Skeletal Muscle Satellite Cell Differentiation via PSMA6-Mediated AKT Signaling Pathway
by Tengxia Ma, Meiling Miao, Xiangquan Liu, Linlin Zhang, Yiwen Guo, Xin Li, Xiangbin Ding, Hong Guo and Debao Hu
Int. J. Mol. Sci. 2025, 26(11), 4963; https://doi.org/10.3390/ijms26114963 - 22 May 2025
Abstract
MSTN has been used as a candidate gene in the genetics, breeding, and improvement of animal breeds. However, the possible mechanism by which the MSTN gene regulates muscle development through PSMA6 is not well understood. Previous methylome and transcriptome sequencing analyses of gluteal [...] Read more.
MSTN has been used as a candidate gene in the genetics, breeding, and improvement of animal breeds. However, the possible mechanism by which the MSTN gene regulates muscle development through PSMA6 is not well understood. Previous methylome and transcriptome sequencing analyses of gluteal muscle tissues from MSTN+/−Luxi cattle and wild-type Luxi cattle identified that the PSMA6 gene exhibited a negative correlation between methylation levels and transcriptional activity. To investigate whether MSTN expression regulates PSMA6 gene expression, we examined the effects of MSTN on DNA methyltransferases (DNMT1, DNMT2, DNMT3A, and DNMT3B) and DNA demethylases (TET1, TET2, and TET3). Additionally, chromatin immunoprecipitation (ChIP) assays were performed to detect the binding interaction between PSMA6 and TET2. In this paper, we first established an MSTN knockdown cellular model to preliminarily validate its regulatory effect on PSMA6 expression. Subsequently, the developmental impact of PSMA6 on bovine skeletal muscle satellite cells was further investigated through both knockdown and overexpression of the PSMA6 gene. Furthermore, we examined changes in the expression of key components of the AKT/mTOR signaling pathway to elucidate the mechanisms underlying the PSMA6-mediated regulation of satellite cell development. The results demonstrate that myostatin (MSTN) inhibition significantly decreased proteasome 20S subunit alpha-6 (PSMA6) gene expression, while increasing demethylase expression, particularly ten-eleven translocation-2 (TET2), which exhibited the most pronounced changes. During the cell proliferation stage, the markers Paired Box 7 (PAX7) and Ki-67 exhibited no significant changes, whereas the PSMA6 gene was either overexpressed or disrupted. Conversely, PSMA6 overexpression altered the myogenic differentiation markers, causing the differential regulation of myosin heavy chain (MyHC) and myogenin (MyoG) expression, with MyHC upregulation and concurrent MyoG downregulation. PSMA6 gene overexpression led to the downregulation of AKT1 and Rac1, as well as the activation of the AKT/mTOR pathway, including key factors such as mTOR, p-mTOR, RPS6, p-RPS6, and RhoA. PSMA6 interference resulted in the downregulation of p-mTOR and the upregulation of p-RPS6. Gene expression profiling in our study revealed that the myostatin (MSTN) knockout model significantly reduced the transcriptional levels of the proteasome α6 subunit (PSMA6) (p < 0.05), with the regulatory intensity showing a significant negative correlation with MSTN expression. This molecular evidence substantiates a negative regulatory axis between MSTN and PSMA6. Functional experiments demonstrated that PSMA6 overexpression specifically enhanced myotube formation rates in bovine skeletal muscle satellite cells, whereas siRNA-mediated PSMA6 knockdown exhibited no significant effects on cellular proliferation, indicating the functional specificity of this gene in myogenic differentiation. Mechanistic investigations further revealed that PSMA6 activates the canonical AKT/mTOR signaling transduction cascade through the phosphorylation of AKT and its downstream effector mTOR, thereby mediating the expression of myogenic regulatory factors MyoD and myogenin. Collectively, these findings demonstrate that MSTN deficiency alleviates the transcriptional repression of PSMA6, remodels skeletal muscle differentiation-associated signaling networks, and ultimately drives the directional differentiation of satellite cells toward myofiber specification. Full article
(This article belongs to the Special Issue Skeletal Muscle Metabolism—Effects of Diet, Exercise and Pharmacotherapies)
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25 pages, 1701 KiB  
Article
Sustaining Organizations Through Harmonized Civic and Employee Identities: Implications for Employee Engagement and Voice Behavior
by Jeong Won Lee
Sustainability 2025, 17(11), 4762; https://doi.org/10.3390/su17114762 - 22 May 2025
Abstract
In pursuit of sustainable management, organizations must not only balance economic, environmental, and social goals but also cultivate human-centered strategies that support long-term viability. Drawing on identity theory, this study introduces civic identity—an individual’s self-concept as a responsible member of society—into the workplace [...] Read more.
In pursuit of sustainable management, organizations must not only balance economic, environmental, and social goals but also cultivate human-centered strategies that support long-term viability. Drawing on identity theory, this study introduces civic identity—an individual’s self-concept as a responsible member of society—into the workplace and examines how its relationship with employee identity (i.e., enhancement and conflict) influences sustainability mechanisms: work engagement, role expansion, and voice behavior. Two field studies were conducted using multi-source data from 339 employees at large conglomerates (study 1) and three-wave data from 121 employees at entrepreneurial firms (study 2). Multiple regression analyses revealed that identity enhancement positively predicted both work engagement and role expansion, which in turn strengthened voice behavior. In contrast, identity conflict showed relatively weaker negative effects, while supplementary analyses indicated that identity separation exerted more pronounced negative influences. Although identity conflict and separation did not significantly affect role expansion in study 2, the results across both studies were largely consistent. By incorporating a neglected nonwork identity that fosters sustainable employee behavior, this research expands the scope of organizational studies and sustainability science. Implications for integrating civic identity into sustainable management strategies are discussed. Full article
(This article belongs to the Special Issue Work and Organizational Psychology and Well-Being Promotion for Sustainable and Healthy Organizations)
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23 pages, 319 KiB  
Article
Conditions for Guaranteeing Non-Overshooting Control of Nonlinear Systems with Full-State Constraints
by Xiang-Qin Xiang and Chi Zhang
Appl. Sci. 2025, 15(11), 5816; https://doi.org/10.3390/app15115816 - 22 May 2025
Abstract
In this paper, the problem of non-overshooting tracking control (NOTC) for a class of nonlinear systems with full-state constraints (FSCs) is studied. Firstly, this paper introduces the mapping constraint function to solve the FSC control problem and transform the controlled system into a [...] Read more.
In this paper, the problem of non-overshooting tracking control (NOTC) for a class of nonlinear systems with full-state constraints (FSCs) is studied. Firstly, this paper introduces the mapping constraint function to solve the FSC control problem and transform the controlled system into a new nonlinear system. Then, to obtain a closed-loop system that can solve the expression of tracking error, this paper transforms the n-order system into a system in which only the n-th subsystem is nonlinear by coordinate transformation, that is, subsystem 1 to subsystem n−1 are linear. Finally, according to the closed-loop system (CLS), the expressions of the first state of CLSs with n=1, n=2, n=3, and n≥4 are solved, respectively. By analyzing these expressions, a wider range of conditions with NOTC are obtained. This algorithm obtains more conditions with non-overshooting. Compared with the existing results, the algorithm in this paper reduces the conservatism. Finally, the algorithm is applied to the single-link robot system, and the effectiveness of the algorithm is verified. That is, the algorithm in this paper not only makes all signals of the CLS bounded, but also makes the overshoot of the system zero. Full article
(This article belongs to the Topic Intelligent Optimization, Decision-Making and Privacy Preservation in Cyber–Physical Systems)
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23 pages, 2903 KiB  
Article
A Mechanistic Insight into the Anti-Staphylococcal Mode of Action of (+)-Usnic Acid and Its Synergy with Norfloxacin Against Methicillin-Resistant Staphylococcus aureus
by Bhavana Gangwar, Santosh Kumar, Parmanand Kumar, Anirban Pal and Mahendra P. Darokar
Biomolecules 2025, 15(6), 750; https://doi.org/10.3390/biom15060750 - 22 May 2025
Abstract
In this study, a global response analysis was performed to explore the mechanism of action of Usnic acid and its synergy with Norfloxacin, a well-known quinolone antibiotic to which MRSA clinical isolates showed resistance (MIC, 500 µg/mL). A microdilution assay, a growth kinetics [...] Read more.
In this study, a global response analysis was performed to explore the mechanism of action of Usnic acid and its synergy with Norfloxacin, a well-known quinolone antibiotic to which MRSA clinical isolates showed resistance (MIC, 500 µg/mL). A microdilution assay, a growth kinetics analysis, a microscopic analysis, and cell-based assays consistently showed that Usnic acid possesses strong anti-staphylococcal activity (MIC, 7.8 µg/mL), causes cell leakage, modulates efflux pump activity, and synergizes with Norfloxacin against the multi-drug-resistant clinical isolate MRSA 2071. Whole-cell proteome profiling using gel-free proteomics-based nano-LC-ESI-QTOF-MS/MS revealed several proteins whose expression was significantly modulated by Usnic acid and Norfloxacin alone or in combination. Usnic acid downregulated the abundance of RNA polymerase subunits (RpoB and RpoC), carbamoyl phosphate synthase large subunit (PyrAB), chaperone (GroEL), and adenylosuccinate synthetase (PurA). Interestingly, proteins found to be upregulated in the presence of Usnic acid and Norfloxacin included oxidative-stress-related proteins such as peroxidase (Tpx), alkyl hydroperoxide reductase (AphC), and general stress protein (UspA). This study clearly shows that Usnic acid affects numerous cellular targets and can potentiate the action of Norfloxacin. Furthermore, an in vivo study showed that UA at low concentrations prevents body weight gain, but changes in other tested toxicological parameters were found to be within normal limits. Thus, UA at low doses appears to be a promising candidate for repurposing old antibiotics through combination therapy against MRSA infections. Full article
(This article belongs to the Special Issue Key Molecules in Traditional Medicine: From Molecular Mechanisms to Therapies Strategies)
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31 pages, 1465 KiB  
Article
Intelligent Flight Procedure Design: A Reinforcement Learning Approach with Pareto-Based Multi-Objective Optimization
by Yunyang Huang, Yanxin Zhang, Yandong Zhu, Zhuo Zhang, Longtao Zhu, Hongyu Yang and Yulong Ji
Aerospace 2025, 12(6), 451; https://doi.org/10.3390/aerospace12060451 - 22 May 2025
Abstract
Current flight procedure design primarily relies on expert experience, lacking a systematic approach to comprehensively balance safety, route simplification, and environmental impact. To address this challenge, this paper proposes a reinforcement-learning-based method that leverages carefully crafted reward engineering to achieve an optimized flight [...] Read more.
Current flight procedure design primarily relies on expert experience, lacking a systematic approach to comprehensively balance safety, route simplification, and environmental impact. To address this challenge, this paper proposes a reinforcement-learning-based method that leverages carefully crafted reward engineering to achieve an optimized flight procedure design, effectively considering safety, route simplicity, and environmental friendliness. To further enhance performance by tackling the low sampling efficiency in the replay buffer, we introduce a multi-objective sampling strategy based on the Pareto frontier, integrated with the soft actor–critic (SAC) algorithm. Experimental results demonstrate that the proposed method generates executable flight procedures in the BlueSky open-source flight simulator, successfully balancing these three conflicting objectives, while achieving a 28.6% increase in convergence speed and a 4% improvement in comprehensive performance across safety, route simplification, and environmental impact compared to the baseline algorithm. This study offers an efficient and validated solution for the intelligent design of flight procedures. Full article
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17 pages, 990 KiB  
Systematic Review
Combination of Drugs in the Treatment of Alcohol Use Disorder: A Meta-Analysis and Meta-Regression Study
by João Vitor Guimarães Mandaji, Maria Olivia Pozzolo Pedro, Kae Leopoldo, João Pini Alemar, Julio Torales, Antonio Ventriglio and João Mauricio Castaldelli-Maia
Brain Sci. 2025, 15(6), 542; https://doi.org/10.3390/brainsci15060542 - 22 May 2025
Abstract
Background: Alcohol Use Disorder (AUD) is highly prevalent among substance use disorders worldwide and is characterized by a multifactorial pathophysiology. AUD treatment is mostly based on combined pharmacotherapy and multidisciplinary clinical approaches. Nonetheless, meta-analytical studies assessing the efficacy of combination therapy are scarcely [...] Read more.
Background: Alcohol Use Disorder (AUD) is highly prevalent among substance use disorders worldwide and is characterized by a multifactorial pathophysiology. AUD treatment is mostly based on combined pharmacotherapy and multidisciplinary clinical approaches. Nonetheless, meta-analytical studies assessing the efficacy of combination therapy are scarcely available. Methods: We searched for randomized clinical trials through PubMed, ClinicalTrials.gov, Cochrane Library, SciELO, Biblioteca Virtual em Saúde, and Google Scholar databases. Original clinical trials published in English and Portuguese were selected. Data collection followed the PRISMA and MOOSE guidelines and was assessed using the Risk of Bias Tool (RoB 2). Heterogeneity was assessed using the Q test. Meta-regression was conducted using Egger’s regression method. Twelve articles were finally included in the analysis, and random-effects models were applied on aggregate trial results. Results: The meta-analysis found that combination therapies led to an average 4.045% increase in abstinence rates (95% CI: 0.415% to 7.675%) compared to monotherapies. Meta-regression showed a strong positive association between the use of naltrexone, acamprosate, and sertraline—either alone or in combination—and treatment success in AUD. The meta-regression also highlighted the impact of patients’ variables, such as gender, age, country, and psychiatric comorbidities, on their treatment outcomes. These findings may identify a potential therapeutic pathway promoting alcohol abstinence, further supported by a Number Needed to Treat (NNT) of 25, as an acceptable value for substance use disorder treatments. Conclusions: Combined pharmacotherapies are more effective than monotherapy in enhancing abstinence rates in AUD treatment, with naltrexone, acamprosate, and sertraline emerging as key adjunctive agents promoting these outcomes. These findings underscore the complexity of AUD as a multifactorial psychiatric condition and highlight the potential of combined pharmacotherapy as a promising strategy for achieving better treatment outcomes, particularly in terms of abstinence rates. Full article
(This article belongs to the Section Neuropsychiatry)
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17 pages, 784 KiB  
Systematic Review
Mesenchymal Stem Cells in Oral and Maxillofacial Surgery: A Systematic Review of Clinical Applications and Regenerative Outcomes
by Gianna Dipalma, Grazia Marinelli, Irene Palumbo, Mariafrancesca Guglielmo, Lilla Riccaldo, Roberta Morolla, Francesco Inchingolo, Andrea Palermo, Alessio Danilo Inchingolo and Angelo Michele Inchingolo
J. Clin. Med. 2025, 14(11), 3623; https://doi.org/10.3390/jcm14113623 - 22 May 2025
Abstract
Aim: This systematic review aims to evaluate the use of mesenchymal stem cells, particularly those derived from bone marrow, adipose tissue, and dental pulp in maxillofacial and oral surgery, focusing on their regenerative potential, clinical applications, and integration with biomaterials. Introduction: [...] Read more.
Aim: This systematic review aims to evaluate the use of mesenchymal stem cells, particularly those derived from bone marrow, adipose tissue, and dental pulp in maxillofacial and oral surgery, focusing on their regenerative potential, clinical applications, and integration with biomaterials. Introduction: Mesenchymal stem cells are multipotent stem cells known for their immunomodulatory and regenerative abilities. Their low immunogenicity and differentiation capacity make them ideal for treating craniofacial defects and enhancing soft tissue repair. Materials and Methods: The review followed PRISMA guidelines and was registered in PROSPERO. The literature was searched across PubMed, Scopus, and Web of Science from 2009 to 2024. Twelve studies met the inclusion criteria and were analyzed for clinical efficacy and methodological quality. Results: Clinical trials demonstrated the safety and regenerative benefits of mesenchymal stem cell in bone and soft tissue reconstruction. Adipose-derived stem cell and dental pulp stem cell showed favorable outcomes in angiogenesis and healing, while bone marrow’s cell proved effective in bone regeneration, particularly when combined with scaffolds. Discussion and Conclusions: Although results are promising, limitations remain in consistency and long-term outcomes. Optimizing scaffold integration, preservation methods, and delivery techniques is crucial. Mesenchymal stem cell-based therapies represent a powerful, minimally invasive alternative to traditional grafting in oral and maxillofacial surgery. Full article
(This article belongs to the Special Issue Oral and Maxillofacial Surgery: Recent Clinical Advances and Future Directions)
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17 pages, 1933 KiB  
Article
Profiling the Tox21 Compound Library for Their Inhibitory Effects on Cytochrome P450 Enzymes
by Srilatha Sakamuru, Jameson Travers, Carleen Klumpp-Thomas, Ruili Huang, Kristine L. Witt, Stephen S. Ferguson, Steven O. Simmons, David M. Reif, Anton Simeonov and Menghang Xia
Int. J. Mol. Sci. 2025, 26(11), 4976; https://doi.org/10.3390/ijms26114976 - 22 May 2025
Abstract
Cytochrome P450 (CYP) enzymes are membrane-bound hemoproteins crucial for drug and xenobiotic metabolism. While more than 50 CYPs have been identified in humans, the isoforms from CYP1, 2, and 3 families contribute to the metabolism of about 80% of clinically approved drugs. To [...] Read more.
Cytochrome P450 (CYP) enzymes are membrane-bound hemoproteins crucial for drug and xenobiotic metabolism. While more than 50 CYPs have been identified in humans, the isoforms from CYP1, 2, and 3 families contribute to the metabolism of about 80% of clinically approved drugs. To evaluate the effects of environmental chemicals on the activities of these important CYP enzyme families, we screened the Tox21 10K compound library to identify chemicals that inhibit CYP1A2, 2C9, 2C19, 2D6, and 3A4 enzymes. The data obtained from these five screenings were analyzed to reveal the structural classes responsible for inhibiting multiple and/or selective CYPs. Some known structural compound classes exhibiting pan-CYP inhibition, such as azole fungicides, along with established clinical inhibitors of CYPs, including erythromycin and verapamil inhibiting CYP3A4 and paroxetine and terbinafine inhibiting CYP2D6, were all confirmed in the current study. In addition, some selective CYP inhibitors, previously unknown but with potent activity (IC50 values < 1 µM), were identified. Examples included yohimbine, an indole alkaloid, and loteprednol, a corticosteroid, which showed inhibitory activity in CYP2D6 and 3A4 assays, respectively. These findings suggest that assessment of a candidate compound’s impact on CYP function may allow pre-emptive mitigation of potential adverse reactions and toxicity during drug development or toxicological characterization of environmental chemicals. Full article
(This article belongs to the Special Issue Cytochrome P450 Mechanism and Reactivity)
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21 pages, 1963 KiB  
Article
Effects of Resveratrol Derivatives on Melanogenesis and Antioxidant Activity in B16F10 Cells
by Soyeon Kim, Changho Jhin, Sullim Lee, Ho Sik Rho and Chan Yoon Park
Int. J. Mol. Sci. 2025, 26(11), 4999; https://doi.org/10.3390/ijms26114999 - 22 May 2025
Abstract
Excessive melanogenesis causes abnormal pigmentation and a higher risk of skin disorders (e.g., melanoma). Resveratrol (RSV), a natural polyphenol, exerts antioxidant and anti-aging effects. However, the effects of RSV and its derivatives on melanogenesis remain unclear. This study investigated their effects on melanogenesis [...] Read more.
Excessive melanogenesis causes abnormal pigmentation and a higher risk of skin disorders (e.g., melanoma). Resveratrol (RSV), a natural polyphenol, exerts antioxidant and anti-aging effects. However, the effects of RSV and its derivatives on melanogenesis remain unclear. This study investigated their effects on melanogenesis and antioxidant activity in B16F10 cells. After measuring cell viability, B16F10 cells were incubated with 50 µM of RSV, dihydroresveratrol (DIRSV), and other RSV derivatives for 24 h. The relative melanin content and tyrosinase activity were quantified. The protein and mRNA levels of melanogenesis-related genes (MITF, CREB, TYR, and TRP) and the binding affinity of RSV derivatives to their target proteins were measured. The antioxidant activity was evaluated using ABTS and DPPH assays. RSV and DIRSV (50 µM) significantly reduced melanin content and tyrosinase activity, respectively. However, other derivatives had no significant effects. RSV, DIRSV, and other derivatives significantly suppressed MITF and CREB levels. Additionally, DIRSV significantly reduced p-CREB and TYR protein levels and showed a higher affinity for CREB than RSV, despite no significant changes in MITF, TYR, or TRP mRNA levels. In the antioxidant assays, RSV and DIRSV exhibited significant ABTS and DPPH radical scavenging activities. DIRSV, like RSV, inhibits melanogenesis and exhibits antioxidant effects in B16F10 cells. However, RSV derivatives demonstrate partial antioxidant activity and inhibit melanogenesis-related proteins but do not significantly affect melanogenesis. DIRSV’s practical applications as a skin-protective and -whitening agent warrant further exploration. Full article
(This article belongs to the Special Issue Potential Health Benefits of Resveratrol: Laboratory-Confirmed Mechanisms of Action)
23 pages, 372 KiB  
Article
Rewiring Sustainability: How Digital Transformation and Fintech Innovation Reshape Environmental Trajectories in the Industry 4.0 Era
by Zhuoqi Teng, Han Xia and Yugang He
Systems 2025, 13(6), 400; https://doi.org/10.3390/systems13060400 (registering DOI) - 22 May 2025
Abstract
This study investigates the long-run impact of digital transformation and fintech innovation on environmental sustainability across OECD countries from 1999 to 2024. Drawing on a novel empirical framework that integrates panel fully modified ordinary least squares, the system-generalized method of moments, and machine [...] Read more.
This study investigates the long-run impact of digital transformation and fintech innovation on environmental sustainability across OECD countries from 1999 to 2024. Drawing on a novel empirical framework that integrates panel fully modified ordinary least squares, the system-generalized method of moments, and machine learning estimators, the analysis captures both linear and nonlinear dynamics while addressing heterogeneity, endogeneity, and structural complexity. Environmental sustainability is measured by per capita CO2 emissions, while digital transformation and fintech innovation are proxied by secure internet servers and G06Q patent applications, respectively. The findings reveal that both digital infrastructure maturity and fintech-driven innovation significantly reduce carbon emissions, suggesting that technologically advanced digital ecosystems serve as effective instruments for climate mitigation. Robustness checks via the system-generalized method of moments confirm the stability of these relationships, while machine learning models—Random Forest and XGBoost—highlight digital variables as top predictors of emissions reduction. The convergence of results across estimation methods underscores the reliability of the digital–environmental nexus. Policy implications emphasize the need to embed sustainability metrics into digital strategies, promote green fintech regulation, and prepare labor markets for Industry 4.0 transitions. These findings position digital and fintech innovation not merely as enablers of economic growth, but as structural levers for achieving environmentally sustainable development in high-income economies. Full article
(This article belongs to the Special Issue Sustainable Business Model Innovation in the Era of Industry 4.0)
29 pages, 6123 KiB  
Article
Lactic Microbiota and Metabolites in Raw Cow’s Milk: Implications for Consumer Health
by María Carmen Sánchez, Eduardo Soria, Arancha Llama-Palacios, Franco Almirón, Alberto Valdés, Alejandro Cifuentes, Marta Hernández, María José Ciudad and Luis Collado
Dairy 2025, 6(3), 24; https://doi.org/10.3390/dairy6030024 (registering DOI) - 22 May 2025
Abstract
This study explores the microbiota and metabolite profile of raw cow’s milk, analyzing the correlation between them and their potential impact on consumer health, focusing on factors like cow’s feeding regimen (conventional vs. grazing), the herd’s geographical location (coastal vs. inland), and the [...] Read more.
This study explores the microbiota and metabolite profile of raw cow’s milk, analyzing the correlation between them and their potential impact on consumer health, focusing on factors like cow’s feeding regimen (conventional vs. grazing), the herd’s geographical location (coastal vs. inland), and the thermal stability of raw milk samples. To achieve this, raw milk quality was assessed through mesophilic bacterial count and thermal stability using the 70° and 80° ethanol test. Metataxonomic analysis was performed using Illumina 16S rRNA hypervariable region sequencing, and untargeted metabolomics was conducted using UHPLC-Q/TOF MS/MS, followed by multivariate correlation analysis. All samples met quality standards. A total of 1258 prokaryotic ASVs were identified, spanning 48 bacterial phyla and one archaeal phylum, with 909 genera and 349 unidentified ASVs. Additionally, 70 metabolites were identified, including essential amino acids, vitamins, and bioactive compounds with antimicrobial, anti-inflammatory, and prebiotic properties. Significant correlations between bacterial diversity and metabolite profiles were observed. Feeding regimen and geographical location influence microbial composition and metabolite abundance, while thermal stability was linked to specific metabolites like oleamide and pyridoxal. These findings suggest that microbiota-derived metabolites can enhance the nutritional and functional value of milk. Further research is needed to understand how environmental and processing factors influence these dynamics. Full article
(This article belongs to the Section Metabolomics and Foodomics)
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30 pages, 1033 KiB  
Review
Targeting Aging Hallmarks with Monoclonal Antibodies: A New Era in Cancer Immunotherapy and Geriatric Medicine
by Michele Dal Bo, Marta Gambirasi, Idris Vruzhaj, Erika Cecchin, Abbas Pishdadian, Giuseppe Toffoli and Amin Safa
Int. J. Mol. Sci. 2025, 26(11), 4982; https://doi.org/10.3390/ijms26114982 - 22 May 2025
Abstract
Aging is characterized by a progressive deterioration in physiological function and an increased susceptibility to age-related diseases, such as cancer. Monoclonal antibodies (mAbs) constitute a novel therapeutic approach aimed at addressing aging mechanisms such as cellular senescence, inflammaging, and immunosenescence. This text presents [...] Read more.
Aging is characterized by a progressive deterioration in physiological function and an increased susceptibility to age-related diseases, such as cancer. Monoclonal antibodies (mAbs) constitute a novel therapeutic approach aimed at addressing aging mechanisms such as cellular senescence, inflammaging, and immunosenescence. This text presents an overview of mAb methods aimed at the markers of aging and their potential application in cancer treatment. The mAbs can be categorized into senolytics, senescence-associated secretory phenotype (SASP) neutralizers, and immune checkpoint inhibitors, each targeting fewer aging-related pathways relevant to cancer therapeutic enhancement than the last. Translating promising preclinical evidence into enhanced efficacy and safety in cancer therapy presents challenges, particularly in older populations. This study examines the therapeutic efficacy of mAbs in the treatment of cancer and age-related disorders, focusing on their current and future roles in oncology practice. Full article
(This article belongs to the Special Issue New Insights in Antibody Therapy)
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15 pages, 1871 KiB  
Article
NIR-Emitting Scintillators Based on CsI Single Crystals
by Dmitriy Sofich, Veronika Gavrilenko, Viktorija Pankratova, Vladimir Pankratov, Ekaterina Kaneva and Roman Shendrik
Crystals 2025, 15(6), 489; https://doi.org/10.3390/cryst15060489 - 22 May 2025
Abstract
The development of efficient scintillators emitting in the red and/or infrared spectral range represents an important scientific challenge, as such materials could find numerous practical applications. This work studies newly grown CsI:Yb,Sm and CsI:Eu,Sm single crystals demonstrating red and infrared luminescence. We measured [...] Read more.
The development of efficient scintillators emitting in the red and/or infrared spectral range represents an important scientific challenge, as such materials could find numerous practical applications. This work studies newly grown CsI:Yb,Sm and CsI:Eu,Sm single crystals demonstrating red and infrared luminescence. We measured luminescence spectra in the visible and near-IR range, excitation spectra across visible, UV, VUV, and X-ray ranges, Raman spectra, and thermoluminescence spectra. The results show that divalent europium and ytterbium ions can efficiently transfer excitation to samarium ions. The light output of the obtained crystals under X-ray excitation was roughly estimated from the X-ray luminescence spectra, with expected values of 37,000 photons/MeV for CsI:Yb,Sm and 40,000 photons/MeV for CsI:Eu,Sm. Full article
(This article belongs to the Section Crystal Engineering)
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23 pages, 9970 KiB  
Article
Carbon-Halloysite Nanocomposites and Their Adsorption Characteristics for Pharmaceuticals—A Naproxen Case Study
by Piotr Słomkiewicz, Beata Szczepanik, Piotr Sakiewicz, Klaudiusz Gołombek and Krzysztof Piotrowski
Materials 2025, 18(11), 2433; https://doi.org/10.3390/ma18112433 (registering DOI) - 22 May 2025
Abstract
The synthesis of carbon-halloysite nanocomposites was carried out using aqueous sucrose solutions as a carbon precursor. Raw and calcined halloysite with different grain size classes were used as a carbon support. The influence of halloysite grain size and the calcination process on the [...] Read more.
The synthesis of carbon-halloysite nanocomposites was carried out using aqueous sucrose solutions as a carbon precursor. Raw and calcined halloysite with different grain size classes were used as a carbon support. The influence of halloysite grain size and the calcination process on the carbon concentration in the composites and their adsorption characteristics towards the separation of naproxen from aqueous solutions was identified experimentally. The kinetic conditions of the process (pseudo-second-order kinetic model) indicate a favorable increase in the number of active sites formed after the deposition of the carbon layer on the surface of halloysite particles. Validation of the Langmuir multi-center isotherm adsorption model indicates a separation mechanism associated with the occurrence of multiple active centers on the nanocomposite adsorbent surface and the effect of separation without dissociation of naproxen particles. The obtained carbon-halloysite nanocomposite, due to the relatively cheap and simple, environmentally friendly production methodology and the required inexpensive raw materials, can be widely used in effective and common, economical treatment of wastewater streams from naproxen. The observed naproxen separation process effects are significant. Full article
(This article belongs to the Special Issue Advances in Surface Engineering Technologies and Their Impact on Surface Integrity and Functional Performance of Additively Manufactured Parts)
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19 pages, 2156 KiB  
Article
An Efficient Q-Learning-Based Multi-Objective Intelligent Hybrid Genetic Algorithm for Mixed-Model Assembly Line Efficiency
by Mudassar Rauf, Jabir Mumtaz, Rabia Adeel, Kaynat Afzal Minhas and Muhammad Usman
Symmetry 2025, 17(6), 811; https://doi.org/10.3390/sym17060811 (registering DOI) - 22 May 2025
Abstract
In real-life mixed-model assembly lines, multiple problems collectively affect the final production’s performance. In this study, mixed-model assembly lines integrated with balancing and sequencing problems are considered simultaneously solved. A comprehensive mathematical model is formulated to evaluate the current multi-objective problem. An intelligent [...] Read more.
In real-life mixed-model assembly lines, multiple problems collectively affect the final production’s performance. In this study, mixed-model assembly lines integrated with balancing and sequencing problems are considered simultaneously solved. A comprehensive mathematical model is formulated to evaluate the current multi-objective problem. An intelligent hybrid genetic algorithm (IHGA) is proposed to solve the integrated mixed-model assembly line balancing and sequencing problem. The performance of the proposed algorithm is triggered by integrating heuristic rules through a generation gap mechanism which helps in reducing search space without succumbing to local optima. Additionally, parametric tuning of the algorithm is performed using Q-learning, enabling adaptive optimization through reinforcement learning. This helps to enhance computational efficiency and achieve robust performance of the proposed algorithm. The performance of the IHGA algorithm is rigorously compared with existing approaches, including a non-dominated sorting genetic algorithm, multi-objective artificial bee colony, multi-objective particle swarm optimization, multi-objective evolutionary algorithm based on Decomposition, and multi-objective grey wolf optimizer. Results demonstrate the superior performance of the proposed algorithm across various metrics, showcasing its efficacy in optimizing mixed-model assembly lines, where symmetry in task allocation and sequencing can significantly enhance operational efficiency in contemporary industrial settings. Additionally, a real-life case study is solved to validate the empirical applicability of the proposed IHGA. The extensive experimental analysis notably shows that the proposed IHGA outperforms the existing methods. Full article
(This article belongs to the Special Issue Advances in Dynamics, Planning and Control of Spacecraft and Related Systems)
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9 pages, 449 KiB  
Article
Increased Odds of Antibiotic Resistance in E. coli Isolates from Recurrent Urinary Tract Infections
by Lauren Frisbie, Ann E. Salm, Jeff Radcliff, Scott J. Weissman, Hema Kapoor and Peter Rabinowitz
LabMed 2025, 2(2), 9; https://doi.org/10.3390/labmed2020009 - 22 May 2025
Abstract
This study included deidentified antibiotic susceptibility results from outpatient urinary Escherichia coli isolates from Washington state which were tested at a large clinical laboratory during 2013–2019. Isolates were categorized as representing the first, second, third, or fourth-or-greater occurrence of infection in data from [...] Read more.
This study included deidentified antibiotic susceptibility results from outpatient urinary Escherichia coli isolates from Washington state which were tested at a large clinical laboratory during 2013–2019. Isolates were categorized as representing the first, second, third, or fourth-or-greater occurrence of infection in data from individual patients. We used logistic regression with the outcome of resistance, adjusting for year of antimicrobial susceptibility test, patient sex, patient age, and facility type. In cases of subsequent infection, we found a significant risk of resistance to levofloxacin, ciprofloxacin, ceftriaxone, trimethoprim-sulfa, nitrofurantoin, ampicillin, gentamicin, and amoxicillin-clavulanate. Our findings suggest that Escherichia coli isolates from recurrent urinary tract infections have a higher rate of resistance to most tested antibiotics than isolates from the first urinary tract infection in a given year. However, susceptibility frequencies did not differ significantly between antibiograms constructed using only the first occurrence in a patient and those constructed using all subsequent occurrences. These findings suggest that the traditional approach of including only the first occurrence of urinary Escherichia coli in a patient may underestimate levels of antibiotic resistance in a community. Such underestimation could negatively affect empiric therapeutic choices, health outcomes, and treatment costs. Full article
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14 pages, 2601 KiB  
Article
Lightning Damage Detection Method Using Autoencoder: A Case Study on Wind Turbines with Different Blade Damage Patterns
by Takuto Matsui, Kazuki Matsuoka and Kazuo Yamamoto
Wind 2025, 5(2), 12; https://doi.org/10.3390/wind5020012 - 22 May 2025
Abstract
There have been numerous reported accidents of lightning strikes damaging wind turbine blades, which poses a serious problem. In certain accidents, the blades that were struck by lightning continued to rotate, resulting in breakage due to centrifugal force. Considering this background, wind turbines [...] Read more.
There have been numerous reported accidents of lightning strikes damaging wind turbine blades, which poses a serious problem. In certain accidents, the blades that were struck by lightning continued to rotate, resulting in breakage due to centrifugal force. Considering this background, wind turbines situated in Japan have been mandated to be equipped with emergency stop devices. Consequently, upon detection of a lightning strike by the device installed on the wind turbine, the turbine is promptly stopped. In order to restart the wind turbine, it is necessary to verify its soundness by conducting a visual inspection. However, conducting prompt inspections can be difficult due to various factors, including inclement weather. Therefore, this process prolongs the downtime of wind turbines and reduces their availability. In this study, an approach was proposed: a SCADA data analysis method using an autoencoder to assess the soundness of wind turbines without visual inspection. The present method selected wind speed and rotational speed as effective features, employing a sliding window for pre-processing, based on previous studies. Besides, the assessment of a trained autoencoder was conducted through the utilization of the confusion matrix and the receiver operating characteristic curve. It was suggested that the availability of wind turbines could be improved by employing this proposed method to remotely and automatically verify the soundness after lightning detection. Full article
(This article belongs to the Special Issue O&M and Innovative Solutions Bringing Scale and Speed to Wind Energy Engineering)
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15 pages, 2203 KiB  
Article
Pre- and Postnatal Fine Particulate Matter Exposure and Renal Fibrogenesis in Adult Male Rats: The Role of Vitamin D Supplementation
by Min-Hwa Son, Hyung-Eun Yim, Yu-Seon Lee, Yoon-Jeong Nam and Ju-Han Lee
Curr. Issues Mol. Biol. 2025, 47(6), 387; https://doi.org/10.3390/cimb47060387 - 22 May 2025
Abstract
Prolonged exposure to fine particulate matter (PM2.5) has been implicated in accelerated aging, including organ fibrosis. This study aimed to investigate whether prenatal and postnatal PM2.5 exposure promotes renal fibrogenesis in adulthood and whether long-term vitamin D supplementation alleviates associated [...] Read more.
Prolonged exposure to fine particulate matter (PM2.5) has been implicated in accelerated aging, including organ fibrosis. This study aimed to investigate whether prenatal and postnatal PM2.5 exposure promotes renal fibrogenesis in adulthood and whether long-term vitamin D supplementation alleviates associated renal injury. Pregnant Sprague-Dawley rats were randomly assigned to three groups: control (normal saline, NS), PM2.5 exposure, and PM2.5 exposure with vitamin D supplementation during gestation and lactation (n = 3/group). Male offspring were subsequently exposed to the same conditions from postnatal weeks 3 to 8 (n = 7/group). On postnatal day 56, PM2.5-exposed rats showed lower body weight and more severe glomerular and tubulointerstitial damage compared to controls. Serum calcium levels were elevated in the PM2.5 group. The expression of intrarenal renin, transforming growth factor-β1, α-smooth muscle actin, and vimentin was upregulated, accompanied by increased collagen deposition. Long-term vitamin D supplementation reversed most of these changes, except for intrarenal vimentin expression and serum calcium levels. These findings indicate that prenatal and postnatal PM2.5 exposure can activate intrarenal renin signaling and fibrogenic pathways, contributing to renal fibrosis later in life. Long-term vitamin D supplementation may provide partial protective effects against PM2.5-induced renal fibrogenesis. Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
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34 pages, 6121 KiB  
Article
Acute Impacts of Hurricane Ian on Benthic Habitats, Water Quality, and Microbial Community Composition on the Southwest Florida Shelf
by Matthew Cole Tillman, Robert Marlin Smith, Trevor R. Tubbs, Adam B. Catasus, Hidetoshi Urakawa, Puspa L. Adhikari and James G. Douglass
Coasts 2025, 5(2), 16; https://doi.org/10.3390/coasts5020016 - 22 May 2025
Abstract
Tropical cyclones can severely disturb shallow, continental shelf ecosystems, affecting habitat structure, diversity, and ecosystem services. This study examines the impacts of Hurricane Ian on the Southwest Florida Shelf by assessing water quality, substrate type, and epibenthic and microbial community characteristics at eight [...] Read more.
Tropical cyclones can severely disturb shallow, continental shelf ecosystems, affecting habitat structure, diversity, and ecosystem services. This study examines the impacts of Hurricane Ian on the Southwest Florida Shelf by assessing water quality, substrate type, and epibenthic and microbial community characteristics at eight sites (3 to 20 m in depth) before and after Ian’s passage in 2022. Hurricane Ian drastically changed substrate type and biotic cover, scouring away epibenthos and/or burying hard substrates in mud and sand, especially at mid depth (10 m) sites (92–98% loss). Following Hurricane Ian, the greatest losses were observed in fleshy macroalgae (58%), calcareous green algae (100%), seagrass (100%), sessile invertebrates (77%), and stony coral communities (71%), while soft coral (17%) and sponge communities (45%) were more resistant. After Ian, turbidity, chromophoric dissolved organic matter, and dissolved inorganic nitrogen and phosphorus increased at most sites, while total nitrogen, total phosphorus, and silica decreased. Microbial communities changed significantly post Ian, with estuary-associated taxa expanding further offshore. The results show that the shelf ecosystem is highly susceptible to disturbances from waves, deposition and erosion, and water quality changes caused by mixing and coastal discharge. More routine monitoring of this environment is necessary to understand the long-term patterns of these disturbances, their interactions, and how they influence the resilience and recovery processes of shelf ecosystems. Full article
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14 pages, 681 KiB  
Article
Evaluation of Navify Mutation Profiler Tertiary Analysis Software Assessing for Hematologic Malignancies
by Ruby Singhrao, Michael J. Clark, Shikha Chugh, Lisha Capucion, Shuba Krishna, Ranga Yerram, Lili Niu, Adama Parham, Amy Harrell, John Duncan, Kristina Clark and Manana Javey
J. Mol. Pathol. 2025, 6(2), 9; https://doi.org/10.3390/jmp6020009 - 22 May 2025
Abstract
Background: Navify® Mutation Profiler (Navify MP) is a cloud-based, tertiary analysis software that provides curation, annotation, and reporting of somatic genomic alterations and biomarker signatures identified by next-generation sequencing. The Navify MP software leverages Association for Molecular Pathology/American Society of Clinical Oncology/College [...] Read more.
Background: Navify® Mutation Profiler (Navify MP) is a cloud-based, tertiary analysis software that provides curation, annotation, and reporting of somatic genomic alterations and biomarker signatures identified by next-generation sequencing. The Navify MP software leverages Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists (AMP/ASCO/CAP) Somatic Variant Classification Guidelines to provide information on detected somatic genomic variants and associated therapies according to region-specific approvals. Methods: This validation study assessed the accuracy of the Navify MP software and curation process for hematologic malignancies as compared to expert opinion. A total of 86 variants derived from hematologic malignancies (including myeloid and lymphoid leukemias, B cell lymphomas, and multiple myeloma) were used to contrive 12 VCF files. The VCFs were made up of the following classes of genomic alterations: single nucleotide variants, small insertions and deletions, fusions, and copy number alterations. Of the 86 variants, 42 were Tier IA, and 44 were non-Tier IA, based on AMP/ASCO/CAP classification. The study was performed at four sites with seven software users (molecular genetics experts). Results: Tier classification agreement between Navify MP and expert user assignment was 91.34% for Tier IA and 95.02% across all hematologic variants. The agreement on associated therapies for the Navify MP-classified Tier IA hematologic variants was 99.08%. Conclusion: Navify MP is a robust automated solution for genomic variant reporting of hematologic malignancies and remains up to date with evolving regional approvals and medical guidelines. Full article
22 pages, 4823 KiB  
Article
Photojournalist Framing in the Ecological Crisis: The DANA Flood Coverage
by Carolina Fernández-Castrillo and Celia Ramos
Journal. Media 2025, 6(2), 77; https://doi.org/10.3390/journalmedia6020077 - 22 May 2025
Abstract
This research focuses on current photojournalism practices in the media representation of the climate crisis, exploring how images published by Spain’s leading digital newspapers contribute to shaping public perception of the phenomenon. Through a mixed-methods approach, this study examines eco-visual reporting in 2023—a [...] Read more.
This research focuses on current photojournalism practices in the media representation of the climate crisis, exploring how images published by Spain’s leading digital newspapers contribute to shaping public perception of the phenomenon. Through a mixed-methods approach, this study examines eco-visual reporting in 2023—a year characterized by unprecedented global temperatures—alongside an examination of the initial month of coverage of the 2024 DANA floods. The main objective of this study is to evaluate whether the visual depiction of climate change in mainstream media aligns with or deviates from the established visual patterns associated with stereotyped iconography and alarmist narratives. This research provides a taxonomy of the predominant thematic elements and their frequency, addressing key issues such as the persistence of worn-out visual tropes, the reliance on stock images, and the episodic nature of its news treatment. The inclusion of the most catastrophic climate disaster of the 21st century in Spain allows for an exploration of how the media pressure inherent to crisis situations intensifies the risk of errors in image attribution and contextualization. Finally, we offer practical recommendations to guide visual coverage toward comprehensive, accurate, and human-centered approaches, aiming to foster public trust and maximize the potential of photojournalism as a key tool in collective mobilization against the climate emergency. Full article
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25 pages, 11933 KiB  
Article
BL-DATransformer Lifespan Degradation Prediction Model of Fuel Cell Using Relative Voltage Loss Rate Health Indicator
by Yinjie Xu, Jing Wang, Donghai Hu, Dagang Lu, Xiaoyan Zhang, Wenxuan Wei, Hua Ding and Shupei Zhang
World Electr. Veh. J. 2025, 16(6), 290; https://doi.org/10.3390/wevj16060290 - 22 May 2025
Abstract
The durability of fuel cells is the main obstacle to their large-scale application. Deep learning-based methods improve the accuracy of fuel cell lifespan degradation prediction. However, their reliance on static health indicators and application in bench experiment environments limits their ability to capture [...] Read more.
The durability of fuel cells is the main obstacle to their large-scale application. Deep learning-based methods improve the accuracy of fuel cell lifespan degradation prediction. However, their reliance on static health indicators and application in bench experiment environments limits their ability to capture degradation trends under dynamic conditions. This paper proposes a novel lifespan degradation prediction method for fuel cells operating in real-world traffic environments, utilizing Relative Voltage Loss Rate (RVLR) as the health indicator. Initially, fuel cell lifespan degradation data with varying characteristics are obtained through a dynamic bench experiment and two sets of road driving experiments. Subsequently, a lifespan degradation prediction model based on the Bidirectional Long Short-Term Memory Dual-Attention Transformer (BL-DATransformer) is proposed. An ablation study is conducted on this architecture, with analysis performed to evaluate the influence of diverse input features on model performance. Finally, the comparison results with LSTM, Transformer, and Informer indicate that under smooth traffic conditions, when the training length is 70%, the RMSE is reduced by 84.32%, 74.94%, and 18.49%, respectively. Under congested traffic conditions, with the same training length, the RMSE is reduced by 88.30%, 78.33%, and 26.52%, respectively. The result demonstrates that the prediction method has high accuracy and practical application value. Full article
(This article belongs to the Special Issue Revolutionizing the Automotive Landscape: Fuel Cell Applications Powering the Future)
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