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Open AccessEditorial

Differential Geometry and Its Application, 3rd Edition

by Mića S. Stanković

Axioms 2026, 15(1), 66; https://doi.org/10.3390/axioms15010066 (registering DOI) - 18 Jan 2026

In this Editorial, we introduce the Special Issue of Axioms entitled “Differential Geometry and Its Application, 3rd Edition [...] Full article

(This article belongs to the Special Issue Differential Geometry and Its Application, 3rd Edition)

22 pages, 2026 KB

Open AccessArticle

Evolutionary Relationships and Genetic Diversity in the Southern Siberian Populations of the Saker Falcon (Falco cherrug), a Young and Endangered Species

by Daria Nikolaevna Rozhkova, Elena Pavlovna Shnayder, Valentina Georgievna Tambovtseva, Igor Vyacheslavovich Karyakin, Alla Veniaminovna Blekhman, Oleg Evgenievich Lazebny, Svetlana Yuryevna Sorokina, Ludmila Sergeevna Zinevich and Alexey Mikhailovich Kulikov

Diversity 2026, 18(1), 50; https://doi.org/10.3390/d18010050 (registering DOI) - 18 Jan 2026

Abstract

Studying intraspecific differentiation in closely related species is essential to clarify the phylogenetic relationships and mechanisms of early stage speciation, particularly in evolutionarily young lineages affected by human-driven population declines. The endangered saker falcon (Falco cherrug), with its ambiguous phylogenetic links [...] Read more.

Studying intraspecific differentiation in closely related species is essential to clarify the phylogenetic relationships and mechanisms of early stage speciation, particularly in evolutionarily young lineages affected by human-driven population declines. The endangered saker falcon (Falco cherrug), with its ambiguous phylogenetic links to the gyrfalcon (F. rusticolus), exemplifies this scenario. This study presents a comprehensive genetic analysis of F. cherrug and F. rusticolus using mtDNA markers and microsatellite loci, focusing on the diversity of southern Siberian saker falcon populations. The genotyping results for these populations were correlated with phenotypic data obtained from long-term monitoring (1999–2021). Our findings provide novel insights into the current subspecific differentiation and the remnants of a nascent subspecies structure that existed before the recent demographic collapse. Furthermore, our results support the hypothesis of the gyrfalcon’s origin as a descendant species of the Asian saker falcon, i.e., an evolutionarily young lineage undergoing divergence. Our data contribute to the understanding of the Hierofalco evolutionary history, particularly through the analysis of heterogeneous mutation rates among mitochondrial haplogroups. This study underscores the critical importance of conservation efforts for wild endangered populations through long-term monitoring integrated with combined genetic approaches. Full article

(This article belongs to the Special Issue Avian Genetic Diversity)

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35 pages, 772 KB

Open AccessArticle

Improvisation and New Venture Performance: Unpacking the Roles of Entrepreneurial Self-Efficacy and Learning Orientation

by Osama Elfghi, Kolawole Iyiola, Ahmad Bassam Alzubi and Hasan Yousef Aljuhmani

Sustainability 2026, 18(2), 975; https://doi.org/10.3390/su18020975 (registering DOI) - 18 Jan 2026

Abstract

New ventures operating in volatile and unpredictable environments must rely on rapid adaptation and decisive action, making improvisation a critical entrepreneurial capability. This study examines how improvisation enhances new venture performance by uncovering the psychological and learning-based mechanisms through which its effects unfold. [...] Read more.

New ventures operating in volatile and unpredictable environments must rely on rapid adaptation and decisive action, making improvisation a critical entrepreneurial capability. This study examines how improvisation enhances new venture performance by uncovering the psychological and learning-based mechanisms through which its effects unfold. Drawing on the Knowledge-Based View (KBV) and Social Learning Theory (SLT), the model proposes that improvisation strengthens entrepreneurial self-efficacy, enabling entrepreneurs to approach uncertainty with greater confidence and adaptive judgment. Using a two-wave survey of 322 startup founders in Turkey and analyses conducted through PROCESS and complementary SEM estimation, the findings show that improvisation significantly boosts both entrepreneurial self-efficacy and new venture performance. Entrepreneurial self-efficacy emerges as a key mediating mechanism, indicating that improvisational experiences help entrepreneurs develop mastery, reinforce capability beliefs, and translate spontaneous action into improved outcomes. The results further suggest that improvisational episodes provide immediate learning cues that enhance situational awareness and decision-making agility, deepening the psychological pathway that links spontaneous behavior to venture performance. Additionally, relative explorative learning significantly moderates the relationship between improvisation and entrepreneurial self-efficacy, demonstrating that entrepreneurs benefit more from improvisation when they actively pursue new knowledge, experiment with unfamiliar approaches, and challenge routine assumptions. This moderating role clarifies when improvisation produces its strongest effects, while the mediating mechanism explains how performance improvements materialize through confidence-building processes. By integrating these mechanisms into a unified explanation, the study advances understanding of the improvisation–performance relationship and highlights the importance of learning-oriented behavior in converting spontaneous action into sustained entrepreneurial advantage. The findings offer theoretical contributions and actionable insights for entrepreneurs seeking to strengthen adaptability, resilience, and competitiveness in fast-changing environments. Full article

(This article belongs to the Special Issue Building Sustainable Businesses: Psychological Drivers, Organizational Strategies and Entrepreneurial Development)

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34 pages, 4044 KB

Open AccessArticle

Modular Chain-of-Thought (CoT) for LLM-Based Conceptual Construction Cost Estimation

by Prashnna Ghimire, Kyungki Kim, Terry Stentz and Tirthankar Roy

Buildings 2026, 16(2), 396; https://doi.org/10.3390/buildings16020396 (registering DOI) - 18 Jan 2026

Abstract

The traditional cost estimation process in construction involves extracting information from diverse data sources and relying on human intuition and judgment, making it time-intensive and error-prone. While recent advancements in large language models offer opportunities to automate these processes, their effectiveness in cost [...] Read more.

The traditional cost estimation process in construction involves extracting information from diverse data sources and relying on human intuition and judgment, making it time-intensive and error-prone. While recent advancements in large language models offer opportunities to automate these processes, their effectiveness in cost estimation tasks remains underexplored. Prior studies have investigated LLM applications in construction, but there is a lack of studies that have systematically evaluated their performance in cost estimation or proposed a framework for systematic evaluations of their performance in cost estimation and ways to enhance their accuracy and reliability through prompt engineering. This study evaluates the performance of pre-trained LLMs (GPT-4o, LLaMA 3.2, Gemini 2.0, and Claude 3.5 Sonnet) for conceptual cost estimation, comparing zero-shot prompting with a modular chain-of-thought framework. The results indicate that zero-shot prompting produced incomplete responses with an average confidence score of 1.91 (64%), whereas the CoT framework improved accuracy to 2.52 (84%) and achieved significant gains across BLEU, ROUGE-L, METEOR, content overlap, and semantic similarity metrics. The proposed modular CoT framework enhances structured reasoning, contextual alignment, and reliability in estimation workflows. This study contributes by developing a conceptual cost estimation framework for LLMs, benchmarking baseline model performance, and demonstrating how structured prompting improves estimation accuracy. This offers a scalable foundation for integrating AI into construction cost estimation workflows. Full article

(This article belongs to the Special Issue Knowledge Management in the Building and Construction Industry)

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21 pages, 8291 KB

Open AccessArticle

Multimodal Building Damage Assessment Method Fusing Adaptive Attention Mechanism and State-Space Modeling

by Rongping Zhu and Xiaoji Lan

Sensors 2026, 26(2), 638; https://doi.org/10.3390/s26020638 (registering DOI) - 18 Jan 2026

Abstract

Rapid and reliable building damage assessment (BDA) is crucial for post-disaster emergency response. However, existing methods face challenges such as complex background interference, the difficulty in jointly modeling local geometric details and global spatial dependencies, and adverse weather conditions. To address these issues, [...] Read more.

Rapid and reliable building damage assessment (BDA) is crucial for post-disaster emergency response. However, existing methods face challenges such as complex background interference, the difficulty in jointly modeling local geometric details and global spatial dependencies, and adverse weather conditions. To address these issues, this paper proposes the Adaptive Difference State-Space Fusion Network (ADSFNet), capable of processing both optical and Synthetic Aperture Radar (SAR) data to alleviate weather-induced limitations. To achieve this, ADSFNet innovatively introduces the Adaptive Difference Attention Fusion (ADAF) module and the Hybrid Selective State-Space Convolution (HSSC) module. Specifically, ADAF integrates pre- and post-disaster features to guide the network to focus on building regions while suppressing background interference. Meanwhile, HSSC synergizes the local texture extraction of CNNs with the global modeling strength of Mamba, enabling the simultaneous capture of cross-building spatial relationships and fine-grained damage details. Experimental results on sub-meter high-resolution MultiModal (BRIGHT) and optical (xBD) datasets demonstrate that ADSFNet attains F1 scores of 71.36% and 73.98%, which are 1.29% and 0.6% higher than the state-of-the-art mainstream methods, respectively. Finally, we leverage the model outputs to construct a disaster-centric knowledge graph and integrate it with Large Language Models to develop an intelligent management system, providing a novel technical pathway for emergency decision-making. Full article

(This article belongs to the Section Sensing and Imaging)

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11 pages, 1232 KB

Open AccessArticle

Impact of Unplanned Radiotherapy Interruptions and Prolonged Overall Treatment Time on Recurrence in Head and Neck Squamous-Cell Carcinoma: A Retrospective Analysis from a Single Institution

by Rabia S. Angiras, Dilson Lobo, Athiyamaan M. Senthiappan, Sourjya Banerjee, Srinivas Challapalli, Johan Sunny, Abhishek Krishna and Paul Simon

Onco 2026, 6(1), 8; https://doi.org/10.3390/onco6010008 (registering DOI) - 17 Jan 2026

Abstract

Introduction: Radiotherapy plays a critical role in the management of head and neck squamous-cell carcinoma (HNSCC); however, the influence of overall treatment time on patient outcomes remains an area of ongoing investigation. The use of radiation, either in conjunction with concurrent chemotherapy [...] Read more.

Introduction: Radiotherapy plays a critical role in the management of head and neck squamous-cell carcinoma (HNSCC); however, the influence of overall treatment time on patient outcomes remains an area of ongoing investigation. The use of radiation, either in conjunction with concurrent chemotherapy or on its own, is crucial when treating HNSCC. Despite the longstanding hypothesis that treatment gaps may adversely affect tumor response and overall survival, there is a paucity of literature on this particular area. This study aims to bridge the knowledge gap and assess the correlation of treatment gaps on recurrences in HNSCC patients. Materials and Methodology: This retrospective study is based on an analysis of data obtained from a single institution between 2017 and 2021. Patients were selected on the basis of the presence of treatment gaps. Data were extracted from medical records and analyzed to evaluate the association between overall treatment time and various patient and treatment-related factors. Various factors thought to contribute to treatment gaps, such as age, TNM Stage, radiation dose, and use of concurrent chemotherapy, were also examined. Results: A total of 212 patients with treatment gaps were evaluated. Of these, 80 individuals experienced recurrences. It was observed that compared to distant metastases, locoregional failure was more frequent (n = 2, 4.2% vs. n = 45, 95.74%). The patients underwent both adjuvant and definitive therapy and were treated with a dose range of 60–70 Gy and concurrent cisplatin chemotherapy. It was noticed that this cohort had a range of 4–43 days of treatment gaps. Notably, 19 out of 47 patients had treatment gaps ≤ 5 days, while 28 out of 47 had gaps exceeding 5 days. It was also observed that patients with treatment gaps of >5 days had poorer quality of life and overall survival. Conclusions: This study identified that the Overall Treatment Time (OTT) had a strong statistical correlation with the development of recurrences. Further, the age of the patient, presence of neutropenia and the duration of the treatment gap were also identified to significantly correlate with the chance of developing recurrences. Full article

(This article belongs to the Topic Cancer Biology and Radiation Therapy: 2nd Edition)

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41 pages, 6937 KB

Open AccessArticle

Ethnobotany of Local Vegetables and Spices in Sakon Nakhon Province, Thailand

by Piyaporn Saensouk, Surapon Saensouk, Phiphat Sonthongphithak, Auemporn Junsongduang, Kamonwan Koompoot, Bin Huang, Wei Shen and Tammanoon Jitpromma

Diversity 2026, 18(1), 49; https://doi.org/10.3390/d18010049 (registering DOI) - 17 Jan 2026

Abstract

Local vegetables and spices are essential components of traditional food and health systems in northeastern Thailand, yet quantitative ethnobotanical evidence remains limited. This study documents the diversity, utilization, and cultural significance of vegetables and spices used in Sang Kho Sub-district, Phu Phan District, [...] Read more.

Local vegetables and spices are essential components of traditional food and health systems in northeastern Thailand, yet quantitative ethnobotanical evidence remains limited. This study documents the diversity, utilization, and cultural significance of vegetables and spices used in Sang Kho Sub-district, Phu Phan District, Sakon Nakhon Province. Ethnobotanical data were collected in 2025 through field surveys, voucher-based plant identification, semi-structured interviews, and participant observation involving 92 informants across 23 villages. Cultural significance and medicinal knowledge were evaluated using the Cultural Importance Index (CI), Informant Consensus Factor (FIC), and Fidelity Level (FL). A total of 113 taxa belonging to 94 genera and 49 plant families were recorded. Poaceae and Zingiberaceae were the most species-rich families. Native species slightly predominated (51.33%), and herbaceous taxa were most common. Leaves were the most frequently used plant part. Most taxa were used as vegetables (92 species), followed by traditional medicines (20 species), spices or seasonings (18 species), and food ingredients or culinary additives (18 species). The highest CI values were recorded for Allium ascalonicum L. (1.152), Capsicum annuum L. (1.098), and Coriandrum sativum L. (1.043). FIC values ranged from 0.60 to 1.00, with complete consensus for circulatory and neurological disorders. Cymbopogon citratus showed the highest FL (75%) for gastrointestinal uses. These findings demonstrate the close integration of food and medicine in local plant-use systems and provide baseline data for food system resilience and cultural knowledge conservation. Full article

(This article belongs to the Special Issue Ethnobotany and Plant Diversity: Conservation and Sustainable Use)

21 pages, 2612 KB

Open AccessArticle

The Role of Individual Cognition in the Formation of Unsafe Behaviors: A Case Study of Construction Workers

by Guanghua Li, Zhijie Xiao, Youqing Chen, Igor Martek and Yuhao Zeng

Buildings 2026, 16(2), 395; https://doi.org/10.3390/buildings16020395 (registering DOI) - 17 Jan 2026

Abstract

As a pillar industry of the national economy for many countries, the construction sector has long faced challenges in workplace safety. Unsafe behaviors among construction workers are the core cause of safety incidents, and controlling these behaviors is key to enhancing safety management. [...] Read more.

As a pillar industry of the national economy for many countries, the construction sector has long faced challenges in workplace safety. Unsafe behaviors among construction workers are the core cause of safety incidents, and controlling these behaviors is key to enhancing safety management. Numerous studies confirm that unsafe behaviors are closely linked to cognitive biases and decision-making errors. However, existing research still has theoretical gaps in analyzing the multi-factor interaction mechanisms from a cognitive perspective. This study constructs a three-stage theoretical model to reveal the formation mechanism of unsafe behaviors, which is validated by structural equation modeling based on the data collected by a questionnaire from ongoing construction projects in Jiangxi Province, China. It is found that (1) Organizational environment (safety atmosphere, safety culture, and safety management) exerts a negative influence on unsafe behavior; (2) While safety atmosphere has no direct impact on safety motivation, the overall organizational environment positively affects individual cognition; (3) Individual cognitive factors exert a negative influence on unsafe behavior, with the following hierarchical order: safety motivation > safety competence > safety values. (4) While safety motivation does not mediate the relationship between safety atmosphere and unsafe behavior, individual cognitive factors overall mediate the relationship between organizational environment and unsafe behavior. This study theoretically enriches the knowledge system of safety behavior and provides a theoretical foundation for optimizing enterprise unsafe behavior management and formulating differentiated management policies. Full article

(This article belongs to the Special Issue Research on Safety Control and Risk Management in Construction Engineering: Progress, Challenges and Strategies)

21 pages, 7451 KB

Open AccessArticle

Distinct Pathways of Cadmium Immobilization as Affected by Wheat Straw- and Soybean Meal-Mediated Reductive Soil Disinfestation

by Tengqi Xu, Jingyi Mei, Cui Li, Lijun Hou, Kun Wang, Risheng Xu, Xiaomeng Wei, Jingwei Zhang, Jianxiao Song, Zuoqiang Yuan, Xiaohong Tian and Yanlong Chen

Agriculture 2026, 16(2), 242; https://doi.org/10.3390/agriculture16020242 (registering DOI) - 17 Jan 2026

Abstract

Both organic matter and iron oxide (FeO) dynamics pose key roles in soil cadmium (Cd) bioavailability. However, the microbially driven transformation of soil organic matter and FeO and their linkages to Cd fractions remain unclear under reductive soil disinfestation (RSD) with different organic [...] Read more.

Both organic matter and iron oxide (FeO) dynamics pose key roles in soil cadmium (Cd) bioavailability. However, the microbially driven transformation of soil organic matter and FeO and their linkages to Cd fractions remain unclear under reductive soil disinfestation (RSD) with different organic sources, which limits our mechanistic understanding of Cd immobilization by RSD. To address this gap, we conducted a 45 day microcosm experiment using a paddy soil contaminated with 22.8 mg/kg Cd. Six treatments were established: untreated control (CK), waterlogged (WF), and RSD-amended soils with 0.7% or 2.1% wheat straw (LWD, HWD) or soybean meal (LSD, HSD). We systematically assessed soil Cd fractionation, organic carbon and FeO concentrations, and bacterial community structure, aiming to clarify differences in Cd immobilization efficiency and the underlying mechanisms between wheat straw and soybean meal. For strongly extractable Cd, wheat straw RSD reduced the soil Cd concentrations from 6.02 mg/kg to 4.32 mg/kg (28.2%), whereas soybean meal RSD achieved a maximum reduction to 2.26 mg/kg (62.5%). Additionally, the soil mobility factor of Cd decreased from 44.6% (CK) to 39.2% (HWD) and 32.5% (HSD), while the distribution index increased from 58.5% (CK) to 62.2% (HWD) and 66.8% (HSD). Notably, the HWD treatment increased soil total organic carbon, humus, and humic acid concentrations by 34.8%, 24.6%, and 28.3%, respectively. Regarding amorphous FeO, their concentrations increased by 19.1% and 33.3% relative to CK. RSD treatments significantly altered soil C/N ratios (5.91–12.5). The higher C/N ratios associated with wheat straw stimulated r-strategist bacteria (e.g., Firmicutes, Bacteroidetes), which promoted carbohydrate degradation and fermentation, thereby enhancing the accumulation of humic substances. In contrast, the lower C/N ratios of soybean meal increased dissolved organic carbon and activated iron-reducing bacteria (FeRB; e.g., Anaeromyxobacter, Clostridium), driving iron reduction and amorphous iron oxide formation. PLS-PM analysis confirmed that wheat straw RSD immobilized Cd primarily through humification, whereas soybean meal RSD relied on FeRB-mediated FeO amorphization. These findings suggest that Cd immobilization in soil under RSD may be regulated by microbially mediated organic matter transformation and iron oxide dynamics, which was affected by organic materials of different C/N ratios. Full article

(This article belongs to the Section Agricultural Soils)

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36 pages, 5250 KB

Open AccessArticle

Nonlinear Gravity-Wave Effects on the Distribution of Chemical Constituents in a Vertically-Sheared Atmospheric Flow

by Ahmed S. Almohaimeed and Lucy J. Campbell

Mathematics 2026, 14(2), 322; https://doi.org/10.3390/math14020322 (registering DOI) - 17 Jan 2026

Abstract

The dynamical processes in the atmosphere are coupled with the chemistry of the atmosphere. Internal gravity waves influence the distribution of chemical constituents in the atmosphere through their effects on the background wind or mean flow. We examine a coupled system of equations [...] Read more.

The dynamical processes in the atmosphere are coupled with the chemistry of the atmosphere. Internal gravity waves influence the distribution of chemical constituents in the atmosphere through their effects on the background wind or mean flow. We examine a coupled system of equations comprising a nonlinear transport equation of Fisher type for the distribution of the chemical species, along with nonlinear Boussinesq equations for internal gravity waves in a vertically stratified and vertically sheared fluid flow in a two-dimensional region. In our model, a horizontally localized gravity-wave packet is generated and propagates upward into a localized region where the chemical species is present. Numerical solutions show that the wave-induced mean flow resulting from nonlinear gravity-wave interactions in the vicinity of a critical level leads to modifications in the distribution of the chemical. An asymptotic analysis of a related qualitatively similar problem gives us information on the dominant behaviour of the chemical concentration perturbation. We conclude that nonlinearity and vertical shear play a vital role in the interplay between gravity-wave dynamics and chemical distributions in the atmosphere. Full article

(This article belongs to the Special Issue Nonlinear Waves: Theory and Applications)

25 pages, 2903 KB

Open AccessArticle

Development of Braided River Delta–Shallow Lacustrine Siliciclastic–Carbonate Mixed Sedimentation in the Upper Ganchaigou Formation, Huatugou Oilfield, Qaidam Basin, China

by Yuxin Liang, Xinmin Song, Youjing Wang and Wenjie Feng

Minerals 2026, 16(1), 92; https://doi.org/10.3390/min16010092 (registering DOI) - 17 Jan 2026

Abstract

This study systematically investigates the lithofacies, sedimentary microfacies, vertical evolution, and spatial distribution of the braided river delta–shallow lacustrine carbonate mixed sedimentary rocks of the Upper Ganchaigou Formation in the Huatugou Oilfield of the Qaidam Basin, China. This study integrates data from field [...] Read more.

This study systematically investigates the lithofacies, sedimentary microfacies, vertical evolution, and spatial distribution of the braided river delta–shallow lacustrine carbonate mixed sedimentary rocks of the Upper Ganchaigou Formation in the Huatugou Oilfield of the Qaidam Basin, China. This study integrates data from field outcrops, core observations, thin section petrography, laboratory analyses, and well-logging interpretations. Based on these datasets, the sedimentary characteristics are identified, and a comprehensive sedimentary model is constructed. The results reveal that the study area contains five clastic facies, three types of mixed sedimentary facies, and ten sedimentary microfacies. Two distinct modes of mixed sedimentation are recognized: component mixing and stratigraphic mixing. A full lacustrine transgression–regression cycle is formed by the two types of mixed sedimentation characteristics, which exhibit noticeable differences in vertical evolution. Component mixing, which occurs in a mixed environment of continuous clastic supply and carbonate precipitation during the transgression, is the primary characteristic of the VIII–X oil formation. The mixed strata that make up the VI–VII oil formation show rhythmic interbedding of carbonate and clastic rocks. During the lacustrine regression, it shows the alternating sedimentary environment regulated by frequent variations in lacustrine levels. The planar distribution is affected by both intensity of sediment from the west and the changes in lacustrine level. During the lacustrine transgression, it is dominated by littoral-shallow lacustrine mixed beach bar and mixed sedimentary delta. On the other hand, during the lacustrine regression, it is dominated by laterally amalgamated sand bodies in the braided-river delta front. Based on this, a mixed sedimentary evolution model controlled by the coupling of “source–lacustrine level” is established. It offers a guide for reconstructing the sedimentary environment in basins that are similar to it and reveals the evolution path of mixed sedimentation in the short-axis source area of arid saline lacustrine basins. Full article

(This article belongs to the Topic Reservoir Genesis and Quality Evolution in Hydrocarbon Systems)

17 pages, 1455 KB

Open AccessArticle

Genipin as an Effective Crosslinker for High-Performance and Flexible Direct-Printed Bioelectrodes

by Kornelia Bobrowska, Marcin Urbanowicz, Agnieszka Paziewska-Nowak, Marek Dawgul and Kamila Sadowska

Molecules 2026, 31(2), 327; https://doi.org/10.3390/molecules31020327 (registering DOI) - 17 Jan 2026

Abstract

The development of efficient bioelectrodes requires suitable fabrication strategies, starting with the electrode material, which affects the electron transfer between the biocatalyst and the electrode surface. Then, selection and adjustment of the enzyme immobilization conditions are essential to enhance the performance of the [...] Read more.

The development of efficient bioelectrodes requires suitable fabrication strategies, starting with the electrode material, which affects the electron transfer between the biocatalyst and the electrode surface. Then, selection and adjustment of the enzyme immobilization conditions are essential to enhance the performance of the bioelectrodes for their desirable utility. In this study, we report the fabrication of a high-performance bioelectrode using a one-step crosslinking of FAD-dependent glucose dehydrogenase (FAD-GDH) and thionine acetate as a redox mediator, with genipin serving as a natural, biocompatible crosslinker. Electrodes were manufactured on flexible polyester substrates using a direct printing technique, enabling reproducible and low-cost production. Among the tested crosslinkers, genipin significantly enhanced the catalytic performance of bioelectrodes. Comparative studies on graphite, silver, and gold electrode materials identified graphite as the most suitable due to its extended electroactive surface area. The developed bioelectrodes applied to glucose biosensing demonstrated a linear amperometric response to glucose in the range of 0.02–2 mM and 0.048–30 mM, covering clinically relevant concentrations. The application of artificial sweat confirmed high detection accuracy. These findings highlight the potential integration of genipin-based enzyme–mediator networks for future non-invasive sweat glucose monitoring platforms. Full article

(This article belongs to the Special Issue 30th Anniversary of Molecules—Recent Advances in Electrochemistry)

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22 pages, 1400 KB

Open AccessArticle

Antibodies to Burkholderia pseudomallei Outer Membrane Proteins Coupled to Nanovaccines Exhibit Cross-Reactivity to B. cepacia Complex and Pseudomonas aeruginosa Homologues

by Alexander J. Badten, Susana Oaxaca-Torres and Alfredo G. Torres

Microorganisms 2026, 14(1), 221; https://doi.org/10.3390/microorganisms14010221 (registering DOI) - 17 Jan 2026

Abstract

Burkholderia pseudomallei complex and B. cepacia complex are two evolutionary distinct clades of pathogens causing human disease. Most vaccine efforts have focused on the former group largely due to their biothreat status and global disease burden. It has been proposed that a vaccine [...] Read more.

Burkholderia pseudomallei complex and B. cepacia complex are two evolutionary distinct clades of pathogens causing human disease. Most vaccine efforts have focused on the former group largely due to their biothreat status and global disease burden. It has been proposed that a vaccine could be developed that simultaneously protects against both groups of Burkholderia by specifically targeting conserved antigens. Only a few studies have set out to identify which antigens may be optimal targets for such a vaccine. We have previously assessed the ability of three highly conserved B. pseudomallei antigens, namely OmpA1, OmpA2, and Pal, coupled to gold nanoparticle vaccines, to protect mice against a homotypic B. pseudomallei challenge. Here, we have expanded our study by demonstrating that antibodies to each of these proteins show varying levels of reactivity to homologues in B. cepacia complex, with OmpA2 antibodies exhibiting the highest cross-reactivity. Remarkably, some nanovaccine immunized mice, particularly those that received OmpA2, produced antibodies that bind Pseudomonas aeruginosa, which harbors distantly related homologous proteins. T cells elicited to Pal and OmpA2 responded to stimulation with B. cepacia complex-derived homologues. Our study supports incorporation of these antigens, particularly OmpA2, for the development of a pan-Burkholderia vaccine. Full article

(This article belongs to the Special Issue Nanoparticle-Based Vaccines and Therapeutics for Multidrug-Resistant Pathogens)

16 pages, 1874 KB

Open AccessReview

LEM-Domain-Containing Inner Nuclear Membrane Proteins: Emerging Regulators of Intranuclear Signaling

by Byongsun Lee, Hyunggeun Lee and Jaekyung Shim

Int. J. Mol. Sci. 2026, 27(2), 942; https://doi.org/10.3390/ijms27020942 (registering DOI) - 17 Jan 2026

Abstract

The LAP2–emerin–MAN1-domain (LEM-D) proteins constitute a family of inner nuclear membrane proteins that play essential roles in the spatial regulation of intranuclear signaling. Defined by the conserved LEM domain, these proteins interact with chromatin, nuclear lamins, and barrier-to-autointegration factor (BAF), thereby linking nuclear [...] Read more.

The LAP2–emerin–MAN1-domain (LEM-D) proteins constitute a family of inner nuclear membrane proteins that play essential roles in the spatial regulation of intranuclear signaling. Defined by the conserved LEM domain, these proteins interact with chromatin, nuclear lamins, and barrier-to-autointegration factor (BAF), thereby linking nuclear architecture to signal-dependent transcriptional control. This review summarizes current knowledge on the structural features and molecular functions of representative LEM-D proteins, including LAP2, emerin, and MAN1, with a particular focus on their emerging roles as regulators of intranuclear signaling pathways. We discuss how these proteins modulate the activity of transcription factors involved in Hedgehog, Wnt/β-catenin, STAT3, Notch, and transforming growth factor-β (TGF-β) signaling by temporally retaining them at the inner nuclear membrane and controlling their access to chromatin. Furthermore, this review highlights the physiological and pathological relevance of LEM-D-mediated signaling regulation, especially in the context of muscle development, regeneration, and nuclear envelope-associated diseases such as muscular dystrophies. By integrating structural, signaling, and disease-related perspectives, this review proposes a conceptual framework in which LEM-D proteins function as critical intranuclear signaling hubs. Understanding these mechanisms provides new insights into nuclear signal transduction and suggests potential therapeutic targets for diseases associated with nuclear envelope dysfunction. Full article

(This article belongs to the Special Issue Protein Signal Transduction in the Nucleus)

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40 pages, 646 KB

Open AccessArticle

Leading Green: How Leadership Styles Shape Environmental Human Resource Management Practices in Greek Hospitality Organizations

by Christos Papademetriou, Dimitrios Belias, Angelos Ntalakos and Ioannis Rossidis

Sustainability 2026, 18(2), 974; https://doi.org/10.3390/su18020974 (registering DOI) - 17 Jan 2026

Abstract

This research focuses on the effects of leadership styles on the implementation of Green Human Resource Management (Green HRM) initiatives in hotels in Greece by staff members, and it recognizes the lack of sustainability research in the Mediterranean hospitality sector. Employing the Full-Range [...] Read more.

This research focuses on the effects of leadership styles on the implementation of Green Human Resource Management (Green HRM) initiatives in hotels in Greece by staff members, and it recognizes the lack of sustainability research in the Mediterranean hospitality sector. Employing the Full-Range Leadership Model, we explore the impact of transformational, transactional, and passive leadership on the implementation of environmental HR practices. The data for this study were obtained from 216 employees in 29 hotels in Greece, who completed the Multifactor Leadership Questionnaire (MLQ-5x) and a Green HRM instrument. Several regression analyses showed that transformational leadership was the most robust positive predictor of Green HRM practices, followed by leadership outcomes and transactional leadership. On the other hand, passive leadership was significantly inversely associated with Green HRM implementation. Demographic variables, such as gender, age, and experience, had a substantial impact on both perceptions of leadership and involvement in Green HRM as well. The results offer significant theoretical implications and practical directions for improving environmental performance in hospitality organizations through the strategic use of leadership development and human resource management ‍‌‍‍‌intervention. Full article

(This article belongs to the Special Issue Advancements and Innovation in Tourism Management and Strategic Management: Sustainable Development Perspective)

16 pages, 3887 KB

Open AccessArticle

Integrative Analysis of Transcriptome and Metabolome Reveals Molecular Mechanisms Underlying Hepatic Differences Between Zaozhuang Heigai Piglets and Duroc×Landrace×Yorkshire Piglets

by Caitong Wang, Jingxuan Li, Xueyan Zhao, Yanping Wang, Xiaodong Zhu, Fuping Zhao, Chuansheng Zhang, Liying Geng and Jiying Wang

Agriculture 2026, 16(2), 241; https://doi.org/10.3390/agriculture16020241 (registering DOI) - 17 Jan 2026

Abstract

Piglets weaning is a critical developmental stage marked by significant metabolic and inflammatory challenges. The hepatic responses during this period may differ among pig breeds with distinct genetic backgrounds. To explore the phenotypic and molecular differences in the livers between the Zaozhuang Heigai [...] Read more.

Piglets weaning is a critical developmental stage marked by significant metabolic and inflammatory challenges. The hepatic responses during this period may differ among pig breeds with distinct genetic backgrounds. To explore the phenotypic and molecular differences in the livers between the Zaozhuang Heigai (HG) pig and Duroc×Landrace×Yorkshire (DLY) piglets and elucidate the regulatory mechanisms of genetic background on liver function, five 35-day-old piglets from each breed were selected. Body weight and liver coefficients were measured; histological features of liver sections were observed, and the transcriptome and metabolome of the liver were determined using mRNA sequencing and non-targeted metabolomics analysis. The results showed that HG piglets had significantly lower body weight (p < 0.01) and slightly higher liver coefficients than DLY piglets. Histological examination revealed that the hepatic lobule structure was intact in both breeds, while mild hepatic congestion was observed in some DLY piglets. Transcriptome analysis identified 429 differentially expressed genes (DEGs) with criteria of FDR adjusted p-values < 0.01 and |log₂(Fold Change)| > 1, and they were significantly enriched in oxidoreductase activity, peroxisome proliferator-activated receptor (PPAR) signaling, and arachidonic acid metabolism pathways. Metabolome analysis identified 169 differentially expressed metabolites (DEMs) with criteria of p < 0.05, VIP > 1, and |log₂(Fold Change)| > 1, and they were significantly enriched in nucleotide metabolism, arginine biosynthesis, and arachidonic acid metabolism pathways. Integrative analysis of DEGs and DEMs showed that arachidonic acid metabolism was the common pathway. Within this pathway, key genes (GPX3, ALOX5, and CBR3) were significantly associated with specific metabolites (15-deoxy-PGJ₂ and phosphatidylcholines) (FDR adjusted p < 0.05), suggesting a gene–metabolite interaction network that coordinates inflammatory regulation and oxidative stress. These findings provide molecular evidence for breed-specific hepatic metabolic regulation during the weaning period and are therefore conducive to the management of weaned piglets and the investigation of local pig characteristics. Full article

(This article belongs to the Section Farm Animal Production)

18 pages, 840 KB

Open AccessArticle

Large Language Models Evaluation of Medical Licensing Examination Using GPT-4.0, ERNIE Bot 4.0, and GPT-4o

by Luoyu Lian, Xin Luo, Kavimbi Chipusu, Muhammad Awais Ashraf, Kelvin K. L. Wong and Wenjun Zhang

Bioengineering 2026, 13(1), 113; https://doi.org/10.3390/bioengineering13010113 (registering DOI) - 17 Jan 2026

Abstract

This study systematically evaluated the performance of three advanced large language models (LLMs)—GPT-4.0, ERNIE Bot 4.0, and GPT-4o—in the 2023 Chinese Medical Licensing Examination. Employing a dataset of 600 standardized questions, we analyzed the accuracy of each model in answering questions from three [...] Read more.

This study systematically evaluated the performance of three advanced large language models (LLMs)—GPT-4.0, ERNIE Bot 4.0, and GPT-4o—in the 2023 Chinese Medical Licensing Examination. Employing a dataset of 600 standardized questions, we analyzed the accuracy of each model in answering questions from three comprehensive sections: Basic Medical Comprehensive, Clinical Medical Comprehensive, and Humanities and Preventive Medicine Comprehensive. Our results demonstrate that both ERNIE Bot 4.0 and GPT-4o significantly outperformed GPT-4.0, achieving accuracies above the national pass mark. The study further examined the strengths and limitations of each model, providing insights into their applicability in medical education and potential areas for future improvement. These findings underscore the promise and challenges of deploying LLMs in multilingual medical education, suggesting a pathway towards integrating AI into medical training and assessment practices. Full article

(This article belongs to the Special Issue New Sights of Data Analysis and Digital Model in Biomedicine)

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24 pages, 1668 KB

Open AccessArticle

Sustainable Greenhouse Grape-Tomato Production Implementing a High-Tech Vertical Aquaponic System

by Ioanna Chatzigeorgiou, Maria Ravani, Ioannis A. Giantsis, Athanasios Koukounaras, Aphrodite Tsaballa and Georgios K. Ntinas

Horticulturae 2026, 12(1), 100; https://doi.org/10.3390/horticulturae12010100 (registering DOI) - 17 Jan 2026

Abstract

Growing pressure on water resources and mineral fertilizer use calls for innovative and resource-efficient agri-food systems. Aquaponics, integrating aquaculture and hydroponics, represents a promising approach for sustainable greenhouse production. This study, aiming to explore alternative water and nutrient sources for greenhouse tomato production [...] Read more.

Growing pressure on water resources and mineral fertilizer use calls for innovative and resource-efficient agri-food systems. Aquaponics, integrating aquaculture and hydroponics, represents a promising approach for sustainable greenhouse production. This study, aiming to explore alternative water and nutrient sources for greenhouse tomato production without compromising plant adaptability or yield, evaluated the co-cultivation of grape tomato and rainbow trout in a vertical decoupled aquaponic system under controlled greenhouse conditions. Two aquaponic nutrient strategies were tested: unmodified aquaponic water (AP) and complemented aquaponic water (CAP), with conventional hydroponics (HP) as a control, in a Deep Water Culture hydroponic system. Plant performance was assessed through marketable yield and physiological parameters, while system performance was evaluated using combined-biomass Energy Use Efficiency (EUE), Freshwater Use Efficiency (fWUE) and Nitrogen Use Efficiency (NUE), accounting for both plant and fish production. CAP significantly improved tomato yield (9.86 kg m⁻²) compared to AP (2.40 kg m⁻²), although it remained lower than HP (12.14 kg m⁻²). Fresh WUE was comparable between CAP and HP (9.22 vs. 9.24 g L⁻¹), demonstrating effective water reuse. In contrast, EUE and NUE were lower in CAP, reflecting the additional energy demand of the recirculating aquaculture system and nutrient limitations of fish wastewater. These results highlight aquaponics as a water-efficient production system while emphasizing that optimized nutrient management and energy strategies are critical for improving its overall sustainability and performance. Full article

(This article belongs to the Special Issue Horticultural Crop Cultivation in Greenhouse Ecosystems: Environmental Regulation and Sustainable Production)

20 pages, 325 KB

Open AccessArticle

Sharp Bounds on the Spectral Radius and Energy of Arithmetic–Geometric Matrix

by Hilal A. Ganie and Amal Alsaluli

Mathematics 2026, 14(2), 321; https://doi.org/10.3390/math14020321 (registering DOI) - 17 Jan 2026

Abstract

Let

Z

be a graph of order n with m edges. Let

A_{a g} (Z)

represents the arithmetic–geometric matrix of

Z

. The eigenvalues of the matrix

A_{a g} (Z)

are called the arithmetic–geometric eigenvalues, and the [...] Read more.

Let

Z

be a graph of order n with m edges. Let

A_{a g} (Z)

represents the arithmetic–geometric matrix of

Z

. The eigenvalues of the matrix

A_{a g} (Z)

are called the arithmetic–geometric eigenvalues, and the eigenvalue with the largest modulus is called the arithmetic–geometric spectral radius of

Z

. The sum of the absolute values of the arithmetic–geometric eigenvalues is called the arithmetic–geometric energy of

Z

. In this paper, we establish sharp upper and lower bounds for the AM-GM spectral radius in terms of various graph parameters and provide a complete characterization of the extremal graphs that attain these bounds. Additionally, we derive new bounds for the AM-GM energy of a graph and identify the corresponding extremal structures. In both contexts, our results significantly improve upon several existing bounds reported in the literature. Full article

25 pages, 4405 KB

Open AccessArticle

Research on Multi-USV Collision Avoidance Based on Priority-Driven and Expert-Guided Deep Reinforcement Learning

by Lixin Xu, Zixuan Wang, Zhichao Hong, Chaoshuai Han, Jiarong Qin and Ke Yang

J. Mar. Sci. Eng. 2026, 14(2), 197; https://doi.org/10.3390/jmse14020197 (registering DOI) - 17 Jan 2026

Abstract

Deep reinforcement learning (DRL) has demonstrated considerable potential for autonomous collision avoidance in unmanned surface vessels (USVs). However, its application in complex multi-agent maritime environments is often limited by challenges such as convergence issues and high computational costs. To address these issues, this [...] Read more.

Deep reinforcement learning (DRL) has demonstrated considerable potential for autonomous collision avoidance in unmanned surface vessels (USVs). However, its application in complex multi-agent maritime environments is often limited by challenges such as convergence issues and high computational costs. To address these issues, this paper proposes an expert-guided DRL algorithm that integrates a Dual-Priority Experience Replay (DPER) mechanism with a Hybrid Reciprocal Velocity Obstacles (HRVO) expert module. Specifically, the DPER mechanism prioritizes high-value experiences by considering both temporal-difference (TD) error and collision avoidance quality. The TD error prioritization selects experiences with large TD errors, which typically correspond to critical state transitions with significant prediction discrepancies, thus accelerating value function updates and enhancing learning efficiency. At the same time, the collision avoidance quality prioritization reinforces successful evasive actions, preventing them from being overshadowed by a large volume of ordinary experiences. To further improve algorithm performance, this study integrates a COLREGs-compliant HRVO expert module, which guides early-stage policy exploration while ensuring compliance with regulatory constraints. The expert mechanism is incorporated into the Soft Actor-Critic (SAC) algorithm and validated in multi-vessel collision avoidance scenarios using maritime simulations. The experimental results demonstrate that, compared to traditional DRL baselines, the proposed algorithm reduces training time by 60.37% and, in comparison to rule-based algorithms, achieves shorter navigation times and lower rudder frequencies. Full article

(This article belongs to the Section Ocean Engineering)

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22 pages, 11111 KB

Open AccessArticle

DeePC Sensitivity for Pressure Control with Pressure-Reducing Valves (PRVs) in Water Networks

by Jason Davda and Avi Ostfeld

Water 2026, 18(2), 253; https://doi.org/10.3390/w18020253 (registering DOI) - 17 Jan 2026

Abstract

This study provides a practice-oriented sensitivity analysis of DeePC for pressure management in water distribution systems. Two public benchmark systems were used, Fossolo (simpler) and Modena (more complex). Each run fixed a monitored node and pressure reference, applied the same randomized identification phase [...] Read more.

This study provides a practice-oriented sensitivity analysis of DeePC for pressure management in water distribution systems. Two public benchmark systems were used, Fossolo (simpler) and Modena (more complex). Each run fixed a monitored node and pressure reference, applied the same randomized identification phase followed by closed-loop control, and quantified performance by the mean absolute error (MAE) of the node pressure relative to the reference value. To better characterize closed-loop behavior beyond MAE, we additionally report (i) the maximum deviation from the reference over the control window and (ii) a valve actuation effort metric, normalized to enable fair comparison across different numbers of valves and, where relevant, different control update rates. Motivated by the need for practical guidance on how hydraulic boundary conditions and algorithmic choices shape DeePC performance in complex water networks, we examined four factors: (1) placement of an additional internal PRV, supplementing the reservoir-outlet PRVs; (2) the control time step

(Δ t)

; (3) a uniform reservoir-head offset

(Δ h)

; and (4) DeePC regularization weights

{(λ}_{g}, λ_{u}, λ_{y})

. Results show strong location sensitivity, in Fossolo, topologically closer placements tended to lower MAE, with exceptions; the baseline MAE with only the inlet PRV was 3.35 [m], defined as a DeePC run with no additions, no extra valve, and no changes to reservoir head, time step, or regularization weights. Several added-valve locations improved the MAE (i.e., reduced it) below this level, whereas poor choices increased the error up to ~8.5 [m]. In Modena, 54 candidate pipes were tested, the baseline MAE was 2.19 [m], and the best candidate (Pipe 312) achieved 2.02 [m], while pipes adjacent to the monitored node did not outperform the baseline. Decreasing

Δ t

across nine tested values consistently reduced MAE, with an approximately linear trend over the tested range, maximum deviation was unchanged (7.8 [m]) across all

Δ t

cases, and actuation effort decreased with shorter steps after normalization. Changing reservoir head had a pronounced effect: positive offsets improved tracking toward a floor of ≈0.49 [m] around

Δ h

≈ +30 [m], whereas negative offsets (below the reference) degraded performance. Tuning of regularization weights produced a modest spread (≈0.1 [m]) relative to other factors, and the best tested combination (λy, λg, λu) = (10², 10⁻³, 10⁻²) yielded MAE ≈ 2.11 [m], while actuation effort was more sensitive to the regularization choice than MAE/max deviation. We conclude that baseline system calibration, especially reservoir heads, is essential before running DeePC to avoid biased or artificially bounded outcomes, and that for large systems an external optimization (e.g., a genetic-algorithm search) is advisable to identify beneficial PRV locations. Full article

(This article belongs to the Special Issue Applications of Artificial Intelligence (AI) in Water Resources System, 2nd Edition)

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13 pages, 394 KB

Open AccessArticle

Trait-Mediated Variation in Plant Interactive Roles Within Plant–Floral Visitor Networks

by Fernanda Baena-Díaz, Brenda Ratoni, Carlos Pinilla Cruz, Ricardo Ayala and Wesley Dáttilo

Plants 2026, 15(2), 289; https://doi.org/10.3390/plants15020289 (registering DOI) - 17 Jan 2026

Abstract

Plant–pollinator interactions are essential to ecosystem functioning, yet the mechanisms that determine why some plant species become highly connected within interaction networks remain insufficiently understood, particularly in tropical coastal systems. Here, we examine how multiple plant traits predict the interactive role of species [...] Read more.

Plant–pollinator interactions are essential to ecosystem functioning, yet the mechanisms that determine why some plant species become highly connected within interaction networks remain insufficiently understood, particularly in tropical coastal systems. Here, we examine how multiple plant traits predict the interactive role of species within a bee–plant network in a coastal ecosystem in the Gulf of Mexico. Using an existing dataset comprising 35 plant species and 47 bee species, we quantified each plant’s interactive role through species degree, betweenness, and closeness centrality. We then evaluated how six traits (i.e., flower number, flower size, flower color, number of stamens, plant height, and life form) influence these network positions. Our results show that four traits significantly predicted plant interactive roles. Plants surrounded by more open flowers and those with larger flowers interacted with a greater diversity of bee species, indicating that resource detectability and accessibility strongly shape visitation patterns. Herbaceous species also exhibited higher interactive roles than woody plants, likely due to their rapid growth, abundant and synchronous flowering, and predictable resource availability in dynamic coastal environments. Additionally, yellow-flowered species received disproportionately more visits and achieved higher interactive roles, consistent with known sensory biases of bees toward yellow wavelengths. In contrast, plant height and stamen number showed no detectable influence on network position. Overall, our findings demonstrate that a combination of vegetative and floral traits (particularly those signaling abundant, accessible, and visually detectable resources) drives the emergence of key plant species within bee–plant networks. Integrating plant traits with network metrics provides a powerful framework for identifying species that sustain pollinator diversity and for predicting community responses to environmental change. Full article

(This article belongs to the Special Issue Plant-Animal Interactions: Highlighting Effects of Plant Anatomy, Natural History, and Environmental Changes)

23 pages, 3958 KB

Open AccessArticle

Performance of the Novel Reactive Access-Barring Scheme for NB-IoT Systems Based on the Machine Learning Inference

by Anastasia Daraseliya, Eduard Sopin, Julia Kolcheva, Vyacheslav Begishev and Konstantin Samouylov

Sensors 2026, 26(2), 636; https://doi.org/10.3390/s26020636 (registering DOI) - 17 Jan 2026

Abstract

Modern 5G+grade low power wide area network (LPWAN) technologies such as Narrowband Internet-of-Things (NB-IoT) operate utilizing a multi-channel slotted ALOHA algorithm at the random access phase. As a result, the random access phase in such systems is characterized by relatively low throughput and [...] Read more.

Modern 5G+grade low power wide area network (LPWAN) technologies such as Narrowband Internet-of-Things (NB-IoT) operate utilizing a multi-channel slotted ALOHA algorithm at the random access phase. As a result, the random access phase in such systems is characterized by relatively low throughput and is highly sensitive to traffic fluctuations that could lead the system outside of its stable operational regime. Although theoretical results specifying the optimal transmission probability that maximizes the successful preamble transmission probability are well known, the lack of knowledge about the current offered traffic load at the BS makes the problem of maintaining the optimal throughput a challenging task. In this paper, we propose and analyze a new reactive access-barring scheme for NB+IoT systems based on machine learning (ML) techniques. Specifically, we first demonstrate that knowing the number of user equipments (UE) experiencing a collision at the BS is sufficient to make conclusions about the current offered traffic load. Then, we show that through utilizing ML-based techniques, one can safely differentiate between events in the Physical Random Access Channel (PRACH) at the base station (BS) side based on only the signal-to-noise ratio (SNR). Finally, we mathematically characterize the delay experienced under the proposed reactive access-barring technique. In our numerical results, we show that by utilizing modern neural network approaches, such as the XGBoost classifier, one can precisely differentiate between events on the PRACH channel with accuracy reaching 0.98 and then associate it with the number of user equipment (UE) competing at the random access phase. Our simulation results show that the proposed approach can keep the successful preamble transmission probability constant at approximately 0.3 in overloaded conditions, when for conventional NB-IoT access, this value is less than 0.05. The proposed scheme achieves near-optimal throughput in multi-channel ALOHA by employing dynamic traffic awareness to adjust the non-unit transmission probability. This proactive congestion control ensures a controlled and bounded delay, preventing latency from exceeding the system’s maximum load capacity. Full article

(This article belongs to the Special Issue Sensor and IoT Technologies for Next-Generation/6G Communication Systems)

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21 pages, 22584 KB

Open AccessArticle

Early-Age Performance Evolution and Multi-Field Coupling Numerical Simulation of Large-Area Concrete Slabs Under Curing Regime Control

by Xiji Hu, Ruizhen Yan, Xin Cheng, Fanqi Meng, Xiaokang Yang and Menglong Zhou

Buildings 2026, 16(2), 394; https://doi.org/10.3390/buildings16020394 (registering DOI) - 17 Jan 2026

Abstract

This study investigates the early-age performance of large-area C30 concrete slabs under different curing regimes using a multi-scale approach combining laboratory experiments, field monitoring, and numerical simulation. The experimental results indicated that standard curing (SC7) maximized the mechanical properties. In contrast, the thermal [...] Read more.

This study investigates the early-age performance of large-area C30 concrete slabs under different curing regimes using a multi-scale approach combining laboratory experiments, field monitoring, and numerical simulation. The experimental results indicated that standard curing (SC7) maximized the mechanical properties. In contrast, the thermal insulation and moisture retention curing (TC) regime significantly reduced temperature gradients and stress mutation amplitudes by 42% compared to wet curing (WC) by leveraging the synergistic effect of aluminum foil and insulating cotton. This makes TC a preferred solution in situations where engineering constraints apply. Field monitoring demonstrated that WC is suitable for humidity-sensitive scenarios with low-temperature control requirements, while TC is more suitable for large-area concrete or low-temperature environments, balancing early strength development and long-term durability. This multi-field coupled model exhibits significant deviations during the early stage (0–7 days) due to complex boundary interactions, but achieves high quantitative accuracy in the long-term steady state (after 14 days), with a maximum error below 8%. The analysis revealed that the key driving factors for stress evolution are early hydration heat–humidity coupling and mid-term boundary transient switching. The study provides a novel, multi-scale validated curing optimization path for crack control in large-area concrete slabs. Full article

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27 pages, 1789 KB

Open AccessReview

The Extracellular Matrix, the Silent ‘Architect’ of Glioma

by Carmen Rubio, Javier Pérez-Villavicencio, Nadia F. Esteban-Román, Ángel Lee, Gervith Reyes-Soto and Moisés Rubio-Osornio

Biomedicines 2026, 14(1), 205; https://doi.org/10.3390/biomedicines14010205 (registering DOI) - 17 Jan 2026

Abstract

The brain’s extracellular matrix (ECM) serves as a dynamic and instructive regulator of glioma progression. The ECM provides structural support while integrating pharmacological and mechanical signals that influence glioma initiation, progression, and treatment resistance. Deviant ECM remodeling fosters tumor heterogeneity, invasion, and immune [...] Read more.

The brain’s extracellular matrix (ECM) serves as a dynamic and instructive regulator of glioma progression. The ECM provides structural support while integrating pharmacological and mechanical signals that influence glioma initiation, progression, and treatment resistance. Deviant ECM remodeling fosters tumor heterogeneity, invasion, and immune evasion by altering stiffness, composition, and cellular matrix signaling. We proposed that ECM remodeling in gliomas not only facilitates tumor growth and heterogeneity but also establishes advantageous biophysical and metabolic conditions that foster treatment resistance and recurrence. Our objective is to analyze current findings regarding the structural, biochemical, and mechanical roles of the brain ECM in glioma growth, emphasizing its contribution to tumor heterogeneity, mechanotransduction, immunological modulation, and its potential as a therapeutic target. Method: A comprehensive literature review was conducted using scientific databases including PubMed, Web of Science, and Scopus. Peer-reviewed literature published between 2000 and 2025 was selected for its relevance to ECM composition, stiffness, remodeling enzymes, extracellular vesicles, and mechanobiological processes in gliomas. Results: Recent investigations demonstrate that glioma cells actively alter the ECM by secreting collagens, laminins, and metalloproteinases, establishing a feedback loop that facilitates invasion and resistance. Discussion: Mechanical variables, such as ECM stiffness and solid stress, influence glioma growth, metabolism, and immune exclusion. Moreover, extracellular vesicles facilitate significant extracellular matrix remodeling and improve communication between tumors and stromal cells. The disruption of ependymal and subventricular extracellular matrix niches enhances invasion and cerebrospinal fluid-mediated signaling. The remodeling of the ECM influences glioma growth through interconnected biochemical, mechanical, and immunological mechanisms. Examining ECM stiffness, crosslinking enzymes, and vesicle-mediated signaling represents a potential therapeutic approach. Integrative methodologies that combine mechanobiology, imaging, and multiomics analysis could uncover ECM-related vulnerabilities to improve glioma treatment. Full article

(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas: 2nd Edition)

31 pages, 630 KB

Open AccessArticle

Sustainable Financial Markets in the Digital Era: FinTech, Crowdfunding and ESG-Driven Market Efficiency in the UK

by Loredana Maria Clim (Moga), Diana Andreea Mândricel and Ionica Oncioiu

Sustainability 2026, 18(2), 973; https://doi.org/10.3390/su18020973 (registering DOI) - 17 Jan 2026

Abstract

In the context of tightening sustainability regulations and rising demands for transparent and responsible capital allocation, understanding how digital financial innovations influence market efficiency has become increasingly important. This study examines the impact of Financial Technology (FinTech) solutions and crowdfunding platforms on sustainable [...] Read more.

In the context of tightening sustainability regulations and rising demands for transparent and responsible capital allocation, understanding how digital financial innovations influence market efficiency has become increasingly important. This study examines the impact of Financial Technology (FinTech) solutions and crowdfunding platforms on sustainable market efficiency, volatility dynamics, and risk structures in the United Kingdom. Using weekly data for the Financial Times Stock Exchange 100 (FTSE 100) index from January 2010 to June 2025, the analysis applies the Lo–MacKinlay variance ratio test to assess compliance with the Random Walk Hypothesis as a proxy for informational efficiency. Firm-level proxies for FinTech and crowdfunding activity are constructed using the Nomenclature of Economic Activities (NACE) and Standard Industrial Classification (SIC) systems. The empirical results indicate substantial deviations from random-walk behavior in crowdfunding-related market segments, where persistent positive autocorrelation and elevated volatility reflect liquidity constraints and informational frictions. By contrast, FinTech-dominated segments display milder inefficiencies and faster information absorption, pointing to more stable price-adjustment mechanisms. After controlling for structural distortions through heteroskedasticity-consistent corrections and volatility adjustments, variance ratios converge toward unity, suggesting a restoration of informational efficiency. The results provide relevant insights for investors, regulators, and policymakers seeking to align financial innovation with the objectives of sustainable financial systems. Full article

(This article belongs to the Special Issue Sustainable Finance, Technologies, and Regulatory Frameworks: Advancing Sustainability in a Digital Era)

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