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18 pages, 797 KB

Open AccessArticle

BI-GBDT: A Graph-Free Behavioral Interaction-Aware Gradient Boosting Framework for Fraud Detection in Large-Scale Payment Systems

by Mustafa Berk Keles and Mehmet Gokturk

Appl. Sci. 2026, 16(2), 876; https://doi.org/10.3390/app16020876 (registering DOI) - 14 Jan 2026

Abstract

Detecting fraudulent and anomalous transactions in large-scale digital payment systems is significantly challenging due to severe class imbalance and the fact that transactional risk is tightly coupled to the historical interactions and behaviors of transacting parties. In this study, a scalable Behavioral Interaction-Aware [...] Read more.

Detecting fraudulent and anomalous transactions in large-scale digital payment systems is significantly challenging due to severe class imbalance and the fact that transactional risk is tightly coupled to the historical interactions and behaviors of transacting parties. In this study, a scalable Behavioral Interaction-Aware Gradient Boosting (BI-GBDT) framework is proposed for anomaly detection in tabular transaction data to overcome these challenges. The methodology models sending and receiving behaviors separately through direction-specific clustering based on transaction frequency and amount. Each transaction is characterized by cluster-pair prevalence ratios, which capture the population-level prevalence of sender–receiver interaction patterns. To handle extreme class imbalance, all transactions are clustered, and a cluster-level risk score is computed as the ratio of anomalous transactions to the total number of transactions within each cluster. This score is incorporated as a feature, serving as a behavioral risk prior highlighting concentrated anomaly. These interaction-aware features are integrated into a GBDT in a big data environment. Experiments were conducted on a large masked real-world payment dataset spanning six months and containing more than 456 million transactions, with the prediction task defined as binary classification between fraudulent and non-fraudulent transactions. Unlike standard GBDT models trained only on transactional attributes and graph-based approaches, BI-GBDT captures sender–receiver interaction patterns in a graph-free manner and outperforms a baseline GBDT, reducing the false positive rate from 37.0% to 4.3%, increasing recall from 52.3% to 72.0%, and improving accuracy from 63.0% to 95.7%. Full article

(This article belongs to the Special Issue Machine Learning and Its Application for Anomaly Detection)

14 pages, 1569 KB

Open AccessArticle

A Transformer–LSTM Hybrid Detector for OFDM-IM Signal Detection

by Leijun Wang, Zian Tong, Kuan Wang, Jinfa Xie, Xidong Peng, Bolong Li, Jiawen Li, Xianxian Zeng, Jin Zhan and Rongjun Chen

Entropy 2026, 28(1), 102; https://doi.org/10.3390/e28010102 (registering DOI) - 14 Jan 2026

Abstract

This paper addresses the signal detection problem in orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems using deep learning (DL) techniques. In particular, a DL-based detector termed FullTrans-IM is proposed, which integrates the Transformer architecture with long short-term memory (LSTM) networks. Unlike [...] Read more.

This paper addresses the signal detection problem in orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems using deep learning (DL) techniques. In particular, a DL-based detector termed FullTrans-IM is proposed, which integrates the Transformer architecture with long short-term memory (LSTM) networks. Unlike conventional methods that treat signal detection as a classification task, the proposed approach reformulates it as a sequence prediction problem by exploiting the sequence modeling capability of the Transformer’s decoder rather than relying solely on the encoder. This formulation enables the detector to effectively learn channel characteristics and modulation patterns, thereby improving detection accuracy and robustness. Simulation results demonstrate that the proposed FullTrans-IM detector achieves superior bit error rate (BER) performance compared with conventional methods such as zero-forcing (ZF) and existing DL-based detectors under Rayleigh fading channels. Full article

(This article belongs to the Special Issue Wireless Communications: Signal Processing Perspectives, 2nd Edition)

25 pages, 3057 KB

Open AccessArticle

Technological Solutions and the Potential of Alternative Fuels for the Decarbonization of Maritime Transport

by Claudio Carlini, Marco Rossi and Danilo Bertini

Energies 2026, 19(2), 418; https://doi.org/10.3390/en19020418 (registering DOI) - 14 Jan 2026

Abstract

European and national maritime regulations, aimed at promoting navigation powered by alternative fuels, highlight the need to explore the adoption of various alternative fuel options for maritime transport. This assessment should consider both technical and practical aspects, particularly for freight and passenger services, [...] Read more.

European and national maritime regulations, aimed at promoting navigation powered by alternative fuels, highlight the need to explore the adoption of various alternative fuel options for maritime transport. This assessment should consider both technical and practical aspects, particularly for freight and passenger services, within the national context in which the sector operates. This document provides a detailed analysis of what is available on the market and the expected results between 2030 and 2050 for the conversion of routes using alternative fuel vessels, both in terms of investment and operational costs. Assessments of vessel fuelling needs were conducted, identifying the potential of different fuels on several key Italian routes, reconstructing their technical characteristics and considering the uncertainty associated with potential changes in fuelling costs (over the life of the vessels) and technological progress. Full article

(This article belongs to the Section L: Energy Sources)

18 pages, 2717 KB

Open AccessArticle

Dietary Defective Jujube as a Corn Substitute: Impacts on Growth Performance, Meat Traits, and Alternaria Toxin Exposure in Lambs

by Letian Zhang, Haoyang Hui, Muhammad Faheem, Yanfeng Xue, Ning Chen and Xiaoling Zhou

Animals 2026, 16(2), 255; https://doi.org/10.3390/ani16020255 (registering DOI) - 14 Jan 2026

Abstract

This study evaluated the effects of replacing corn with defective jujube (DJ) on growth, digestibility, blood biochemical indices, meat performance, and the presence of Alternaria toxin residues in Karakul lambs. Thirty-six lambs were split into groups given 0%, 15%, or 30% DJ, replacing [...] Read more.

This study evaluated the effects of replacing corn with defective jujube (DJ) on growth, digestibility, blood biochemical indices, meat performance, and the presence of Alternaria toxin residues in Karakul lambs. Thirty-six lambs were split into groups given 0%, 15%, or 30% DJ, replacing 0%, 45.45%, and 90.91% of corn. The trial lasted 75 days, with 15 days for adaptation and 60 days for measurement. Digestibility for crude protein and ether extract of male lambs increased in the DJ30 group over CON (p < 0.05). High-density lipoprotein decreased in DJ30 (p < 0.01), while triglycerides and total cholesterol in DJ30 dropped (p < 0.05). Blood urea nitrogen and aspartate aminotransferase decreased in DJ15 and DJ30 (p < 0.01). Superoxide dismutase and catalase rose in DJ30 (p < 0.01), while malondialdehyde declined (p < 0.05). Growth hormone and insulin-like growth factor-1 increased in DJ30 (p < 0.01). Feeding DJ did not affect meat production or quality. No Alternaria toxins were detected in rumen, liver, or meat. Feeding 15–30% DJ improved nitrogen utilization, lipid metabolism, and blood antioxidant levels in lambs and reduced the risk of liver damage, while no Alternaria toxin remained in organs. A 30% DJ substitution for corn is a safe strategy for lamb feeding. Full article

(This article belongs to the Collection A Sustainable Approach to Non-Conventional Feeding Resources and Rearing Strategies)

19 pages, 1945 KB

Open AccessArticle

Deep Learning for Building Attribute Classification from Street-View Images for Seismic Exposure Modeling

by Rajesh Kumar, Claudio Rota, Flavio Piccoli and Gianluigi Ciocca

Appl. Sci. 2026, 16(2), 875; https://doi.org/10.3390/app16020875 (registering DOI) - 14 Jan 2026

Abstract

Exposure models are essential for seismic risk assessment to determine environmental vulnerabilities during earthquakes. However, developing these models at scale is challenging because it relies on manual inspection of buildings, which increases costs and introduces significant delays. Developing fast, consistent, and easy-to-deploy automated [...] Read more.

Exposure models are essential for seismic risk assessment to determine environmental vulnerabilities during earthquakes. However, developing these models at scale is challenging because it relies on manual inspection of buildings, which increases costs and introduces significant delays. Developing fast, consistent, and easy-to-deploy automated methods to support this process has become a priority. In this study, we investigate the use of deep learning to accelerate the classification of architectural and structural attributes from street-view imagery. Using the Alvalade dataset, which contains 4007 buildings annotated with 10 multi-class attributes, we evaluated the performance of multiple architecture types. Our analysis shows that deep learning models can successfully extract key structural features, achieving an average macro accuracy of 57%, and a Precision, Recall, and F1-score of 61%, 57%, and 56%, respectively. We also show that prediction quality is further improved by leveraging multi-view imagery of the target buildings. These results demonstrate that deep learning can be an effective solution to reduce the manual effort required for the development of reliable large-scale exposure models, offering a practical solution toward more efficient seismic risk assessment. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

22 pages, 777 KB

Open AccessArticle

Elevating Morals, Elevating Actions: The Interplay of CSR, Transparency, and Guest Pro-Social and Pro-Environmental Behaviors in Hotels

by Kutay Arda Yildirim, Hasan Kilic and Hamed Rezapouraghdam

Sustainability 2026, 18(2), 866; https://doi.org/10.3390/su18020866 (registering DOI) - 14 Jan 2026

Abstract

In the hospitality industry, corporate social responsibility practices are getting more recognition as a strategic driver of stakeholders’ sustainable behaviors. This study creates and tests a moderated serial mediation model that connects hotel CSR activities to guests’ pro-environmental behavior (PROE). In addition, moral [...] Read more.

In the hospitality industry, corporate social responsibility practices are getting more recognition as a strategic driver of stakeholders’ sustainable behaviors. This study creates and tests a moderated serial mediation model that connects hotel CSR activities to guests’ pro-environmental behavior (PROE). In addition, moral elevation (ME) and pro-social behaviors of guests (PSO) are posited as affective and behavioral mediating mechanisms, whereas the perceived transparency (TRA) of hotel actions is investigated as a moderator. The survey data were collected from 426 hotel guests who had stayed in hotels in the Turkish Republic of Northern Cyprus (TRNC) and used partial least squares structural equation modeling (PLS-SEM) to analyze it. The findings reveal that CSR does have a positive effect on ME, which sequentially makes ME affect PSO and PROE behavior positively. The research shows that the moderator TRA also amplifies the relationship strength between CSR and ME, which suggests that transparent actions of hotels do have a positive emotional impact on guests. The research contributes to hospitality literature and also sustainability literature by identifying ME as an emotional mechanism and TRA as a moderating condition that alter guests’ behaviors. As managerial implications, the research underlines the value of creating CSR practices that are both transparent and authentic to guests and stakeholders to ultimately maximize the engagement of guests in the context of sustainability. Full article

(This article belongs to the Special Issue Sustainable Tourism Marketing: Towards Transparent Communication to Empower Informed Decisions)

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11 pages, 1178 KB

Open AccessArticle

Species and Functional Trait Determinants of Biochar Carbon Retention: Insights from Uniform Smoldering Experiments

by Jingyuan Wang

Forests 2026, 17(1), 116; https://doi.org/10.3390/f17010116 (registering DOI) - 14 Jan 2026

Abstract

Understanding the influence of tree species and their intrinsic traits on biochar yield and carbon retention is essential for optimizing the conversion of biomass to biochar in carbon-negative systems. While it is well-established that pyrolysis temperature and broad feedstock categories significantly affect biochar [...] Read more.

Understanding the influence of tree species and their intrinsic traits on biochar yield and carbon retention is essential for optimizing the conversion of biomass to biochar in carbon-negative systems. While it is well-established that pyrolysis temperature and broad feedstock categories significantly affect biochar properties, the extent of species-level variation within woody biomass under standardized pyrolysis conditions remains insufficiently quantified. Here, we synthesized biochar from seven common subtropical tree species at 600 °C under oxygen-limited smoldering conditions and quantified three key indices: biochar yield (Y), carbon recovery efficiency (ηC), and carbon enrichment factor (EC). We further examined the relationships of these indices with feedstock characteristics (initial carbon content, wood density) and functional group identity (conifer vs. broadleaf). Analysis of variance revealed significant interspecific differences in ηC but weaker effects on Y, indicating that species identity primarily governs carbon retention rather than total mass yield. Broadleaf species (Liquidambar formosana, Castanea mollissima) exhibited consistently higher ηC and EC than conifers (Pinus massoniana, P. elliottii), reflecting higher lignin content and wood density that favor aromatic char formation. Principal component and cluster analyses clearly separated coniferous and broadleaf taxa, accounting for over 80% of total variance in carbon-related traits. Regression models showed that feedstock carbon content, biochar carbon content, and wood density together explained 15.5% of the variance in ηC, with feedstock carbon content exerting a significant negative effect, whereas wood density correlated positively with carbon retention. These findings demonstrate that tree species and their functional traits jointly determine carbon fixation efficiency during smoldering. High initial carbon content alone does not guarantee enhanced carbon recovery; instead, wood density and lignin-derived structural stability dominate retention outcomes. Our results underscore the need for trait-based feedstock selection to improve biochar quality and carbon sequestration potential, and provide a mechanistic framework linking species identity, functional traits, and carbon stabilization in biochar production. Full article

(This article belongs to the Section Forest Ecology and Management)

16 pages, 2058 KB

Open AccessArticle

Towards a Resilience Innovation Blueprint for Flood-Affected Schools in the UK

by Olutayo Ekundayo, David Proverbs, Robby Soetanto, Phil Emonson, Jamie Cooper, Peter Coddington, Harvey Speed and Charlotte Smith

Water 2026, 18(2), 226; https://doi.org/10.3390/w18020226 (registering DOI) - 14 Jan 2026

Abstract

Flooding is an increasing climate risk in the UK, yet schools remain marginal in resilience planning. Flood events disrupt education, heighten pupil anxiety, increase staff workload and unsettle communities, but these experiences are rarely documented in ways that inform policy. This study examines [...] Read more.

Flooding is an increasing climate risk in the UK, yet schools remain marginal in resilience planning. Flood events disrupt education, heighten pupil anxiety, increase staff workload and unsettle communities, but these experiences are rarely documented in ways that inform policy. This study examines how schools in the East and West Midlands regions of the UK have experienced and adapted to flooding. Eight qualitative case studies were undertaken in flood-affected schools using semi-structured interviews with key staff, site visits and documentary evidence. Interview transcripts were thematically analysed using NVivo to explore past flood events, levels of preparedness, and readiness for measures such as Property Flood Resilience, Sustainable Drainage Systems and Climate Action Plans. Findings show wide variation in awareness, emergency procedures and engagement with local authorities. Most schools had faced flooding or near misses but lacked formal guidance or flood-specific plans, leading to improvised responses led internally by staff. Despite limited funding, inconsistent communication and exclusion from wider planning, schools demonstrated adaptive potential and willingness to support community preparedness. The study offers evidence to guide headteachers, policymakers and local authorities in strengthening school-based flood resilience and supporting the development of a resilience innovation blueprint for flood-prone schools in the UK. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

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23 pages, 796 KB

Open AccessArticle

Institutional and Policy Barriers to GIS-Based Waste Management: Evidence from Rural Municipalities in Vhembe District, South Africa

by Aifani Confidence Tahulela and Shervin Hashemi

Environments 2026, 13(1), 51; https://doi.org/10.3390/environments13010051 (registering DOI) - 14 Jan 2026

Abstract

Municipal solid waste management (MSWM) remains a critical environmental governance challenge in rural and peri-urban regions of the Global South, where service delivery gaps exacerbate illegal dumping and public health risks. Geographic Information Systems (GIS) are increasingly promoted as decision-support tools to improve [...] Read more.

Municipal solid waste management (MSWM) remains a critical environmental governance challenge in rural and peri-urban regions of the Global South, where service delivery gaps exacerbate illegal dumping and public health risks. Geographic Information Systems (GIS) are increasingly promoted as decision-support tools to improve waste collection efficiency and environmental monitoring; however, their adoption in resource-constrained municipalities remains limited. This study investigates the institutional and policy barriers shaping GIS readiness in four rural municipalities within South Africa’s Vhembe District. Using a qualitative case-study design, semi-structured interviews were conducted with 29 municipal officials across managerial and operational levels, complemented by 399 community responses to an open-ended survey question. Thematic analysis, guided by Institutional Theory and the Technology Acceptance Model (TAM), identified five interrelated themes: waste production and disposal behaviours, collection and infrastructure constraints, institutional and operational challenges, policy and standardisation gaps, and technology readiness. The findings reveal that weak service reliability, fragmented governance structures, limited human and financial capacity, and inconsistent policy enforcement collectively undermine GIS adoption, despite its high perceived usefulness among officials. The study demonstrates that the effectiveness of GIS as an environmental management tool is contingent on institutional readiness rather than technological availability alone and highlights the need for integrated reforms in service delivery, institutional capacity, and policy implementation to enable GIS-supported sustainable waste management. Full article

24 pages, 2688 KB

Open AccessArticle

Spatial Prediction of Soil Texture at the Field Scale Using Synthetic Images and Partitioning Strategies

by Yiang Wang, Shinai Ma, Shuai Bao, Yuxin Ma, Yan Zhang, Dianyao Wang, Yihan Ma and Huanjun Liu

Remote Sens. 2026, 18(2), 279; https://doi.org/10.3390/rs18020279 (registering DOI) - 14 Jan 2026

Abstract

In the field of smart agriculture, soil property data at the field scale drives the precision decision-making of agricultural inputs such as seeds and chemical fertilizers. However, soil texture has significant spatial variability at the field scale, and traditional remote sensing monitoring methods [...] Read more.

In the field of smart agriculture, soil property data at the field scale drives the precision decision-making of agricultural inputs such as seeds and chemical fertilizers. However, soil texture has significant spatial variability at the field scale, and traditional remote sensing monitoring methods have certain data intermittency, which limits small-scale prediction research. In this study, based on the Google Earth Engine platform, soil synthetic images were generated according to different time intervals using mean compositing and median compositing modes, image bands were extracted, and spectral indices were introduced; combined with the random forest algorithm, the effects of different compositing time windows, compositing modes, and compositing data types on prediction accuracy were evaluated; and three partitioning strategies based on crop growth, soil synthetic image brightness, and soil type were adopted to conduct local partitioning regression of soil texture. The results show that: (1) The use of mean compositing of multi-year May images from 2021 to 2024 can improve prediction accuracy. When this method is combined with the “band reflectance + spectral indices” dataset, compared with other compositing methods, the R² of clay particles, silt particles, and sand particles can be increased by 8.89%, 9.50%, and 2.48% on average. (2) Compared with using only image band data, the introduction of spectral indices can significantly improve the prediction accuracy of soil texture at the field scale, and the R² of clay particles, silt particles, and sand particles is increased by 4.58%, 3.43%, and 4.59% on average, respectively. (3) Global regression is superior to local partitioning regression; however, the local partitioning regression strategy based on soil type has good accuracy performance. Under the optimal compositing method, the average R² of soil particles of each size fraction is only 1.08% lower than that of global regression, which has great application potential. This study innovatively constructs a comprehensive strategy of “moisture spectral indices + specific compositing time window + specific compositing mode + soil type partitioning”, providing a new paradigm for soil texture prediction at the field scale in Northeastern China, and lays the foundation for data-driven water and fertilizer decision-making. Full article

(This article belongs to the Special Issue Advances in Remote Sensing for Soil Property Mapping)

9 pages, 484 KB

Open AccessReview

Analysis of Factors Associated with Active and Sedentary Behaviors of Children and Adolescents Considering Bronfenbrenner’s Bioecological Theory: A Scoping Review Protocol

by Vinícius Tenório Moraes da Silva, Rafael dos Santos Henrique, José Ywgne, Francisco Salviano Sales Nobre, Paulo Henrique Guerra and Leonardo Gomes de Oliveira Luz

Adolescents 2026, 6(1), 9; https://doi.org/10.3390/adolescents6010009 (registering DOI) - 14 Jan 2026

Abstract

The present study proposes to identify information from health, educational and sports science studies that used Bronfenbrenner’s theory of human development to verify the complex relationship between factors associated with physical activity (PA) and sedentary behavior (SB) in children and adolescents. The scoping [...] Read more.

The present study proposes to identify information from health, educational and sports science studies that used Bronfenbrenner’s theory of human development to verify the complex relationship between factors associated with physical activity (PA) and sedentary behavior (SB) in children and adolescents. The scoping review will be developed across seven databases (PubMed, Scopus, SPORTDiscus, Web of Science, PsycINFO, ERIC, and Scielo). The inclusion criteria were formulated based on the PCC (Population, Concept, Context) framework: (a) children and adolescents (5–17 years); (b) studies on PA and/or SB that used Bronfenbrenner’s theory; (c) any context. Only peer-reviewed journal articles published in English, Spanish, or Portuguese will be included; grey literature will not be included. Finally, two reviewers will screen studies using Rayyan. A standardized charting form will be used to extract data on study characteristics and the factors mapped considering Bronfenbrenner’s theory components. This study is expected to show how Bronfenbrenner’s theory has been applied to explain PA and SB in children and adolescents, as well as to map the methodological tools used in this area, identifying gaps and providing a clear framework for future research on the complex and multilevel determinants of PA and SB in children and adolescents. Full article

(This article belongs to the Section Adolescent Health Behaviors)

19 pages, 1116 KB

Open AccessArticle

Creation of High-Density Néel Skyrmions by Interfacial-Proximity Engineering

by Tingjia Zhang, Chendi Yang, Xiaowei Lv, Ke Pei, Xiao Yang, Wuyang Tan, Junye Pan, Jiazhuan Qin, Meichen Wen, Wei Li, Jia Liang and Renchao Che

Materials 2026, 19(2), 340; https://doi.org/10.3390/ma19020340 (registering DOI) - 14 Jan 2026

Abstract

Two-dimensional ferromagnets are promising for compact spintronic devices. However, their centrosymmetric structure inherently suppresses the Dzyaloshinskii–Moriya interaction (DMI), hindering the stabilization of chiral spin texture. Here, a tunable DMI induced by interface symmetry breaking in Fe₃GeTe₂/MoS₂ vdW heterostructures [...] Read more.

Two-dimensional ferromagnets are promising for compact spintronic devices. However, their centrosymmetric structure inherently suppresses the Dzyaloshinskii–Moriya interaction (DMI), hindering the stabilization of chiral spin texture. Here, a tunable DMI induced by interface symmetry breaking in Fe₃GeTe₂/MoS₂ vdW heterostructures is reported. We find that the interfacial DMI stabilizes Néel-type skyrmions in Fe₃GeTe₂/MoS₂ heterostructures under zero magnetic field, with nucleation observed at 64 Oe and annihilation at 800 Oe via Lorentz transmission electron microscopy (LTEM). Skyrmion density peaks (~0.57 skyrmions/μm²) at a Fe₃GeTe₂ thickness of ~30 nm and decays beyond ~60 nm, indicating a finite penetration depth of the proximity effect. Such modulated DMI enables a stabilized nucleation of Néel type skyrmions, allowing for precise control over their density, revealed by Lorentz transmission electron microscopy. Thickness-dependent measurements confirm the interfacial origin of this stabilization. Skyrmion density reaches peak in thin Fe₃GeTe₂ layers and decays beyond ~60 nm, defining the finite penetration depth of the proximity effect. Micromagnetic simulations reproduce the field-dependent evolution of skyrmions, showing a strong correlation to interfacial DMI. First-principles calculations attribute this DMI to asymmetric charge redistribution and spin–orbit coupling at the heterointerface. This work establishes interface engineering as a universal strategy for stabilizing skyrmions in centrosymmetric vdW ferromagnets, offering a thickness-tunable platform for next-generation two-dimensional spintronic devices. Full article

(This article belongs to the Section Thin Films and Interfaces)

24 pages, 4037 KB

Open AccessArticle

Deadbeat Control for a Three-Phase Solar T-Type Inverter and Comparison with PI Control

by HanJoon Jang and Il Song Kim

Energies 2026, 19(2), 417; https://doi.org/10.3390/en19020417 (registering DOI) - 14 Jan 2026

Abstract

This paper proposes a deadbeat-based current control method for a three-phase T-type solar inverter to improve transient performance and harmonic immunity compared with conventional PI control. The control framework adopts a double-loop structure, in which the photovoltaic (PV) voltage is regulated by a [...] Read more.

This paper proposes a deadbeat-based current control method for a three-phase T-type solar inverter to improve transient performance and harmonic immunity compared with conventional PI control. The control framework adopts a double-loop structure, in which the photovoltaic (PV) voltage is regulated by a perturb-and-observe (P&O)-based maximum power point tracking (MPPT) algorithm in the outer loop, while d–q axis currents are controlled in the inner loop. A performance comparison between the PI control and the proposed deadbeat control was conducted using an ESS T-type inverter with an inner current control loop, and the results were validated through combined simulation and experimental investigations. Under experimental conditions, when the d-axis reference current was stepped from 5.2 A to 9.2 A, the deadbeat controller achieved a transient settling time of approximately 1.89 ms, representing a 47.5% reduction compared to the 3.6 ms observed with the PI control. Furthermore, under 7th harmonic injection (0.225), the total harmonic distortion (THD) was reduced from 12.9% to 4.3%. These results demonstrate that the proposed deadbeat control strategy provides faster transient response and enhanced robustness against harmonic disturbances in three-phase T-type inverter applications. Full article

(This article belongs to the Special Issue Progress and Challenges in Solar Photovoltaic Materials and Intelligent Control)

32 pages, 1237 KB

Open AccessReview

Occupational Exposure to Solar Ultraviolet Radiation: A Systematic Review of Protective Measures

by Ricardo Rocha, Joana Santos, João Santos Baptista, Joana Guedes and Carlos Carvalhais

Safety 2026, 12(1), 10; https://doi.org/10.3390/safety12010010 (registering DOI) - 14 Jan 2026

Abstract

Solar ultraviolet radiation (UVR) is classified as a Group 1 carcinogen and poses a significant occupational hazard to outdoor workers. Despite preventive guidelines, adherence to protective measures remains inconsistent. This systematic review identified the protective measures adopted by healthy outdoor workers and assessed [...] Read more.

Solar ultraviolet radiation (UVR) is classified as a Group 1 carcinogen and poses a significant occupational hazard to outdoor workers. Despite preventive guidelines, adherence to protective measures remains inconsistent. This systematic review identified the protective measures adopted by healthy outdoor workers and assessed their adherence to and the effectiveness of these measures. Following the PRISMA 2020 statement, the review searched Scopus, Web of Science, and PubMed for peer-reviewed studies published between 2015 and 2025. Eligible studies included at least 100 healthy participants and evaluated preventive or protective measures against solar UVR. Independent reviewers extracted data and assessed risk of bias using the McMaster Critical Review Form. From 17,756 records, 51 studies met the inclusion criteria after screening and a subsequent snowballing process. The identified protective strategies clustered into physical, behavioural, and organisational categories. Adherence ranged from low to moderate, with structured interventions and employer support improving compliance. Sunscreen use remained low due to perceived inconvenience and lack of provision. Overall, the evidence revealed substantial variability in implementation and effectiveness across occupations. Strengthened regulations and integrated interventions combining education, personal protective equipment, and organisational measures are essential. Future research should prioritise longitudinal designs and objective indicators such as biomarkers and dosimetry. Full article

26 pages, 681 KB

Open AccessReview

Flourishing Circularity: A Resource Assessment Framework for Sustainable Strategic Management

by Jean Garner Stead

Sustainability 2026, 18(2), 867; https://doi.org/10.3390/su18020867 (registering DOI) - 14 Jan 2026

Abstract

This paper introduces flourishing circularity as a transformative approach to resource assessment that transcends both traditional Resource-Based View (RBV) theory and conventional circular economy concepts. We demonstrate RBV’s fundamental limitations in addressing the polycrisis of breached planetary boundaries and social inequities. Similarly, while [...] Read more.

This paper introduces flourishing circularity as a transformative approach to resource assessment that transcends both traditional Resource-Based View (RBV) theory and conventional circular economy concepts. We demonstrate RBV’s fundamental limitations in addressing the polycrisis of breached planetary boundaries and social inequities. Similarly, while the circular economy focuses on resource reuse and recycling, it often merely delays environmental degradation rather than reversing it. Flourishing circularity addresses these shortcomings by reconceptualizing natural and social capital not as externalities but as foundational sources of all value creation. We develop a comprehensive framework for assessing resources within an open systems perspective, where competitive advantage increasingly derives from a firm’s ability to regenerate the systems upon which all business depends. The paper introduces novel assessment tools that capture the dynamic interplay between organizational activities and coevolving social and ecological systems. We outline the core competencies required for flourishing circularity: regenerative approaches to social and natural capital, and systems thinking with cross-boundary collaboration capabilities. These competencies translate into competitive advantage as stakeholders increasingly favor organizations that enhance system health. The framework provides practical guidance for transforming resource assessment from extraction to regeneration, enabling business models that create value through system enhancement rather than depletion. Full article

9 pages, 419 KB

Open AccessBrief Report

Using Plasma Amyloid Beta Oligomer to Screen in Alzheimer’s Disease: A Pilot Study

by Pin-Chieh Hsu, Jia-Ying Yang, Ling-Chun Huang and Yuan-Han Yang

Int. J. Mol. Sci. 2026, 27(2), 846; https://doi.org/10.3390/ijms27020846 - 14 Jan 2026

Abstract

Previous studies have shown that plasma amyloid-beta oligomers (AβOs), the toxic form of amyloid-beta (Aβ), are a critical issue in the development or worsening of Alzheimer’s disease (AD) and can be regarded as a blood marker for screening in dementia. We examined plasma [...] Read more.

Previous studies have shown that plasma amyloid-beta oligomers (AβOs), the toxic form of amyloid-beta (Aβ), are a critical issue in the development or worsening of Alzheimer’s disease (AD) and can be regarded as a blood marker for screening in dementia. We examined plasma AβOs with their related biomarkers in a case–control study to clarify these issues. A total of 16 patients diagnosed with Alzheimer’s dementia (AD) and 16 cognitively normal controls (NCs) were recruited to compare their plasma biomarkers, AβO, Aβ_1-40, and Aβ_1-42, also referring to other parameters like APOE ε4 status, Clinical Dementia Rating^®-Sum of Boxes (CDR^®-SB), and Mini Mental Status Examination (MMSE) scores. In plasma concentrations of Aβ_1-40, Aβ_1-42, and AβO, the mean concentrations were significantly different between the two groups. There is a significant increase in the concentrations of Aβ_1-40 and AβO, while Aβ_1-42 is decreased in individuals with AD compared to NC. AβO was statistically associated with the Aβ_1-40 and Aβ_1-42/Aβ_1-40 ratio. Higher plasma concentrations of AβO were significantly associated with AD compared to non-dementia controls. This suggests that AβOs can be potential plasma biomarkers to screen in AD. However, a study recruiting more individuals is necessary to examine the association, if any. Full article

(This article belongs to the Special Issue Recent Advances in Dementia with Lewy Bodies (DLB) and Alzheimer’s Disease (AD))

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26 pages, 38461 KB

Open AccessArticle

High-Resolution Snapshot Multispectral Imaging System for Hazardous Gas Classification and Dispersion Quantification

by Zhi Li, Hanyuan Zhang, Qiang Li, Yuxin Song, Mengyuan Chen, Shijie Liu, Dongjing Li, Chunlai Li, Jianyu Wang and Renbiao Xie

Micromachines 2026, 17(1), 112; https://doi.org/10.3390/mi17010112 - 14 Jan 2026

Abstract

Real-time monitoring of hazardous gas emissions in open environments remains a critical challenge. Conventional spectrometers and filter wheel systems acquire spectral and spatial information sequentially, which limits their ability to capture multiple gas species and dynamic dispersion patterns rapidly. A High-Resolution Snapshot Multispectral [...] Read more.

Real-time monitoring of hazardous gas emissions in open environments remains a critical challenge. Conventional spectrometers and filter wheel systems acquire spectral and spatial information sequentially, which limits their ability to capture multiple gas species and dynamic dispersion patterns rapidly. A High-Resolution Snapshot Multispectral Imaging System (HRSMIS) is proposed to integrate high spatial fidelity with multispectral capability for near real-time plume visualization, gas species identification, and concentration retrieval. Operating across the 7–14

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m spectral range, the system employs a dual-path optical configuration in which a high-resolution imaging path and a multispectral snapshot path share a common telescope, allowing for the simultaneous acquisition of fine two-dimensional spatial morphology and comprehensive spectral fingerprint information. Within the multispectral path, two

5 \times 5

microlens arrays (MLAs) combined with a corresponding narrowband filter array generate 25 distinct spectral channels, allowing concurrent detection of up to 25 gas species in a single snapshot. The high-resolution imaging path provides detailed spatial information, facilitating spatio-spectral super-resolution fusion for multispectral data without complex image registration. The HRSMIS demonstrates modulation transfer function (MTF) values of at least 0.40 in the high-resolution channel and 0.29 in the multispectral channel. Monte Carlo tolerance analysis confirms imaging stability, enabling the real-time visualization of gas plumes and the accurate quantification of dispersion dynamics and temporal concentration variations. Full article

(This article belongs to the Special Issue Gas Sensors: From Fundamental Research to Applications, 2nd Edition)

12 pages, 737 KB

Open AccessArticle

Hitting the Target: Model-Informed Precision Dosing of Tobramycin in Pediatric Patients with Cystic Fibrosis

by Jake M. Brockmeyer, Laura Bio, Carlos Milla and Adam Frymoyer

Pharmaceuticals 2026, 19(1), 150; https://doi.org/10.3390/ph19010150 - 14 Jan 2026

Abstract

Background: Tobramycin is a key therapy for pulmonary exacerbations in children and adolescents with cystic fibrosis (CF), yet its variable pharmacokinetics (PK) combined with narrow therapeutic index necessitates therapeutic drug monitoring (TDM) during clinical care to optimize exposure while minimizing toxicity. Model-informed precision [...] Read more.

Background: Tobramycin is a key therapy for pulmonary exacerbations in children and adolescents with cystic fibrosis (CF), yet its variable pharmacokinetics (PK) combined with narrow therapeutic index necessitates therapeutic drug monitoring (TDM) during clinical care to optimize exposure while minimizing toxicity. Model-informed precision dosing (MIPD) is a potentially powerful tool to support dose individualization in clinical care that leverages population PK models and Bayesian forecasting. Herein, we evaluated the performance of an MIPD initiative at our hospital for once-daily tobramycin in pediatric patients with CF. Methods: Tobramycin practices at a single CF center before (2016–2018) and after (2019–2025) implementation of an MIPD initiative in CF patients < 21 years were evaluated. TDM during the pre-MIPD period used traditional log-linear AUC calculations, while the post-MIPD period used a commercial MIPD software platform integrated within the electronic health record. Outcomes included attainment of the target 24 h area-under-the-curve (AUC₂₄ 80–120 mg·h/L), number of TDM samples and dose adjustments during the first 7 days of treatment, and rates of acute kidney injury (AKI). Results: A total of 114 treatment courses were analyzed (77 pre-MIPD, 37 post-MIPD). Post-MIPD target attainment was 75.7% at TDM1, 89.2% at TDM2, and 100% at TDM3, significantly higher than pre-MIPD at corresponding cycles. The post-MIPD period required fewer TDM samples (4.2 vs. 7.1; p < 0.001) and dose adjustments (0.7 vs. 1.8; p < 0.001) in the first 7 days. AKI incidence remained low and comparable between periods. Conclusions: Implementation of an MIPD initiative for tobramycin in pediatric patients with CF led to the early attainment of therapeutic AUC₂₄ targets while reducing TDM burden and dose adjustments. Full article

(This article belongs to the Special Issue Pediatric Drug Therapy: Safety, Efficacy, and Personalized Medicine)

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25 pages, 355 KB

Open AccessArticle

Killing and 2-Killing 1-Forms on Poisson Doubly Warped Product Manifolds

by Bang-Yen Chen, Majid Ali Choudhary, Foued Aloui and Ibrahim Al-Dayel

Mathematics 2026, 14(2), 301; https://doi.org/10.3390/math14020301 - 14 Jan 2026

Abstract

In this paper we investigate Killing and 2-Killing 1-forms on a Poisson doubly warped product manifold (

PDWPM

). We establish a connection between the property of 1-form on a

PDWPM

and its components on the factor manifolds to be Killing or 2-Killing. [...] Read more.

In this paper we investigate Killing and 2-Killing 1-forms on a Poisson doubly warped product manifold (

PDWPM

). We establish a connection between the property of 1-form on a

PDWPM

and its components on the factor manifolds to be Killing or 2-Killing. We also demonstrate that a Killing 1-form on a

PDWPM

generates a contravariant Ricci soliton factor manifold if and only if it is a contravariant Einstein manifold. Additionally, we provide necessary and sufficient conditions for a

PDWPM

to be a Poisson singly warped product manifold (

PSWPM

). Finally, we present examples of Killing and 2-Killing 1-forms on

PDWPM s

with one-dimensional, and two-dimensional base spaces. Full article

(This article belongs to the Special Issue Advances in Differential Geometry and Its Applications, 2nd Edition)

14 pages, 555 KB

Open AccessArticle

The Association Between Composite Healthy Lifestyle Score and Type 2 Diabetes Risk in the Korean Population: The Korean Genome and Epidemiology Study

by Daeyun Kim, Minji Kang, Dongmin Kim, Juyoung Park and Jihye Kim

Nutrients 2026, 18(2), 273; https://doi.org/10.3390/nu18020273 - 14 Jan 2026

Abstract

Background/Objectives: Modifiable lifestyle factors, particularly diet, are important for preventing type 2 diabetes (T2D); however, the evidence regarding this from prospective studies is limited in the Asian population. We therefore evaluated whether a diet-inclusive healthy lifestyle score (HLS) predicts incident T2D in [...] Read more.

Background/Objectives: Modifiable lifestyle factors, particularly diet, are important for preventing type 2 diabetes (T2D); however, the evidence regarding this from prospective studies is limited in the Asian population. We therefore evaluated whether a diet-inclusive healthy lifestyle score (HLS) predicts incident T2D in a community-based cohort. Methods: We analyzed 7185 T2D-free adults from the KoGES Ansan–Ansung cohort, constructing the HLS (range: 0–5) based on five lifestyle factors: non-smoking, ≥30 min/day of moderate-to-vigorous physical activity, low-risk alcohol consumption (≤40 g/day for men; ≤20 g/day for women), BMI of 18.5–24.9 kg/m², and a healthy diet, defined as a healthy plant-based diet index within the top 40th percentile. Cox proportional hazards regression models were employed to examine the association between HLS and incident T2D risk. Results: During a median follow-up of 17.5 years, 1223 cases of T2D were identified. Compared to individuals with a score of 0 or 1, those with a score of 5 had a 56% lower risk of T2D after adjustment for potential confounders (HR: 0.44, 95% CI: 0.32–0.62), and these associations remained consistent across subgroups stratified by age, sex, family history of T2D, hypertension, and residential area. However, the association was stronger among non-users of anti-diabetic medication than among users. Conclusions: Adherence to a healthier lifestyle, as indicated by a higher HLS, was significantly associated with a reduced risk of developing T2D among Korean adults. These findings underscore the importance of promoting integrated healthy lifestyle behaviors to prevent T2D. Full article

(This article belongs to the Section Nutritional Epidemiology)

12 pages, 1187 KB

Open AccessArticle

Assessment of Sunshine Duration for Various Time Resolutions Based on Pyranometric Data (An Example from Temperate Transition Climate of Central Europe)

by Krzysztof Błażejczyk, Jarosław Baranowski and Anna Błażejczyk

Atmosphere 2026, 17(1), 83; https://doi.org/10.3390/atmos17010083 - 14 Jan 2026

Abstract

Sunshine duration (SD) is one of the essential meteorological variables. It represents the sum of time for which direct solar radiation with an intensity above 120 W∙m⁻² reaches the Earth’s surface. In the contemporary observational routine, automatic electronic devices are [...] Read more.

Sunshine duration (SD) is one of the essential meteorological variables. It represents the sum of time for which direct solar radiation with an intensity above 120 W∙m⁻² reaches the Earth’s surface. In the contemporary observational routine, automatic electronic devices are in use. The pyranometric method based on the measurements of global solar radiation measurements (K_glob) is also proposed by WMO to assess SD. The aim of the paper is to study the accuracy of the Slob–Monna method (SD-WMO), recommended by WMO to calculate sunshine duration. Alternatively, the author’s method, which is based on the Ångström clearness index (SD-ACI), was used to approximate SD. In this purpose, two years series of SD and K_glob observations at four locations in Poland (well representing Central European transitional climate zone) were analyzed. The result shows that, for SD-WMO, sunshine duration values are on average 16% higher than observed ones. For the SD-ACI method, they are only 5% higher. When verifying the accuracy of SD-WMO and SD-ACI approximations, we have found that both for daily and monthly periods the calculated SD sums are closer to the observed ones in the case of SD-ACI than for the SD-WMO method. The correlation coefficients are, respectively, 0.98 and 0.82 (for daily sums) as well as 0.99 and 0.88 for monthly sums. Full article

(This article belongs to the Section Meteorology)

38 pages, 13699 KB

Open AccessReview

A Comprehensive Review of Magnetic Coupling Mechanisms, Compensation Networks, and Control Strategies for Electric Vehicle Wireless Power Transfer Systems

by Yanxia Wu, Pengqiang Nie, Zhenlin Wang, Lijuan Wang, Seiji Hashimoto and Takahiro Kawaguchi

Processes 2026, 14(2), 287; https://doi.org/10.3390/pr14020287 - 14 Jan 2026

Abstract

Wireless power transfer (WPT) has emerged as a key enabling technology for the large-scale adoption of electric vehicles (EVs), offering enhanced charging flexibility, improved safety, and seamless integration with intelligent transportation and renewable energy infrastructures. This paper presents a comprehensive review and technical [...] Read more.

Wireless power transfer (WPT) has emerged as a key enabling technology for the large-scale adoption of electric vehicles (EVs), offering enhanced charging flexibility, improved safety, and seamless integration with intelligent transportation and renewable energy infrastructures. This paper presents a comprehensive review and technical synthesis of WPT technologies spanning both near-field and far-field domains, including inductive power transfer (IPT), magnetically coupled resonant WPT (MCR-WPT), capacitive power transfer (CPT), microwave power transfer (MPT), and laser wireless charging (LPT). Particular emphasis is placed on MCR-WPT, the most widely adopted approach for EV wireless charging, for which the coupler structures, resonant compensation networks, power converter architectures, and control strategies are systematically analyzed. The review further identifies that hybrid WPT architectures, adaptive compensation design and wide-coverage coupling mechanisms will be central to enabling high-power, long-distance, and misalignment-resilient wireless charging solutions for next-generation electric transportation systems. Full article

(This article belongs to the Special Issue Modern Machine Learning Applications in Control and Optimization of Energy Power and Storage Systems)

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4 pages, 325 KB

Open AccessEditorial

Editorial for Special Issue “Technological Advances Around Next-Generation Sequencing”

by Gaurav Tripathi

Curr. Issues Mol. Biol. 2026, 48(1), 83; https://doi.org/10.3390/cimb48010083 - 14 Jan 2026

Abstract

Over the past three decades, advances in high-throughput technologies have played a major role in the transformation of biomedical science, which has enabled unprecedented exploration of genomes, transcriptomes, and proteomes [...] Full article

(This article belongs to the Special Issue Technological Advances Around Next-Generation Sequencing Application)

35 pages, 4505 KB

Open AccessReview

Surface-Modified Magnetic Nanoparticles for Photocatalytic Degradation of Antibiotics in Wastewater: A Review

by Melissa Ariza Gonzalez, Supawitch Hoijang, Dang B. Tran, Quoc Minh Tran, Refia Atik, Rafiqul Islam, Sugandika Maparathne, Sujitra Wongthep, Ramtin Yarinia, Ruwanthi Amarasekara, Pailinrut Chinwangso and T. Randall Lee

Appl. Sci. 2026, 16(2), 844; https://doi.org/10.3390/app16020844 - 14 Jan 2026

Abstract

Recent advancements in nanotechnology and materials science have enabled the development of magnetic photocatalysts with improved efficiency, stability, and reusability, offering a promising approach for wastewater treatment. The integration of magnetic nanoparticles (MNPs) into photocatalytic processes has gained significant attention as a sustainable [...] Read more.

Recent advancements in nanotechnology and materials science have enabled the development of magnetic photocatalysts with improved efficiency, stability, and reusability, offering a promising approach for wastewater treatment. The integration of magnetic nanoparticles (MNPs) into photocatalytic processes has gained significant attention as a sustainable method for addressing emerging pollutants—such as antibiotics and pharmaceutical compounds—which pose environmental and public health risks, including the proliferation of antibiotic resistance. Surface modification techniques, specifically applied to MNPs, are employed to enhance their photocatalytic performance by improving surface reactivity, reducing nanoparticle agglomeration, and increasing photocatalytic activity under both visible and ultraviolet (UV) light irradiation. These modifications also facilitate the selective adsorption and degradation of target contaminants. Importantly, the modified nanoparticles retain their magnetic properties, allowing for facile separation and reuse in multiple treatment cycles via external magnetic fields. This review provides a comprehensive overview of recent developments in surface-modified MNPs for wastewater treatment, with a focus on their physicochemical properties, surface modification strategies, and effectiveness in the removal of antibiotics from aqueous environments. Furthermore, the review discusses advantages over conventional treatment methods, current limitations, and future research directions, emphasizing the potential of this technology for sustainable and efficient water purification. Full article

(This article belongs to the Special Issue Applications of Nanoparticles in the Environmental Sciences)

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23 pages, 1222 KB

Open AccessArticle

Dissolvable Face Mask with Liposomal Licorice Extract and Kojic Acid: An Innovative Approach for Skin Brightening

by Theerada Taesotikul, Supusson Pengnam, Thapakorn Charoenying, Boonnada Pamornpathomkul, Prin Chaksmithanont, Prasopchai Patrojanasophon and Chaiyakarn Pornpitchanarong

Cosmetics 2026, 13(1), 21; https://doi.org/10.3390/cosmetics13010021 - 14 Jan 2026

Abstract

This study developed a biodegradable dissolvable face mask incorporating liposomal kojic acid (KA) and licochalcone A from licorice extract (LE) to enhance skin delivery and performance. Liposomes were prepared by thin-film hydration method. The film matrix, composed of PVA/PVP/PEG400/HA, was optimized using factorial [...] Read more.

This study developed a biodegradable dissolvable face mask incorporating liposomal kojic acid (KA) and licochalcone A from licorice extract (LE) to enhance skin delivery and performance. Liposomes were prepared by thin-film hydration method. The film matrix, composed of PVA/PVP/PEG400/HA, was optimized using factorial design to achieve suitable mechanical strength and rapid dissolution. The optimized mask, containing liposomal KA (1% w/v) and licochalcone A (0.025% w/v), was evaluated for antioxidant activity, ex vivo skin deposition, and short-term efficacy (Approval from the Institutional Review Board of Silpakorn University, Thailand; Ethics Approval No. REC 67.1001-146-7726/COA 68.0320-013 Date of registration: 20 March 2025). The optimized liposomes exhibited a mean particle size of 66–72 nm, entrapment efficiency above 65%, and a zeta potential of −12.5 mV (licochalcone A) and −1.67 mV (KA). Liposomal licochalcone A and KA showed potent antioxidant activity compared to their native forms. The optimized film dissolved within approximately 15 min on moist skin and showed favorable handling properties. Ex vivo studies revealed significantly higher skin deposition of both KA and licochalcone A from the liposomal mask compared with free and liposomal dispersions (p < 0.05). In a 7-day clinical evaluation, the mask significantly improved skin hydration and reduced melanin index (p < 0.05). No irritation or adverse reactions were observed, and user satisfaction was high. This liposomal dissolvable mask offered an effective, well-tolerated, and eco-friendly approach to enhancing skin brightness and hydration, supporting its potential as a sustainable cosmeceutical innovation. Full article

(This article belongs to the Section Cosmetic Formulations)

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17 pages, 3884 KB

Open AccessArticle

Fucoidan Extracted from Fucus vesiculosus Ameliorates Colitis-Associated Neuroinflammation and Anxiety-like Behavior in Adult C57BL/6 Mice

by Xiaoyu Song, Na Li, Xiujie Li, Bo Yuan, Xuan Zhang, Sheng Li, Xiaojing Yang, Bing Qi, Shixuan Yin, Chunxue Li, Yangting Huang, Ben Zhang, Yanjie Guo, Jie Zhao and Xuefei Wu

Mar. Drugs 2026, 24(1), 42; https://doi.org/10.3390/md24010042 - 14 Jan 2026

Abstract

Fucoidan, a complex sulfated polysaccharide derived from marine brown seaweeds, exhibits broad biological activities, including anticoagulant, antitumor, antiviral, anti-inflammatory and lipid-lowering effects. Fucoidan confers neuroprotection in animal models of a broad spectrum of brain disorders such as Parkinson’s disease (PD) and depression. However, [...] Read more.

Fucoidan, a complex sulfated polysaccharide derived from marine brown seaweeds, exhibits broad biological activities, including anticoagulant, antitumor, antiviral, anti-inflammatory and lipid-lowering effects. Fucoidan confers neuroprotection in animal models of a broad spectrum of brain disorders such as Parkinson’s disease (PD) and depression. However, the effect of fucoidan on gut-derived neuroinflammation and associated behavioral changes has been scarcely investigated. In comparison to fucoidan from other brown seaweeds, that from Fucus vesiculosus exhibited a better neuroprotective effect in vivo and more potent radical scavenging activity in vitro. Fucoidan from Laminaria japonica ameliorates behavioral disorders related to acute ulcerative colitis (UC) in aged mice. It is of interest to assess the effects of fucoidan administration on intestinal and brain inflammation in the acute colitis mouse model. Fucoidan treatment ameliorated DSS-induced intestinal pathology, reduced the inflammatory mediator expression in the gut and brain, and activated intestinal macrophages and cortical microglia in the UC mice. It also protected the intestinal mucosal barrier and blood–brain barrier as well as prevented neuronal damage, while alleviating anxiety-like behavior in UC mice. These results suggest fucoidan supplementation may help prevent brain disorders, such as depression and PD, potentially involving gut–brain axis-related mechanisms, as fucoidan suppresses gut-derived neuroinflammation. Full article

(This article belongs to the Special Issue Advances in Research on Fucoidan: Potential as Drug and Functional Food)

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