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17 pages, 1275 KiB

Open AccessTechnical Note

Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB

by Francesco Paciolla, Giovanni Popeo, Alessia Farella and Simone Pascuzzi

Remote Sens. 2025, 17(15), 2746; https://doi.org/10.3390/rs17152746 (registering DOI) - 7 Aug 2025

Thermal cameras are becoming popular in several applications of precision agriculture, including crop and soil monitoring, for efficient irrigation scheduling, crop maturity, and yield mapping. Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, [...] Read more.

Thermal cameras are becoming popular in several applications of precision agriculture, including crop and soil monitoring, for efficient irrigation scheduling, crop maturity, and yield mapping. Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, to deeply understand the variability of crop and soil conditions. However, few commercial software programs, such as PIX4D Mapper, can process thermal images, and their functionalities are very limited. This paper reports on the implementation of a custom MATLAB^® R2024a script to extract agronomic information from thermal orthomosaics obtained from images acquired by the DJI Mavic 3T drone. This approach enables us to evaluate the temperature at each point of an orthomosaic, create regions of interest, calculate basic statistics of spatial temperature distribution, and compute the Crop Water Stress Index. In the authors’ opinion, the reported approach can be easily replicated and can serve as a valuable tool for scientists who work with thermal images in the agricultural sector. Full article

12 pages, 2038 KiB

Open AccessCommunication

Total Synthesis of Surfactant-Mimetic Nanocolloids via Regioselective Silica Deposition on Bottlebrush Polymers

by Junyi Zeng, Linlin Li, Li Ai, Kai Song, Heng Zhai and Chenglin Yi

Appl. Sci. 2025, 15(15), 8766; https://doi.org/10.3390/app15158766 (registering DOI) - 7 Aug 2025

Abstract

Molecular-mimetic nanocolloids (MMNCs) are promising for advanced materials, yet self-assembly fabrication faces challenges in purity and programmability. We report a total synthesis strategy for surfactant-mimetic nanocolloids (SMNCs), an amphiphilic MMNC subclass. SMNCs consist of a ~5 nm silica nanoparticle head and a bottlebrush [...] Read more.

Molecular-mimetic nanocolloids (MMNCs) are promising for advanced materials, yet self-assembly fabrication faces challenges in purity and programmability. We report a total synthesis strategy for surfactant-mimetic nanocolloids (SMNCs), an amphiphilic MMNC subclass. SMNCs consist of a ~5 nm silica nanoparticle head and a bottlebrush polymer tail. Regioselective silica deposition on linear-block-brush polymers via the modified sol–gel method enables precise control. This strategy is versatile and can be adapted to synthesize other MMNCs with different components. It offers a more controlled alternative to self-assembly methods, advancing MMNC synthesis and enabling their broader use in emerging technologies. Full article

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35 pages, 21105 KiB

Open AccessReview

A Review: The Beauty of Serendipity Between Integrated Circuit Security and Artificial Intelligence

by Chen Dong, Decheng Qiu, Bolun Li, Yang Yang, Chenxi Lyu, Dong Cheng, Hao Zhang and Zhenyi Chen

Sensors 2025, 25(15), 4880; https://doi.org/10.3390/s25154880 (registering DOI) - 7 Aug 2025

Abstract

Integrated circuits are the core of a cyber-physical system, where tens of billions of components are integrated into a tiny silicon chip to conduct complex functions. To maximize utilities, the design and manufacturing life cycle of integrated circuits rely on numerous untrustworthy third [...] Read more.

Integrated circuits are the core of a cyber-physical system, where tens of billions of components are integrated into a tiny silicon chip to conduct complex functions. To maximize utilities, the design and manufacturing life cycle of integrated circuits rely on numerous untrustworthy third parties, forming a global supply chain model. At the same time, this model produces unpredictable and catastrophic issues, threatening the security of individuals and countries. As for guaranteeing the security of ultra-highly integrated chips, detecting slight abnormalities caused by malicious behavior in the current and voltage is challenging, as is achieving computability within a reasonable time and obtaining a golden reference chip; however, artificial intelligence can make everything possible. For the first time, this paper presents a systematic review of artificial-intelligence-based integrated circuit security approaches, focusing on the latest attack and defense strategies. First, the security threats of integrated circuits are analyzed. For one of several key threats to integrated circuits, hardware Trojans, existing attack models are divided into several categories and discussed in detail. Then, for summarizing and comparing the numerous existing artificial-intelligence-based defense strategies, traditional and advanced artificial-intelligence-based approaches are listed. Finally, open issues on artificial-intelligence-based integrated circuit security are discussed from three perspectives: in-depth exploration of hardware Trojans, combination of artificial intelligence, and security strategies involving the entire life cycle. Based on the rapid development of artificial intelligence and the initial successful combination with integrated circuit security, this paper offers a glimpse into their intriguing intersection, aiming to draw greater attention to these issues. Full article

(This article belongs to the Collection Integrated Circuits and Systems for Smart Sensor Applications)

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36 pages, 3675 KiB

Open AccessArticle

A Biodiversity Hotspot for European Invertebrates of Community Importance (Natura 2000), Bârnova-Repedea Forest in Romania (ROSCI0135)

by Irinel Eugen Popescu and Irina Neta Gostin

Conservation 2025, 5(3), 41; https://doi.org/10.3390/conservation5030041 (registering DOI) - 7 Aug 2025

Abstract

ROSCI0135 Bârnova-Repedea Forest, covering 12,236.20 ha, is a relatively large Natura 2000 site from Romania, though not as large as other Natura 2000 sites. However, in terms of the number of invertebrate species of community importance, with 18 species present, Bârnova Forest ranks [...] Read more.

ROSCI0135 Bârnova-Repedea Forest, covering 12,236.20 ha, is a relatively large Natura 2000 site from Romania, though not as large as other Natura 2000 sites. However, in terms of the number of invertebrate species of community importance, with 18 species present, Bârnova Forest ranks as the fourth richest site in Romania, with the following species: Helix pomatia, Cordulegaster heros, Coenagrion ornatum, Paracaloptenus caloptenoides, Carabus variolosus, Rhysodes sulcatus, Cucujus cinnaberinus, Rosalia alpina, Morimus funereus, Cerambyx cerdo, Lucanus cervus, Bolbelasmus unicornis, Osmoderma barnabita (eremita), Parnassius mnemosyne, Zerynthia polyxena, Euphydryas maturna, Lycaena dispar, and Euplagia quadripunctaria. Bârnova-Repedea Forest can be considered a true mosaic of habitats, providing favourable conditions for the existence of these rare Natura 2000 species. The threats to the site are complex and challenging to manage. Full article

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20 pages, 1737 KiB

Open AccessReview

A Systematic Review on Assistive Technology Terminologies, Concepts, and Definitions

by Jordam Wilson Lourenço, Paulo Alexandre Correia de Jesus, Franciele Lourenço, Osiris Canciglieri Junior and Jones Luís Schaefer

Technologies 2025, 13(8), 349; https://doi.org/10.3390/technologies13080349 (registering DOI) - 7 Aug 2025

Abstract

This study examines the diversity of terminologies associated with assistive technology (AT), a crucial field that promotes autonomy and inclusion for people with disabilities. Although the wide use of assistive technology is observed in the literature, a variety of terms are often used [...] Read more.

This study examines the diversity of terminologies associated with assistive technology (AT), a crucial field that promotes autonomy and inclusion for people with disabilities. Although the wide use of assistive technology is observed in the literature, a variety of terms are often used interchangeably, which hinders research, technological development, and the formulation of public policies. In this sense, this systematic review aimed to identify, categorise, and analyse the diversity of terms used to describe AT in the scientific literature, contributing to greater conceptual clarity and supporting structured and interdisciplinary development in the field. A comprehensive search was conducted in July 2024 across the Scopus, Web of Science, and PubMed databases, covering publications from 1989 to 2024. Eligible studies were peer-reviewed journal articles in English that conceptually defined at least one AT-related term. The selection process followed the PRISMA 2020 guidelines and included studies from Q1 and Q2 journals to ensure academic rigour. A total of 117 studies were included out of 11,941 initial records. Sixteen distinct terms were identified and grouped into five clusters based on semantic and functional similarities: Cluster 1—Technologies for assistance and inclusion. Cluster 2—Functional assistive devices. Cluster 3—Assistive interaction interfaces. Cluster 4—Assistive environmental technologies. Cluster 5—Assistive systems. A complementary meta-analysis revealed geographic and temporal trends, indicating that terms such as “assistive technology” and “assistive device” are globally dominant. In contrast, others, like “enabling technology,” are more context-specific and emerging. The findings contribute theoretically by providing a structured framework for understanding AT terminology and practically by supporting the design of public policy and interdisciplinary communication. Full article

(This article belongs to the Special Issue Innovations in Design, Development and Evaluation of Assistive Technologies)

25 pages, 409 KiB

Open AccessArticle

Development of a Course to Prepare Nurses to Train Expert Patients

by Manacés Dos Santos-Becerril, Francisca Sánchez-Ayllón, Isabel Morales-Moreno, Flavia Barreto-Tavares-Chiavone, Isabelle Campos-de Acevedo, Ana Luisa Petersen-Cogo, Marcos Antônio Ferreira-Junior and Viviane Euzebia Pereira Santos

Healthcare 2025, 13(15), 1939; https://doi.org/10.3390/healthcare13151939 (registering DOI) - 7 Aug 2025

Abstract

Introduction: With the emergence of the expert patient and the expansion of health literacy, the importance of planning and building health technologies aimed at teaching and training health professionals, especially nurses, due to their activities with patients in Primary Health Care, with the [...] Read more.

Introduction: With the emergence of the expert patient and the expansion of health literacy, the importance of planning and building health technologies aimed at teaching and training health professionals, especially nurses, due to their activities with patients in Primary Health Care, with the aim of meeting the real and constant demands of the expert patient, is evident. Methods: Methodological study with a quantitative approach. The course was constructed based on a scope review, scientific reference, and observational visits during the months of September 2021 and August 2022. For validation, an organized electronic form was used with general information about the research and items of the course constructed for later evaluation by the judges with the three-point Likert scale and with the application of the Delphi Technique between the months of September and October 2022; for the agreement of the judges, the Content Validation Coefficient > 0.8 was considered. Results: Based on the content selected in the scope review, the reference contribution, and the observational visits, the course was constructed. Nine judges participated in the validation stage in Delphi I with a total Content Validation Coefficient above 0.90 and with some suggestions for modifications and improvements pointed out by them. In Delphi II, six judges evaluated the course, resulting in a total Content Validation Coefficient of 0.99. Conclusions: The course developed was considered valid to support the training of Primary Health Care nurses in the formation of the expert patient, with a view to promoting patient autonomy in self-care management, optimizing Primary Health Care, and reducing unnecessary hospital admissions. Full article

(This article belongs to the Special Issue Nursing, Coaching, Oncology and Chronic Diseases: Future Insights and Perspectives)

20 pages, 4589 KiB

Open AccessArticle

Loss of SPRED3 Causes Primary Hypothyroidism and Alters Thyroidal Expression of Autophagy Regulators LC3, p62, and ATG5 in Mice

by Celine Dogan, Luisa Haas, Rebecca Holzapfel, Franziska Schmitt, Denis Hepbasli, Melanie Ullrich, Michael R. Bösl, Marco Abeßer, Kai Schuh and Sina Gredy

Int. J. Mol. Sci. 2025, 26(15), 7660; https://doi.org/10.3390/ijms26157660 (registering DOI) - 7 Aug 2025

Abstract

Sprouty-related proteins with enabled/vasodilator-stimulated phosphoprotein homology 1 (EVH1) domain (SPREDs) are negative regulators of the Ras/MAPK signaling pathway and are known to modulate developmental and endocrine processes. While the roles of SPRED1 and SPRED2 are increasingly understood, the physiological relevance of SPRED3 remains [...] Read more.

Sprouty-related proteins with enabled/vasodilator-stimulated phosphoprotein homology 1 (EVH1) domain (SPREDs) are negative regulators of the Ras/MAPK signaling pathway and are known to modulate developmental and endocrine processes. While the roles of SPRED1 and SPRED2 are increasingly understood, the physiological relevance of SPRED3 remains elusive. To elucidate its function, we generated SPRED3 knockout (KO) mice and performed phenotypic, molecular, and hormonal analyses. SPRED3-deficient mice exhibited growth retardation and a non-Mendelian genotype distribution. X-Gal staining revealed Spred3 promoter activity in the thyroid, adrenal gland, pituitary, cerebral cortex, and kidney. Hormonal profiling identified elevated thyroid-stimulating hormone (TSH) and reduced thyroxine (T₄) levels, indicating primary hypothyroidism. Thyroidal extracellular signal-regulated kinase (ERK) signaling was mildly reduced in SPRED3 KO mice, and immunoblotting revealed altered expression of autophagy regulators, including reduced sequestosome 1 (p62), increased autophagy-related gene 5 (ATG5), as well as an elevated microtubule-associated protein 1 light chain 3 (LC3) II/I ratio and a decreased pBeclin/Beclin ratio in SPRED3 KO mice. Our findings indicate that SPRED3 is involved in thyroidal homeostasis and plays a regulatory role in autophagy processes within the thyroid gland. Full article

(This article belongs to the Special Issue Transgenic Mice in Human Diseases: Insights from Molecular Research (5th Edition))

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14 pages, 1993 KiB

Open AccessArticle

Supplementation of Calcium Through Seed Enrichment Technique Enhances Germinability and Early Growth of Timothy (Phleum pratense L.) Under Salinity Conditions

by Masahiro Akimoto and Li Ma

Agronomy 2025, 15(8), 1905; https://doi.org/10.3390/agronomy15081905 (registering DOI) - 7 Aug 2025

Abstract

Calcium ameliorates salt-related growth defects in plants. The objective of this study was to determine whether supplying calcium through a seed enrichment technique enhances the germinability and early growth of timothy (Phleum pratense L.) under saline conditions. For seed enrichment, timothy seeds [...] Read more.

Calcium ameliorates salt-related growth defects in plants. The objective of this study was to determine whether supplying calcium through a seed enrichment technique enhances the germinability and early growth of timothy (Phleum pratense L.) under saline conditions. For seed enrichment, timothy seeds were soaked in CaCl₂ solutions at concentrations of 50 mM or 100 mM for 24 h at room temperature. Seeds treated with distilled water served as the control. Under distilled water conditions, germination rates among the seeds showed minimal variation, approximately 95% on average. However, in a 200 mM NaCl environment, the germination rate of the control seeds significantly decreased to 25%, while the germination rates of the Ca-enriched seeds remained high, exceeding 86%. Additionally, the Ca-enriched seeds germinated more quickly than the control seeds. When plants were grown with distilled water, the total dry matter weights did not differ significantly among the treatment types. However, under salt stress with 100 mM NaCl, the plants derived from Ca-enriched seeds thrived and exhibited higher dry matter weights compared to the control plants. The Ca-enriched seeds contained more soluble sugars and demonstrated higher catalase activity than the control seeds, and their corresponding plants accumulated less sodium under salt stress compared to the control plants. Seed enrichment is an effective technique for supplying calcium to timothy, and a concentration of 50 mM of CaCl₂ in the treatment solution is sufficient to achieve salt tolerance. Full article

(This article belongs to the Special Issue Responses of Forage Crops to Environmental Stresses and Stress Alleviating Strategies)

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17 pages, 1001 KiB

Open AccessArticle

A Preliminary Evaluation of the Use of Solid Residues from the Distillation of Medicinal and Aromatic Plants as Fertilizers in Mediterranean Soils

by Anastasia-Garyfallia Karagianni, Anastasia Paraschou and Theodora Matsi

Agronomy 2025, 15(8), 1903; https://doi.org/10.3390/agronomy15081903 (registering DOI) - 7 Aug 2025

Abstract

The current study focuses on a preliminary evaluation of the use of solid residues produced from the distillation of selected medicinal and aromatic plants (MAP) as fertilizers for alkaline soils. Specifically, the residues of hemp (Cannabis sativa L.), helichrysum (Helichrysum Italicum [...] Read more.

The current study focuses on a preliminary evaluation of the use of solid residues produced from the distillation of selected medicinal and aromatic plants (MAP) as fertilizers for alkaline soils. Specifically, the residues of hemp (Cannabis sativa L.), helichrysum (Helichrysum Italicum (Roth) G. Don), lavender (Lavandula angustifolia Mill.), oregano (Origanum vulgare L.), rosemary (Rosmarinus officinalis L.) and sage (Salvia officinalis L.) were added in an alkaline and calcareous soil at the rates of 0 (control), 1, 2, 4 and 8%, in three replications (treatments), and the treated soils were analyzed. The results showed that upon application of the residues, soil electrical conductivity (EC), organic C, total N and the C/N ratio significantly increased, especially at the 4 and 8% rates. The same was found for soil available P, K, B, Cu and Mn. The effects of the residues on soil pH, cation exchange capacity (CEC) and available Zn and Fe were rather inconclusive, whereas soil available N significantly decreased, which was somewhat unexpected. From the different application rates tested, it seems that all residues could improve soil fertility (except N?) when they were applied to soil at rates of 2% and above, without exceeding the 8% rate. The reasons for the latter statement are soil EC and available Mn: the doubling of EC upon application of the residues and the excessive increase in soil available Mn in treatments with 8% residues raise concerns of soil salinization and Mn phytotoxicity risks, respectively. This work provides the first step towards the potential agronomic use of solid residues from MAP distillation in alkaline soils. However, for the establishment of such a perspective, further research is needed in respect to the effect of residues on plant growth and soil properties, by means of at least pot experiments. Based on the results of the current study, the undesirable effect of residues on soil available N should be investigated in depth, since N is the most important essential element for plant growth, and possible risks of micronutrient phytotoxicities should also be studied. In addition, application rates between 2 and 4% should be studied extensively in order to recommend optimum application rates of residues to producers. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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11 pages, 638 KiB

Open AccessCommunication

Millet in Bioregenerative Life Support Systems: Hypergravity Resilience and Predictive Yield Models

by Tatiana S. Aniskina, Arkady N. Kudritsky, Olga A. Shchuklina, Nikita E. Andreev and Ekaterina N. Baranova

Life 2025, 15(8), 1261; https://doi.org/10.3390/life15081261 (registering DOI) - 7 Aug 2025

Abstract

The prospects for long-distance space flights are becoming increasingly realistic, and one of the key factors for their implementation is the creation of sustainable systems for producing food on site. Therefore, the aim of our work is to assess the prospects for using [...] Read more.

The prospects for long-distance space flights are becoming increasingly realistic, and one of the key factors for their implementation is the creation of sustainable systems for producing food on site. Therefore, the aim of our work is to assess the prospects for using millet in biological life support systems and to create predictive models of yield components for automating plant cultivation control. The study found that stress from hypergravity (800 g, 1200 g, 2000 g, and 3000 g) in the early stages of millet germination does not affect seedlings or yield. In a closed system, millet yield reached 0.31 kg/m², the weight of 1000 seeds was 8.61 g, and the yield index was 0.06. The paper describes 40 quantitative traits, including six leaf and trichome traits and nine grain traits from the lower, middle and upper parts of the inflorescence. The compiled predictive regression equations allow predicting the accumulation of biomass in seedlings on the 10th and 20th days of cultivation, as well as the weight of 1000 seeds, the number of productive inflorescences, the total above-ground mass, and the number and weight of grains per plant. These equations open up opportunities for the development of computer vision and high-speed plant phenotyping programs that will allow automatic correction of the plant cultivation process and modeling of the required yield. Predicting biomass yield will also be useful in assessing the load on the waste-free processing system for plant waste at planetary stations. Full article

(This article belongs to the Special Issue Physiological Responses of Plants Under Abiotic Stresses)

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52 pages, 7563 KiB

Open AccessArticle

Design and Evaluation of a Inonotus obliquus–AgNP–Maltodextrin Delivery System: Antioxidant, Antimicrobial, Acetylcholinesterase Inhibitory and Cytotoxic Potential

by Ana-Maria Stanoiu, Cornelia Bejenaru, Adina-Elena Segneanu, Gabriela Vlase, Ionela Amalia Bradu, Titus Vlase, George Dan Mogoşanu, Maria Viorica Ciocîlteu, Andrei Biţă, Roxana Kostici, Dumitru-Daniel Herea and Ludovic Everard Bejenaru

Polymers 2025, 17(15), 2163; https://doi.org/10.3390/polym17152163 (registering DOI) - 7 Aug 2025

Abstract

Inonotus obliquus, a medicinal mushroom valued for its bioactive compounds, has not been previously characterized from Romanian sources. This study presents the first comprehensive chemical and biological screening of I. obliquus, introducing novel polymer-based encapsulation systems to enhance the stability and [...] Read more.

Inonotus obliquus, a medicinal mushroom valued for its bioactive compounds, has not been previously characterized from Romanian sources. This study presents the first comprehensive chemical and biological screening of I. obliquus, introducing novel polymer-based encapsulation systems to enhance the stability and bioavailability of its bioactive constituents. Two distinct delivery systems were designed to enhance the functionality of I. obliquus extracts: (i) microencapsulation in maltodextrin (MIO) and (ii) a sequential approach involving preparation of silver nanoparticle-loaded I. obliquus (IO–AgNPs), followed by microencapsulation to yield the hybrid MIO–AgNP system. Comprehensive metabolite profiling using GC–MS and ESI–QTOF–MS revealed 142 bioactive constituents, including terpenoids, flavonoids, phenolic acids, amino acids, coumarins, styrylpyrones, fatty acids, and phytosterols. Structural integrity and successful encapsulation were confirmed by XRD, FTIR, and SEM analyses. Both IO–AgNPs and MIO–AgNPs demonstrated potent antioxidant activity, significant acetylcholinesterase inhibition, and robust antimicrobial effects against Staphylococcus aureus, Bacillus cereus, Pseudomonas aeruginosa, and Escherichia coli. Cytotoxicity assays revealed pronounced activity against MCF-7, HCT116, and HeLa cell lines, with MIO–AgNPs exhibiting superior efficacy. The synergistic integration of maltodextrin and AgNPs enhanced compound stability and bioactivity. As the first report on Romanian I. obliquus, this study highlights its therapeutic potential and establishes polymer-based nanoencapsulation as an effective strategy for optimizing its applications in combating microbial resistance and cancer. Full article

(This article belongs to the Section Polymer Applications)

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30 pages, 1329 KiB

Open AccessArticle

The Multi-Branch Deep-Learning-Based Approach to Heart Dysfunction Classification

by Krzysztof Hryniów, Bartosz Puszkarski and Marcin Iwanowski

Appl. Sci. 2025, 15(15), 8765; https://doi.org/10.3390/app15158765 (registering DOI) - 7 Aug 2025

Abstract

Cardiovascular diseases (CVDs), which remain globally one of the most common causes of death, are usually diagnosed based on the electrocardiogram (ECG) signal. To support human experts, modern deep-learning models are used for CVD classification problems as an early warning. This article proposes [...] Read more.

Cardiovascular diseases (CVDs), which remain globally one of the most common causes of death, are usually diagnosed based on the electrocardiogram (ECG) signal. To support human experts, modern deep-learning models are used for CVD classification problems as an early warning. This article proposes a novel multi-branch architecture focused on processing various modalities of the ECG signal in parallel branches, replacing typical single-input architectures. Each branch is given separate input in the form of the raw signal, domain knowledge, the wavelet transform of the signal, or the signal with drift removed. The proposed method is based on deep-learning core models that can incorporate various modern neural networks. It was thoroughly tested on N-BEATS, LSTM, and GRU neural networks. The proposed architecture allows the retention of the speed of the neural network. At the same time, the combination of independently computed branches improves model performance, which finally exceeds the performance obtained by classical single-branch architectures. Full article

(This article belongs to the Special Issue Advances in Electrocardiogram (ECG) Signal Processing and Its Applications)

22 pages, 7483 KiB

Open AccessArticle

Preventive Diagnosis of Biological Colonization and Salt-Related Decay on the Frescoes of the “Oratorio dell’Annunziata” (Riofreddo, Latium, Italy) to Improve Conservation Plans

by Flavia Bartoli, Annalaura Casanova Municchia, Marco Tescari, Ilaria Ciccone, Paolo Rosati, Alessandro Lazzara and Maria Catrambone

Appl. Sci. 2025, 15(15), 8762; https://doi.org/10.3390/app15158762 (registering DOI) - 7 Aug 2025

Abstract

The frescoed Annunziata Oratory chapel in Riofreddo (Italy), a unique testimony to the pontificate of Martin V, sheds light on the trade routes of Ninfa in the first half of the 15th century. Despite having undergone several restorations in the past (the most [...] Read more.

The frescoed Annunziata Oratory chapel in Riofreddo (Italy), a unique testimony to the pontificate of Martin V, sheds light on the trade routes of Ninfa in the first half of the 15th century. Despite having undergone several restorations in the past (the most recent in the 2010s), the Oratory presents serious conservation issues. At first glance, there are no evident signs of biological colonization; rather, the most obvious damage is attributed to detachments and saline efflorescence. Biological colonization at several points was identified using various diagnostic field and laboratory techniques such as ATPase point analysis, field stereoscopy in visible and UV light, culture-based and molecular approaches, Raman spectroscopy, and SEM analysis, biological colonization at several points was identified. The characterization of salt efflorescence was carried out using ion chromatography analysis. The presence of bacteria, fungi and algae, which are also linked to saline efflorescence, was observed. A clear correlation between the biological colonization and salt efflorescence composition was highlighted by our results, as well as the potential sources of microorganisms and salts via the capillary rise of groundwater. This early diagnostic approach regarding the presence of lithobionts and salt efflorescence demonstrates the complex interplay between environmental factors and microbial colonization, which can lead to biodeterioration processes. Full article

(This article belongs to the Special Issue Application of Biology to Cultural Heritage III)

19 pages, 258 KiB

Open AccessArticle

Strategic Digital Change in Action: A Transferable Model for Teacher Competence Development

by Alberto A. Jiménez-Hidalgo, Linda Castañeda and María Dolores Lettelier

Educ. Sci. 2025, 15(8), 1018; https://doi.org/10.3390/educsci15081018 (registering DOI) - 7 Aug 2025

Abstract

This article presents a case of strategic and participatory institutional innovation in higher education, focused on developing teacher digital competence (TDC) as a key enabler of sustainable digital transformation. In response to the post-pandemic challenges faced by the National University of Cuyo (UNCuyo), [...] Read more.

This article presents a case of strategic and participatory institutional innovation in higher education, focused on developing teacher digital competence (TDC) as a key enabler of sustainable digital transformation. In response to the post-pandemic challenges faced by the National University of Cuyo (UNCuyo), a large and multi-campus public university in Argentina, the European CUTE methodology was adapted and implemented to align professional development with institutional planning. Grounded in the DigCompEdu framework, this action-oriented process moved beyond individual initiatives to create a coordinated, multi-level strategy involving educators, department leaders, and university authorities. Through a research-based design that included context analysis, participatory diagnosis, and co-designed interventions, the project built a shared understanding of digital teaching needs and institutional readiness. The implementation highlights how locally adapted frameworks, collaborative structures, and iterative decision-making can drive meaningful change across a complex university system. This case contributes to the international conversation on how higher education institutions can operationalize innovation at scale by investing in teacher competence, inclusive processes, and strategic alignment. Lessons learned from this experience are relevant for universities seeking to build institutional capacity for digital transformation in diverse educational contexts with potential downstream benefits for student learning and inclusion. Full article

(This article belongs to the Special Issue Higher Education Development and Technological Innovation)

24 pages, 2005 KiB

Open AccessSystematic Review

Remote Sensing for Wildfire Mapping: A Comprehensive Review of Advances, Platforms, and Algorithms

by Ruth E. Guiop-Servan, Alexander Cotrina-Sanchez, Jhoivi Puerta-Culqui, Manuel Oliva-Cruz and Elgar Barboza

Fire 2025, 8(8), 316; https://doi.org/10.3390/fire8080316 (registering DOI) - 7 Aug 2025

Abstract

The use of remote sensing technologies for mapping forest fires has experienced significant growth in recent decades, driven by advancements in remote sensors, processing platforms, and artificial intelligence algorithms. This study presents a review of 192 scientific articles published between 1990 and 2024, [...] Read more.

The use of remote sensing technologies for mapping forest fires has experienced significant growth in recent decades, driven by advancements in remote sensors, processing platforms, and artificial intelligence algorithms. This study presents a review of 192 scientific articles published between 1990 and 2024, selected using PRISMA criteria from the Scopus database. Trends in the use of active and passive sensors, spectral indices, software, and processing platforms as well as machine learning and deep learning approaches are analyzed. Bibliometric analysis reveals a concentration of publications in Northern Hemisphere countries such as the United States, Spain, and China as well as in Brazil in the Southern Hemisphere, with sustained growth since 2015. Additionally, the publishers, journals, and authors with the highest scientific output are identified. The normalized burn ratio (NBR) and the normalized difference vegetation index (NDVI) were the most frequently used indices in fire mapping, while random forest (RF) and convolutional neural networks (CNN) were prominent among the applied algorithms. Finally, the main technological and methodological limitations as well as emerging opportunities to enhance fire detection, monitoring, and prediction in various regions are discussed. This review provides a foundation for future research in remote sensing applied to fire management. Full article

(This article belongs to the Special Issue Advances in Remote Sensing for Burned Area Mapping)

25 pages, 1564 KiB

Open AccessReview

COPD and Comorbid Mental Health: Addressing Anxiety, and Depression, and Their Clinical Management

by Rayan A. Siraj

Medicina 2025, 61(8), 1426; https://doi.org/10.3390/medicina61081426 (registering DOI) - 7 Aug 2025

Abstract

Anxiety and depression are common comorbidities in patients with chronic obstructive pulmonary disease (COPD), which can contribute to increased morbidity, reduced quality of life, and worse clinical outcomes. Nevertheless, these psychological conditions remain largely overlooked. This narrative review includes studies published between 1983 [...] Read more.

Anxiety and depression are common comorbidities in patients with chronic obstructive pulmonary disease (COPD), which can contribute to increased morbidity, reduced quality of life, and worse clinical outcomes. Nevertheless, these psychological conditions remain largely overlooked. This narrative review includes studies published between 1983 and 2025 to synthesise the current evidence on the risk factors, clinical impacts, and therapeutic strategies for these comorbidities. While the exact mechanisms leading to their increased prevalence are not fully understood, growing evidence implicates a combination of biological (e.g., systemic inflammation), social (e.g., isolation and stigma), and behavioural (e.g., smoking and inactivity) factors. Despite current guidelines recommending the identification and management of these comorbidities in COPD, they are not currently included in COPD assessments. Undetected and unmanaged anxiety and depression have serious consequences, including poor self-management, non-adherence to medications, increased risk of exacerbation and hospitalisations, and even mortality; thus, there is a need to incorporate screening as part of COPD assessments. There is robust evidence showing that pulmonary rehabilitation, a core non-pharmacological intervention, can improve mood symptoms, enhance functional capacity, and foster psychosocial resilience. Psychological therapies such as cognitive behavioural therapy (CBT), mindfulness-based approaches, and supportive counselling have also demonstrated value in reducing emotional distress and improving coping mechanisms. Pharmacological therapies, particularly selective serotonin reuptake inhibitors (SSRIs) and serotonin–norepinephrine reuptake inhibitors (SNRIs), are commonly prescribed in moderate to severe cases or when non-pharmacological approaches prove inadequate. However, the evidence for their efficacy in COPD populations is mixed, with concerns about adverse respiratory outcomes and high discontinuation rates due to side effects. There are also barriers to optimal care, including underdiagnosis, a lack of screening protocols, limited provider training, stigma, and fragmented multidisciplinary coordination. A multidisciplinary, biopsychosocial approach is essential to ensure early identification, integrated care, and improved outcomes for patients with COPD. Full article

(This article belongs to the Special Issue Latest Advances in Asthma and COPD)

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13 pages, 645 KiB

Open AccessArticle

Pedagogical Qualities of Artificial Intelligence-Assisted Teaching: An Exploratory Analysis of a Personal Tutor in a Voluntary Business Higher-Education Course

by Nikša Alfirević, Marko Hell and Darko Rendulić

Appl. Sci. 2025, 15(15), 8764; https://doi.org/10.3390/app15158764 (registering DOI) - 7 Aug 2025

Abstract

There is minimal research concerning the role of custom-trained artificial intelligence (AI) tools in higher education, with a lack of research concerning the pedagogical qualities of an AI-based personal tutor. To fill this literature gap, we examined how a custom GPT personal tutor [...] Read more.

There is minimal research concerning the role of custom-trained artificial intelligence (AI) tools in higher education, with a lack of research concerning the pedagogical qualities of an AI-based personal tutor. To fill this literature gap, we examined how a custom GPT personal tutor shapes key teaching and learning qualities. Using the mixed-methods approach, we aimed to demonstrate preliminary and exploratory empirical evidence concerning the contribution of custom-trained AI tutors to building up students’ competencies. Our research analyzed the subjective assessments of students related to the GPT tutor’s contribution to improving their competencies. Both the qualitative and quantitative empirical results confirmed the positive contribution. In addition, we triangulated the results to evaluate the potential of custom-trained AI chatbots in higher education, focusing on undergraduate business courses. However, the results of this study cannot be generalized to the entire student population of business schools, since the participation in the AI-assisted tutor program was voluntary, attracting only intrinsically motivated students. Full article

(This article belongs to the Special Issue Adaptive E-Learning Technologies and Experiences)

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32 pages, 1625 KiB

Open AccessArticle

Institutional, Resource-Based, Stakeholder and Legitimacy Drivers of Green Manufacturing Adoption in Industrial Enterprises

by Lukáš Juráček, Lukáš Jurík and Helena Makyšová

Adm. Sci. 2025, 15(8), 311; https://doi.org/10.3390/admsci15080311 (registering DOI) - 7 Aug 2025

Abstract

The present paper investigates the adoption of green manufacturing approaches among industrial enterprises in Slovakia, emphasizing the interplay between institutional pressures and enterprise-level resources. Based on a survey of 88 enterprises from energy- and material-intensive sectors, the study evaluates how regional context and [...] Read more.

The present paper investigates the adoption of green manufacturing approaches among industrial enterprises in Slovakia, emphasizing the interplay between institutional pressures and enterprise-level resources. Based on a survey of 88 enterprises from energy- and material-intensive sectors, the study evaluates how regional context and enterprise size influence the adoption of green practices. Using logistic regression and the chi-squared test, the findings reveal minimal regional variation, suggesting strong isomorphic effects of harmonised European Union environmental regulations. In contrast, enterprise size significantly correlates with the adoption of complex green practices, confirming the relevance of the resource-based view. These results highlight the dominance of internal capabilities over regional factors in green transition pathways within small post-transition economies. The study contributes to cross-national theorising by showing how resource asymmetries, rather than institutional diversity, shape environmental behaviour in uniform regulatory environments. Specifically, the paper examines how institutional pressures, enterprise-level resources, stakeholders, and legitimacy influence the adoption of green manufacturing practices in Slovak industrial enterprises. The study draws on institutional theory, the resource-based view, stakeholder theory, and legitimacy theory to explore the relationship between enterprise size, regional location, and the adoption levels of green manufacturing. Full article

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18 pages, 6388 KiB

Open AccessArticle

Spatial–Temporal Hotspot Management of Photovoltaic Modules Based on Fiber Bragg Grating Sensor Arrays

by Haotian Ding, Rui Guo, Huan Xing, Yu Chen, Jiajun He, Junxian Luo, Maojie Chen, Ye Chen, Shaochun Tang and Fei Xu

Sensors 2025, 25(15), 4879; https://doi.org/10.3390/s25154879 (registering DOI) - 7 Aug 2025

Abstract

Against the backdrop of an urgent energy crisis, solar energy has attracted sufficient attention as one of the most inexhaustible and friendly types of environmental energy. Faced with long service and harsh environment, the poor performance ratios of photovoltaic arrays and safety hazards [...] Read more.

Against the backdrop of an urgent energy crisis, solar energy has attracted sufficient attention as one of the most inexhaustible and friendly types of environmental energy. Faced with long service and harsh environment, the poor performance ratios of photovoltaic arrays and safety hazards are frequently boosted worldwide. In particular, the hot spot effect plays a vital role in weakening the power generation performance and reduces the lifetime of photovoltaic (PV) modules. Here, our research reports a spatial–temporal hot spot management system integrated with fiber Bragg grating (FBG) temperature sensor arrays and cooling hydrogels. Through finite element simulations and indoor experiments in laboratory conditions, a superior cooling effect of hydrogels and photoelectric conversion efficiency improvement have been demonstrated. On this basis, field tests were carried out in which the FBG arrays detected the surface temperature of the PV module first, and then a classifier based on an optimized artificial neural network (ANN) recognized hot spots with an accuracy of 99.1%. The implementation of cooling hydrogels as a feedback mechanism achieved a 7.7 °C reduction in temperature, resulting in a 5.6% enhancement in power generation efficiency. The proposed strategy offers valuable insights for conducting predictive maintenance of PV power plants in the case of hot spots. Full article

(This article belongs to the Special Issue Advances in Fiber Optic Sensors: Innovations, Challenges and Applications)

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25 pages, 5704 KiB

Open AccessArticle

Structural and Functional Effects of the Interaction Between an Antimicrobial Peptide and Its Analogs with Model Bacterial and Erythrocyte Membranes

by Michele Lika Furuya, Gustavo Penteado Carretero, Marcelo Porto Bemquerer, Sumika Kiyota, Magali Aparecida Rodrigues, Tarcillo José de Nardi Gaziri, Norma Lucia Buritica Zuluaga, Danilo Kiyoshi Matsubara, Marcio Nardelli Wandermuren, Karin do Amaral Riske, Hernan Chaimovich, Shirley Schreier and Iolanda Midea Cuccovia

Biomolecules 2025, 15(8), 1143; https://doi.org/10.3390/biom15081143 (registering DOI) - 7 Aug 2025

Abstract

Antimicrobial peptides (AMPs) are a primary defense against pathogens. Here, we examined the interaction of two BP100 analogs, R²R⁵-BP100 (where Arg substitutes Lys 2 and 5) and R²R⁵-BP100-A-NH-C₁₆ (where an Ala and a C [...] Read more.

Antimicrobial peptides (AMPs) are a primary defense against pathogens. Here, we examined the interaction of two BP100 analogs, R²R⁵-BP100 (where Arg substitutes Lys 2 and 5) and R²R⁵-BP100-A-NH-C₁₆ (where an Ala and a C₁₆ hydrocarbon chain are added to the R²R⁵-BP100 C-terminus), with membrane models. Large unilamellar vesicles (LUVs) and giant unilamellar vesicles (GUVs) were prepared with the major lipids in Gram-positive (GP) and Gram-negative (GN) bacteria, as well as red blood cells (RBCs). Fluorescence data, dynamic light scattering (DLS), and zeta potential measurements revealed that upon achieving electroneutrality through peptide binding, vesicle aggregation occurred. Circular dichroism (CD) spectra corroborated these observations, and upon vesicle binding, the peptides acquired α-helical conformation. The peptide concentration, producing a 50% release of carboxyfluorescein (C₅₀) from LUVs, was similar for GP-LUVs. With GN and RBC-LUVs, C₅₀ decreased in the following order: BP100 > R²R⁵-BP100 > R²R⁵BP100-A-NH-C₁₆. Optical microscopy of GP-, GN-, and RBC-GUVs revealed the rupture or bursting of the two former membranes, consistent with a carpet mechanism of action. Using GUVs, we confirmed RBC aggregation by BP100 and R²R⁵-BP100. We determined the minimal inhibitory concentrations (MICs) of peptides for a GN bacterium (Escherichia coli (E. coli)) and two GP bacteria (two strains of Staphylococcus aureus (S. aureus) and one strain of Bacillus subtilis (B. subtilis)). The MICs for S. aureus were strain-dependent. These results demonstrate that Lys/Arg replacement can improve the parent peptide’s antimicrobial activity while increasing hydrophobicity renders the peptide less effective and more hemolytic. Full article

(This article belongs to the Topic Antimicrobial Agents and Nanomaterials—2nd Edition)

17 pages, 815 KiB

Open AccessArticle

The Home as a Modulator of Milk Immunity: Association Between Domestic Factors and Immune Cell Populations in Human Breast Milk

by Agata Tomaszewska, Klaudia Porębska, Alicja Jeleniewska, Katarzyna Królikowska, Agnieszka Lipińska-Opałka, Agnieszka Gościńska, Robert Zdanowski, Milena Pogonowska and Bolesław Kalicki

Nutrients 2025, 17(15), 2574; https://doi.org/10.3390/nu17152574 (registering DOI) - 7 Aug 2025

Abstract

Background/Objectives: Human breast milk is a biologically active fluid. It contains immune cells, stem cells, epithelial cells, and lactocytes. These components may support infant development and immune defense. While milk composition is known to vary with physiological and nutritional factors, the impact of [...] Read more.

Background/Objectives: Human breast milk is a biologically active fluid. It contains immune cells, stem cells, epithelial cells, and lactocytes. These components may support infant development and immune defense. While milk composition is known to vary with physiological and nutritional factors, the impact of the home environment remains poorly understood. The aim of this study was to examine how selected conditions affect the cellular composition of breast milk. Methods: We conducted a cross-sectional study involving 49 lactating mothers of healthy infants under 6 months of age. Breast milk samples were analyzed using flow cytometry. We measured proportions of immune cells (CD3⁺, CD4⁺, CD8⁺, CD19⁺, and CD16/56⁺), hematopoietic stem cells (CD34⁺), mesenchymal stem cells (CD105⁺, CD73⁺, and CD44⁺), and lactocytes (CD326⁺ CD73⁺ and CD326⁺ CD73⁻ phenotypes). Participants completed a questionnaire assessing number of children, co-sleeping, pet ownership, and number of household members. Results: Mothers with more than one child showed higher percentages of CD4⁺ (p = 0.047) and CD8⁺ (p = 0.031) T cells and fewer CD73⁺ lactocytes (p = 0.028). Co-sleeping was associated with lower levels of CD3⁺ T cells in milk (p = 0.021). Pet ownership correlated with a lower proportion of cytotoxic CD8⁺ cells (p = 0.048). The number of household members had no significant effect. Conclusions: Domestic factors such as number of children, co-sleeping, and pet exposure are associated with shifts in the immune and lactocyte cell composition of breast milk. These findings suggest that breast milk dynamically adapts to maternal and household-level immune stimuli. Full article

(This article belongs to the Special Issue The Impact of Human Milk’s Structure–Function on Early Human Health and Lifespan)

26 pages, 423 KiB

Open AccessArticle

Pro-Environmental Behavior and Attitudes Towards Recycling in Slovak Republic

by Silvia Lorincová and Mária Osvaldová

Recycling 2025, 10(4), 159; https://doi.org/10.3390/recycling10040159 (registering DOI) - 7 Aug 2025

Abstract

Climate changes have increased interest in the circular economy, an alternative model that seeks to minimize environmental impact and maximize resource reuse. A key element of this model is individuals’ behaviors and attitudes, which determine the overall efficiency of recycling processes. The study [...] Read more.

Climate changes have increased interest in the circular economy, an alternative model that seeks to minimize environmental impact and maximize resource reuse. A key element of this model is individuals’ behaviors and attitudes, which determine the overall efficiency of recycling processes. The study fills the gap by investigating how selected socio-demographic factors affect attitudes and intentions toward recycling and material reuse in the Slovak Republic, by using the Perceived Characteristics of Innovating (PCI) framework. Through a two-way ANOVA, we tested the hypotheses that higher education correlates with stronger recycling attitudes and that women are more willing than men to engage in circular practices. The results show that gender differences in consumer attitudes towards the circular economy do occur, but their magnitude is often conditioned by education level. Education proved to be the strongest predictor of ecological behavior: respondents with higher education reported stronger beliefs in the importance of recycling and a greater willingness to act sustainably. The interaction between gender and education revealed that university-educated women hold the most pronounced pro-environmental attitudes, underscoring the importance of gender-sensitive educational strategies. It is recommended that environmental education and outreach focus on less-educated groups, particularly women, who have high potential to influence their communities. Full article

17 pages, 2119 KiB

Open AccessArticle

Spatiotemporal Ionospheric TEC Prediction with Deformable Convolution for Long-Term Spatial Dependencies

by Jie Li, Jian Xiao, Haijun Liu, Xiaofeng Du and Shixiang Liu

Atmosphere 2025, 16(8), 950; https://doi.org/10.3390/atmos16080950 (registering DOI) - 7 Aug 2025

Abstract

SA-ConvLSTM is a recently proposed spatiotemporal model for total electron content (TEC) prediction, which effectively catches long-term temporal evolution and global-scale spatial correlations in TEC. However, its reliance on standard convolution limits spatial feature extraction to fixed regular regions, reducing the flexibility for [...] Read more.

SA-ConvLSTM is a recently proposed spatiotemporal model for total electron content (TEC) prediction, which effectively catches long-term temporal evolution and global-scale spatial correlations in TEC. However, its reliance on standard convolution limits spatial feature extraction to fixed regular regions, reducing the flexibility for irregular TEC variations. To address this limitation, we enhance SA-ConvLSTM by incorporating deformable convolution, proposing SA-DConvLSTM. This achieves adaptive spatial feature extraction through learnable offsets in convolutional kernels. Building on this improvement, we design ED-SA-DConvLSTM, a TEC spatiotemporal prediction model based on an encoder–decoder architecture with SA-DConvLSTM as its fundamental block. Firstly, the effectiveness of the model improvement was verified through an ablation experiment. Subsequently, a comprehensive quantitative comparison was conducted between ED-SA-DConvLSTM and baseline models (C1PG, ConvLSTM, and ConvGRU) in the region of 12.5° S–87.5° N and 25° E–180° E. The experimental results showed that the ED-SA-DConvLSTM exhibited superior performance compared to C1PG, ConvGRU, and ConvLSTM, with prediction accuracy improvements of 10.27%, 7.65%, and 7.16% during high solar activity and 11.46%, 4.75%, and 4.06% during low solar activity, respectively. To further evaluate model performance under extreme conditions, we tested the ED-SA-DConvLSTM during four geomagnetic storms. The results showed that the proportion of its superiority over the baseline models exceeded 58%. Full article

(This article belongs to the Section Upper Atmosphere)

18 pages, 2436 KiB

Open AccessArticle

Leveraging IGOOSE-XGBoost for the Early Detection of Subclinical Mastitis in Dairy Cows

by Rui Guo and Yongqiang Dai

Appl. Sci. 2025, 15(15), 8763; https://doi.org/10.3390/app15158763 (registering DOI) - 7 Aug 2025

Abstract

Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE [...] Read more.

Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE Optimization Algorithm (IGOOSE), is presented in this work as an innovative approach for predicting subclinical mastitis in order to overcome these problems. The Dairy Herd Improvement (DHI) records of 4154 cows served as the model’s original foundation. A total of 3232 samples with 21 characteristics made up the final dataset, following extensive data cleaning and preprocessing. To overcome the shortcomings of the original GOOSE algorithm in intricate, high-dimensional problem spaces, three significant enhancements were made. First, an elite inverse strategy was implemented to improve population initialization, enhancing the algorithm’s balance between global exploration and local exploitation. Second, an adaptive nonlinear control factor was added to increase the algorithm’s stability and convergence speed. Lastly, a golden sine strategy was adopted to reduce the risk of premature convergence to suboptimal solutions. According to experimental results, the IGOOSE-XGBoost model works better than other models in predicting subclinical mastitis, especially when it comes to recognizing somatic cell scores, which are important markers of the illness. This study provides a strong predictive framework for managing the health of dairy cows, allowing for the prompt identification and treatment of subclinical mastitis, which enhances the efficiency and quality of milk supply. Full article

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33 pages, 4895 KiB

Open AccessArticle

Scalable Energy Management Model for Integrating V2G Capabilities into Renewable Energy Communities

by Niccolò Pezzati, Eleonora Innocenti, Lorenzo Berzi and Massimo Delogu

World Electr. Veh. J. 2025, 16(8), 450; https://doi.org/10.3390/wevj16080450 (registering DOI) - 7 Aug 2025

Abstract

To promote a more decentralized energy system, the European Commission introduced the concept of Renewable Energy Communities (RECs). Meanwhile, the increasing penetration of Electric Vehicles (EVs) may significantly increase peak power demand and consumption ramps when charging sessions are left uncontrolled. However, by [...] Read more.

To promote a more decentralized energy system, the European Commission introduced the concept of Renewable Energy Communities (RECs). Meanwhile, the increasing penetration of Electric Vehicles (EVs) may significantly increase peak power demand and consumption ramps when charging sessions are left uncontrolled. However, by integrating smart charging strategies, such as Vehicle-to-Grid (V2G), EV storage can actively support the energy balance within RECs. In this context, this work proposes a comprehensive and scalable model for leveraging smart charging capabilities in RECs. This approach focuses on an external cooperative framework to optimize incentive acquisition and reduce dependence on Medium Voltage (MV) grid substations. It adopts a hybrid strategy, combining Mixed-Integer Linear Programming (MILP) to solve the day-ahead global optimization problem with local rule-based controllers to manage power deviations. Simulation results for a six-month case study, using historical demand data and synthetic charging sessions generated from real-world events, demonstrate that V2G integration leads to a better alignment of overall power consumption with zonal pricing, smoother load curves with a 15.5% reduction in consumption ramps, and enhanced cooperation with a 90% increase in shared power redistributed inside the REC. Full article

(This article belongs to the Special Issue Power and Energy Systems for E-Mobility, 2nd Edition)

25 pages, 745 KiB

Open AccessReview

Design and Application of Superhydrophobic Magnetic Nanomaterials for Efficient Oil–Water Separation: A Critical Review

by Rabiga M. Kudaibergenova, Elvira A. Baibazarova, Didara T. Balpanova, Gulnar K. Sugurbekova, Aizhan M. Serikbayeva, Marzhan S. Kalmakhanova, Nazgul S. Murzakasymova, Arman A. Kabdushev and Seitzhan A. Orynbayev

Molecules 2025, 30(15), 3313; https://doi.org/10.3390/molecules30153313 (registering DOI) - 7 Aug 2025

Abstract

Superhydrophobic magnetic nanomaterials (SHMNMs) are emerging as multifunctional platforms for efficient oil–water separation due to their combination of extreme water repellency, strong oil affinity, and external magnetic responsiveness. This review presents a comprehensive analysis of recent advances in the design, synthesis, and environmental [...] Read more.

Superhydrophobic magnetic nanomaterials (SHMNMs) are emerging as multifunctional platforms for efficient oil–water separation due to their combination of extreme water repellency, strong oil affinity, and external magnetic responsiveness. This review presents a comprehensive analysis of recent advances in the design, synthesis, and environmental application of SHMNMs. The theoretical foundations of superhydrophobicity and the physicochemical behavior of magnetic nanoparticles are first outlined, followed by discussion of their synergistic integration. Key fabrication techniques—such as sol–gel synthesis, electrospinning, dip-coating, laser-assisted processing, and the use of biomass-derived precursors—are critically assessed in terms of their ability to tailor surface morphology, chemical functionality, and long-term durability. The review further explores the mechanisms of oil adsorption, magnetic separation, and material reusability under realistic environmental conditions. Special attention is paid to the scalability, mechanical resilience, and environmental compatibility of SHMNMs in the context of water treatment technologies. Current limitations, including reduced efficiency in harsh media, potential environmental risks, and challenges in material regeneration, are discussed. This work provides a structured overview that could support the rational development of next-generation superhydrophobic materials tailored for sustainable and high-performance separation of oil and organic pollutants from water. Full article

(This article belongs to the Special Issue Recent Advances in Superhydrophobic Materials and Their Application)

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