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Recent Articles  

21 pages, 5225 KB  
Article
Estimation of Cotton LAI and Yield Through Assimilation of the DSSAT Model and Unmanned Aerial System Images
by Hui Peng, Esirige, Haibin Gu, Ruhan Gao, Yueyang Zhou, Xinna Men and Ze Wang
Drones 2026, 10(1), 27; https://doi.org/10.3390/drones10010027 (registering DOI) - 3 Jan 2026
Abstract
Cotton (Gossypium hirsutum L.) is a primary global commercial crop, and accurate monitoring of its growth and yield prediction are essential for optimizing water management. This study integrates leaf area index (LAI) data derived from unmanned aerial system (UAS) imagery into the [...] Read more.
Cotton (Gossypium hirsutum L.) is a primary global commercial crop, and accurate monitoring of its growth and yield prediction are essential for optimizing water management. This study integrates leaf area index (LAI) data derived from unmanned aerial system (UAS) imagery into the Decision Support System for Agrotechnology Transfer (DSSAT) model to improve cotton growth simulation and yield estimation. The results show that the normalized difference vegetation index (NDVI) exhibited higher estimation accuracy for the cotton LAI during the squaring stage (R2 = 0.56, p < 0.05), whereas the modified triangle vegetation index (MTVI) and enhanced vegetation index (EVI) demonstrated higher and more stable accuracy in the flowering and boll-setting stages (R2 = 0.64 and R2 = 0.76, p < 0.05). After assimilating LAI data, the optimized DSSAT model accurately represented canopy development and yield variation under different irrigation levels. Compared with the DSSAT, the assimilated model reduced yield prediction error from 40–52% to 3.6–6.3% under 30%, 60%, and 90% irrigation. These findings demonstrate that integrating UAS-derived LAI data with the DSSAT substantially enhances model accuracy and robustness, providing an effective approach for precision irrigation and sustainable cotton management. Full article
(This article belongs to the Special Issue Advances in the Use of UAVs for Monitoring and Analysis of Forage and Agricultural Crops: Technologies, Methods and Applications)
29 pages, 21723 KB  
Article
MSCANet: Multi-Scale Spatial-Channel Attention Network for Urbanization Intelligent Monitoring
by Zhande Dong, Daoye Zhu, Min Huang, Qifeng Lin, Lasse Møller-Jensen and Elisabete A. Silva
Remote Sens. 2026, 18(1), 159; https://doi.org/10.3390/rs18010159 (registering DOI) - 3 Jan 2026
Abstract
Rapid urbanization drives economic growth but also brings complex environmental and social issues, highlighting the urgent need for efficient urbanization monitoring techniques. However, datasets for urbanization monitoring are often lacking in rapidly developing urban areas. At the methodological level, Convolutional Neural Networks (CNNs) [...] Read more.
Rapid urbanization drives economic growth but also brings complex environmental and social issues, highlighting the urgent need for efficient urbanization monitoring techniques. However, datasets for urbanization monitoring are often lacking in rapidly developing urban areas. At the methodological level, Convolutional Neural Networks (CNNs) and Transformer-based models for urbanization monitoring exhibit limitations in balancing computational efficiency and global modeling. The recently emerging parallel large kernel convolutional networks partially alleviate the conflict between global modeling and computational efficiency, but they employ simple element-wise addition to fuse multi-scale features. This crude mechanism struggles to fully leverage multi-scale information. To address this, this paper takes Accra, the capital of Ghana, as a case study and proposes an urbanization monitoring framework covering both dataset construction and model design. Methodologically, we propose the Multi-Scale Spatial-Channel Attention Network (MSCANet). Its core component, the Multi-Scale Spatial-Channel Attention Module (MSCAM), jointly models spatial and channel dimensions to mitigate the common confusion problem in parallel large kernel convolutional architectures. Furthermore, we adaptively modified the MSCAM to propose the Multi-Scale Spatial-Channel Attention Feature Fusion Module (MSCA-FFM) module for effectively integrating multi-modal information during the fusion stage. Experimental results show that MSCANet achieves optimal performance on the self-built Accra dataset, with a mean intersection over union (mIoU) of 95.02%, an overall accuracy (OA) of 98.70%, and a mean F1 Score (mF1) of 97.43%. To further validate the model’s generalization capability, supplementary experiments were conducted on the public ISPRS Potsdam dataset. The results demonstrate that the MSCANet series of models remain competitive, achieving an overall mIoU of 80.92%, with particularly strong performance in the “Building” (mIoU 92.26%) and “Impervious surface” (mIoU 84.63%) categories. Full article
(This article belongs to the Special Issue GeoAI and EO Big Data Driven Advances in Earth Environmental Science (Second Edition))
16 pages, 3297 KB  
Article
Accurate Automatic Object Identification Under Complex Lighting Conditions via AI Vision on Enhanced Infrared Polarization Images
by Ruixin Jia, Hongming Fei, Han Lin, Yibiao Yang, Xin Liu, Mingda Zhang and Liantuan Xiao
Optics 2026, 7(1), 3; https://doi.org/10.3390/opt7010003 (registering DOI) - 3 Jan 2026
Abstract
Object identification (OI) is widely used in fields like autonomous driving, security, robotics, environmental monitoring, and medical diagnostics. OI using infrared (IR) images provides high visibility in low light for all-day operation compared to visible light. However, the low contrast often causes OI [...] Read more.
Object identification (OI) is widely used in fields like autonomous driving, security, robotics, environmental monitoring, and medical diagnostics. OI using infrared (IR) images provides high visibility in low light for all-day operation compared to visible light. However, the low contrast often causes OI failure in complex scenes with similar target and background temperatures. Therefore, there is a stringent requirement to enhance IR image contrast for accurate OI, and it is ideal to develop a fully automatic process for identifying objects in IR images under any lighting condition, especially in photon-deficient conditions. Here, we demonstrate for the first time a highly accurate automatic IR OI process based on the combination of polarization IR imaging and artificial intelligence (AI) vision (Yolov7), which can quickly identify objects with a high discrimination confidence level (DCL, up to 0.96). In addition, we demonstrate that it is possible to achieve accurate IR OI in complex environments, such as photon-deficient, foggy conditions, and opaque-covered objects with a high DCL. Finally, through training the model, we can identify any object. In this paper, we use a UAV as an example to conduct experiments, further expanding the capabilities of this method. Therefore, our method enables broad OI applications with high all-day performance. Full article
20 pages, 3773 KB  
Article
Design and Experimental Validation of a Tailless Flapping-Wing Micro Aerial Vehicle with Long Endurance and High Payload Capability
by Chaofeng Wu, Yiming Xiao, Jiaxin Zhao, Qingcheng Guo, Feng Cui, Xiaosheng Wu and Wu Liu
Drones 2026, 10(1), 26; https://doi.org/10.3390/drones10010026 (registering DOI) - 3 Jan 2026
Abstract
The tailless flapping-wing micro aerial vehicle (FW-MAV) exhibits capabilities for hovering and agile six-degree-of-freedom flight, demonstrating potential for missions in complex environments such as forests and indoor spaces. However, limited payload and endurance restrict their practical application. This study presents a novel tailless [...] Read more.
The tailless flapping-wing micro aerial vehicle (FW-MAV) exhibits capabilities for hovering and agile six-degree-of-freedom flight, demonstrating potential for missions in complex environments such as forests and indoor spaces. However, limited payload and endurance restrict their practical application. This study presents a novel tailless FW-MAV named X-fly, incorporating a lightweight crank-rocker mechanism with high thrust-to-weight ratio. The optimized flapping-wing mechanism achieves a maximum single-side lift of 28.7 gf, with a lift-to-power ratio of 6.67 gf/W, outperforming conventional direct-drive propellers using the same motor. The X-fly employs servo-controlled stroke planes for tailless attitude stabilization and rapid disturbance recovery. It features a 36 cm wingspan and a net weight of 18.9 g (without battery). Using a commercially available 1100 mAh battery weighing 21.6 g, it demonstrates a peak lift-to-weight ratio of 1.42 at 3.8 V and achieves a maximum flight endurance of 33.2 min. When equipped with a 250 mAh battery weighing 5.5 g, it can carry an additional payload equal to its own net weight. The X-fly attains a maximum speed of 6 m/s and demonstrates high agility during forest flight. Furthermore, it successfully performs a simulated reconnaissance mission with an onboard camera, confirming its potential for practical applications. Full article
(This article belongs to the Section Drone Design and Development)
35 pages, 760 KB  
Review
Researching Race: A Review of Principal Preparation Literature Through the Lens of Critical Race Methodology
by Rachel Roegman, Osly J. Flores and Joonkil Ahn
Educ. Sci. 2026, 16(1), 67; https://doi.org/10.3390/educsci16010067 (registering DOI) - 3 Jan 2026
Abstract
The purpose of this systematic review was to synthesize the literature to better understand how the field researched principal preparation in relation to race and racism. Using a critical race theory methodological lens (CRM), we analyzed 36 studies of current candidates or recent [...] Read more.
The purpose of this systematic review was to synthesize the literature to better understand how the field researched principal preparation in relation to race and racism. Using a critical race theory methodological lens (CRM), we analyzed 36 studies of current candidates or recent graduates with an emphasis on the research design and methods. The research chosen for inclusion was (1) empirical, (2) focused on principal preparation programs in the U.S., (3) focused on preparing candidates around issues related to race and racism, and (4) published between 2012 and 2024. Literature was drawn from three major databases that include journals in the field of educational leadership, ERIC, ProQuest, and Education Full Text, in the summer of 2025. It is important to note that our literature search focusing on peer-reviewed articles poses a limitation in terms of the comprehensiveness of the sampled literature, thus excluding potentially important information sources. To analyze the studies, we created a scoring rubric to assess the degree to which each article addressed each CRM tenet. To assess risk of bias, each article was scored by two authors, and the third author also scored the article if the first two disagreed. Our findings show that focus on race and racism was present in most studies reviewed, and almost half centered on the experiences of candidates of color. However, most of the studies reviewed conformed to traditional research paradigms and methods, as illustrated by choices related to frameworks, methods, and data sources. We offer recommendations for researchers of principal preparation who are interested in more critical work related to race and racism, and we argue for increased opportunities for scholars to meet, discuss, and collaborate across institutions around how they are studying leadership preparation for racial equity. The review is registered through Open Science Framework. Full article
(This article belongs to the Special Issue School Leadership and School Improvement, 2nd Edition)
41 pages, 4086 KB  
Perspective
Isotopic Labeling in IR Spectroscopy of Surface Species: A Powerful Approach to Advanced Surface Investigations
by Konstantin Hadjiivanov, Dimitar Panayotov and Mihail Mihaylov
Catalysts 2026, 16(1), 57; https://doi.org/10.3390/catal16010057 (registering DOI) - 3 Jan 2026
Abstract
This paper summarizes the main applications of isotopic substitution in infrared surface studies, including surface characterization, determination of the structure of adsorbed species, and clarification of catalytic reaction mechanisms. While acknowledging the key pioneering contributions to the field, we focus on the recent [...] Read more.
This paper summarizes the main applications of isotopic substitution in infrared surface studies, including surface characterization, determination of the structure of adsorbed species, and clarification of catalytic reaction mechanisms. While acknowledging the key pioneering contributions to the field, we focus on the recent developments and the future potential of the technique. The applications are grouped into two main categories, according to the extent of isotopic substitution. The first category involves systems in which one or more atoms in specific positions are fully replaced by their isotopes. This classical approach remains fundamental for establishing whether the spectral signature of a given compound is related to the presence of a specific atom. The second category concerns partial isotopic exchange. These studies unravel different vibrational interactions and provide valuable structural information that cannot be obtained through full substitution. Finally, we discuss some applications related to the mechanisms of catalytic reactions. The perspective concludes with a discussion of the emerging opportunities and future perspectives for more systematic and effective implementation of isotopic substitution in infrared surface studies. Full article
(This article belongs to the Section Catalytic Materials)
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18 pages, 2097 KB  
Article
Highly Conserved Influenza A Nucleoprotein as a Target for Broad-Spectrum Intervention: Characterization of a Monoclonal Antibody with Pan-Influenza Reactivity
by Jingrui Liu, Wenming Gao, Kunkun Zhao, Zongmei Huang, Lin Liu, Jingjing Chang, Xiaoyang Cao, Wenwen Zhou, Xiaojie Zhou, Yuman Liu, Xinsheng Li and Yapeng Song
Vet. Sci. 2026, 13(1), 45; https://doi.org/10.3390/vetsci13010045 (registering DOI) - 3 Jan 2026
Abstract
Influenza A viruses remain a persistent global health challenge due to their rapid antigenic evolution, zoonotic potential, and pandemic threat. Universal countermeasures targeting conserved viral components are urgently needed to enhance diagnostic, surveillance, and therapeutic capabilities. Here, we report the generation and characterization [...] Read more.
Influenza A viruses remain a persistent global health challenge due to their rapid antigenic evolution, zoonotic potential, and pandemic threat. Universal countermeasures targeting conserved viral components are urgently needed to enhance diagnostic, surveillance, and therapeutic capabilities. Here, we report the generation and characterization of a high-affinity monoclonal antibody (2D8 mAb) against the nucleoprotein (NP) of the H9N2 avian influenza virus, a subtype with increasing relevance to human infections. Importantly, 2D8 mAb exhibited robust cross-reactivity with a broad spectrum of influenza A viruses, including H1, H3, H5, H7, and H9 subtypes, while showing no cross-reactivity with unrelated viral pathogens. Epitope mapping identified its binding target as a highly conserved NP motif 38RFYIQMCTEL47, which is invariant across all major human influenza A lineages. Isotyping revealed 2D8 mAb to be of the IgG2b/κ subclass, with an exceptionally high titer (1:20,480,000) as determined by ELISA. Given the essential role of NP in viral replication and host adaptation, this antibody offers a powerful platform for next-generation diagnostic assays capable of detecting a wide range of human and zoonotic influenza A viruses using a single reagent. Moreover, it holds potential for guiding the design of universal antiviral strategies targeting structurally constrained regions of the influenza virus. Our findings provide a valuable resource for advancing pan-influenza A interventions, with direct implications for improving pandemic preparedness and strengthening global influenza surveillance in both clinical and public health settings. Full article
19 pages, 5000 KB  
Article
Deep Learning-Based Diffraction Identification and Uncertainty-Aware Adaptive Weighting for GNSS Positioning in Occluded Environments
by Chenhui Wang, Haoliang Shen, Yanyan Liu, Qingjia Meng and Chuang Qian
Remote Sens. 2026, 18(1), 158; https://doi.org/10.3390/rs18010158 (registering DOI) - 3 Jan 2026
Abstract
In natural canyons and urban occluded environments, signal anomalies induced by the satellite diffraction effect are a critical error source affecting the positioning accuracy of deformation monitoring. This paper proposes a deep learning-based method for diffraction signal identification and mitigation. The method utilizes [...] Read more.
In natural canyons and urban occluded environments, signal anomalies induced by the satellite diffraction effect are a critical error source affecting the positioning accuracy of deformation monitoring. This paper proposes a deep learning-based method for diffraction signal identification and mitigation. The method utilizes a LSTM network to deeply mine the time-series characteristics of GNSS observation data. We systematically analyze the impact of azimuth, elevation, SNR, and multi-feature combinations on model recognition performance, demonstrating that single features suffer from incomplete information or poor discrimination. Experimental results show that the multi-dimensional feature scheme of “SNR + Elevation + Azimuth” effectively characterizes both signal strength and spatial geometric information, achieving complementary feature advantages. The overall recognition accuracy of the proposed method reaches 84.2%, with an accuracy of 88.0% for anomalous satellites that severely impact positioning precision. Furthermore, we propose an Adaptive Weighting Method for Diffraction Mitigation Based on Uncertainty Quantification. This method constructs a variance inflation model using the probability vector output from the LSTM Softmax layer and introduces Information Entropy to quantify prediction uncertainty, ensuring that the weighting model possesses protection capability when the model fails or is uncertain. In processing a set of GNSS data collected in a highly-occluded environment, the proposed method significantly outperforms traditional cut-off elevation and SNR mask strategies, improving the AFR to 99.9%, and enhancing the positioning accuracy in the horizontal and vertical directions by an average of 80.1% and 76.4%, respectively, thereby effectively boosting the positioning accuracy and reliability in occluded environments. Full article
(This article belongs to the Special Issue High-Precision Urban Positioning: GNSS and Multi-Sensor Fusion Technologies)
24 pages, 1201 KB  
Review
The Interplay of One-Carbon Metabolism, Mitochondrial Function, and Developmental Programming in Ruminant Livestock
by Kazi Sarjana Safain, Kendall C. Swanson and Joel S. Caton
J. Dev. Biol. 2026, 14(1), 3; https://doi.org/10.3390/jdb14010003 (registering DOI) - 3 Jan 2026
Abstract
Maternal nutrition during gestation profoundly influences fetal growth, organogenesis, and long-term offspring performance through developmental programming. Among the molecular mechanisms responsive to maternal nutrient availability, one-carbon metabolism plays a central role by integrating folate, methionine, choline, and vitamin B12 pathways that regulate [...] Read more.
Maternal nutrition during gestation profoundly influences fetal growth, organogenesis, and long-term offspring performance through developmental programming. Among the molecular mechanisms responsive to maternal nutrient availability, one-carbon metabolism plays a central role by integrating folate, methionine, choline, and vitamin B12 pathways that regulate methylation, nucleotide synthesis, and antioxidant defense. These processes link maternal nutritional status to epigenetic remodeling, cellular proliferation, and redox balance during fetal development. Mitochondria act as nutrient sensors that translate maternal metabolic cues into bioenergetic and oxidative signals, shaping tissue differentiation and metabolic flexibility. Variations in maternal diet have been associated with shifts in fetal amino acid, lipid, and energy metabolism, suggesting adaptive responses to constrained intrauterine environments. This review focuses on the molecular interplay between one-carbon metabolism, mitochondrial function, and metabolomic adaptation in developmental programming of ruminant livestock. Understanding these mechanisms offers opportunities to design precision nutritional strategies that enhance fetal growth, offspring productivity, and long-term resilience in livestock production systems. Full article
(This article belongs to the Special Issue Mitochondrial Function and Dysfunction in Developmental Biology Metabolism)
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13 pages, 420 KB  
Article
Home-Based REM Sleep Without Atonia in Patients with Parkinson’s Disease: A Post Hoc Analysis of the ZEAL Study
by Hiroshi Kataoka, Masahiro Isogawa, Hitoki Nanaura, Hiroyuki Kurakami, Miyoko Hasebe, Kaoru Kinugawa, Takao Kiriyama, Tesseki Izumi, Masato Kasahara and Kazuma Sugie
NeuroSci 2026, 7(1), 6; https://doi.org/10.3390/neurosci7010006 (registering DOI) - 3 Jan 2026
Abstract
REM sleep behavioral disorder (RBD) is of increasing interest in Parkinson’s disease (PD). Previous studies exploring the association between REM sleep without atonia (RWA) and clinical PD features or other objective sleep metrics are scarce and have used PSG findings. A mobile electroencephalography [...] Read more.
REM sleep behavioral disorder (RBD) is of increasing interest in Parkinson’s disease (PD). Previous studies exploring the association between REM sleep without atonia (RWA) and clinical PD features or other objective sleep metrics are scarce and have used PSG findings. A mobile electroencephalography (EEG)/electrooculography (EOG) recording system with two channels can objectively measure sleep parameters, including RWA, during natural sleep at home. We investigated whether RWA measured on a portable recording device at home could be associated with clinical PD features or other sleep metrics using baseline data from the ZEAL study. Differences between patients with and without RWA was analyzed using ANCOVA test. REM sleep length was significantly longer in patients with RWA than in those without RWA. A multivariate comparison using ANCOVA showed a significant difference in log-transformed REM sleep duration of patients with RWA after adjustment for potential confounders (adjusted mean difference of 1.203; 95% confidence interval 0.468 to 1.937; p = 0.003). The strength of this study was that it evaluated the association between RWA during natural sleep at home and clinical variables as well as other sleep metrics. The major result was that patients with and without RWA did not differ in their clinical variables, and there was no relation between RWA and objective sleep metrics other than REM sleep. The duration of REM sleep may be associated with RWA during natural sleep at home. Full article
(This article belongs to the Special Issue Parkinson's Disease Research: Current Insights and Future Directions)
53 pages, 1299 KB  
Review
Mapping Global Research Trends on Aflatoxin M1 in Dairy Products: An Integrative Review of Prevalence, Toxicology, and Control Approaches
by Marybel Abi Rizk, Lea Nehme, Selma P. Snini, Hussein Hassan, Florence Mathieu and Youssef El Rayess
Foods 2026, 15(1), 166; https://doi.org/10.3390/foods15010166 (registering DOI) - 3 Jan 2026
Abstract
Aflatoxin M1 (AFM1), a hydroxylated metabolite of aflatoxin B1 (AFB1), is a potent hepatotoxic and carcinogenic compound frequently detected in milk and dairy products. Its thermal stability and resistance to processing make it a persistent public health [...] Read more.
Aflatoxin M1 (AFM1), a hydroxylated metabolite of aflatoxin B1 (AFB1), is a potent hepatotoxic and carcinogenic compound frequently detected in milk and dairy products. Its thermal stability and resistance to processing make it a persistent public health concern, especially in regions prone to fungal contamination of animal feed. This review integrates bibliometric mapping (2015–2025) with toxicological and mitigation perspectives to provide a comprehensive understanding of AFM1. The bibliometric analysis reveals a sharp global rise in research output over the last decade, with Iran, China, and Brazil emerging as leading contributors and Food Control identified as the most prolific journal. Five research clusters were distinguished: feed contamination pathways, analytical detection, toxicological risk, regulatory frameworks, and mitigation strategies. Toxicological evidence highlights AFM1’s mutagenic and hepatocarcinogenic effects, intensified by co-exposure to other mycotoxins or hepatitis B infection. Although regulatory limits range from 0.025 µg/kg in infant formula (EU) to 0.5 µg/kg in milk (FDA), non-compliance remains prevalent in developing regions. Current mitigation approaches—adsorbents (bentonite, zeolite), oxidation (ozone, hydrogen peroxide), and biological detoxification via lactic acid bacteria and yeasts—show promise but require optimization for industrial application. Persistent challenges include climatic variability, inadequate feed monitoring, and heterogeneous regulations. This review emphasizes the need for harmonized surveillance, improved analytical capacity, and sustainable intervention strategies to ensure dairy safety and protect consumer health. Full article
(This article belongs to the Section Food Toxicology)
21 pages, 1167 KB  
Review
Iron Therapy in Pediatric Iron Deficiency and Iron-Deficiency Anemia: Efficacy, Safety, and Formulation-Specific Trade-Offs—A Narrative Review
by Guido Leone, Marta Arrabito, Giovanna Russo and Milena La Spina
Hematol. Rep. 2026, 18(1), 6; https://doi.org/10.3390/hematolrep18010006 (registering DOI) - 3 Jan 2026
Abstract
Background/Objectives: Iron deficiency (ID) is the most common nutritional disorder in childhood worldwide. It has profound consequences for growth, neurodevelopment, behaviour, and overall health. Despite the long-standing efficacy of oral ferrous salts, their poor gastrointestinal tolerability and adherence challenges have spurred the [...] Read more.
Background/Objectives: Iron deficiency (ID) is the most common nutritional disorder in childhood worldwide. It has profound consequences for growth, neurodevelopment, behaviour, and overall health. Despite the long-standing efficacy of oral ferrous salts, their poor gastrointestinal tolerability and adherence challenges have spurred the development of alternative formulations and innovative dosing strategies. Methods: We conducted a narrative review of national and international guidelines, pediatric randomized controlled trials, observational and cohort studies, cost-effectiveness analyses, diagnostic method papers, and reviews, with emphasis on diagnostic innovations, therapeutic outcomes, tolerability, and formulation-specific efficacy. Results: Ferrous salts remain the gold standard for efficacy, low cost, and guideline endorsement, but up to 40% of children experience GI intolerance. Therefore, a lower dosage of ferrous salts has been proposed for IDA as still being an efficacious and better-tolerated schedule. Also, alternate-day dosing improves absorption and tolerability and is supported by a recent pediatric RCT. Newer formulations—ferric polymaltose, ferrous bisglycinate, co-processed bisglycinate with alginate (Feralgine™), and vesicular encapsulated forms such as sucrosomial and liposomal ferric pyrophosphate—showed improved tolerability and palatability, supporting adherence with hematologic outcomes comparable to ferrous salts, particularly in children with intolerance, malabsorption, or inflammatory comorbidities. Intravenous iron is effective and safe with modern preparations and is reserved for severe anemia, malabsorption, or oral therapy failure. Conclusions: Oral ferrous salts should remain the first-line therapy in pediatric ID/IDA. Future pediatric trials should prioritize head-to-head comparisons of formulations, hepcidin-guided dosing, and patient-centred outcomes, including neurocognitive trajectories and quality of life. Full article
(This article belongs to the Special Issue Anaemia in Focus: Challenges and Solutions in Haematology)
41 pages, 2833 KB  
Article
Emerging Resident Concerns as Signals of a Paradigm Shift in the Spatial Infrastructure for Integrated Community Care: Focusing on Yeonpyeong Island, a Medically Isolated Declining Region of Korea
by Yeun Sook Lee, Eun Jung Jun and Jae Hyun Park
Buildings 2026, 16(1), 218; https://doi.org/10.3390/buildings16010218 (registering DOI) - 3 Jan 2026
Abstract
Across East Asia, rapid population aging and regional decline threaten the sustainability of rural and island communities. Yeonpyeong Island provides a critical context for examining how spatial infrastructure shapes older residents’ daily challenges. The aim of this study is to identify how older [...] Read more.
Across East Asia, rapid population aging and regional decline threaten the sustainability of rural and island communities. Yeonpyeong Island provides a critical context for examining how spatial infrastructure shapes older residents’ daily challenges. The aim of this study is to identify how older adults evaluate their housing and community environments and to determine whether these perceptions signal a transition toward more integrated and community-based care settings. Using a primary quantitative survey of 102 older residents, supplemented by contextual input from a local representative, the study analyzes how health decline, mobility constraints, and housing obsolescence interact with aspirations for service-integrated and socially connected living. Composite scores for perceived home modification needs remained consistently in the mid-to-upper range (approximately 3.5–4.0 on a 5-point scale). Acceptance of alternative, cohousing-type community housing also remained above the midpoint (approximately 3.5–4.1), reflecting an unusually high level of openness in a setting traditionally characterized by low receptivity to residential change and limited local housing alternatives. Safety risks, poor accessibility, and inadequate facilities function as push factors, while preferences for shared programs, proximity-based reassurance, and integrated hubs operate as pull factors, together signaling readiness for more supportive communal living. By integrating Push–Pull Theory with Environmental Press and Life-Space perspectives, the study contributes theoretically by extending these frameworks to the community scale and empirically by providing resident-level evidence from an under-researched island context. The findings highlight how older adults act as evaluators of their environments, articulating practical signals for spatial restructuring and integrated care planning. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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18 pages, 746 KB  
Review
AML Disparities Across Racial Ancestry Groups: A Spotlight on the NPM1 Mutations
by Sarvath Aafreen Sanaullah, Pierre-Alexandre Vidi and Timothy S. Pardee
Int. J. Mol. Sci. 2026, 27(1), 510; https://doi.org/10.3390/ijms27010510 (registering DOI) - 3 Jan 2026
Abstract
Racial and ethnic disparities in acute myeloid leukemia (AML) survival persist despite advances in treatment, with non-Hispanic black (NHB) patients and Hispanic patients often experiencing worse outcomes than Non-Hispanic White (NHW) patients due to a combination of clinical, socioeconomic, and biological factors. This [...] Read more.
Racial and ethnic disparities in acute myeloid leukemia (AML) survival persist despite advances in treatment, with non-Hispanic black (NHB) patients and Hispanic patients often experiencing worse outcomes than Non-Hispanic White (NHW) patients due to a combination of clinical, socioeconomic, and biological factors. This review focuses on these disparities and emphasizes potential contributions of biology, as illustrated by the effects of the nucleophosmin 1 (NPM1) mutation. Mutation landscapes and chromosomal abnormalities strongly influence AML patient outcomes. While AML cases with NPM1 mutations are associated with favorable prognoses for NHW patients, NHB patients with NPM1-mutated AML have adverse outcomes. Thus, treatment algorithms and prognostic systems based on outcomes from a single racial ancestry group are inadequate. Beyond the more traditional socioeconomic determinants of health, addressing disparities in AML to achieve equity in care requires exploring biological factors linked to ancestry that shape treatment response. Full article
(This article belongs to the Special Issue Molecular Research in Hematologic Malignancies)
6 pages, 305 KB  
Editorial
Advances in Artificial Intelligence for Plant Research
by Guoxiong Zhou, Liujun Li and Xiaoyulong Chen
Plants 2026, 15(1), 142; https://doi.org/10.3390/plants15010142 (registering DOI) - 3 Jan 2026
Abstract
Editorial on Research Topic [...] Full article
(This article belongs to the Special Issue Advances in Artificial Intelligence for Plant Research)
14 pages, 1308 KB  
Article
A Selective RAG-Enhanced Hybrid ML-LLM Framework for Efficient and Explainable Fatigue Prediction Using Wearable Sensor Data
by Soonho Ha, Taeyoung Lee, Hyungjun Seo, Sujung Yoon and Hwamin Lee
Bioengineering 2026, 13(1), 58; https://doi.org/10.3390/bioengineering13010058 (registering DOI) - 3 Jan 2026
Abstract
Fatigue is a multifactorial phenomenon affecting both physical and psychological performance, particularly in high-stress occupations. Although wearable sensors enable continuous monitoring, conventional machine-learning (ML) models can produce unstable, weakly calibrated, and opaque predictions in real-world settings. To improve reliability and interpretability, we developed [...] Read more.
Fatigue is a multifactorial phenomenon affecting both physical and psychological performance, particularly in high-stress occupations. Although wearable sensors enable continuous monitoring, conventional machine-learning (ML) models can produce unstable, weakly calibrated, and opaque predictions in real-world settings. To improve reliability and interpretability, we developed a selective Retrieval-Augmented Generation (RAG)–enhanced hybrid ML–LLM framework that integrates the efficiency of ML with the reasoning capability of large language models (LLMs). Using wearable and ecological momentary assessment data from 297 emergency responders (9543 seven-day windows), logistic regression, XGBoost, and LSTM models were trained to classify fatigue levels dichotomized by the median of daily tiredness scores. The LLM was selectively activated only for borderline ML outputs (0.45 ≤ p ≤ 0.55), using symbolic rules and retrieved analog examples. In the uncertainty region, performance improved from 0.556/0.684/0.635/0.659 to 0.617/0.703/0.748/0.725 (accuracy/precision/recall/F1). On the full test set, performance similarly improved from 0.707/0.739/0.918/0.819 to 0.718/0.741/0.937/0.827, with gains confirmed by McNemar’s paired comparison test (p < 0.05). SHAP-based ML interpretation and LLM reasoning analyses independently identified short-term sleep duration and heart-rate variability as dominant predictors, providing transparent explanations for model behavior. This framework enhances classification robustness, interpretability, and efficiency, offering a scalable solution for real-world fatigue monitoring. Full article
(This article belongs to the Special Issue Bringing Precision Medicine into the Clinical Practice: The Role of Explainable Artificial Intelligence and Interpretable Models)
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21 pages, 2944 KB  
Article
Geraniin Mitigates Neuropathic Pain Through Antioxidant, Anti-Inflammatory, and Nitric Oxide Modulation in a Rat Model of Chronic Constriction Injury
by Chih-Chuan Yang, Mao-Hsien Wang, Yi-Wen Lin, Chih-Hsiang Fang, Yu-Chuan Lin, Kuo-Chi Chang and Cheng-Chia Tsai
Int. J. Mol. Sci. 2026, 27(1), 507; https://doi.org/10.3390/ijms27010507 (registering DOI) - 3 Jan 2026
Abstract
Neuropathic pain (NPP) remains therapeutically challenging, with oxidative/nitrosative stress and neuroinflammation—amplified by nitric oxide (NO)—as key drivers. This study investigated geraniin (GRN), a naturally occurring hydrolyzable ellagitannin widely distributed in various plant species, including Phyllanthus spp. and Nephelium lappaceum (rambutan), in a rat [...] Read more.
Neuropathic pain (NPP) remains therapeutically challenging, with oxidative/nitrosative stress and neuroinflammation—amplified by nitric oxide (NO)—as key drivers. This study investigated geraniin (GRN), a naturally occurring hydrolyzable ellagitannin widely distributed in various plant species, including Phyllanthus spp. and Nephelium lappaceum (rambutan), in a rat model of sciatic nerve chronic constriction injury (CCI), focusing on NO-pathway involvement. Male Wistar rats (n = 8/group) received intraperitoneal GRN (3, 10, 30, or 100 mg/kg) or vehicle (1% DMSO in saline) daily for 21 days. Behavioral (thermal hyperalgesia, mechanical allodynia, sciatic functional index), electrophysiological (nerve conduction velocity), and biochemical markers—oxidative/nitrosative stress (nitrite, MDA), antioxidant defenses (GSH, SOD, CAT), inflammation (TNF-α, IL-1β, IL-6, MPO), and apoptosis (caspase-3)—were quantified. L-arginine or L-NAME was co-administered to probe NO signaling. GRN at 30 and 100 mg/kg produced significant antinociceptive and neuroprotective effects; 30 mg/kg was selected for detailed analysis. By day 21, GRN improved pain thresholds and nerve conduction, enhanced antioxidant capacity, suppressed inflammatory mediators, and reduced caspase-3 activity. L-arginine reversed, whereas L-NAME potentiated these effects, confirming NO-dependent modulation. Collectively, GRN mitigates CCI-induced NPP via coordinated antioxidant, anti-inflammatory, and anti-apoptotic actions, supporting its potential as a multi-target candidate for pharmacokinetic and translational development. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Phytochemicals in Antioxidation, Antimicrobial, and Cytoprotective Properties)
25 pages, 24683 KB  
Article
APOBEC3C Suppresses Prostate Cancer by Regulating Key Molecules Involved in Cellular Inflammation, Cell Cycle Arrest, and DNA Damage Response
by Zhongqi Pang, Jianshe Wang, Yidan Xu, Bo Ji, Minghua Ren and Beichen Ding
Cancers 2026, 18(1), 170; https://doi.org/10.3390/cancers18010170 (registering DOI) - 3 Jan 2026
Abstract
Background: Prostate cancer (PCa) is a prevalent malignancy with a rising incidence. Advanced PCa, often resistant to therapy, remains a major clinical challenge, underscoring the need to identify novel molecular drivers. Methods: Utilizing transcriptomic data from the TCGA and GEO databases, we identified [...] Read more.
Background: Prostate cancer (PCa) is a prevalent malignancy with a rising incidence. Advanced PCa, often resistant to therapy, remains a major clinical challenge, underscoring the need to identify novel molecular drivers. Methods: Utilizing transcriptomic data from the TCGA and GEO databases, we identified APOBEC3C (A3C) as a key candidate through WGCNA, differential expression analysis, and LASSO regression. Its clinical relevance was assessed via Kaplan–Meier survival analysis. Then, we validated A3C expression patterns using immunohistochemistry and Western blot in normal and malignant prostate cell lines. The functional effects of A3C on proliferation, migration, and invasion and mechanisms of such were evaluated through in vitro gain- and loss-of-function assays (CCK-8, Ki67 staining, wound healing, Transwell, Western blot, etc.). Results:A3C was significantly downregulated in PCa, and this low expression strongly correlated with adverse clinicopathological features, including advanced T stage, higher Gleason scores, and worse survival. Bioinformatically, high A3C expression was associated with an activated anti-tumor immune microenvironment, characterized by enhanced CD8+ T cell infiltration, reduced M2 macrophage abundance, and upregulation of the immune checkpoint CD40. In vitro, A3C overexpression effectively suppressed PCa cell proliferation, migration, and invasion, while its knockdown promoted these malignant phenotypes. Mechanistically, A3C enhances the expression of the STING1 and its downstream related molecules Caspase-1, IL-18, and IL-1β; upregulates DNA damage-protective genes (GSTP1 and GPX3); and enhances the expression of cell cycle regulator GAS1. Conclusions: This study establishes A3C as a suppressor in PCa, which impedes tumor progression by regulating key molecules involved in cellular inflammation, cell cycle arrest, and DNA damage response. Full article
(This article belongs to the Section Molecular Cancer Biology)
22 pages, 4932 KB  
Article
Poly(levodopa)-Modified β-(1 → 3)-D-Glucan Hydrogel Enriched with Triangle-Shaped Nanoparticles as a Biosafe Matrix with Enhanced Antibacterial Potential
by Anna Michalicha, Vladyslav Vivcharenko, Anna Tomaszewska, Magdalena Kulpa-Greszta, Barbara Budzyńska, Dominika Fila, Judit Buxadera-Palomero, Agnieszka Krawczyńska, Cristina Canal, Dorota Kołodyńska, Anna Belcarz-Romaniuk and Robert Pązik
Molecules 2026, 31(1), 181; https://doi.org/10.3390/molecules31010181 (registering DOI) - 3 Jan 2026
Abstract
Biomaterials derived from natural-origin polymers often lack the desired functionality and additional features, such as antibacterial properties, which could be beneficial in the design of modern wound dressings. Our research aimed to fabricate biosafe antibacterial dressings through the modification of curdlan-based hydrogels with [...] Read more.
Biomaterials derived from natural-origin polymers often lack the desired functionality and additional features, such as antibacterial properties, which could be beneficial in the design of modern wound dressings. Our research aimed to fabricate biosafe antibacterial dressings through the modification of curdlan-based hydrogels with triangle-shaped silver nanoparticles (AgTNPs) and poly(L-DOPA) (PL). The prepared hydrogels, including physicochemical, structural, biological, and antibacterial assessments, were thoroughly characterized. All formulations were confirmed to be non-toxic toward eukaryotic cells. The presence of PL in the hydrogels significantly reduced mortality in the zebrafish larvae model, highlighting the improved biocompatibility of the hydrogels. The three-component hydrogel (CUR-PL-AgT) demonstrated a high antibacterial effectiveness against Staphylococcus aureus and Pseudomonas aeruginosa. Additionally, the same three-component material outperformed a hydrogel containing only AgTNPs in promoting blood clot formation. Furthermore, PL enhanced the heat generating capability of hydrogels, showing their potential in medical applications where the temperature effects can stimulate biological processes of different natures. Full article
(This article belongs to the Special Issue Biopolymers for Drug Delivery Systems)
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31 pages, 3358 KB  
Article
Exploring Sierra Leone’s Water Sector: A Governance and Stakeholder Analysis
by Henrietta E. M. George-Williams, Dexter V. L. Hunt and Christopher D. F. Rogers
Sustainability 2026, 18(1), 491; https://doi.org/10.3390/su18010491 (registering DOI) - 3 Jan 2026
Abstract
Sierra Leone’s water sector faces a “paradox of scarcity in abundance”: despite plentiful natural water resources, access to safe, reliable, and affordable supply remains limited, particularly for vulnerable populations. This paper investigates the governance dynamics and stakeholder relationships that underpin these challenges, drawing [...] Read more.
Sierra Leone’s water sector faces a “paradox of scarcity in abundance”: despite plentiful natural water resources, access to safe, reliable, and affordable supply remains limited, particularly for vulnerable populations. This paper investigates the governance dynamics and stakeholder relationships that underpin these challenges, drawing on a mixed-methods approach combining desktop research, surveys, and 37 semi-structured interviews. Using stakeholder and social network analysis, the study identifies key actors and their roles, interests, influence, and interdependencies, while also examining systemic barriers across social, technical, economic, environmental, and political dimensions. The findings reveal a highly fragmented governance landscape, characterised by overlapping mandates, donor dependency, weak enforcement, and the marginalisation of community voices. Although recent reforms—including new regulatory institutions, donor-funded infrastructure projects, and community-based initiatives—represent progress, they remain largely piecemeal, reactive, and insufficient to address entrenched structural deficiencies. The paper concludes that Sierra Leone’s water crisis is less a problem of resource scarcity than one of governance. Achieving sustainable water security requires integrated, system-wide reforms that strengthen institutional capacity, enhance coordination, enforce accountability, and embed inclusive stakeholder participation. Full article
(This article belongs to the Section Sustainable Water Management)
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35 pages, 10452 KB  
Review
Recent Advances of g-C3N4/LDHs Composite Photocatalysts in Water Pollution Treatment
by Jing Li, Yaping Guo and Jie Bai
Molecules 2026, 31(1), 180; https://doi.org/10.3390/molecules31010180 (registering DOI) - 3 Jan 2026
Abstract
Water pollution poses a pressing global environmental threat, driving an urgent need for efficient, stable, and eco-friendly water treatment techniques. Semiconductor photocatalysis has emerged as a highly promising solution, utilizing solar energy to thoroughly degrade pollutants under mild conditions without secondary pollution. Among [...] Read more.
Water pollution poses a pressing global environmental threat, driving an urgent need for efficient, stable, and eco-friendly water treatment techniques. Semiconductor photocatalysis has emerged as a highly promising solution, utilizing solar energy to thoroughly degrade pollutants under mild conditions without secondary pollution. Among numerous photocatalysts, the graphitic carbon nitride (g-C3N4)/layered double hydroxides (LDHs) heterostructures represent a kind of high-performance photocatalysts that combine the integrated advantages of both components. These composites exhibit enhanced visible-light absorption, a highly efficient charge separation and transfer, and a significantly increased specific surface area that promotes the enrichment and degradation of pollutants. The synergistic interaction between g-C3N4 and LDHs not only mitigates their individual limitations but also creates a superior photocatalytic system with improved adsorption capacity and reaction kinetics. This review systematically summarizes recent advances in g-C3N4/LDHs composite photocatalysts for aquatic pollutant removal. It elaborates on the structural synergies, synthesis routes, and optimization strategies, with a particular focus on applications and mechanistic insights into the degradation of various pollutants-including organic dyes, drugs, and phenolics. Finally, the review outlines current challenges and future research directions, such as deepening mechanistic understanding, designing multifunctional systems, and advancing toward scalable implementation, providing a valuable reference for developing next-generation photocatalytic water treatment technologies. Full article
(This article belongs to the Section Photochemistry)
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22 pages, 606 KB  
Article
Smart Hospitality in the 6G Era: The Role of AI and Terahertz Communication in Next-Generation Hotel Infrastructure
by Vuk Mirčetić, Aleksandra Vujko, Martina Arsić, Darjan Karabašević and Svetlana Vukotić
World 2026, 7(1), 4; https://doi.org/10.3390/world7010004 (registering DOI) - 3 Jan 2026
Abstract
This study investigates how next-generation digital infrastructures—terahertz (THz) communication and AI-driven network orchestration—shape perceived service quality, luxury perception, and loyalty within the context of luxury hospitality. An empirical survey was conducted among 693 guests at Torre Melina Gran Meliá (Barcelona) between June 2024 [...] Read more.
This study investigates how next-generation digital infrastructures—terahertz (THz) communication and AI-driven network orchestration—shape perceived service quality, luxury perception, and loyalty within the context of luxury hospitality. An empirical survey was conducted among 693 guests at Torre Melina Gran Meliá (Barcelona) between June 2024 and June 2025. Using a refined 38-item Likert-scale instrument, a three-factor structure was validated: (F1) Network Performance (speed, stability, coverage, seamless roaming, and multi-device reliability), (F2) Luxury Perception (modernity, innovation, and brand image), and (F3) Service Loyalty (satisfaction, return intentions, recommendations, and willingness to pay a premium). The results reveal that superior network performance functions both practically and symbolically. Functionally, it enables uninterrupted video calls, smooth streaming, low-latency gaming, and reliable multi-device usage—now considered essential utilities for contemporary travelers. Symbolically, high-performing and intelligently managed connectivity conveys technological leadership and exclusivity, thereby enhancing the hotel’s luxury image. Collectively, these effects create a “virtuous cycle” in which technical excellence reinforces perceptions of luxury, which in turn amplifies satisfaction and loyalty behaviors. From a managerial perspective, advanced connectivity should be viewed as a strategic investment and brand differentiator rather than a cost center. THz-ready, AI-orchestrated networks support personalization, dynamic bandwidth allocation (i.e., real-time adjustment of network capacity in response to fluctuating user demand), and monetizable premium service tiers, directly strengthening guest retention and brand equity. Ultimately, next-generation connectivity emerges not as an ancillary amenity but as a defining pillar of luxury hospitality in the emerging 6G era. Full article
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29 pages, 9907 KB  
Article
Climate-Driven Cryospheric Changes and Their Impacts on Glacier Runoff Dynamics in the Northern Tien Shan
by Aigul N. Akzharkynova, Berik Iskakov, Gulnara Iskaliyeva, Nurmakhambet Sydyk, Rustam Abdrakhimov, Alima A. Amangeldi, Aibek Merekeyev and Aleksandr Chigrinets
Atmosphere 2026, 17(1), 63; https://doi.org/10.3390/atmos17010063 (registering DOI) - 3 Jan 2026
Abstract
Glaciers in the Northern Tien Shan are a major source of Ile River runoff, supplying water to Kazakhstan’s largest city, Almaty. Under ongoing climate warming, their degradation alters the magnitude and seasonality of river discharge, increasing water-resource vulnerability. This study quantifies long-term changes [...] Read more.
Glaciers in the Northern Tien Shan are a major source of Ile River runoff, supplying water to Kazakhstan’s largest city, Almaty. Under ongoing climate warming, their degradation alters the magnitude and seasonality of river discharge, increasing water-resource vulnerability. This study quantifies long-term changes in glacier area, firn-line elevation, and glacier runoff in the northern Tien Shan from 1955 to 2021. The analysis uses multi-decadal meteorological observations, hydrological records, multi-temporal Landsat-7/8 and Sentinel-2 imagery, and DEMs combined with empirical and semi-empirical runoff estimation methods. The glacier area has declined by more than 45–60% since 1955, accompanied by a rise in firn-line altitude from ~3400 to 3700 m. At the Mynzhylky station, mean summer air temperature increased by 0.88 °C, reflecting persistent warming in glacierized elevations. The contribution of glacier meltwater to annual discharge decreased from ~32% in 1955–1990 to ~25% in 1991–2021, while total and vegetation-period runoff increased due to modified seasonal hydrological conditions. These results demonstrate the impact of climate warming on glacier-fed runoff in the Northern Tien Shan and highlight the need to integrate glacier degradation into water-resource management and long-term water-security assessments. Full article
(This article belongs to the Special Issue Climate Change in the Cryosphere and Its Impacts)
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23 pages, 9412 KB  
Article
Ballistic Performance of 7A52/7A62 Aluminum Alloy Laminates: A Numerical Investigation of Configuration Effect
by Qunjiao Wang, Meilin Yin, Jiangong Zhou, Xinyu Liu, Hui Zhang, Ruibin Mei, Zejun Chen, Yu Cao, Qiang Wang, Fuguan Cong and Yunlong Zhang
Materials 2026, 19(1), 179; https://doi.org/10.3390/ma19010179 (registering DOI) - 3 Jan 2026
Abstract
This study presents a systematic numerical investigation into the ballistic performance of 7A52/7A62 aluminum alloy laminated plates with varying configurations. The dynamic mechanical behavior of the base alloys, 7A52 and 7A62, was first characterized experimentally, and the corresponding Johnson-Cook (J-C) constitutive parameters were [...] Read more.
This study presents a systematic numerical investigation into the ballistic performance of 7A52/7A62 aluminum alloy laminated plates with varying configurations. The dynamic mechanical behavior of the base alloys, 7A52 and 7A62, was first characterized experimentally, and the corresponding Johnson-Cook (J-C) constitutive parameters were calibrated. Using the calibrated J-C model, a series of numerical simulations were performed on several structural configurations, including single-layer (7A52-A, 7A62-B), double-layer (AB, BA), and four-layer laminates (ABAB, BAAB, ABBA, BABA). The results demonstrate that four-layer laminates exhibit markedly better ballistic performance than monolithic and double-layer plates. Among them, the ABAB stacking sequence—arranged in an alternating soft–hard–soft–hard pattern—shows the optimal performance, yielding a residual projectile velocity of only 256 m/s. This represents an approximately 27% reduction compared to the monolithic high-strength 7A62 plate. The overall ranking of ballistic performance is as follows: ABAB > BAAB > ABBA > BABA. Energy-based analysis further indicates that multi-interface delamination, coupled with plastic deformation and damage evolution, improves the energy-absorption efficiency of the laminated plates and thus enhances their ballistic resistance. This study offers valuable guidance for the lightweight design of laminated 7XXX-series aluminum alloy protective plates. Full article
(This article belongs to the Special Issue Advances in Al/Mg/Cu Alloys and Their Composites: Welding, Additive Manufacturing, Heterogeneous Microstructures, and Mechanical Properties)
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17 pages, 2223 KB  
Article
Physicochemical Properties and Diatom Diversity in the Sediments of Lake Batur: Insights from a Volcanic Alkaline Ecosystem
by Ulvienin Harlianti, Silvia Jannatul Fajar, Satria Bijaksana, Irwan Iskandar, Rachmat Fajar Lubis, Rey Donne S. Papa, Putu Billy Suryanata and Ni Komang Tri Suandayani
Earth 2026, 7(1), 5; https://doi.org/10.3390/earth7010005 (registering DOI) - 3 Jan 2026
Abstract
Lake Batur, located within a volcanic caldera in Bali, Indonesia, is subjected to anthropogenic pressures related to agriculture, aquaculture, tourism, and religious activities, which may affect its water quality and ecology condition. This study investigates the physicochemical properties of lake water and diatom [...] Read more.
Lake Batur, located within a volcanic caldera in Bali, Indonesia, is subjected to anthropogenic pressures related to agriculture, aquaculture, tourism, and religious activities, which may affect its water quality and ecology condition. This study investigates the physicochemical properties of lake water and diatom assemblages preserved in lake sediments to provide insight into environmental conditions in this volcanic alkaline ecosystem. Water quality parameters, including pH, temperature, electrical conductivity (EC), and total dissolved solids (TDS), were measured. Vertical profiles of temperature and conductivity revealed stable stratification, with minimal variation below 20 m water depth. Elevated nitrogen concentrations, including nitrate (NO3−), nitrite (NO2−), and ammonium (NH4+), were observed, particularly in the southern basin, suggesting localized nutrient enrichment. Scanning electron microscopy (SEM) analysis of lake sediment samples identified ten diatom genera, including Ulnaria, Denticula, and Discostella, which are commonly associated with nutrient-enriched freshwater environments. Overall, the results indicate that Lake Batur exhibits conditions consistent with early-stage eutrophication in localized areas, highlighting the importance of continuous monitoring and targeted management strategies to protect the ecological integrity of this volcanic lake system. Full article
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24 pages, 2917 KB  
Article
A Demand Prediction-Driven Algorithm for Dynamic Shared Autonomous Vehicle Relocation: Integrating Deep Learning and System Optimization
by Hui-Yong Zhang, Kun Zhao, Wei-Xin Yu, Meng Zeng, Si-Qi Wang and Fang Zong
Sustainability 2026, 18(1), 489; https://doi.org/10.3390/su18010489 (registering DOI) - 3 Jan 2026
Abstract
This paper develops a dynamic repositioning mechanism for shared autonomous vehicles (SAVs) driven by travel demand. A prediction model for SAV travel demand is constructed by the proposed GRU-FC network. On this basis, an integer programming model for empty-vehicle dispatching which aims to [...] Read more.
This paper develops a dynamic repositioning mechanism for shared autonomous vehicles (SAVs) driven by travel demand. A prediction model for SAV travel demand is constructed by the proposed GRU-FC network. On this basis, an integer programming model for empty-vehicle dispatching which aims to maximize the SAV revenue while minimizing the costs of vehicle relocation and operation is formulated. The results indicate that, relative to relying solely on natural vehicle dispatching, the proposed dispatching scheme reduces empty vehicle dispatches by 21.00% and increases total system profit by 38.89%. The findings theoretically improve the dynamic optimization theory of SAV dispatching and provide theoretical support for algorithm design based on the “demand-pull” principle. The method proposed in this paper is beneficial to optimizing the dynamic vehicle dispatching theory of SAVs. It helps to boost system revenue, reduce empty driving costs, alleviate traffic pressure, and lower energy consumption and environmental pollution, thereby fostering sustainable urban mobility and supporting the Sustainable Development Goals of clean energy and sustainable cities. Full article
(This article belongs to the Special Issue Sustainable Transportation Systems and Travel Behaviors)
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