MDPI - Publisher of Open Access Journals

15 pages, 645 KiB

Open AccessArticle

An Octant-Based Multi-Objective Optimization Approach for Lightning Warning in High-Risk Industrial Areas

by Marcos Antonio Alves, Bruno Alberto Soares Oliveira, Douglas Batista da Silva Ferreira, Ana Paula Paes dos Santos, Osmar Pinto, Jr., Fernando Pimentel Silvestrow, Daniel Calvo and Eugenio Lopes Daher

Atmosphere 2025, 16(7), 798; https://doi.org/10.3390/atmos16070798 (registering DOI) - 30 Jun 2025

Abstract

Lightning strikes are a major hazard in tropical regions, especially in northern Brazil, where open-area industries such as mining are highly exposed. This study proposes an octant-based multi-objective optimization approach for spatial lightning alert systems, focusing on minimizing both false alarm rate (FAR) [...] Read more.

Lightning strikes are a major hazard in tropical regions, especially in northern Brazil, where open-area industries such as mining are highly exposed. This study proposes an octant-based multi-objective optimization approach for spatial lightning alert systems, focusing on minimizing both false alarm rate (FAR) and failure-to-warn (FTW). The method uses NSGA-III to optimize a configuration vector consisting of directional radii and alert thresholds, based solely on historical lightning location data. Experiments were conducted using four years of cloud-to-ground lightning data from a mining area in Pará, Brazil. Fifteen independent runs were executed, each with 96 individuals and up to 150 generations. The results showed a clear trade-off between FAR and FTW, with optimal solutions achieving up to 16% reduction in FAR and 50% reduction in FTW when compared to a quadrant-based baseline. The use of the hypervolume metric confirmed consistent convergence across runs. Sensitivity analysis revealed spatial patterns in optimal configurations, supporting the use of directional tuning. The proposed approach provides a flexible and interpretable model for risk-based alert strategies, compliant with safety regulations such as NBR 5419/2015 and NR-22. It offers a viable solution for automated alert generation in high-risk environments, especially where detailed meteorological data is unavailable. Full article

(This article belongs to the Special Issue Recent Insights and Advances in Lightning and Other Thunderstorm-Related Transient Events)

44 pages, 1683 KiB

Open AccessArticle

Modeling of Energy Management System for Fully Autonomous Vessels with Hybrid Renewable Energy Systems Using Nonlinear Model Predictive Control via Grey Wolf Optimization Algorithm

by Harriet Laryea and Andrea Schiffauerova

J. Mar. Sci. Eng. 2025, 13(7), 1293; https://doi.org/10.3390/jmse13071293 (registering DOI) - 30 Jun 2025

Abstract

This study presents a multi-objective predictive energy management system (EMS) for optimizing hybrid renewable energy systems (HRES) in autonomous marine vessels. The objective is to minimize fuel consumption and emissions while maximizing renewable energy usage and pure-electric sailing durations. The EMS combines nonlinear [...] Read more.

This study presents a multi-objective predictive energy management system (EMS) for optimizing hybrid renewable energy systems (HRES) in autonomous marine vessels. The objective is to minimize fuel consumption and emissions while maximizing renewable energy usage and pure-electric sailing durations. The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. The HRES architecture comprises photovoltaic arrays, vertical-axis wind turbines (VAWTs), diesel engines, generators, and a battery storage system. A ship dynamics model was used to represent propulsion power under realistic sea conditions. Simulations were conducted using real-world operational and environmental datasets, with state prediction enhanced by an Extended Kalman Filter (EKF). Performance is evaluated using marine-relevant indicators—fuel consumption; emissions; battery state of charge (SOC); and emission cost—and validated using standard regression metrics. The NMPC-GWO algorithm consistently outperformed both NMPC-GA and RB approaches, achieving high prediction accuracy and greater energy efficiency. These results confirm the reliability and optimization capability of predictive EMS frameworks in reducing emissions and operational costs in autonomous maritime operations. Full article

(This article belongs to the Special Issue Advancements in Hybrid Power Systems for Marine Applications)

66 pages, 6945 KiB

Open AccessReview

Towards Resilient Cities: Systematic Review of the Literature on the Use of AI to Optimize Water Harvesting and Mitigate Scarcity

by Victor Martin Maldonado Benitez, Oswaldo Morales Matamoros and Jesús Jaime Moreno Escobar

Water 2025, 17(13), 1978; https://doi.org/10.3390/w17131978 (registering DOI) - 30 Jun 2025

Abstract

This article develops a systematic literature review with a focus on the optimization of water harvesting through the use of artificial intelligence (AI) applications. These are framed in the search for sustainable solutions to the growing problem of water scarcity in urban environments. [...] Read more.

This article develops a systematic literature review with a focus on the optimization of water harvesting through the use of artificial intelligence (AI) applications. These are framed in the search for sustainable solutions to the growing problem of water scarcity in urban environments. The analysis is oriented towards urban resilience and smart water management, incorporating interdisciplinary approaches such as systems thinking to understand the complex dynamics involved in water governance. The results indicate a growing trend in the utilisation of AI in various domains, including demand forecasting, leak detection, and catchment infrastructure optimization. Additionally, the findings suggest its application in water resilience modelling and adaptive urban planning. The text goes on to examine the challenges associated with the integration of technology in urban contexts, including the critical aspects of governance and regulation of AI, water consumption, energy and carbon emissions from the use of this technology, as well as the regulation of water management in digital transformation scenarios. The study identifies the most representative patents that combat the problem, and in parallel proposes lines of research aimed at strengthening the water resilience and sustainability of cities. The strategic role of AI as a catalyst for innovation in the transition towards smarter, more integrated and adaptive water management systems is also highlighted. Full article

(This article belongs to the Special Issue Urban Stormwater Harvesting, and Wastewater Treatment and Reuse)

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23 pages, 7337 KiB

Open AccessArticle

Population Cohort-Validated PM_2.5-Induced Gene Signatures: A Machine Learning Approach to Individual Exposure Prediction

by Yu-Chung Wei, Wen-Chi Cheng, Pinpin Lin, Zhi-Yao Zhang, Chi-Hsien Chen, Chih-Da Wu, Yue Leon Guo and Hung-Jung Wang

Toxics 2025, 13(7), 562; https://doi.org/10.3390/toxics13070562 (registering DOI) - 30 Jun 2025

Abstract

Transcriptomic profiling has shown that exposure to PM_2.5, a common air pollutant, can modulate gene expression, which has been linked to negative health effects and diseases. However, there are few population-based cohort studies on the association between PM_2.5 exposure and [...] Read more.

Transcriptomic profiling has shown that exposure to PM_2.5, a common air pollutant, can modulate gene expression, which has been linked to negative health effects and diseases. However, there are few population-based cohort studies on the association between PM_2.5 exposure and specific gene set expression. In this study, we used an unbiased transcriptomic profiling approach to examine gene expression in a mouse model exposed to PM_2.5 and to identify PM_2.5-responsive genes. The gene expressions were further validated in both the human cell lines and a population-based cohort study. Two cohorts of healthy older adults (aged ≥ 65 years) were recruited from regions characterized by differing levels of PM_2.5. Logistic regression and decision tree algorithms were then utilized to construct predictive models for PM_2.5 exposure based on these gene expression profiles. Our results indicated that the expression of five genes (FAM102B, PPP2R1B, OXR1, ITGAM, and PRP38B) increased with PM_2.5 exposure in both cell-based assay and population-based cohort studies. Furthermore, the predictive models demonstrated high accuracy in classifying high-and-low PM_2.5exposure, potentially supporting the integration of gene biomarkers into public health practices. Full article

(This article belongs to the Section Air Pollution and Health)

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18 pages, 2038 KiB

Open AccessArticle

Intuitive Recognition of a Virtual Agent’s Learning State Through Facial Expressions in VR

by WonHyong Lee and Dong Hwan Jin

Electronics 2025, 14(13), 2666; https://doi.org/10.3390/electronics14132666 (registering DOI) - 30 Jun 2025

Abstract

As artificial intelligence agents become integral to immersive virtual reality environments, their inherent opacity presents a significant challenge to transparent human–agent communication. This study aims to determine if a virtual agent can effectively communicate its learning state to a user through facial expressions, [...] Read more.

As artificial intelligence agents become integral to immersive virtual reality environments, their inherent opacity presents a significant challenge to transparent human–agent communication. This study aims to determine if a virtual agent can effectively communicate its learning state to a user through facial expressions, and to empirically validate a set of designed expressions for this purpose. We designed three animated facial expression sequences for a stylized three-dimensional avatar, each corresponding to a distinct learning outcome: clear success (Case A), mixed performance (Case B), and moderate success (Case C). An initial online survey (

n = 93

) first confirmed the general interpretability of these expressions, followed by a main experiment in virtual reality (

n = 30

), where participants identified the agent’s state based solely on these visual cues. The results strongly supported our primary hypothesis (H1), with participants achieving a high overall recognition accuracy of approximately 91%. While user background factors did not yield statistically significant differences, observable trends suggest they may be worthy of future investigation. These findings demonstrate that designed facial expressions serve as an effective and intuitive channel for real-time, affective explainable artificial intelligence (affective XAI), contributing a practical, human-centric method for enhancing agent transparency in collaborative virtual environments. Full article

(This article belongs to the Special Issue Advances in Human-Computer Interaction: Challenges and Opportunities)

17 pages, 3603 KiB

Open AccessArticle

Implementation of a Second-Order TVD Transport Algorithm in the General Ocean Model (GOM)

by Jungwoo Lee, Jun Lee, Sang-Leen Yun and Seog-Ku Kim

J. Mar. Sci. Eng. 2025, 13(7), 1296; https://doi.org/10.3390/jmse13071296 (registering DOI) - 30 Jun 2025

Abstract

This study presents the implementation of a scalar transport algorithm in the recently developed General Ocean Model (GOM), a three-dimensional, unstructured grid, finite volume/finite difference model. Solving the advection–diffusion transport equation is an essential part of any ocean circulation model since the baroclinic [...] Read more.

This study presents the implementation of a scalar transport algorithm in the recently developed General Ocean Model (GOM), a three-dimensional, unstructured grid, finite volume/finite difference model. Solving the advection–diffusion transport equation is an essential part of any ocean circulation model since the baroclinic density gradient distinguishes saline water from freshwater. To achieve both high accuracy and computational efficiency, we adopted a second-order semi-implicit Total Variation Diminishing (TVD) scheme. The TVD approach, known for its ability to suppress non-physical oscillations near steep gradients, provides a higher-fidelity representation of salinity fronts without introducing significant numerical artifacts. The TVD algorithm is constructed with the first-order Upwind scheme, which is known for suffering from excessive numerical diffusion, and the higher-order anti-diffusive flux term. The implemented transport algorithm is evaluated using two standard test cases, an ideal lock exchange problem and a U-shaped channel problem, and it is further applied to simulate salinity dynamics in Mobile Bay, Alabama. The model results from both the first-order Upwind and second-order TVD schemes are compared. The results indicate that the TVD scheme marginally improves the resolution of salinity fronts while maintaining computational stability and efficiency. The implementation enables a flexible and straightforward transition between the first-order scheme, which is faster than the second-order scheme, and the second-order scheme, which is less diffusive than the first-order scheme, enhancing the GOM’s capability for realistic and efficient salinity simulations in a tidally driven estuarine system. Full article

(This article belongs to the Section Coastal Engineering)

21 pages, 5268 KiB

Open AccessArticle

CM-YOLO: A Multimodal PCB Defect Detection Method Based on Cross-Modal Feature Fusion

by Haowen Lan, Jiaxiang Luo, Hualiang Zhang and Xu Yan

Sensors 2025, 25(13), 4108; https://doi.org/10.3390/s25134108 (registering DOI) - 30 Jun 2025

Abstract

By integrating information from RGB images and depth images, the feature perception capability of a defect detection algorithm can be enhanced, making it more robust and reliable in detecting subtle defects on printed circuit boards. On this basis, inspired by the concept of [...] Read more.

By integrating information from RGB images and depth images, the feature perception capability of a defect detection algorithm can be enhanced, making it more robust and reliable in detecting subtle defects on printed circuit boards. On this basis, inspired by the concept of differential amplification, we propose a novel and general weighted feature fusion method within the YOLO11 dual-stream detection network framework, which we name CM-YOLO. Based on the differential amplification approach, we introduce a Differential Amplification Weighted Fusion (DAWF) module, which separates multimodal features into common-mode and differential-mode features to preserve and enhance modality-specific characteristics. Then, the SE-Weighted Fusion module is used to fuse the common-mode and differential-mode features.In addition, we introduce a Cross-Attention Spatial and Channel (CASC) module into the detection network to enhance feature extraction capability. Extensive experiments show that the proposed CM-YOLO method achieves a mean Average Precision (mAP) of 0.969, demonstrating the accuracy and effectiveness of CM-YOLO. Full article

(This article belongs to the Section Sensing and Imaging)

20 pages, 1278 KiB

Open AccessArticle

Longer Truck to Reduce CO₂ Emissions: Study and Proposal Accepted for Analysis in Spain

by Yesica Pino, Juan L. Elorduy and Angel Gento

Sustainability 2025, 17(13), 6026; https://doi.org/10.3390/su17136026 (registering DOI) - 30 Jun 2025

Abstract

The transport industry in the European Union plays a key role in the economy. However, due to persistent political, social, and technological changes, examining optimization strategies in transportation has become a crucial task to minimize expenditure, promote sustainable solutions, and address environmental degradation [...] Read more.

The transport industry in the European Union plays a key role in the economy. However, due to persistent political, social, and technological changes, examining optimization strategies in transportation has become a crucial task to minimize expenditure, promote sustainable solutions, and address environmental degradation concerns. This study analyzes the effectiveness of a new truck trailer design, adapted from existing European models, which improves load capacity through an extended trailer length. The increased length (and, by extension, volume) is expected to reduce the number of vehicles for freight transportation, thereby improving road congestion and reducing environmental impacts, which include GHG emissions and overall carbon footprint. To achieve this objective, a comprehensive analysis of current European regulations on articulated vehicles and road trains was carried out, alongside a review of related case studies implemented or under development across the European Union member states. Additionally, a pilot study was conducted using the proposed 18 m semi-trailer across 14 real-life freight routes involving loads from several suppliers and manufacturers. This study therefore demonstrates the economic benefits and reduction in pollutant emissions related to the extended design and evaluates its impact on road infrastructure conditions, given the total length of 20.55 m. Full article

(This article belongs to the Special Issue Green Logistics and Sustainable Economy—2nd Edition)

22 pages, 520 KiB

Open AccessReview

RAS Mutations in Advanced Colorectal Cancer: Mechanisms, Clinical Implications, and Novel Therapeutic Approaches

by Osman Sütcüoğlu, Hasan Çağrı Yıldırım, Elvina Almuradova, Damla Günenç and Şuayib Yalçın

Medicina 2025, 61(7), 1202; https://doi.org/10.3390/medicina61071202 (registering DOI) - 30 Jun 2025

Abstract

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality globally, posing significant treatment challenges, particularly in its metastatic form (mCRC). This review comprehensively examines the pivotal role of RAS mutations, specifically KRAS and NRAS, which are detected in approximately 40–45% of mCRC [...] Read more.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality globally, posing significant treatment challenges, particularly in its metastatic form (mCRC). This review comprehensively examines the pivotal role of RAS mutations, specifically KRAS and NRAS, which are detected in approximately 40–45% of mCRC cases, and their impact on treatment decisions and patient outcomes. We assess the effectiveness of standard treatments within the RAS mutant population, highlighting the challenges and limitations these therapies face. Recent advancements in targeted therapies, particularly the focus on novel agents such as KRAS G12C inhibitors, including sotorasib and adagrasib, have shown promising efficacy in overcoming resistance to conventional treatments. Furthermore, this review discusses future directions, emphasizing the need for research into non-RAS targets to address the complexities of resistance mechanisms and improve therapeutic outcomes. This review aims to provide a detailed overview of the current treatments and innovative approaches, supporting the development of personalized management strategies for patients with mCRC. Full article

(This article belongs to the Section Oncology)

16 pages, 834 KiB

Open AccessArticle

Structural and Quantitative Analysis of Polyfluoroalkyl Substances (PFASs) and Para-Phenylenediamines (PPDs) by Direct Analysis in Real Time Ion Mobility Mass Spectrometry (DART-IM-MS)

by Calum Bochenek, Jack Edwards, Zhibo Liu and Chrys Wesdemiotis

Molecules 2025, 30(13), 2828; https://doi.org/10.3390/molecules30132828 (registering DOI) - 30 Jun 2025

Abstract

Polyfluoroalkyl substances (PFASs) and para-phenylenediamines (PPDs) are emerging classes of anthropogenic contaminants that are environmentally persistent (most often found in ground and surface water sources), bioaccumulative, and harmful to human health. These chemicals are currently regulated in the US by the Environmental Protection [...] Read more.

Polyfluoroalkyl substances (PFASs) and para-phenylenediamines (PPDs) are emerging classes of anthropogenic contaminants that are environmentally persistent (most often found in ground and surface water sources), bioaccumulative, and harmful to human health. These chemicals are currently regulated in the US by the Environmental Protection Agency (EPA), the Food and Drug Administration (FDA), and the Occupational Safety and Health Administration (OSHA). Analysis of these contaminants is currently spearheaded by mass spectrometry (MS) coupled to liquid chromatography (LC) because of their high sensitivity and separation capabilities. Although effective, a major flaw in LC-MS analysis is its large consumption of solvents and the amount of time required for each experiment. Direct analysis in real time mass spectrometry (DART-MS) is a new technique that offers high sensitivity and permits rapid analysis with little to no sample preparation. Herein, we present the qualitative and quantitative analysis of PFASs and PPDs by high-resolution DART-MS, interfaced with ion mobility (IM) and tandem mass spectrometry (MS/MS) characterization, demonstrating the utility of this multidimensional approach for the fast separation and detection of environmental contaminants. Full article

(This article belongs to the Section Analytical Chemistry)

24 pages, 941 KiB

Open AccessReview

Could Sodium-Glucose Co-Transporter-2 Inhibitors and Glucagon-like Peptide-1 Receptor Agonists Play a Role in Gout Treatment?

by Dan Kaufmann and Naomi Schlesinger

Pharmaceutics 2025, 17(7), 865; https://doi.org/10.3390/pharmaceutics17070865 (registering DOI) - 30 Jun 2025

Abstract

Gout, a metabolic and autoinflammatory disease, is the most common form of inflammatory arthritis worldwide. Hyperuricemia may result in monosodium urate (MSU) crystals forming and depositing in joints and surrounding tissues, triggering an autoinflammatory response. Effective urate-lowering therapies, as well as anti-inflammatory medications, [...] Read more.

Gout, a metabolic and autoinflammatory disease, is the most common form of inflammatory arthritis worldwide. Hyperuricemia may result in monosodium urate (MSU) crystals forming and depositing in joints and surrounding tissues, triggering an autoinflammatory response. Effective urate-lowering therapies, as well as anti-inflammatory medications, are used to treat gout. Over the past few decades, new antihyperglycemic drug classes with different modes of action have been added to treat hyperglycemia in type 2 diabetes mellitus (T2DM). Two of these drug classes, sodium–glucose co-transporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists (RAs), have reduced cardiovascular and renal events and mortality. Several clinical studies have demonstrated that SGLT2 inhibitors possess urate-lowering properties, which may be beneficial for treating gout patients, particularly those with comorbid T2DM. Regarding SGLT2 inhibitors, some researchers have suggested that their benefits are partly explained by their ability to reduce serum urate (SU) levels, probably through increased urinary uric acid excretion. The effect of GLP-1 RA on SU levels and urinary excretion of uric acid in humans is unclear. This paper reviews the mechanisms of action of SGLT2 inhibitors and GLP-1RA, both approved and in development. Additionally, it examines what is known about their structure–activity relationships, uricosuric effects, pharmacokinetic profiles, and adverse effects. Full article

(This article belongs to the Special Issue Recent Advances in Inhibitors for Targeted Therapies)

33 pages, 3819 KiB

Open AccessReview

Phytotherapy and the Role of Bioactive Compounds in Modulating Mechanisms of Overweight and Obesity Comorbid with Depressive Symptoms—A Scoping Review of Mechanisms of Action

by Klaudia Sochacka and Sabina Lachowicz-Wiśniewska

Molecules 2025, 30(13), 2827; https://doi.org/10.3390/molecules30132827 (registering DOI) - 30 Jun 2025

Abstract

Obesity and depression frequently coexist, sharing overlapping molecular pathways such as inflammation, oxidative stress, gut microbiota dysbiosis, and neuroendocrine dysfunction. Recent research highlights the therapeutic potential of plant-derived bioactive compounds in targeting these shared mechanisms. This scoping review followed Preferred Reporting Items for [...] Read more.

Obesity and depression frequently coexist, sharing overlapping molecular pathways such as inflammation, oxidative stress, gut microbiota dysbiosis, and neuroendocrine dysfunction. Recent research highlights the therapeutic potential of plant-derived bioactive compounds in targeting these shared mechanisms. This scoping review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and included 261 peer-reviewed studies identified through PubMed, Scopus, and the Web of Science up to December 2024. Studies were screened based on predefined inclusion and exclusion criteria. This review synthesizes data from peer-reviewed studies, including both preclinical and clinical investigations, focusing on polyphenols, flavonoids, alkaloids, and other phytochemicals with anti-inflammatory, antioxidant, neuroprotective, and metabolic effects. Compounds such as quercetin, epigallocatechin gallate (EGCG), resveratrol, curcumin, anthocyanins, and luteolin demonstrate promise in modulating adenosine monophosphate-activated protein kinase (AMPK), brain-derived neurotrophic factor (BDNF), nuclear factor kappa B (NF-κB), and gut–brain axis pathways. Our scoping review, conducted in accordance with PRISMA guidelines, identifies promising combinations and mechanisms for integrative phytotherapy. These findings underscore the potential of botanical strategies in developing future interventions for metabolic and mood comorbidities. Full article

(This article belongs to the Special Issue Bioactive Compounds from Foods for Health Benefits)

15 pages, 555 KiB

Open AccessArticle

Cascade Genetic Testing for Hereditary Cancer Predisposition: Characterization of Patients in a Catchment Area of Southern Italy

by Anna Bilotta, Elisa Lo Feudo, Valentina Rocca, Emma Colao, Francesca Dinatolo, Serena Marianna Lavano, Paola Malatesta, Lucia D’Antona, Rosario Amato, Francesco Trapasso, Nicola Perrotti, Giuseppe Viglietto, Francesco Baudi and Rodolfo Iuliano

Genes 2025, 16(7), 795; https://doi.org/10.3390/genes16070795 (registering DOI) - 30 Jun 2025

Abstract

Background: The national guidelines, informed by evidence from the National Institutes of Health (NIH), define the cri-teria for genetic testing of BRCA1/2 and other genes associated with Hereditary Breast and Ovarian Cancer (HBOC) and Lynch Syndrome (LS). When a germline pathogenic variant [...] Read more.

Background: The national guidelines, informed by evidence from the National Institutes of Health (NIH), define the cri-teria for genetic testing of BRCA1/2 and other genes associated with Hereditary Breast and Ovarian Cancer (HBOC) and Lynch Syndrome (LS). When a germline pathogenic variant (PV) is identified in an index case, clinical recommendations advise informing at-risk relatives about the availability of predictive genetic testing, as early identification of carriers allows for timely implementation of preventive measures. Methods:This retrospective observational study examined data collected between 2017 and 2024 at the Medical Genetics Unit of the “Renato Dulbecco” University Hospital in Catanzaro, Italy. The analysis focused on trends in the identification of individuals carrying PVs in cancer predisposition genes (CPGs) and the subsequent uptake of cascade genetic testing (CGT) among their family members. Results: Over the study period, from 116 probands were performed 257 CGTs on 251 relatives.A notable reduction of approximately ten years in median age was observed, 39% were found to carry familial mutation and were referred to personalized cancer prevention programs. Among these, 62% accessed Oncological Genetic Counselling (CGO) within one year of the proband’s diagnosis, suggesting effective communication and outreach. Conclusions: The findings highlight the critical role of effective CGO and intrafamilial communication in hereditary cancer prevention. The identification of PVs, followed by timely CGTs and implementation of preventive strategies, sig-nificantly contributes to early cancer risk management. Periodic monitoring of CGT uptake and outcome trends, as demonstrated in this study, is essential to refine and optimize genetic services and public health strategies. Full article

(This article belongs to the Section Human Genomics and Genetic Diseases)

26 pages, 1044 KiB

Open AccessArticle

Strategic Dynamics of Circular Economy Initiatives in Food Systems: A Game Theory Perspective

by Valérie Lacombe and Juste Rajaonson

Sustainability 2025, 17(13), 6025; https://doi.org/10.3390/su17136025 (registering DOI) - 30 Jun 2025

Abstract

This paper analyses how strategic interactions between actors influence the development of circular economy (CE) initiatives in food systems. Using a case study from Saint-Hyacinthe, a mid-sized and agri-food technopole in Québec (Canada), we investigate how cooperation, competition, and power asymmetries shape CE [...] Read more.

This paper analyses how strategic interactions between actors influence the development of circular economy (CE) initiatives in food systems. Using a case study from Saint-Hyacinthe, a mid-sized and agri-food technopole in Québec (Canada), we investigate how cooperation, competition, and power asymmetries shape CE adoption across the supply chain. Drawing on game theory and a typology of management dynamics, the study identifies four patterns: negotiated management, constrained leadership, hierarchical relationships, and competitive behaviour. Empirical data were collected through two collaborative workshops involving public, private, and community-based actors, resulting in 244 coded entries across 12 boards. These allowed us to assess actors’ interests, attitudes, and capacities in relation to CE strategies at upstream, midstream, and downstream stages. The results show that strategies aligned with dominant interests and existing capacities are more likely to be supported, while those requiring structural change are tolerated or marginalized. Findings highlight the role of incentive mechanisms, institutional flexibility, and coordination in enabling more transformative circular initiatives. By adopting a stage-sensitive perspective, this study also fills a gap in the literature by examining how actor dynamics differ across upstream, midstream, and downstream segments of the food system, contributing to CE research by applying game theory to actor configurations and interaction dynamics in food systems. It calls for further exploration of interdependencies and contextual conditions that either facilitate or hinder the emergence of effective, inclusive, and systemic CE transitions. Full article

(This article belongs to the Special Issue Food, Supply Chains, and Sustainable Development—Second Edition)

9 pages, 473 KiB

Open AccessBrief Report

Correlation of Different Non-Invasive Neuromonitoring Tools Assessing Intracranial Hemodynamics

by Rossella Zangari, Luca D’Amelio, Elisa Gouvea Bogossian and Fabio Silvio Taccone

Brain Sci. 2025, 15(7), 710; https://doi.org/10.3390/brainsci15070710 (registering DOI) - 30 Jun 2025

Abstract

Background: Intracranial pressure (ICP) monitoring is crucial in managing acute brain injury (ABI) to prevent secondary brain injury. While invasive techniques remain the gold standard, they can carry notable risks, such as infection and hemorrhage. Non-invasive techniques are increasingly used, but their inter-modality [...] Read more.

Background: Intracranial pressure (ICP) monitoring is crucial in managing acute brain injury (ABI) to prevent secondary brain injury. While invasive techniques remain the gold standard, they can carry notable risks, such as infection and hemorrhage. Non-invasive techniques are increasingly used, but their inter-modality correlation and concordance have not been systematically evaluated. This study aimed to assess the correlation and concordance among four commonly used non-invasive neuromonitoring tools in patients with ABI undergoing invasive ICP monitoring. Methods: This was a secondary analysis of prospectively collected data from 100 adult patients admitted to the intensive care unit with traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), or intracerebral hemorrhage (ICH) who underwent invasive ICP monitoring. Simultaneous assessments using optic nerve sheath diameter (ONSD), transcranial Doppler-derived pulsatility index (PI), estimated ICP (eICP), and the neurological pupil index (NPi) were performed. Correlation between modalities was assessed using Spearman’s correlation coefficient (ρ), and concordance was evaluated with Cohen’s kappa coefficient (k). Results: We found weak correlations between ONSD and PI (ρ = 0.29), ONSD and NPi (ρ = −0.33), and PI and NPi (ρ = −0.33); moderate correlations between ONSD and eICP (ρ = 0.54) and PI and eICP (ρ = 0.48); and a strong inverse correlation between eICP and NPi (ρ = −0.71; all p < 0.05). Concordance was generally low, with the highest agreement between PI and eICP (k = 0.69). Most other tool pairings showed poor-to-fair concordance (k ≤ 0.30). Conclusions: Non-invasive neuromonitoring tools show variable correlation and limited agreement, suggesting they are not interchangeable. Each modality captures different aspects of cerebral physiology, supporting the use of a multimodal approach to improve accuracy in ICP estimation. Full article

(This article belongs to the Section Neurosurgery and Neuroanatomy)

32 pages, 6770 KiB

Open AccessArticle

The Design and Experiment of a Motion Control System for the Whole-Row Reciprocating Seedling Picking Mechanism of an Automatic Transplanter

by Jiawei Shi, Jianping Hu, Wei Liu, Junpeng Lv, Yongwang Jin, Mengjiao Yao and Che Wang

Agriculture 2025, 15(13), 1423; https://doi.org/10.3390/agriculture15131423 (registering DOI) - 30 Jun 2025

Abstract

Aiming at the problem that the whole row of reciprocating seedling picking mechanism is prone to inertial impacts during operation due to its excessive mass, causing seedling damage and positioning errors, this study builds a motion control system with a PLC controller as [...] Read more.

Aiming at the problem that the whole row of reciprocating seedling picking mechanism is prone to inertial impacts during operation due to its excessive mass, causing seedling damage and positioning errors, this study builds a motion control system with a PLC controller as the core and proposes a composite motion control strategy based on planned S-curve acceleration and deceleration and fuzzy PID to achieve rapid response, precise positioning, and smooth operation of the seedling picking mechanism. By establishing the objective function and constraint conditions and taking into account the dynamic change of the seedling picking displacement, the S-curve acceleration and deceleration control algorithm is planned in six and seven stages to meet the requirements of a smooth transition of the speed and continuous change of the acceleration curve of the seedling picking mechanism during movement. A fuzzy PID positioning control system is designed, the control system transfer function is constructed, and fuzzy rules are formulated to dynamically compensate for the error and its rate of change to meet the requirements of fast response and no overshoot oscillation of the positioning control system. The speed and acceleration of the seedling picking mechanism under the six-segment and seven-segment S-curve acceleration and deceleration motion control conditions were simulated using MATLAB2024a simulation software and compared with the trapezoidal acceleration and deceleration motion control. The planned S-curve acceleration and deceleration control algorithm has a more stable control effect on the seedling picking mechanism when it operates under the conditions of the dynamic change of the displacement, and it meets the design requirements of seedling picking efficiency. The positioning control system was modeled and simulated using the Simulink simulation platform. When KP = 15, KI = 3, and KD = 1, the whole-row seedling picking control system ran stably, responded quickly, and had no overshoot. Compared with the PID control system with fixed parameters, the fuzzy PID control system reduced the time consumption in the rising stage by 24.5% and shortened the overall stabilization process by 17.6%. The zero overshoot characteristic was ensured, and the response speed was faster. When a disturbance signal is added, the overshoot of the fuzzy PID control system is reduced by 2.4%, and the response speed is increased by 6.8% compared with the fixed-parameter PID control system. The dynamic response rate and anti-disturbance performance are better than those of the fixed-parameter PID control system. A bench comparison test was carried out. The results showed that the S-curve acceleration and deceleration motion control algorithm reduced the average mass loss rate of seedlings by 46.19% compared with the trapezoidal acceleration and deceleration motion control algorithm, and the seedling picking efficiency met the design requirements. Fuzzy PID positioning control was used, and the maximum displacement error of the end effector during seedling picking was −1.4 mm, and the average relative error rate was 0.22%, which met the positioning accuracy requirements of the end effector in the X-axis direction and verified the stability and accuracy of the designed control system. The designed control system was tested in the field, and the average comprehensive success rate of seedling picking and throwing reached 96.2%, which verified the feasibility and practicality of the control system. Full article

(This article belongs to the Special Issue Soil-Machine Systems and Its Related Digital Technologies Application)

30 pages, 3322 KiB

Open AccessArticle

Genomic and Functional Characterization of Multidrug-Resistant E. coli: Insights into Resistome, Virulome, and Signaling Systems

by Vijaya Bharathi Srinivasan, Naveenraj Rajasekar, Karthikeyan Krishnan, Mahesh Kumar, Chankit Giri, Balvinder Singh and Govindan Rajamohan

Antibiotics 2025, 14(7), 667; https://doi.org/10.3390/antibiotics14070667 (registering DOI) - 30 Jun 2025

Abstract

Introduction: Genetic plasticity and adaptive camouflage in critical pathogens have contributed to the global surge in multidrug-resistant (MDR) infections, posing a serious threat to public health and therapeutic efficacy. Antimicrobial resistance, now a leading cause of global mortality, demands urgent action through diagnostics, [...] Read more.

Introduction: Genetic plasticity and adaptive camouflage in critical pathogens have contributed to the global surge in multidrug-resistant (MDR) infections, posing a serious threat to public health and therapeutic efficacy. Antimicrobial resistance, now a leading cause of global mortality, demands urgent action through diagnostics, vaccines, and therapeutics. In India, the Indian Council of Medical Research’s surveillance network identifies Escherichia coli as a major cause of urinary tract infections, with increasing prevalence in human gut microbiomes, highlighting its significance across One Health domains. Methods: Whole-genome sequencing of E. coli strain ECG015, isolated from a human gut sample, was performed using the Illumina NextSeq platform. Results: Genomic analysis revealed multiple antibiotic resistance genes, virulence factors, and efflux pump components. Phylogenomic comparisons showed close relatedness to pathovars from both human and animal origins. Notably the genome encoded protein tyrosine kinases (Etk/Ptk and Wzc) and displayed variations in the envelope stress-responsive CpxAR two-component system. Promoter analysis identified putative CpxR-binding sites upstream of genes involved in resistance, efflux, protein kinases, and the MazEF toxin–antitoxin module, suggesting a potential regulatory role of CpxAR in stress response and persistence. Conclusions: This study presents a comprehensive genomic profile of E. coli ECG015, a gut-derived isolate exhibiting clinically significant resistance traits. For the first time, it implicates the CpxAR two-component system as a potential central regulator coordinating antimicrobial resistance, stress kinase signaling, and programmed cell death. These findings lay the groundwork for future functional studies aimed at targeting stress-response pathways as novel intervention strategies against antimicrobial resistance. Full article

(This article belongs to the Special Issue Genomic Analysis of Drug-Resistant Pathogens)

23 pages, 4452 KiB

Open AccessArticle

Absorption Heat Transformer and Vapor Compression Heat Pump as Alternative Options for Waste Heat Upgrade in the Industry

by Giorgio Villa, Josè Luis Corrales Ciganda, Gianluca Abrami and Tommaso Toppi

Energies 2025, 18(13), 3454; https://doi.org/10.3390/en18133454 (registering DOI) - 30 Jun 2025

Abstract

Increasing the temperature of waste heat is crucial to enable its recovery. Vapor compression heat pumps and absorption heat transformers are the two heat upgrade technologies most commonly used for this purpose. Heat pumps have the advantage of entirely recovering the waste heat [...] Read more.

Increasing the temperature of waste heat is crucial to enable its recovery. Vapor compression heat pumps and absorption heat transformers are the two heat upgrade technologies most commonly used for this purpose. Heat pumps have the advantage of entirely recovering the waste heat and the disadvantage of requiring electricity as input. Heat transformers need a negligible amount of electricity but reject at part of the waste heat input at low temperature. Due to these differences, the choice between the two options depends on the application. In this work, the environmental and economic performance of heat pumps and heat transformers are compared in some relevant applications. Indications about the most suitable technology are provided based on the availability of the waste heat, of the CO₂ content of the electricity and of the electricity–gas price ratio. Heat pumps perform better when the waste heat availability is limited compared to the upgraded heat requirements and has a better environmental profile when the electricity has low carbon content. Heat transformer results are often economically convenient, especially when the availability of waste heat is large. Full article

(This article belongs to the Special Issue Advances in Refrigeration and Heat Pump Technologies)

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15 pages, 1835 KiB

Open AccessArticle

Mapping the Maxillary Artery and Lateral Pterygoid Muscle Relationship: Insights from Radiological and Meta-Analytic Evidence

by Maria Piagkou, George Triantafyllou, Panagiotis Papadopoulos-Manolarakis, Fotis Demetriou, George Tsakotos, Łukasz Olewnik and Fabrice Duparc

Medicina 2025, 61(7), 1201; https://doi.org/10.3390/medicina61071201 (registering DOI) - 30 Jun 2025

Abstract

Background/Objectives: Variations in the course of the maxillary artery (MA) relative to the lateral pterygoid muscle (LPM) pose critical challenges in surgical, anesthetic, and interventional procedures involving the infratemporal fossa (ITF). These variations can increase the risk of hemorrhage, nerve injury, or [...] Read more.

Background/Objectives: Variations in the course of the maxillary artery (MA) relative to the lateral pterygoid muscle (LPM) pose critical challenges in surgical, anesthetic, and interventional procedures involving the infratemporal fossa (ITF). These variations can increase the risk of hemorrhage, nerve injury, or incomplete anesthesia. The present study aimed to elucidate the topographic relationship between the MA and LPM by combining high-resolution radiological imaging with a comprehensive analysis of anatomical literature. Materials and Methods: A retrospective review of 250 brain computed tomography angiographies (CTAs), totaling 500 sides, was conducted to classify the MA course as lateral (superficial), medial (deep), or intramuscular. Additionally, a systematic review and meta-analysis of 32 eligible studies—including 5938 arteries—was performed following PRISMA 2020 and Evidence-Based Anatomy (EBA) guidelines. Study quality and risk of bias were assessed using the Anatomical Quality Assurance (AQUA) tool. Results: In the imaging cohort, the MA coursed lateral to the LPM in 64.2% of sides, medial in 29.6%, and through the muscle fibers in 6.2%. A rare temporalis-traversing variant was identified in 3.0% of cases. Bilateral symmetry was observed in 77.6% of patients. Meta-analytic findings indicated a pooled prevalence of 79.6% for the lateral course, 19.9% for the medial course, and 0.01% for the intramuscular course. Cadaveric studies and Asian populations showed a higher incidence of lateral variants, while imaging-based studies more frequently detected medial and transmuscular paths. Conclusion: While the MA most often follows a lateral course relative to the LPM, clinically significant variation—including medial, intramuscular, and temporalis-traversing routes—exists. These variants complicate access during maxillofacial surgery, TMJ procedures, and regional anesthesia. Findings emphasize the importance of individualized preoperative vascular mapping to improve procedural safety and outcomes in the ITF. Full article

(This article belongs to the Special Issue The Aesthetic Face of Orthognathic Surgery)

16 pages, 2346 KiB

Open AccessArticle

A Genome-Wide Association Study of Anti-Müllerian Hormone (AMH) Levels in Samoan Women

by Zeynep Erdogan-Yildirim, Jenna C. Carlson, Mohanraj Krishnan, Jerry Z. Zhang, Geralyn Lambert-Messerlian, Take Naseri, Satupaitea Viali, Nicola L. Hawley, Stephen T. McGarvey, Daniel E. Weeks and Ryan L. Minster

Genes 2025, 16(7), 793; https://doi.org/10.3390/genes16070793 (registering DOI) - 30 Jun 2025

Abstract

Background/Objectives:The anti-Müllerian hormone (AMH) is a key biomarker of the ovarian reserve, correlating with ovarian follicle count, fertility outcomes, and menopause timing. Understanding its genetic determinants has broad implications for female reproductive health. However, prior genome-wide association studies (GWASs) have focused exclusively [...] Read more.

Background/Objectives:The anti-Müllerian hormone (AMH) is a key biomarker of the ovarian reserve, correlating with ovarian follicle count, fertility outcomes, and menopause timing. Understanding its genetic determinants has broad implications for female reproductive health. However, prior genome-wide association studies (GWASs) have focused exclusively on women of European ancestry, limiting insights into diverse populations. Methods: We conducted a GWAS to identify genetic loci associated with circulating AMH levels in a sample of 1185 Samoan women from two independently recruited samples. Using a Cox mixed-effects model we accounted for AMH levels below detectable limits and meta-analysed the summary statistics using a fixed-effect model. To prioritize variants and genes, we used FUMA and performed colocalization and transcriptome-wide association analysis (TWAS). We also assessed whether any previously reported loci were replicated in our GWAS. Results: We identified eleven genome-wide suggestive loci, with the strongest signal at ARID3A (19-946163-G-C; p = 2.32 × 10⁻⁷) and replicated rs10093345 near EIF4EBP1. The gene-based testing revealed ARID3A and R3HDM4 as significant genes. Integrating GWAS results with expression quantitative trait loci via TWAS, we detected seven transcriptome-wide significant genes. The lead variant in ARID3A is in high linkage disequilibrium (r² = 0.79) with the known age-at-menopause variant 19-950694-G-A. Nearby KISS1R is a biologically plausible candidate gene that encodes the kisspeptin receptor, a regulator of ovarian follicle development linked to AMH levels. Conclusions: This study expands our understandings of AMH genetics by focusing on Samoan women. While these findings may be particularly relevant to Pacific Islanders, they hold broader implications for reproductive phenotypes such as the ovarian reserve, menopause timing, and polycystic ovary syndrome. Full article

(This article belongs to the Section Human Genomics and Genetic Diseases)

19 pages, 1169 KiB

Open AccessArticle

Research on the Characteristics and Influencing Factors of Spatial Integration of Resource-Based Coal Cities—A Case Study of the Central Urban Area of Huaibei

by Yawei Hou, Jiang Chang, Ya Yang and Yuan Yao

Sustainability 2025, 17(13), 6024; https://doi.org/10.3390/su17136024 (registering DOI) - 30 Jun 2025

Abstract

Background: The integration of mining and urban spaces in coal-resource-based cities holds significant implications for urban transformation and sustainable development. However, existing research lacks an in-depth analysis of its characteristics and driving factors. Methods: This study takes the central urban area of Huaibei [...] Read more.

Background: The integration of mining and urban spaces in coal-resource-based cities holds significant implications for urban transformation and sustainable development. However, existing research lacks an in-depth analysis of its characteristics and driving factors. Methods: This study takes the central urban area of Huaibei City as a case, utilizing historical documents, POI data, and spatial analysis methods to explore the evolution patterns and influencing factors of mining–urban spatial integration. Standard deviation ellipse analysis was employed to examine historical spatial changes, while a binary logistic regression model and principal component analysis were constructed based on 300 m × 300 m grid units to assess the roles of 11 factors, including location, transportation, commerce, and natural environment. Results: The results indicate that mining–urban spatial integration exhibits characteristics of lag, clustering, transportation dominance, and continuity. Commercial activity density, particularly leisure, dining, and shopping facilities, serves as a core driving factor. Road network density, along with the areas of educational and residential zones, positively promotes integration, whereas water surface areas (such as subsidence zones) significantly inhibit it. Among high-integration areas, Xiangshan District stands as the most economically prosperous city center; Lieshan–Yangzhuang mining area blends traditional and modern elements; and Zhuzhuang–Zhangzhuang mining area reflects the industrial landscape post-transformation. Conclusions: The study reveals diverse integration patterns under the synergistic effects of multiple factors, providing a scientific basis for optimizing spatial layouts and coordinating mining–urban development in coal-resource-based cities. Future research should continue to pay attention to the dynamic changes of spatial integration of mining cities, explore more effective integrated development models, and promote the rational and efficient use of urban space and the sustainable development of cities. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Resources and Sustainable Utilization)

20 pages, 3646 KiB

Open AccessArticle

A Meta-Learner Based on the Combination of Stacking Ensembles and a Mixture of Experts for Balancing Action Unit Recognition

by Andrew Sumsion and Dah-Jye Lee

Electronics 2025, 14(13), 2665; https://doi.org/10.3390/electronics14132665 (registering DOI) - 30 Jun 2025

Abstract

Facial action units (AUs) are used throughout animation, clinical settings, and robotics. AU recognition usually works better for these downstream tasks when it achieves high performance across all AUs. Current facial AU recognition approaches tend to perform unevenly across all AUs. Among other [...] Read more.

Facial action units (AUs) are used throughout animation, clinical settings, and robotics. AU recognition usually works better for these downstream tasks when it achieves high performance across all AUs. Current facial AU recognition approaches tend to perform unevenly across all AUs. Among other potential reasons, one cause is their focus on improving the overall average F1 score, where good performance on a small number of AUs increases the overall average F1 score even with poor performance on other AUs. Building on our previous success, which achieved the highest average F1 score, this work focuses on improving its performance across all AUs to address this challenge. We propose a mixture of experts as the meta-learner to combine the outputs of an explicit stacking ensemble. For our ensemble, we use a heterogeneous, negative correlation, explicit stacking ensemble. We introduce an additional measurement called Borda ranking to better evaluate the overall performance across all AUs. As indicated by this additional metric, our method not only maintains the best overall average F1 score but also achieves the highest performance across all AUs on the BP4D and DISFA datasets. We also release a synthetic dataset as additional training data, the first with balanced AU labels. Full article

(This article belongs to the Special Issue Advancements in Artificial Intelligence (AI) for Engineering Applications)

19 pages, 580 KiB

Open AccessArticle

Fault Detection System for Smart City Distribution Networks: A Long Short-Term Memory-Based Approach

by A. Herrada, C. Orozco-Henao, Juan Diego Pulgarín Rivera, J. Mora-Flórez and J. Marín-Quintero

Energies 2025, 18(13), 3453; https://doi.org/10.3390/en18133453 (registering DOI) - 30 Jun 2025

Abstract

One of the primary goals of smart cities is to enhance the welfare and comfort of their citizens. In this context, minimizing the time required to detect fault events becomes a crucial factor in improving the reliability of distribution networks. Fault detection presents [...] Read more.

One of the primary goals of smart cities is to enhance the welfare and comfort of their citizens. In this context, minimizing the time required to detect fault events becomes a crucial factor in improving the reliability of distribution networks. Fault detection presents a notable challenge in the operation of Smart City Distribution Networks (SCDN) due to complex operating conditions, such as changes in the network topology, the connection and disconnection of distributed energy resources (DERs), and varying microgrid operation modes, all of which can impact the reliability of protection systems. To address these challenges, this paper proposes a fault detection system based on Long Short-Term Memory (LSTM), leveraging instantaneous local current measurements. This approach eliminates the need for voltage signals, synchronization processes, and communication systems for fault detection. On the other hand, LSTM methods enable the implicit extraction of features from current signals and classifies normal operation and fault events through a binary classification formulation. The proposed fault detector was validated on several intelligent electronic devices (IED) deployed in the modified IEEE 34-node test system. The obtained results demonstrate that the proposed detector achieves a 90% accuracy in identifying faults using instantaneous current values as short as 1/4 of a cycle. The results obtained and its easy implementation indicate potential for real-life applications. Full article

(This article belongs to the Section F: Electrical Engineering)

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24 pages, 688 KiB

Open AccessReview

A Review of the Diagnostic Approaches for the Detection of Antimicrobial Resistance, Including the Role of Biosensors in Detecting Carbapenem Resistance Genes

by Kaily Kao and Evangelyn C. Alocilja

Genes 2025, 16(7), 794; https://doi.org/10.3390/genes16070794 (registering DOI) - 30 Jun 2025

Abstract

Antimicrobial resistance (AMR) is a rapidly growing global concern resulting from the overuse of antibiotics in both agricultural and clinical settings, the lack of surveillance for resistant bacteria, and the low quality of some available antimicrobial agents. Resistant pathogens are no longer susceptible [...] Read more.

Antimicrobial resistance (AMR) is a rapidly growing global concern resulting from the overuse of antibiotics in both agricultural and clinical settings, the lack of surveillance for resistant bacteria, and the low quality of some available antimicrobial agents. Resistant pathogens are no longer susceptible to common clinical antimicrobials, which decreases the effectiveness of medicines used to treat infections caused by these organisms. Carbapenems are an important class of antibiotics due to their broad-spectrum effectiveness in treating infections caused by Gram-positive and Gram-negative organisms. Carbapenem-resistant bacteria have been found not only in healthcare but also in the environment and food supply chain, where they have the potential to spread to pathogens and infect humans and animals. Current methods of detecting AMR genes are expensive and time-consuming. While these methods, like polymerase chain reactions or whole-genome sequencing, are considered the “gold standard” for diagnostics, the development of inexpensive, rapid diagnostic assays is necessary for effective AMR detection and management. Biosensors have shown potential for success in diagnostic testing due to their ease of use, inexpensive materials, rapid results, and portable nature. Biosensors can be combined with nanomaterials to produce sensitive and easily interpretable results. This review presents an overview of carbapenem resistance, current and emerging detection methods of antimicrobial resistance, and the application of biosensors for rapid diagnostic testing for bacterial resistance. Full article

(This article belongs to the Special Issue Mobile Genetic Elements and Microbial Multidrug Resistance)

23 pages, 4615 KiB

Open AccessReview

Ductile–Brittle Transition Mechanism and Dilute Solution Softening Effect of Body-Centered Cubic Metals

by Jie Zhang, Tianliang Zhao, Tingping Hou, Yan Li and Kaiming Wu

Metals 2025, 15(7), 743; https://doi.org/10.3390/met15070743 (registering DOI) - 30 Jun 2025

Abstract

Body-centered cubic (BCC) metals, extensively utilized in low-alloy high-strength steels and heat-resistant alloys, exhibit a pronounced ductile–brittle transition (DBT) at cryogenic temperatures, marked by a well-defined yet narrow ductile–brittle transition temperature (DBTT) window. This paper overviews the research progress regarding the DBT mechanism [...] Read more.

Body-centered cubic (BCC) metals, extensively utilized in low-alloy high-strength steels and heat-resistant alloys, exhibit a pronounced ductile–brittle transition (DBT) at cryogenic temperatures, marked by a well-defined yet narrow ductile–brittle transition temperature (DBTT) window. This paper overviews the research progress regarding the DBT mechanism of BCC metals. This mechanism was recently found to be related to the mobility of screw dislocation relative to edge dislocation, a decrease in which can induce a critical drop in the proliferation efficiency of dislocation sources. Furthermore, this paper summarizes the current research on the dilute solution softening effect of BCC metals, which has been frequently observed and studied in refractory alloys. The mechanism of this effect involves the low-temperature mobility of screw dislocations that could be promoted by specific solute atoms through kink pair nucleation. This offers a potential strategy for reducing the DBTT of low-alloy steels using a dilute solution, namely microalloying in metallurgy. However, the current understanding of the relationship between the macroscopic ductility of BCC alloys and the dilute solution softening effect is limited. This review aimed to draw attention to this relationship and strengthen related research. Full article

(This article belongs to the Special Issue Recent Insights into Mechanical Properties of Metallic Alloys)

15 pages, 698 KiB

Open AccessArticle

Basic Research on the Adsorption Capacity and Enhancement of Bamboo Charcoal for the Prevention of Nitrate Groundwater Pollution

by Nur Maisarah Mohamad Sarbani, Hiroyuki Harada, Mitsuru Aoyagi, Jun Nishimoto and Seiichiro Yonemura

Water 2025, 17(13), 1979; https://doi.org/10.3390/w17131979 (registering DOI) - 30 Jun 2025

Abstract

Pollution of soil and groundwater by chemical fertilizers is an alarming environmental problem. Both bamboo powder and charcoal are known to adsorb nitrates. This study aimed to recommend an effective method by applying a mixture of chemical fertilizers and bamboo charcoal to soil [...] Read more.

Pollution of soil and groundwater by chemical fertilizers is an alarming environmental problem. Both bamboo powder and charcoal are known to adsorb nitrates. This study aimed to recommend an effective method by applying a mixture of chemical fertilizers and bamboo charcoal to soil to prevent NO₃ leaching through adsorption. Magnesium treatment and hydrogelation were investigated to increase the amount of NO₃ adsorption and improve handling properties, and subsequently, their behavior in soil was examined. The maximum adsorption of nitrate in bamboo charcoal powder (BC) with a particle size of 15 µm or less was 4.44 mg/g. When the BC was treated with magnesium chloride (Mg-BC), the maximum adsorption capacity was 99.09 mg/g. The Langmuir adsorption model fits well for both BC and Mg-BC. When Mg-BC was hydrogelized (Gel-Mg-BC), the Freundlich equation provided a better fit, with the maximum adsorption estimated at 25–30 mg/g. When the soil was mixed with Mg-BC hydrogel and treated with a nitric acid solution, the nitrate concentration in the leachate decreased by approximately 15–60% (depending on the feed concentration) compared to that in the leachate from the soil alone. Full article

(This article belongs to the Special Issue Adsorption Technologies in Wastewater Treatment Processes)

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