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14 pages, 248 KB

Open AccessArticle

Norwegian Adolescents’ Multidimensional Understandings of Wellbeing: A Qualitative Study

by Sultana Ali Norozi and Anne Torhild Klomsten

Behav. Sci. 2026, 16(1), 81; https://doi.org/10.3390/bs16010081 (registering DOI) - 7 Jan 2026

Adolescence is a period of significant physical, cognitive, and social change, during which various challenges can affect wellbeing. Understanding adolescents’ own perceptions of wellbeing is crucial for developing effective support strategies. This study explores how Norwegian adolescents conceptualize their wellbeing. Using a qualitative [...] Read more.

Adolescence is a period of significant physical, cognitive, and social change, during which various challenges can affect wellbeing. Understanding adolescents’ own perceptions of wellbeing is crucial for developing effective support strategies. This study explores how Norwegian adolescents conceptualize their wellbeing. Using a qualitative design, semi-structured interviews were conducted with 26 adolescents aged 16–19 years, and the data are analyzed thematically. The findings reveal that wellbeing is viewed as multidimensional, encompassing physical health, social relationships, academic performance, and personal growth. Family support and community engagement emerge as central to promoting adolescents’ wellbeing. The study provides valuable insight into how young people in Norway define and experience wellbeing, emphasizing the need to integrate their perspectives into policies and interventions aimed at supporting adolescent development and mental health. Full article

(This article belongs to the Special Issue Promoting Social–Emotional and Academic Support in Educational Settings)

10 pages, 547 KB

Open AccessArticle

Parent Experience and Attitudes Towards Newborn Bloodspot Screening in Ireland

by Mairéad Bracken-Scally, Anna O’Loughlin and Heather Burns

Int. J. Neonatal Screen. 2026, 12(1), 2; https://doi.org/10.3390/ijns12010002 (registering DOI) - 7 Jan 2026

Abstract

The aim of the evaluation was to gather information on parents’ experiences and attitudes towards the Irish National Newborn Bloodspot Screening Programme (NNBSP). An interviewer-administered survey was completed by 151 parents whose babies underwent newborn bloodspot screening (NBS) between 2023 and 2025 and [...] Read more.

The aim of the evaluation was to gather information on parents’ experiences and attitudes towards the Irish National Newborn Bloodspot Screening Programme (NNBSP). An interviewer-administered survey was completed by 151 parents whose babies underwent newborn bloodspot screening (NBS) between 2023 and 2025 and for whom the screening result was normal. Results suggest that NBS is highly acceptable to parents, with 100% glad their baby underwent screening. The majority (95%) felt they were provided the information needed to understand the importance of NBS for their baby, and 93% are in favour of screening for more conditions. Positive aspects of NBS reported by parents included the following: blood sampling being undertaken in the home, the sample-taker being very nice and being advised in advance to keep the baby’s heel warm to ease the sampling process. Negative aspects of NBS reported included the following: having to return to the hospital for sampling, the baby becoming distressed, not receiving adequate information and not receiving the screening results. Parents were more likely to report negative experiences if the sample was not taken at home and if the sample was taken by a healthcare professional other than a public health nurse. Parents offered recommendations for improvements to the programme. This study provides important insights into parents’ experiences and attitudes towards NBS in Ireland. Full article

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15 pages, 2725 KB

Open AccessFeature PaperArticle

Twig and Leaf Morphological Traits and Photosynthetic Physiological Characteristics of Periploca sepium in Response to Different Light Environments in Taohe Riparian Forests

by Min Ma, Chengzhang Zhao, Qun Li, Gang Hou and Junxian Chen

Plants 2026, 15(2), 179; https://doi.org/10.3390/plants15020179 (registering DOI) - 7 Jan 2026

Abstract

Understanding the variations in twig and leaf morphologies and photosynthetic physiological characteristics of riparian forest plants in heterogeneous habitats is of great significance for revealing their phenotypic plasticity mechanisms and ecological adaptation strategies. In this study, the riparian forest plant Periploca sepium Bunge [...] Read more.

Understanding the variations in twig and leaf morphologies and photosynthetic physiological characteristics of riparian forest plants in heterogeneous habitats is of great significance for revealing their phenotypic plasticity mechanisms and ecological adaptation strategies. In this study, the riparian forest plant Periploca sepium Bunge was selected as the research object. According to the canopy light environment experienced by the P. sepium population, three habitats were established: under-canopy, gap, and full-sun areas. We studied the twig and leaf morphological and photosynthetic characteristics of P. sepium under heterogeneous light environments, as well as the relationships between these two aspects. Plants in the under-canopy area developed long and thick twigs with few large leaves, coupled with high actual photosynthetic efficiency of photosystem II (Y(II)) and low non-photochemical quenching (NPQ), whereas those in the full-sun area exhibited the opposite covariation strategy. Significant correlations between twig and leaf morphologies and photosynthetic physiological characteristics were found across all habitats. The coordinated variations in twig and leaf morphologies and photosynthetic physiology of P. sepium embody a resource investment trade-off strategy that plants have evolved through long-term adaptation to heterogeneous light environments. Full article

(This article belongs to the Special Issue Photosynthesis and Plant Physiology Under Climate Change)

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21 pages, 3102 KB

Open AccessArticle

An Enhanced Hybrid Astar Path Planning Algorithm Using Guided Search and Corridor Constraints

by Na Che, Xianwei Zeng, Jian Zhao, Haiyan Wang and Qinsheng Du

Sensors 2026, 26(2), 379; https://doi.org/10.3390/s26020379 (registering DOI) - 7 Jan 2026

Abstract

Aiming at the problems of large search space, unstable computational efficiency, and lack of safety of generated paths in complex environments of traditional HybridA* algorithms, this paper proposes an improved HybridA* algorithm based on Voronoi diagrams and safe corridors (GCHybridA*) to overcome these [...] Read more.

Aiming at the problems of large search space, unstable computational efficiency, and lack of safety of generated paths in complex environments of traditional HybridA* algorithms, this paper proposes an improved HybridA* algorithm based on Voronoi diagrams and safe corridors (GCHybridA*) to overcome these challenges. The method first reduces ineffective node expansion by constructing a Voronoi path away from obstacles and smoothing it, followed by selecting key guidance points to provide stage-like goals for path search. Then, an innovative safe corridor is generated and the path search is restricted to the safe corridor area to guarantee the safety of the path, and an adaptive step-size mechanism is designed to balance the search efficiency and path quality. The experimental results show that the GCHybridA* algorithm significantly outperforms the conventional HybridA* algorithm, with an average reduction of 83.7% in node expansions while maintaining zero potential collision points across all four typical maps. This study provides an innovative and robust solution for efficient and safe path planning in autonomous driving systems. This study provides an innovative and robust solution for global path planning in autonomous driving systems, focusing on static environment navigation with safety guarantees. Full article

(This article belongs to the Section Sensors and Robotics)

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11 pages, 1048 KB

Open AccessArticle

Effect of Preoperative Sarcopenic Obesity on Outcomes in Patients with Gastric Cancer After Surgery

by Itaru Hashimoto, Keisuke Komori, Norihiro Akimoto, Yuta Nakayama, Shinsuke Nagasawa, Yukio Maezawa, Kyohei Kanematsu, Takanobu Yamada, Norio Yukawa, Aya Saito, Takashi Ogata and Takashi Oshima

Cancers 2026, 18(2), 191; https://doi.org/10.3390/cancers18020191 (registering DOI) - 7 Jan 2026

Abstract

Background/Objectives: Preoperative body composition has been implicated as a factor affecting clinical outcomes in several types of cancer. However, there is limited evidence regarding whether preoperative body composition can predict the prognosis following gastrectomy for gastric cancer (GC). We aimed to investigate the [...] Read more.

Background/Objectives: Preoperative body composition has been implicated as a factor affecting clinical outcomes in several types of cancer. However, there is limited evidence regarding whether preoperative body composition can predict the prognosis following gastrectomy for gastric cancer (GC). We aimed to investigate the role of preoperative body composition as a prognostic factor for overall survival (OS) and relapse-free survival (RFS) after gastrectomy for GC. Methods: This prospective study included 540 patients who underwent gastrectomy for GC at the Kanagawa Cancer Center, Japan, between December 2013 and November 2017. Preoperative body composition was assessed using the skeletal muscle index and visceral adipose tissue area derived from computed tomography scans. Patients were classified into four groups: non-sarcopenic non-obesity (NN), sarcopenic non-obesity (SN), non-sarcopenic obesity (NO), and sarcopenic obesity (SO). Results: A total of 448 patients (NN, 184; SN, 52; NO, 186; SO, 26) were included in the final analysis. In terms of OS, the SO group showed significantly worse survival than the NN group (72.1% vs. 87.6%, p = 0.01). Similarly, regarding RFS, the SO group had significantly worse outcomes than the NN group (68.4% vs. 86.2%, p = 0.007). Multivariate analysis identified SO as an independent risk factor for both OS (hazard ratio [HR], 3.18; 95% confidence interval [CI], 1.33–7.64; p = 0.01) and RFS (HR, 3.08; 95% CI, 1.36–6.95; p = 0.01). Conclusions: Preoperative SO was associated with poorer outcomes in patients undergoing gastrectomy for GC. Full article

(This article belongs to the Special Issue Clinical Outcomes in Upper GI Cancers)

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3 pages, 181 KB

Open AccessEditorial

Editorial—Medicinal Plants: Advances in Phytochemistry and Ethnobotany II

by Fabio Boylan and Dâmaris Silveira

Plants 2026, 15(2), 181; https://doi.org/10.3390/plants15020181 (registering DOI) - 7 Jan 2026

Abstract

The relationship between humankind and the environment has been pivotal to survival since Homo sapiens’ primordial ancestors [...] Full article

(This article belongs to the Special Issue Medicinal Plants: Advances in Phytochemistry and Ethnobotany II)

23 pages, 380 KB

Open AccessReview

LLM-Assisted Scoping Review of Artificial Intelligence in Brazilian Public Health: Lessons from Transfer and Federated Learning for Resource-Constrained Settings

by Fabiano Tonaco Borges, Gabriela do Manco Machado, Maíra Araújo de Santana, Karla Amorim Sancho, Giovanny Vinícius Araújo de França, Wellington Pinheiro dos Santos and Carlos Eduardo Gomes Siqueira

Int. J. Environ. Res. Public Health 2026, 23(1), 81; https://doi.org/10.3390/ijerph23010081 (registering DOI) - 7 Jan 2026

Abstract

Artificial intelligence (AI) has become a strategic technology for global health, with increasing relevance amid the climate emergency and persistent digital inequalities. This study examines how AI has been applied in Brazilian healthcare through a scoping review with an in-depth methodological synthesis, focusing [...] Read more.

Artificial intelligence (AI) has become a strategic technology for global health, with increasing relevance amid the climate emergency and persistent digital inequalities. This study examines how AI has been applied in Brazilian healthcare through a scoping review with an in-depth methodological synthesis, focusing on Transfer Learning (TL) and Federated Learning (FL) as approaches to address data scarcity, privacy, and technological dependence. We searched PubMed, SciELO, and the CNPq Theses and Dissertations Repository for peer-reviewed studies on AI applications in Brazil, screened titles using AI-assisted tools with manual validation, and analyzed thematic patterns across methodological and infrastructural dimensions. Among 349 studies retrieved, six explicitly used TL or FL. These techniques were frequently implemented through multi-country research consortia, demonstrating scalability and feasibility for collaborative model training under privacy constraints. However, they remain marginal in mainstream practice despite their ability to deploy AI solutions with limited computational resources while preserving data sovereignty. The findings indicate an emerging yet uneven integration of resource-aware AI in Brazil, underscoring its potential to advance equitable innovation and digital autonomy in health systems of the Global South. Full article

(This article belongs to the Section Global Health)

15 pages, 555 KB

Open AccessArticle

Comprehensive Genomic Characterization of 102 Cervical Adenocarcinoma Tumors

by Gejla Toromani, Grace S. Saglimbeni, Bhanu Surabi Upadhyayula, Eugene Manu, Tyson J. Morris, Beau Hsia and Abubakar Tauseef

Medicina 2026, 62(1), 123; https://doi.org/10.3390/medicina62010123 (registering DOI) - 7 Jan 2026

Abstract

Backgroundand Objectives: Cervical adenocarcinoma (CAC) is a histologically distinct subtype of cervical cancer with a rising incidence in many regions. While the roles of key driver mutations are known, a comprehensive understanding of its genomic landscape, particularly variations across different populations [...] Read more.

Backgroundand Objectives: Cervical adenocarcinoma (CAC) is a histologically distinct subtype of cervical cancer with a rising incidence in many regions. While the roles of key driver mutations are known, a comprehensive understanding of its genomic landscape, particularly variations across different populations and tumor stages, remains incomplete. This study aims to characterize the somatic genomic landscape of CAC by identifying recurrent mutations, copy number alterations (CNAs), and patterns of co-occurrence, with a focus on variations across racial groups and between primary and metastatic tumors. Materials and Methods: We conducted a comprehensive genomic analysis of 102 tumor samples from 99 patients diagnosed with cervical adenocarcinoma using data from the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) database. Results: The most frequently mutated genes were PIK3CA (25.5%), TP53 (21.6%), ARID1A (20.6%), and KRAS (16.7%). Significant amplification of ERBB2 was also observed (n = 3; 4.83%). Our analysis revealed notable genomic disparities across racial groups, with TP53 mutations being significantly more frequent in White patients compared to Asian and Black patients (p = 0.0236). Furthermore, we identified significant co-occurrence between mutations in KRAS and MSH2 (p = 0.011) as well as ATM and STK11 (p = 0.037). In comparing tumor types, mutations in BCL6 were found to be significantly enriched in metastatic samples. Conclusions: This study validates the primary drivers of cervical adenocarcinoma and reveals novel findings, including notable racial disparities in TP53 mutation frequency and unique patterns of co-occurring mutations. These findings highlight the genomic heterogeneity of the disease and suggest that ancestry and tumor evolution may influence its molecular pathogenesis, offering potential avenues for the development of targeted therapies and personalized biomarkers. Full article

(This article belongs to the Special Issue Diagnosis and Treatment of Cervical Cancer: Second Edition)

13 pages, 2198 KB

Open AccessArticle

Characterising Ice Motion Variability at Helheim Glacier Front from Continuous GPS Observations

by Christopher Pearson, James Colinese, Tavi Murray and Stuart Edwards

Glacies 2026, 3(1), 1; https://doi.org/10.3390/glacies3010001 (registering DOI) - 7 Jan 2026

Abstract

Understanding short-term glacier motion is vital for assessing ice sheet dynamics in a warming climate. This study investigates the tidal and diurnal influences on the flow of Helheim Glacier, one of Greenland’s fastest-flowing marine-terminating glaciers, using data from 18 high-frequency GPS sensors and [...] Read more.

Understanding short-term glacier motion is vital for assessing ice sheet dynamics in a warming climate. This study investigates the tidal and diurnal influences on the flow of Helheim Glacier, one of Greenland’s fastest-flowing marine-terminating glaciers, using data from 18 high-frequency GPS sensors and a regional tide gauge collected during summer 2013. A Kalman filter was applied to separate and quantify glacier velocity, tidal admittance, and diurnal melt-driven acceleration. Results reveal a high level of tidal admittance affecting the horizontal flow speed of the glacier, especially at the centre of the glacier, which is propagated upstream. This admittance corresponds to a 0.38–0.68 m/day reduction from the mean at high spring tide and a comparable increase at low tide. The glacier’s vertical motion showed strong tidal control close to the terminus, of 0.6–1.05 m during high spring tides, but this was significantly reduced more than 1 km from the terminus. Diurnal variations in horizontal speed are less spatially and temporally variable, with most nodes experiencing changes from a mean speed of ±0.1–0.3 m/day. These findings demonstrate that both tidal forcing and meltwater input to the basal system exert a significant, and potentially spatially variable, control on glacier dynamics, highlighting the need to incorporate short-period external forcing into predictive models of marine-terminating glacier behaviour. Full article

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34 pages, 894 KB

Open AccessReview

Leptospirosis in Southeast Asia: Investigating Seroprevalence, Transmission Patterns, and Diagnostic Challenges

by Chembie A. Almazar, Yvette B. Montala and Windell L. Rivera

Trop. Med. Infect. Dis. 2026, 11(1), 18; https://doi.org/10.3390/tropicalmed11010018 (registering DOI) - 7 Jan 2026

Abstract

Leptospirosis remains a significant public health and economic burden in Southeast Asia, particularly in low- and middle-income countries where environmental, occupational, and socioeconomic factors contribute to its endemicity. Transmission is driven by close interactions between humans and infected animal reservoirs, alongside climatic conditions [...] Read more.

Leptospirosis remains a significant public health and economic burden in Southeast Asia, particularly in low- and middle-income countries where environmental, occupational, and socioeconomic factors contribute to its endemicity. Transmission is driven by close interactions between humans and infected animal reservoirs, alongside climatic conditions such as heavy rainfall and flooding. The region’s high but variable seroprevalence reflects inconsistencies in diagnostic methodologies and surveillance systems, complicating disease burden estimation. Major gaps persist in diagnostic capabilities, with current tools often unsuitable for resource-limited settings, leading to underdiagnosis and delayed treatment. Environmental modeling and spatial epidemiology are underutilized due to limited interdisciplinary data integration and predictive capacity. Addressing these challenges requires a One Health approach that integrates human, animal, and environmental health sectors. Key policy recommendations include harmonized surveillance, standardized and validated diagnostics, expanded vaccination programs, improved animal husbandry, and targeted public education. Urban infrastructure improvements and early warning systems are also critical, particularly in disaster-prone areas. Strengthened governance, cross-sectoral collaboration, and investment in research and innovation are essential for sustainable leptospirosis control. Implementing these measures will enhance preparedness, reduce disease transmission, and contribute to improved public health outcomes in all sectors across the region. Full article

(This article belongs to the Special Issue One-Health Perspectives and Solutions in Antimicrobial Resistance and Infectious Disease)

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28 pages, 2986 KB

Open AccessArticle

Critiquing Spatial Justice: Morphological Characteristics and Inherent Differences in Government-Subsidized Rental Housing in Shanghai’s Five New Towns

by Chenghao Xu and Zhenyu Li

Buildings 2026, 16(2), 252; https://doi.org/10.3390/buildings16020252 (registering DOI) - 7 Jan 2026

Abstract

In recent years, the rapid construction of government-subsidized rental housing (GRH) has partially alleviated housing pressures caused by the growing number of migrant workers and persistently high rental costs in Shanghai. However, its overriding emphasis on construction and allocation efficiency neglects the realization [...] Read more.

In recent years, the rapid construction of government-subsidized rental housing (GRH) has partially alleviated housing pressures caused by the growing number of migrant workers and persistently high rental costs in Shanghai. However, its overriding emphasis on construction and allocation efficiency neglects the realization of spatial justice, particularly in underdeveloped urban areas. This study adopts a mixed-methods approach to examine all 25 GRHs completed and operational in Shanghai’s Five New Towns, employing morphological characteristics and inherent differences to analyze their impacts on spatial justice. First, this study integrates urban functions and spatial justice elements to establish a systematic classification framework and an evaluative system for GRH, and then assesses the achievement of spatial justice across existing projects. Subsequently, morphological analysis is employed to examine how GRHs shape the socio-spatial context of new towns, thereby assessing their role in reinforcing or undermining spatial justice. Finally, this study establishes data logic between typological factors and morphological characteristics and analyzes the inherent differences among various types of GRH by using Fisher’s exact test. The results reveal that although the existing GRHs are situated in different urban geospatial contexts, they exhibit a severe homogenization phenomenon in terms of construction modality, planning layout, and community boundary, with only the residential scale showing inherent differences. The research findings highlight a systematic neglect of spatial justice in the current GRH development paradigm and reveal the underlying causes. This study contributes to the discourse on spatial justice in GRH development by broadening its dimensions, and it provides valuable insights for promoting the realization of spatial justice through multi-tiered policy framework, place-making design strategy, and a joint operation model. Full article

(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)

15 pages, 859 KB

Open AccessArticle

The Impact of Perceptual Load and Distractors’ Perceptual Grouping on Visual Search in ASD

by Wenyi Shen, Yijie Huang, Lin Zhang and Shimin Fu

Behav. Sci. 2026, 16(1), 80; https://doi.org/10.3390/bs16010080 (registering DOI) - 7 Jan 2026

Abstract

This study examined potential visual search advantages in individuals with autism spectrum disorder (ASD) and explored the roles of distractor grouping and perceptual load by comparing their performance with that of typically developing (TD) controls. Participants were required to search for large or [...] Read more.

This study examined potential visual search advantages in individuals with autism spectrum disorder (ASD) and explored the roles of distractor grouping and perceptual load by comparing their performance with that of typically developing (TD) controls. Participants were required to search for large or small targets under two levels of perceptual load, with distractors being either large or small. The results showed the following: (1) Search speed in the ASD group was slower than that of the TD group. (2) The effect of distractor grouping was stronger in the Target–Nontarget (T-N) size-inconsistent condition than in the consistent condition. Both groups showed a T-N size-consistency effect—response speeds in the T-N size-inconsistent condition were faster, indicating that distractor grouping improves search efficiency. (3) Under high load, the TD group exhibited a stronger T-N size-consistency effect than the ASD group, whereas no significant difference was observed under low load. This suggests that distractor grouping in the ASD group is less effective than in TD participants under high load. (4) Under the T-N size-inconsistent condition, participants with ASD detected small targets faster under low load, whereas TD participants detected large targets faster under high load. This indicates that distractor grouping facilitates visual search in ASD under low load. Both groups focus more on targets under high load. In conclusion, although ASD shows no search advantage, improving distractor grouping can speed up target search. Nevertheless, under high load, distractor grouping in individuals with ASD is weaker than in TD individuals, consistent with the weak central coherence theory. Additionally, ASD displays size asymmetry that is influenced by load, with distractor grouping aiding target detection in low load and reducing distractor processing under high load. Full article

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15 pages, 2129 KB

Open AccessArticle

Chromosome-Level Genome Assembly of Ormosia henryi Provides Insights into Evolutionary Resilience and Precision Conservation

by Xiaoming Tian, Bin Yuan, Cun Mou, Guangfeng Xiang, Lu Zhu, Gaofei Li, Chao Liu, Xiangpeng Li, Fuliang Hu and Hao Lv

Plants 2026, 15(2), 180; https://doi.org/10.3390/plants15020180 (registering DOI) - 7 Jan 2026

Abstract

Ormosia henryi, a rare and endemic timber tree in China, possesses exceptional economic and ecological value, but it has experienced a critical decline in wild populations. We integrated PacBio HiFi and Hi-C technologies to generate a superior, chromosome-level genome assembly, establishing a [...] Read more.

Ormosia henryi, a rare and endemic timber tree in China, possesses exceptional economic and ecological value, but it has experienced a critical decline in wild populations. We integrated PacBio HiFi and Hi-C technologies to generate a superior, chromosome-level genome assembly, establishing a more robust genetic foundation than existing draft sequences. The resulting assembly (2.64 Gb; Contig N50 = 39.17 Mb; and Scaffold N50 = 338.40 Mb) exhibits high continuity and completeness, effectively overcoming the assembly challenges associated with high heterozygosity (1.37%) and repetitive sequence content (83.89%). Comparative genomic analysis revealed that O. henryi diverged from Lupinus albus approximately 53.82 million years ago and underwent two independent whole-genome duplication events. The historical accumulation of evolutionary resilience is reflected in the significant expansion of 276 gene families enriched in photosynthesis and phenylpropanoid biosynthesis, alongside 122 genes under positive selection involved in DNA repair and proteostasis. These genomic signatures elucidate a stable genetic foundation. While wild populations have sharply declined in recent decades, this suggests that this status underscores the overwhelming impact of intense external anthropogenic pressures, such as overexploitation and habitat fragmentation, which may have overridden the species’ inherent adaptive capacity and slow life-history strategy. This high-quality genomic resource identifies key candidate loci, such as the PIF1 helicase for growth regulation, and provides a critical framework for screening elite germplasm for population restoration. Consequently, this study establishes a theoretical and molecular basis for transitioning from fundamental research to the precision conservation and sustainable industrial application of this high-value woody species. Full article

(This article belongs to the Special Issue Molecular Mechanisms of Interaction and Adaptation Between Non-Model Plants and the Environment)

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17 pages, 380 KB

Open AccessArticle

The Effect of an Educational Intervention Program on Allied Health Students’ Knowledge and Attitudes Regarding Organ Donation and Transplantation

by Falastine Hamdan, Loai Alfarajat, Rafi Alnjadat, Eshraq Almomani, Mohammad Etoom and Salwa AbuAlrub

Nurs. Rep. 2026, 16(1), 15; https://doi.org/10.3390/nursrep16010015 (registering DOI) - 7 Jan 2026

Abstract

Background: A significant shortage of available organs for transplantation persists globally, with insufficient education on organ donation recognized as a key contributing factor. Allied health students, when equipped with accurate knowledge, have the potential to serve as advocates for organ donation, influencing public [...] Read more.

Background: A significant shortage of available organs for transplantation persists globally, with insufficient education on organ donation recognized as a key contributing factor. Allied health students, when equipped with accurate knowledge, have the potential to serve as advocates for organ donation, influencing public attitudes through their social networks. Enhancing their understanding may contribute to increased organ donation awareness and acceptance within the broader community. Methods: This study employed a quasi-experimental design to examine the effect of an educational intervention program on allied health students’ knowledge and attitudes toward organ donation and transplantation. A total of 150 allied health students were recruited through simple random sampling. Data were collected using a valid and reliable translated self-administered online questionnaire. Participants were divided into intervention and control groups. Descriptive statistics, independent sample t-tests, and one-way ANOVA were used for data analysis. Results: Following the intervention, the mean score of knowledge and attitudes in the intervention group (M = 41.09, SD = 2.57) was significantly higher than that in the control group (M = 40.29, SD = 2.40), with a t-value of −3.49 and a p-value of <0.001. These results indicate that the educational program had a statistically significant positive effect on participants’ knowledge and attitudes regarding organ donation and transplantation. Conclusions: The implementation of the educational intervention significantly improved allied health students’ knowledge and attitudes toward organ donation and transplantation. This suggests that targeted educational programs for future health professionals may be an effective strategy to promote organ donation awareness and address the shortage of organ donors. Full article

(This article belongs to the Section Nursing Education and Leadership)

5 pages, 153 KB

Open AccessEditorial

Advances in Carbon Fiber Reinforced Polymers

by Francesca Lionetto

Materials 2026, 19(2), 231; https://doi.org/10.3390/ma19020231 (registering DOI) - 7 Jan 2026

Abstract

Carbon fiber reinforced polymers (CFRPs) have become increasingly widespread across a remarkable range of industries thanks to their unique combination of strength, lightness and durability [...] Full article

(This article belongs to the Special Issue Carbon Fiber Reinforced Polymers (2nd Edition))

23 pages, 4022 KB

Open AccessArticle

Machine Learning—Driven Analysis of Agricultural Nonpoint Source Pollution Losses Under Variable Meteorological Conditions: Insights from 5 Year Site-Specific Tracking

by Ran Jing, Yinghui Xie, Zheng Hu, Xingjian Yang, Xueming Lin, Wenbin Duan, Feifan Zeng, Tianyi Chen, Xin Wu, Xiaoming He and Zhen Zhang

Sustainability 2026, 18(2), 590; https://doi.org/10.3390/su18020590 (registering DOI) - 7 Jan 2026

Abstract

Agricultural nonpoint source pollution is emerging as one of the increasingly serious environmental concerns all over the world. This study conducted field experiments in Zengcheng District, Guangzhou City, from 2019 to 2023 to explore the mechanisms by which different crop types, fertilization modes, [...] Read more.

Agricultural nonpoint source pollution is emerging as one of the increasingly serious environmental concerns all over the world. This study conducted field experiments in Zengcheng District, Guangzhou City, from 2019 to 2023 to explore the mechanisms by which different crop types, fertilization modes, and meteorological conditions affect the loss of nitrogen and phosphorus in agricultural nonpoint source pollution. In rice and corn, the CK and PK treatment groups showed significant fitting advantages, such as the R² of rice-CK reaching 0.309. MAE was 0.395, and the R² of corn-PK was as high as 0.415. For compound fertilization groups such as NPK and OF, the model fitting ability decreased, such as the R² of rice-NPK dropping to 0.193 and the R² of corn-OF being only 0.168. In addition, the overall performance of the model was limited in the modeling of total phosphorus. A relatively good fit was achieved in corn (such as NPK group R² = 0.272) and in vegetables and citrus. R² was mostly below 0.25. The results indicated that fertilization management, crop types, and meteorological conditions affected nitrogen and phosphorus losses in agricultural runoff. Cornfields under conventional nitrogen, phosphorus, and potassium fertilizer (NPK) and conventional nitrogen and potassium fertilizer treatment without phosphorus fertilizer (NK) treatments exhibited the highest nitrogen losses, while citrus fields showed elevated phosphorus concentrations under NPK and PK treatments. Organic fertilizer treatments led to moderate nutrient losses but greater variability. Organic fertilizer treatments resulted in moderate nutrient losses but showed greater interannual variability. Meteorological drivers differed among crop types. Nitrogen enrichment was mainly associated with high temperature and precipitation, whereas phosphorus loss was primarily triggered by short-term extreme weather events. Linear regression models performed well under simple fertilization scenarios but struggled with complex nutrient dynamics. Crop-specific traits such as flooding in rice fields, irrigation in corn, and canopy coverage in citrus significantly influenced nutrient migration. The findings of this study highlight that nutrient losses are jointly regulated by crop systems, fertilization practices, and meteorological variability, particularly under extreme weather conditions. These findings underscore the necessity of crop-specific and climate-adaptive nutrient management strategies to reduce agricultural nonpoint source pollution. By integrating long-term field observations with machine learning–based analysis, this study provides scientific evidence to support sustainable fertilizer management, protection of water resources, and environmentally responsible agricultural development in subtropical regions. The proposed approaches contribute to sustainable land and water resource utilization and climate-resilient agricultural systems, aligning with the goals of sustainable development in rapidly urbanizing river basins. Full article

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15 pages, 3058 KB

Open AccessArticle

Influence of N₂/Ar Flow Ratio on the Microstructure and Electrochemical Capacitive Performance of TiN Thin-Film Electrodes for Micro-Supercapacitors

by Jiaxin Tan, Lin Yi, Min Zhang and Suyuan Bai

Coatings 2026, 16(1), 69; https://doi.org/10.3390/coatings16010069 (registering DOI) - 7 Jan 2026

Abstract

With the rapid development of the Internet of Things (IoT), micro-energy storage devices face increasing demands for miniaturization, high energy density, and high power density. Owing to their excellent electrical conductivity and mechanical strength, TiN thin films are promising candidates for micro-supercapacitor electrodes. [...] Read more.

With the rapid development of the Internet of Things (IoT), micro-energy storage devices face increasing demands for miniaturization, high energy density, and high power density. Owing to their excellent electrical conductivity and mechanical strength, TiN thin films are promising candidates for micro-supercapacitor electrodes. In this work, TiN thin films were prepared by direct current magnetron sputtering under different N₂/Ar flow ratios. The effects of the N₂/Ar flow ratio on the crystal structure, surface morphology, roughness, and electrochemical capacitive performance of TiN thin films were systematically investigated. The results show that at lower N₂/Ar flow ratios, the films consist of a mixture of TiN and Ti₂O₃ phases, while at higher N₂/Ar ratios, single-phase TiN with a preferred orientation along the (220) plane is detected in the obtained films. AFM measurements indicate that the root mean square roughness first increases and then decreases with increases in N₂/Ar flow ratios, and it reaches a maximum of around 15.9 nm when the N₂/Ar flow ratio is 5:15. XPS results show that the 5:15 sample contains the highest oxygen vacancy concentration, offering it the best conductivity, which is confirmed by four-probe measurements. Electrochemical tests demonstrate that the N₂/Ar flow ratio has a significant influence on the specific capacitance of TiN films, with the highest value of 3.29 mF/cm² achieved at a N₂/Ar flow ratio of 5:15, which is likely due to the rough and porous surface and much better conductivity of the as-deposited films. This study provides an important experimental basis for optimizing the performance of TiN thin-film electrodes. Full article

(This article belongs to the Special Issue Research Progress and Prospect of Functional Thin Films & Hard Protective Coatings)

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28 pages, 621 KB

Open AccessArticle

Integrating Artificial Intelligence (AI) in Primary Health Care (PHC) Systems: A Framework-Guided Comparative Qualitative Study

by Farzaneh Yousefi, Reza Dehnavieh, Maude Laberge, AliAkbar Haghdoost, Maxime Sasseville, Somayeh Noori Hekmat, Mohammad Mehdi Ghaemi and Mohsen Nadali

Healthcare 2026, 14(2), 145; https://doi.org/10.3390/healthcare14020145 (registering DOI) - 7 Jan 2026

Abstract

Background/Objectives: The integration of artificial intelligence (AI) into primary health care (PHC) holds significant potential to enhance efficiency, equity, and clinical decision-making. However, its implementation remains uneven across contexts. This study aimed to identify the systemic, contextual, and governance-related determinants influencing AI [...] Read more.

Background/Objectives: The integration of artificial intelligence (AI) into primary health care (PHC) holds significant potential to enhance efficiency, equity, and clinical decision-making. However, its implementation remains uneven across contexts. This study aimed to identify the systemic, contextual, and governance-related determinants influencing AI readiness in PHC, comparing two distinct health systems, Quebec (Canada) and Iran. Methods: A qualitative, comparative design was employed. Data were collected through semi-structured interviews and focus group discussions with key informants in both settings. A framework-guided content analysis was conducted based on the four Primary Care Evaluation Tool (PCET): stewardship, financing, resource generation, and service delivery. The analysis explored shared context-specific challenges and requirements for AI implementation in PHC. Results: Analysis revealed that AI readiness is shaped more by systemic coherence rather than technological availability alone. Across both contexts, governance- and financing-related challenges were reported by the majority of participants, alongside limited data interoperability. In Quebec, challenges were more commonly articulated around operational and ethical concerns, including workflow integration, transparency, and professional trust. In contrast, participants in Iran emphasized foundational deficiencies in governance stability, financing mechanisms, and digital infrastructure as primary barriers. Across both settings, adaptive governance, sustainable investment, data standardization, and workforce capacity-building consistently emerged as key requirements for AI integration in PHC. Conclusions: AI readiness in PHC is a multidimensional process, in which implementation priorities must align with system maturity. This comparative analysis underscores that while high-resource systems must prioritize ethical integration and workflow alignment, middle-resource settings require foundational investments in governance and infrastructure. This reinforces that AI readiness is a context-dependent and phased process rather than a one-size-fits-all endeavor. Full article

(This article belongs to the Special Issue Artificial Intelligence in Health Services Research and Organizations)

20 pages, 1709 KB

Open AccessArticle

Kinematic Analysis and Workspace Evaluation of a New Five-Axis 3D Printer Based on Hybrid Technologies

by Azamat Mustafa, Rustem Kaiyrov, Yerik Nugman, Mukhagali Sagyntay, Nurtay Albanbay, Algazy Zhauyt, Zharkynbek Turgunov, Ilyas Dyussebayev and Yang Lei

Robotics 2026, 15(1), 16; https://doi.org/10.3390/robotics15010016 (registering DOI) - 7 Jan 2026

Abstract

Additive manufacturing technologies for metals are developing rapidly. Among them, wire arc additive manufacturing (WAAM) has become widespread due to its accessibility. However, parts produced using WAAM require surface post-processing; therefore, hybrid technologies have emerged that combine additive and subtractive processes within a [...] Read more.

Additive manufacturing technologies for metals are developing rapidly. Among them, wire arc additive manufacturing (WAAM) has become widespread due to its accessibility. However, parts produced using WAAM require surface post-processing; therefore, hybrid technologies have emerged that combine additive and subtractive processes within a single compact manufacturing complex. Such systems make it possible to organize single-piece and small-batch production, including for the repair and restoration of equipment in remote areas. For this purpose, hybrid equipment must be lightweight, compact for transportation, provide sufficient workspace, and be capable of folding for transport. This paper proposes the concept of a multifunctional metal 3D printer based on hybrid technology, where WAAM is used for printing, and mechanical post-processing is applied to obtain finished parts. To ensure both rigidity and low mass, a 3-UPU parallel manipulator and a worktable with two rotational degrees of freedom are employed, enabling five-axis printing and machining. The printer housing is foldable for convenient transportation. The kinematics of the proposed 3D printer are investigated as an integrated system. Forward and inverse kinematics problems are solved, the velocities and accelerations of the moving platform center are calculated, singular configurations are analyzed, and the workspace of the printer is determined. Full article

(This article belongs to the Section Industrial Robots and Automation)

18 pages, 3505 KB

Open AccessArticle

Fastener Flexibility Analysis of Metal-Composite Hybrid Joint Structures Based on Explainable Machine Learning

by Xinyu Niu and Xiaojing Zhang

Aerospace 2026, 13(1), 58; https://doi.org/10.3390/aerospace13010058 (registering DOI) - 7 Jan 2026

Abstract

Metal-composite joints, leveraging the high specific strength/stiffness and superior fatigue resistance of carbon fiber reinforced polymers (CFRP) alongside metallic materials’ excellent toughness and formability, have become prevalent in aerospace structures. Fastener flexibility serves as a critical parameter governing load distribution prediction and fatigue [...] Read more.

Metal-composite joints, leveraging the high specific strength/stiffness and superior fatigue resistance of carbon fiber reinforced polymers (CFRP) alongside metallic materials’ excellent toughness and formability, have become prevalent in aerospace structures. Fastener flexibility serves as a critical parameter governing load distribution prediction and fatigue life assessment, where accurate quantification directly impacts structural reliability. Current approaches face limitations: experimental methods require extended testing cycles, numerical simulations exhibit computational inefficiency, and conventional machine learning (ML) models suffer from “black-box” characteristics that obscure mechanical principle alignment, hindering aerospace implementation. This study proposes an integrated framework combining numerical simulation with explainable ML for fastener flexibility analysis. Initially, finite element modeling (FEM) constructs a dataset encompassing geometric features, material properties, and flexibility values. Subsequently, a random forest (RF) prediction model is developed with five-fold cross-validation and residualanalysis ensuring accuracy. SHapley Additive exPlanations (SHAP) methodology then quantifies input features’ marginal contributions to flexibility predictions, with results interpreted in conjunction with theoretical flexibility formulas to elucidate key parameter influence mechanisms. The approach achieves 0.99 R2 accuracy and 0.11 s computation time while resolving explainability challenges, identifying fastener diameter-to-plate thickness ratio as the dominant driver with negligible temperature/preload effects, thereby providing a validated efficient solution for aerospace joint optimization. Full article

(This article belongs to the Section Aeronautics)

10 pages, 2434 KB

Open AccessArticle

Brucella, Coxiella, and Theileria Species DNA in Haemaphysalis qinghaiensis Ticks Collected from Goats and Sheep in Qinghai Province, Northwest China

by Kun Li, Xuxin Yang, Jianling Wang, Shengyu Li, Xu Zhao, Shengjun Cai, Leyu Wu, Guoqiang An, Hongyan Zhao, Dongri Piao, Qingqing Xu, Yu Fan, Jiquan Li and Hai Jiang

Trop. Med. Infect. Dis. 2026, 11(1), 17; https://doi.org/10.3390/tropicalmed11010017 (registering DOI) - 7 Jan 2026

Abstract

Haemaphysalis qinghaiensis is an endemic tick species distributed in the western plateau areas of China. Although they are three-host ticks, infesting multiple animals (including humans), the occurrence of various tick-borne agents has barely been investigated. In this study, we collected 136 H. qinghaiensis [...] Read more.

Haemaphysalis qinghaiensis is an endemic tick species distributed in the western plateau areas of China. Although they are three-host ticks, infesting multiple animals (including humans), the occurrence of various tick-borne agents has barely been investigated. In this study, we collected 136 H. qinghaiensis specimens from sheep and goats in Menyuan County in Qinghai Province, northwest China. The Brucella, Coxiella, and Theileria/Babesia species’ DNA were detected by nested or hemi-nested PCR and further identified by amplifying their key genes. Brucella abortus and B. melitensis DNA were detected, with positive rates of 3.68% and 4.41%, respectively. This may be the first report that suggests that H. qinghaiensis harbors Brucella spp., the agents of human brucellosis. The Coxiella endosymbiont of Haemaphysalis qinghaiensis, a non-pathogenic Coxiella, was identified with an extremely high positive rate of 97.06%. In addition, two Theileria species, Theileria luwenshuni (75.00%) and Theileria uilenbergi (16.18%), were detected. Our results suggest the circulation of Brucella spp. and Theileria spp. in goats and sheep in the study area. Whether H. qinghaiensis ticks play a role in the maintenance and transmission of these agents has yet to be determined. Due to their human pathogenicity and their high positive rates in ticks, surveillance in local populations with relative symptoms is necessary. Full article

(This article belongs to the Special Issue The Distribution and Diversity of Tick-Borne Zoonotic Pathogens)

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51 pages, 698 KB

Open AccessArticle

Quantum Anomalies as Intrinsic Algebraic Curvature: A Unified AQFT Interpretation of Renormalization Ambiguities

by Andrei T. Patrascu

Quantum Rep. 2026, 8(1), 3; https://doi.org/10.3390/quantum8010003 (registering DOI) - 7 Jan 2026

Abstract

Quantum anomalies are traditionally understood as classical symmetries that fail to survive quantization, while experimental “anomalies” denote deviations between theoretical predictions and measured values. In this work, we develop a unified framework in which both phenomena can be interpreted through the lens of [...] Read more.

Quantum anomalies are traditionally understood as classical symmetries that fail to survive quantization, while experimental “anomalies” denote deviations between theoretical predictions and measured values. In this work, we develop a unified framework in which both phenomena can be interpreted through the lens of algebraic quantum field theory (AQFT). Building on the renormalization group viewed as an extension problem, we show that renormalization ambiguities correspond to nontrivial elements of Hochschild cohomology, giving rise to a deformation of the observable algebra

A * B = A B + ε ω (A, B)

, where

ω

is a Hochschild 2-cocycle. We interpret

ω

as an intrinsic algebraic curvature of the net of local algebras, namely the (local) Hochschild class that measures the obstruction to trivializing infinitesimal scheme changes by inner redefinitions under locality and covariance constraints. The transported product is associative; its first-order expansion is associative up to

O (ε^{2})

while preserving the *-structure and Ward identities to the first order. We prove the existence of nontrivial cocycles in the perturbative AQFT setting, derive the conditions under which the deformed product respects positivity and locality, and establish the compatibility with current conservation. The construction provides a direct algebraic bridge to standard cohomological anomalies (chiral, trace, and gravitational) and yields correlated deformations of physical amplitudes. Fixing the small deformation parameter

ε

from the muon

(g - 2)

discrepancy, we propagate the framework to predictions for the electron

(g - 2)

, charged lepton EDMs, and other low-energy observables. This approach reduces reliance on ad hoc form-factor parametrizations by organizing first-order scheme-induced deformations into correlation laws among low-energy observables. We argue that interpreting quantum anomalies as manifestations of algebraic curvature opens a pathway to a unified, testable account of renormalization ambiguities and their phenomenological consequences. We emphasize that the framework does not eliminate renormalization or quantum anomalies; rather, it repackages the finite renormalization freedom of pAQFT into cohomological data and relates it functorially to standard anomaly classes. Full article

52 pages, 1112 KB

Open AccessReview

Scoping Review of the Socioeconomic Value of Working Equids, and the Impact of Educational Interventions Aimed at Improving Their Welfare

by Amelia Cameron, Sarah L. Freeman, Isabella Wild, Jessica Burridge and Katie Burrell

Animals 2026, 16(2), 165; https://doi.org/10.3390/ani16020165 (registering DOI) - 7 Jan 2026

Abstract

^‡ Current address: Pool House Equine Hospital, Lichfield, WS13 8RD, UK [...] Full article

(This article belongs to the Special Issue Working Equids: Welfare, Health and Behavior)

14 pages, 1117 KB

Open AccessArticle

In Silico Functional and Structural Analysis of STAT4 Variants of Uncertain Significance

by Karla Mayela Bravo-Villagra, Eric Jonathan Maciel-Cruz, Rosa Michel Martínez-Contreras, Itzae Adonai Gutiérrez-Hurtado, Alexis Missael Vizcaíno-Quirarte, José Francisco Muñoz-Valle and Andres López-Quintero

Genes 2026, 17(1), 72; https://doi.org/10.3390/genes17010072 (registering DOI) - 7 Jan 2026

Abstract

Background: The STAT4 gene plays a key role in immune regulation and is associated with susceptibility to autoimmune diseases such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Objectives: The objective of this study is to analyze variants of uncertain significance [...] Read more.

Background: The STAT4 gene plays a key role in immune regulation and is associated with susceptibility to autoimmune diseases such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Objectives: The objective of this study is to analyze variants of uncertain significance (VUSs) in STAT4 using bioinformatics tools to predict their functional and structural impact. Methods: A total of 48,295 variants of the STAT4 gene (ENSG00000138378) were retrieved from the Ensembl database. A tiered filtering approach was used to assess VUS pathogenicity, integrating in silico prediction tools such as SIFT, PolyPhen, MutPred2, and Align-GVGD, as well as structural modeling platforms including Chimera, ModRefiner, Missense3D, HOPE, and DynaMut2. Results: Eighty missense VUSs were identified; of these, 13 were prioritized based on concordant signals across multiple computational predictors. These variants showed significant alterations in the physicochemical properties of the protein, including changes in hydrophobicity and disruption of hydrogen bonding. Notably, the rs140675301 (Glu128Val) variant lies within a conserved loop, and in silico analyses suggest that this mutation may alter kinase specificity regarding the phosphorylation of serine 130. Conclusions: The integrative use of the bioinformatic tools employed represents a valuable preliminary step prior to undertaking more complex and resource-intensive functional studies. This complementary strategy strengthens the interpretative framework for VUS, guiding subsequent experimental validation and supporting a structured assessment of variant relevance, particularly in the context of immune-related genes such as STAT4. Full article

(This article belongs to the Special Issue Advances in Bioinformatics of Human Diseases)

47 pages, 734 KB

Open AccessArticle

Digital–Intelligent Synergy Empowers Chinese Firms’ Internationalization: A Dual Perspective Based on Green Innovation and Stable Investment

by Jinsong Zhang and Yu Zhang

Sustainability 2026, 18(2), 588; https://doi.org/10.3390/su18020588 (registering DOI) - 7 Jan 2026

Abstract

Amid the rapid growth of the digital economy and increasing global competition, the role of digital–intelligent technologies in enabling corporate internationalization has gained significant attention. From the perspective of “digital–intelligent synergy,” this study constructs a mediated moderation model to explore the impact mechanism [...] Read more.

Amid the rapid growth of the digital economy and increasing global competition, the role of digital–intelligent technologies in enabling corporate internationalization has gained significant attention. From the perspective of “digital–intelligent synergy,” this study constructs a mediated moderation model to explore the impact mechanism of digital–intelligent synergy on corporate internationalization. The findings indicate that data assets, artificial intelligence, and digital–intelligent coupling coordination significantly enhance overseas revenue. Green technology innovation mediates this relationship, while investor stability exerts an asymmetrical moderating effect. This strengthens both the direct effect of digital–intelligent synergy on internationalization and its impact on green innovation, though not the path from green innovation to international performance. Further analysis indicates that self-use data assets significantly promote firm internationalization, while transactional data assets do not. Both AI technology and applications markedly enhance overseas expansion. For digital–intelligent coupling coordination, the level of coordination—not merely coupling intensity—positively affects internationalization level. By integrating green innovation and investor behavior perspectives, this study reveals the complex mechanisms through which digital–intelligent synergy empowers internationalization, offering theoretical and policy insights for corporate global expansion in the digital–green transition era. Full article

28 pages, 3231 KB

Open AccessArticle

Enhancing EV Hosting Capacity in Distribution Networks Using WAPE-Based Dynamic Control

by Al-Amin, G. M. Shafiullah, Md Shoeb and S. M. Ferdous

Sustainability 2026, 18(2), 589; https://doi.org/10.3390/su18020589 (registering DOI) - 7 Jan 2026

Abstract

Precisely assessing electric vehicle hosting capacity (EVHC) is critical for ensuring the secure integration of EVs and optimizing the use of distribution network resources. Although optimization-based methods such as Particle Swarm Optimization (PSO) can identify a high theoretical HC under steady-state voltage constraints, [...] Read more.

Precisely assessing electric vehicle hosting capacity (EVHC) is critical for ensuring the secure integration of EVs and optimizing the use of distribution network resources. Although optimization-based methods such as Particle Swarm Optimization (PSO) can identify a high theoretical HC under steady-state voltage constraints, these static formulations fail to capture short-term dynamics such as photovoltaic (PV) intermittency and uncoordinated EV arrivals. As a result, the hosting capacity that can actually be used in practice is often reduced to a much lower capacity to keep the system operating safely. This study compares optimization-based and simulation-based HC assessments and introduces a Weighted Average Power Estimator (WAPE)-based dynamic control framework to preserve the higher HC identified by optimization under real-world conditions. Case studies on a modified IEEE 13-bus system show PV drops of 90% during a 4-s cloud event. Studies also demonstrate that a sudden clustering of multiple EVs would significantly lower effective HC. With WAPE control, the system maintains stable operation at full HC, holding the bus voltage within an acceptable range (400–430 V) during the two events, representing a 2–3% voltage improvement. In addition, WAPE allows the EV to continue charging at a lower rate during disturbances, reducing the total charging time by almost 10% compared with completely stopping the charging process. Overall, the proposed WAPE substantially improves the usable and sustainable HC of distribution networks, ensuring reliable EV integration under dynamic and uncertain operating conditions. Full article

(This article belongs to the Special Issue Energy Technology, Power Systems and Sustainability)

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