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While dissolution dominates the genesis of karst systems, physical erosion processes also play a significant role in their development. Lowering of the water table exposes caves to vadose conditions, reducing roof-supporting buoyancy and potentially leading to catastrophic conduit ceiling failure and cave collapse. The locations and extents of collapse areas are not always identifiable at the landscape surface. High-resolution topographic data derived from LiDAR were used to develop a digital elevation model (DEM) that isolates areas that may have sustained episodes of cave collapse and improves our understanding of past hydrogeological and geomorphological conditions of the system. Cave level delineation from LiDAR data was used to assign elevations to cave entrances. Spatial susceptibility to past collapse was evaluated using a weighted multi-criteria analysis that integrated terrain slope, proximity to mapped cave entrances, and distance to surface streams. Areas identified as having a high likelihood of collapse spatially coincide with cave level contacts and known karst windows and terraces, indicating that this replicated methodology is effective as an initial survey tool for identifying collapse-prone areas in karst landscapes. Full article

(This article belongs to the Section Natural Hazards)

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26 pages, 1701 KB

Open AccessArticle

Serious Games for Just Energy Transitions: Theoretical Framework and Application to Enhance Decision-Making for Sustainability

by Vasiliki Kioupi, Morgan Campbell, Gbemi Oluleye and Zoe M. Harris

Sustainability 2026, 18(5), 2382; https://doi.org/10.3390/su18052382 (registering DOI) - 1 Mar 2026

Abstract

Just energy transitions require diverse voices to be considered, but appropriate tools are still lacking. This study aimed to identify a tool by which diverse views could be considered in decision-making for climate change and energy transitions. Specifically, a literature review was conducted to understand the current status and gaps in the use and the application of Serious Games (SGs) in the field of sustainability. This was further used to construct a framework of criteria for selecting SGs that can enable diversity in decision-making. A specific Serious Game was selected using the framework criteria and applied in qualitative analysis that investigated a gameplay and method of data collection and analysis to assess the impact group diversity has on collective decision-making for sustainability and the quality of outcomes produced. The New Shores game was used within the context of sustainability and resilience to climate disasters. A more diverse and a less diverse group (age, ethnicity, gender, and professional role) were recruited in winter 2021, to play the game in online workshops and make decisions to sustainably develop an island while balancing personal and community wellbeing. The way each group engaged with each other and addressed the challenges of the gameplay were qualitatively evaluated to scrutinise levels of collaboration; collective decision-making and the final status of the island was quantitatively analysed to assess quality of outcomes produced by each group. Positive findings indicate that heterogenous groups demonstrated stronger collaboration, prioritised collective goals, and achieved more socially equitable and resilient outcomes compared to homogenous groups. While small scale and exploratory, the positive findings of this study indicate the need for further sustained research into use of Serious Games for sustainability decision-making, to better understand how diverse groups make decisions in game playing contexts and the extent and conditions needed for these patterns’ transfer to real-world contexts. Full article

(This article belongs to the Special Issue Achieving Sustainability: Role of Technology and Innovation)

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13 pages, 1780 KB

Open AccessArticle

The Transcription Factor AcMYC2 Alleviates Chilling Injury by Improving Cold Resistance of Kiwifruit ‘Taishan 1’

by Qi Guo, Meilin Zhou, Mi Xun, Miao An, Huihui Han, Xuanyao Ren, Hanxiao Wang, Wei Lv, Shijin Wang, Jian Li and Guotian Li

Plants 2026, 15(5), 759; https://doi.org/10.3390/plants15050759 (registering DOI) - 1 Mar 2026

Abstract

Kiwifruit, classified as a respiratory climacteric fruit, faces challenges due to its limited resistance to storage and transportation. Although low-temperature storage is a cost-effective and widely used method, the cold injury it induces poses significant hurdles to industrial development. In this study, we selected ‘Taishan 1’, the dominant kiwifruit cultivar in Shandong Province, as the experimental material. Through transcriptome sequencing, we identified the key gene AcMYC2, which plays a crucial role in the kiwifruit’s response to low-temperature stress. Subsequently, virus-induced gene silencing (VIGS) was performed on ‘Taishan 1’ kiwifruit, and gene overexpression was validated in tomatoes. The results demonstrated that AcMYC2 enhances cold tolerance in kiwifruit accompanied by multiple physiological processes, including antioxidant activity, lipid metabolism, and cell wall degradation. These findings offer significant insights into mitigating cold injury during low-temperature storage of kiwifruit and provide a theoretical foundation for advancing postharvest preservation techniques. Full article

(This article belongs to the Special Issue Biochemical Responses of Horticultural Crops to Abiotic Stresses)

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14 pages, 2784 KB

Open AccessArticle

Structural, Textural, and Functional Properties of Plant-Based Meat Analogs Prepared by High-Moisture Extrusion of Soy–Wheat–Mung Bean Multi-Protein System

by Ka Li, Yu Zhao, Siqi Wang, Yan Zhang and Xiaonan Sui

Foods 2026, 15(5), 824; https://doi.org/10.3390/foods15050824 (registering DOI) - 1 Mar 2026

Abstract

High-moisture extrusion (HME) is critical for plant-based meat analogs with meat-like fibrous structures. To expand HME protein sources, this study explored mung bean protein (MBP) substitution (0–50%, dry basis) effects on structural, textural and functional properties of soy protein concentrate (SPC)–wheat gluten (WG) HME products. At 20% MBP addition, the proteins formed a dense layered fibrous network, and the fibrous degree of the extrudates reached the peak. MBP > 40% disrupted the continuous protein network. The optimal rehydration for 20% MBP dried extrudates was 60 °C for 40 min, preserving fibrous texture. Protein interaction analysis indicated that hydrogen bonds and disulfide bonds played an important role in stabilizing the protein network structure. Overall, MBP can be incorporated into SPC-WG-based HME products to diversify protein sources, providing a feasible strategy for developing high-quality, nutritionally diversified plant-based meats. Full article

(This article belongs to the Section Food Engineering and Technology)

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12 pages, 212 KB

Open AccessArticle

Fresh Food for Health: The Impact of Onsite Produce Events at Federally Qualified Health Centers

by Keisha M. Macon, Julia I. Caldwell, Natallie Kochumian, Dipa Shah and Tony Kuo

Sci 2026, 8(3), 52; https://doi.org/10.3390/sci8030052 (registering DOI) - 1 Mar 2026

Abstract

This study assessed whether frequent attendance of onsite produce events at Federally Qualified Health Centers is associated with increased fruit and vegetable consumption, reduced food insecurity, and enrollment in food assistance. A deeper understanding of these relationships may help program implementers and health practitioners improve healthy food access among low-income patients by screening for food insecurity and offering onsite produce distribution events at clinic sites. Using a cross-sectional observational design, study data originated from an intercept survey of 886 adults who attended free produce events at 14 clinic locations in Los Angeles County during 2021–2023. Multivariable models assessed associations between attendance frequency and the main outcomes: fruit and vegetable consumption, food insecurity, and enrollment in food assistance (i.e., SNAP, WIC). Compared with first-time attendees, frequent attendees had higher odds of meeting the MyPlate recommendations for fruit (adjusted odds ratio [AOR] = 1.37, p = 0.012) and vegetable (AOR = 1.47, p = 0.019) consumption. Frequent attendees, compared with first-time attendees, also had marginally lower odds of food insecurity (AOR = 0.73, p = 0.077), with no effect on food assistance enrollment. These findings suggest safety-net health centers can play meaningful, multi-faceted roles in increasing patient access to healthy food by screening for food insecurity and offering onsite free produce distributions at their clinic sites. Full article

(This article belongs to the Section Biology Research and Life Sciences)

34 pages, 1780 KB

Open AccessArticle

Hyaluronic Acid-Like Skin Plumping and Radiance Benefits of a Porphyridium Sulfated Exopolysaccharide- and Natural PDRN-Rich Extract

by Fabien Havas, Shlomo Krispin, Moshe Cohen and Joan Attia-Vigneau

Mar. Drugs 2026, 24(3), 99; https://doi.org/10.3390/md24030099 (registering DOI) - 1 Mar 2026

Abstract

Red microalga Porphyridium cruentum produces a sulfated exopolysaccharide (EPS), which enables its survival in challenging intertidal and spray zones. Extracellular polysaccharide hyaluronic acid (HA) plays important roles in skin hydration, elasticity, and volume. However, with aging, HA decreases and loses effectiveness, reducing skin moisture retention and firmness, and increasing signs of aging. An effective topical alternative to injectable HA replacement remains a largely unmet need. An extract of Porphyridium cultivated in natural sunlight, rich in EPS and polydeoxyribonucleotides (PDRNs), significantly activated the ADORA2A receptor in a CHO model, as well as reduced inflammation and increased collagen and HA production, autophagic flux, and key autophagy gene expression in dermal fibroblast cultures. In a double-blind clinical trial with placebo and HA benchmark controls, the Porphyridium extract delivered significant HA-like skin plumpness, hydration, and radiance benefits, and reduced signs of aging. The extract generally equaled or exceeded the HA benchmark. Its meaningful, swift HA-like activity shows potential for a safe, natural, and arguably more powerful HA-like alternative. Full article

(This article belongs to the Special Issue Marine Natural Products with Anti-Aging Activity, 2nd Edition)

35 pages, 4738 KB

Open AccessReview

AI-Driven Design of Sustainable Flame-Retardant Biodegradable Polymer Composites

by Jinfeng Zhang, António Benjamim Mapossa, Yuxin Liu and Uttandaraman Sundararaj

Appl. Sci. 2026, 16(5), 2405; https://doi.org/10.3390/app16052405 (registering DOI) - 1 Mar 2026

Abstract

The growing demand for lightweight, high-performance, and fire-safe polymer materials has accelerated research into advanced flame-retardant composites. Traditional experimental approaches to designing sustainable flame-retardant biodegradable polymer composites still rely heavily on empirical formulation and iterative testing, which are time-consuming and costly, and they often struggle to capture the coupled effects of chemical composition, processing conditions, and material performance. Recent advances in artificial intelligence (AI) provide opportunities to address these challenges by learning formulation–structure–performance relationships from curated datasets and by translating materials chemistry and flame-retardant mechanisms into data-ready descriptors and targets. This review summarizes recent progress of AI-assisted approaches to design sustainable flame-retardant biodegradable polymer composites, emphasizing machine learning, deep learning, and active learning methods for predicting and optimizing key fire performance metrics, including limiting oxygen index and heat release-related parameters. Biodegradable-specific limitations, including narrow processing window, thermal degradation, and moisture sensitivity, are discussed in the content of descriptor selection and constraint-aware optimization, together with the role of interpretable/explainable models in supporting experimentally actionable guidance. Current challenges such as limited data availability, protocol variability, model transferability, and interpretability are highlighted, and emerging solutions, including data harmonization, standardized fire testing, and physics-informed models are outlined. AI-assisted strategies are expected to play a central role in accelerating efficient, sustainable, halogen-free, and performance-driven development of next-generation flame-retardant biodegradable polymer composites. Full article

(This article belongs to the Special Issue Advances in Polymer Composites: Mechanical Performance, Manufacturing Process and Applications)

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13 pages, 1049 KB

Open AccessArticle

New Insights Into the Combined Antiviral Effect of Extracts from Nerium oleander and Boswellia sacra Against Respiratory Syncytial Virus: A Preliminary Report

by Rebecca Piras, Luca Virdis, Valeria Manca, Marta Cogoni, Vanessa Palmas, Matthew G. Donadu, Aldo Manzin, Giuseppina Sanna and Luay Rashan

Pathogens 2026, 15(3), 260; https://doi.org/10.3390/pathogens15030260 (registering DOI) - 1 Mar 2026

Abstract

In recent years, the emergence of drug-resistant pathogens and the limitations of current therapies have highlighted the need for innovative strategies to combat emerging viral infections. Natural compounds, derived from plants, are playing an increasingly significant role in the research of novel and effective therapies. Boswellia sacra, a frankincense-producing tree widely distributed in Yemen and Oman, and Nerium oleander, a common ornamental and medicinal plant, are examples of plants with well-documented antimicrobial properties. Their extracts have demonstrated good activity against a wide range of infections, which is attributed to the anti-inflammatory and immunomodulatory compounds they contain. Based on these findings, we assessed, in vitro, the broad-spectrum antiviral activity of combined extracts obtained from Boswellia sacra and Nerium oleander. The extract mixture NOBS7(1) was found to be active against the respiratory virus RSV, Herpesvirus simplex type 1, and Coxsackievirus 5. Furthermore, a combination of cell-based assays was performed to provide additional insights into their potential mechanism of action. Full article

(This article belongs to the Special Issue Antiviral Strategies Against Human Respiratory Viruses)

26 pages, 1648 KB

Open AccessReview

Contaminated Soils as Potential Secondary Sources of Critical Metals: Remediation Technologies and Recovery Perspectives

by Gianniantonio Petruzzelli, Francesca Pedron, Elisabetta Franchi, Danilo Fusini and Meri Barbafieri

Environments 2026, 13(3), 132; https://doi.org/10.3390/environments13030132 (registering DOI) - 1 Mar 2026

Abstract

Critical metals play a crucial role in advancing sustainable energy technologies, with their demand steadily increasing due to the global push for a circular economy. At present, critical metals are primarily extracted from mineral resources, but critical metal-contaminated soils could often be considered as an alternative source of these elements. There is a growing need for remediation approaches that not only decontaminate soils but also recover valuable metals, thereby aligning with the principles of a circular economy. This review aims to suggest soil remediation strategies able to tackle critical metals contamination, particularly those capable of extracting these elements (dual-purpose technologies). Existing studies indicate that critical metal-contaminated soils are commonly found near mining sites, but their increasing use is spreading these elements into the whole environment. Considering nickel as an example of critical metal, we examine some consolidated technologies which, in addition to remediation, enable the recovery of this critical metal from the soil. Phytomining demonstrated significant potential in extracting nickel from contaminated soils. Electrokinetic treatment and soil washing can be considered as a promising methodology to clean up soils, also facilitating nickel recovery. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Soil Contamination and Remediation)

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22 pages, 1651 KB

Open AccessReview

The Ubiquitin-Specific Protease Family: Master Regulators of Renal Fibrosis Pathogenesis and Therapeutic Targets

by Yinhang Wang, Dadui Ren, Wenjun Zhao, Yongmei Zhang and Xuemei Zhang

Int. J. Mol. Sci. 2026, 27(5), 2318; https://doi.org/10.3390/ijms27052318 (registering DOI) - 1 Mar 2026

Abstract

Ubiquitin-specific proteases (USPs) constitute the largest and most diverse family of deubiquitinating enzymes (DUBs), playing a pivotal role in maintaining protein homeostasis through reversible post-translational modifications (PTMs). Renal fibrosis represents the final common pathway of various chronic kidney diseases (CKDs), ultimately leading to irreversible nephron loss and end-stage renal disease (ESRD). With CKD affecting over 10% of the global adult population, fibrosis imposes a substantial clinical and economic burden. Despite this, effective antifibrotic therapies remain clinically elusive. Emerging evidence highlights the critical involvement of USPs in the pathogenesis of renal fibrosis through the potentiation of pro-fibrotic signaling pathways, inflammation, oxidative stress, cell cycle arrest and cellular senescence, as well as some other pathways. This review comprehensively summarizes the current understanding of USPs in renal fibrosis, detailing their structural characteristics, molecular mechanisms, and specific regulatory roles. Furthermore, we discuss recent advances in developing small-molecule USP inhibitors, providing novel insights into targeting the ubiquitin–proteasome system as a promising therapeutic strategy for combating renal fibrosis. Full article

(This article belongs to the Special Issue Fine-Tuning Proteostasis: Insights into Ubiquitination and Deubiquitination Pathways)

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25 pages, 2735 KB

Open AccessFeature PaperArticle

Beyond Traditional Forecasting Methods: Evaluating LSTM Performance on Diverse Time Series

by Zoltán Baráth, Péter Veres and Ágota Bányai

Mathematics 2026, 14(5), 838; https://doi.org/10.3390/math14050838 (registering DOI) - 1 Mar 2026

Abstract

Time series forecasting performance is strongly influenced by the structural properties of the underlying data, yet learning-based models are often applied without sufficient validation of this dependency. This study evaluates a uniformly configured Long Short-Term Memory (LSTM) model on five real-world weekly time series with different levels of periodicity, noise, and volatility. Forecasting is performed in a single-step setting using a fixed sliding window of 12 weeks under a consistent training, validation, and testing framework. Model performance is assessed using mean squared error (MSE) and the coefficient of determination R². The results show that for well-structured series, both the LSTM model and Holt’s exponential smoothing achieve very low MSE values with R² scores close to one, indicating excellent predictive accuracy. For other items, performance varies across methods, with either the LSTM or Holt model providing the best results depending on the data structure. These findings confirm that high forecasting accuracy can be achieved with both advanced and classical methods, and that data characteristics play a more decisive role than model complexity. Full article

(This article belongs to the Special Issue Soft Computing in Computational Intelligence and Machine Learning)

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22 pages, 1960 KB

Open AccessReview

Micro- and Mesoporous Silica-Based Materials as Support Catalysts in Reforming Reactions

by Chiara Nunnari, Antonio Fotia, Angela Malara, Anastasia Macario and Patrizia Frontera

Catalysts 2026, 16(3), 218; https://doi.org/10.3390/catal16030218 (registering DOI) - 1 Mar 2026

Abstract

Reforming processes are key technologies for the production of hydrogen and synthesis gas from hydrocarbon feedstocks, with steam reforming and dry reforming being the most extensively studied routes. Steam reforming remains the dominant industrial process due to its high efficiency and economic viability; however, its associated CO₂ emissions raise environmental concerns, partially mitigated through an integration with carbon capture and storage technologies. Dry reforming has emerged as an attractive alternative, although it requires high operating temperatures and suffers from catalyst deactivation. Catalyst design is therefore critical for improving process efficiency and stability. Supported metal catalysts, particularly Ni-based systems, are widely employed, with the support material playing a decisive role in metal dispersion, resistance to sintering and coking, and reaction selectivity. Microporous and mesoporous silica-based materials, including zeolites and ordered mesoporous silicas, offer tunable structural and surface properties that enhance catalytic performance. The novelty of this work lies in its holistic approach to reforming catalysis, where the catalytic performance is not discussed solely in terms of active metals, but is systematically correlated with the surface properties, chemical composition, and structural features of silica-based supports. Moreover, this study expands the perspective to alternative and less-explored feedstocks. By considering multiple fuels and support types, the study provides new design guidelines for developing more efficient and sustainable reforming catalysts. Full article

(This article belongs to the Special Issue Microporous and Mesoporous Materials for Catalytic Applications, 2nd Edition)

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18 pages, 3194 KB

Open AccessArticle

Engineering of Extracellular Vesicles for Targeted Delivery of Prodigiosin

by Ivan Guryanov, Sirina Sabirova, Svetlana Batasheva, Svetlana Konnova, Arthur Khannanov, Marianna Kutyreva and Ekaterina Naumenko

BioTech 2026, 15(1), 21; https://doi.org/10.3390/biotech15010021 (registering DOI) - 1 Mar 2026

Abstract

The therapeutic potential of prodigiosin as a hydrophobic anticancer agent can be enhanced by various approaches, one of which is the loading of PG into extracellular vesicles. Drug distribution and stability in aqueous media play a crucial role in targeting and accumulation, thereby enabling the attainment of therapeutically effective drug concentrations. Extracellular vesicles are nano-sized, cell-derived vesicles with a lipid bilayer membrane. Extracellular vesicles can be utilized as drug carriers for both water-soluble and non-water-soluble therapeutic agents. We hypothesized that microvesicles could effectively address the current challenges of prodigiosin delivery. Several different techniques have been developed for fabricating extracellular vesicles. These include microvesicles induction by cytochalasin B treatment as well as cell cultivation in serum depleted media. In our study, prodigiosin, like cytochalasin B, demonstrated efficacy in microvesicles formation based on protein quantification and Nanoparticle Tracking Analysis. In addition, Nanoparticle Tracking Analysis showed that vesicles from mesenchymal stem cells are more stable under ultrasound exposure. Microvesicles encapsulating prodigiosin, compared to unmodified naïve ones, demonstrated slightly increased zeta potentials and hydrodynamic diameters, which probably contributed to better stability. We demonstrated that ultrasonic treatment for the loading of prodigiosin does not significantly increase the proportion of prodigiosin-positive microvesicles in comparison with microvesicles induced with prodigiosin; moreover, this method cannot be considered as optimal due to its disadvantages, such as particle aggregation. Prodigiosin-induced and prodigiosin-loaded microvesicles from mesenchymal stem cells were significantly smaller and less polydisperse in size. Overall, prodigiosin encapsulated in extracellular vesicles might be more suitable for medical and clinical applications compared to pure forms of PG due to their cell membrane compatibility. Full article

(This article belongs to the Section Medical Biotechnology)

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15 pages, 253 KB

Open AccessArticle

Which Components of Test Anxiety Predict University Dropout?

by Luca Csirmaz and Krisztian Kasos

Youth 2026, 6(1), 29; https://doi.org/10.3390/youth6010029 (registering DOI) - 1 Mar 2026

Abstract

As test anxiety has evolved conceptually, identifying specific components contributing to educational success is essential. This study is the first to examine how different components of test anxiety are related to university dropout. Hungarian university students were recruited through the university’s website and asked to complete a series of online questionnaires at three different points over two years to monitor test anxiety levels and potential dropout or graduation during this period. Of the 98 students who completed assessments at all time points, by the final measurement, 69 had already either graduated or dropped out of their studies. Test anxiety was measured using the multidimensional TAM-C-SF (Test Anxiety Measure for College Students—Short Form). Study dropout was defined as leaving a program before graduation. Task-irrelevant behaviors—a component of test anxiety that includes restless and avoidance behaviors—were significantly associated with dropout. Higher values of cognitive interference were also significantly associated with a higher likelihood of dropout. Task-irrelevant behaviors and cognitive interference might play a key role in academic persistence among university students. These findings highlight the importance of a multidimensional approach to assessing test anxiety and suggest interventional techniques that may help diminish these factors to support students in succeeding in their studies. Full article

16 pages, 36949 KB

Open AccessArticle

Evaluating Architecture Scalability and Transfer Learning in Urban Scene Segmentation Using Explainable AI

by Tanmay Sunil Hatkar, Abhinav Pandey and Saad B. Ahmed

Big Data Cogn. Comput. 2026, 10(3), 75; https://doi.org/10.3390/bdcc10030075 (registering DOI) - 1 Mar 2026

Abstract

Semantic segmentation plays a pivotal role in autonomous driving, enabling pixel-level understanding of road scenes. Although transformer-based models such as SegFormer have shown exceptional performance on large datasets, their generalization to smaller and geographically diverse datasets remains underexplored. In this work, we analyze the scalability and transferability of SegFormer variants (B3, B4, B5) using CamVid as the base dataset. We perform cross-dataset transfer learning to KITTI and IDD, evaluate class-level performance, and explore explainable AI via confidence heatmaps. Our findings show that SegFormer-B5 achieves the highest accuracy (

82.4

% mIoU) on CamVid, while transfer learning from CamVid improves mIoU on KITTI by

2.57

% and enhances class-specific predictions in IDD by over 70%. These results highlight the practical potential of SegFormer in real-world segmentation systems and the interpretability benefits of confidence-based visual analysis. Full article

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