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19 pages, 5883 KB

Open AccessArticle

Pulse-Controlled Electrodeposition of Ni/ZrO₂ with Coumarin Additive: A Parametric Study

by Maria Myrto Dardavila and Constantina Kollia

Coatings 2025, 15(12), 1400; https://doi.org/10.3390/coatings15121400 (registering DOI) - 1 Dec 2025

Ni/ZrO₂ composite coatings are increasingly employed, yet the influence of organic additives under a pulse current regime on their electrodeposition remains insufficiently addressed. This study investigates the combined effect of pulse frequency (0.01–100 Hz) and coumarin concentration (0–2 mmol L⁻¹) [...] Read more.

Ni/ZrO₂ composite coatings are increasingly employed, yet the influence of organic additives under a pulse current regime on their electrodeposition remains insufficiently addressed. This study investigates the combined effect of pulse frequency (0.01–100 Hz) and coumarin concentration (0–2 mmol L⁻¹) on the co-deposition behavior, microstructure, and properties of Ni/ZrO₂ coatings electrodeposited from a Watts-type bath. The structural, morphological, and compositional features were analyzed through SEM/EDS, FE-SEM, and XRD, while microhardness and surface roughness were determined to establish processing–structure–property correlations. The results revealed that coumarin acts as an effective levelling agent, promoting smoother and finer-grained coatings while modifying ZrO₂ incorporation and Ni crystallographic orientation. Increasing coumarin concentration led to a notable refinement of nickel crystallites and a rise in hardness, reaching values close to 650 HV under optimal PC conditions. Pulse frequency was found to strongly influence the microstructural characteristics and particle co-deposition rates, particularly at low frequencies, where a balance between additive adsorption and current modulation favored particle incorporation and enhanced the microhardness. It was demonstrated that the synergistic control of pulse parameters and coumarin concentration enables the design of Ni/ZrO₂ composite coatings with tailored microstructure, low roughness, and superior hardness for demanding applications. Full article

(This article belongs to the Section Surface Characterization, Deposition and Modification)

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23 pages, 3223 KB

Open AccessArticle

What Potential Does the Metaverse Hold for Overcoming Supply Chain Geopolitical Disruptions Through Scenario-Based Planning and Risk Management?

by Kamdem Poupi Arnold Brice, Aratrika De, Wiysenyuy Louis Nyuydzeran, Kamese Jordan Junior and Tagne Poupi Theodore Armand

Virtual Worlds 2025, 4(4), 55; https://doi.org/10.3390/virtualworlds4040055 (registering DOI) - 1 Dec 2025

Abstract

Geopolitical disruptions such as trade wars, sanctions, and political instability threaten global supply chain (SC) resilience. As a result, multinational corporations face financial losses, operational delays, and strategic uncertainties, creating an urgent demand for innovative risk management and scenario-planning strategies. Traditional risk management [...] Read more.

Geopolitical disruptions such as trade wars, sanctions, and political instability threaten global supply chain (SC) resilience. As a result, multinational corporations face financial losses, operational delays, and strategic uncertainties, creating an urgent demand for innovative risk management and scenario-planning strategies. Traditional risk management methods struggle to keep pace with the complexity of these events. This study explores the metaverse, combining VR, AR, digital twins, AI, and blockchain, as a tool for enhancing SC risk management. By enabling immersive scenario planning, real-time risk visualization, and collaborative decision-making, the metaverse supports agile and resilient supply chains. This research proposes a conceptual framework integrating key fourth industrial revolution (4IR) technologies to address geopolitical SC disruptions systematically. This model fosters digital preparedness, simulation-based learning, and adaptive coordination. While technological, organizational, and regulatory challenges persist, the study demonstrates that metaverse-enabled systems can support future-ready SC resilience strategies. Full article

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10 pages, 1593 KB

Open AccessArticle

Upcycling Medical Tablet Blister Waste into High-Performance Triboelectric Nanogenerators for Sustainable Energy Harvesting

by Vikram Lakshmi Suneetha, Velpula Mahesh, Khanapuram Uday Kumar and Rajaboina Rakesh Kumar

Nanoenergy Adv. 2025, 5(4), 19; https://doi.org/10.3390/nanoenergyadv5040019 (registering DOI) - 1 Dec 2025

Abstract

The increasing accumulation of medical waste, especially discarded pharmaceutical blister packs, poses both environmental risks and missed opportunities for resource recovery. In this work, we demonstrate, for the first time, the direct upcycling of tablet blister waste into a potential frictional layer in [...] Read more.

The increasing accumulation of medical waste, especially discarded pharmaceutical blister packs, poses both environmental risks and missed opportunities for resource recovery. In this work, we demonstrate, for the first time, the direct upcycling of tablet blister waste into a potential frictional layer in triboelectric nanogenerators (TENGs). The polymer structure of blister packs, combined with Silicone rubber as a counter frictional layer, enabled the fabrication of durable TENG devices (TS-TENGs). Systematic electrical testing revealed that the TS-TENG achieved an open-circuit voltage of approximately 300 V, a short-circuit current of about 40 μA, and a peak power density of 3.54 W/m² at an optimal load resistance of 4 MΩ. The devices maintained excellent stability over 10,000 mechanical cycles, confirming their durability. Practical demonstrations included powering 240 LEDs, four LED lamps, and portable electronic devices, such as calculators and hygrometers, through capacitor charging. This study shows that not only can tablet blister waste be used as a triboelectric material but it also presents a sustainable method to reduce pharmaceutical waste while advancing self-powered systems. The approach offers a scalable and low-cost means to integrate medical waste management with renewable energy technologies. Full article

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14 pages, 1118 KB

Open AccessArticle

Using Machine Learning to Identify Predictors of Heterogeneous Intervention Effects in Childhood Obesity Prevention

by Elizabeth Mannion, Kristine Bihrmann, Nanna Julie Olsen, Berit Lilienthal Heitmann and Christian Ritz

Data 2025, 10(12), 196; https://doi.org/10.3390/data10120196 (registering DOI) - 1 Dec 2025

Abstract

Obesity prevention interventions in children often produce small or null effects. However, ignoring heterogeneous responses may widen pre-existing inequalities. This secondary analysis explored baseline predictors of differential effects on BMI z-score, Fat mass (%), stress, and sleep outcomes in obesity-susceptible, healthy-weight children (n [...] Read more.

Obesity prevention interventions in children often produce small or null effects. However, ignoring heterogeneous responses may widen pre-existing inequalities. This secondary analysis explored baseline predictors of differential effects on BMI z-score, Fat mass (%), stress, and sleep outcomes in obesity-susceptible, healthy-weight children (n = 543). A modified LASSO regression was applied to baseline characteristics, including physical activity and socio-demographics. Few predictors were retained. For BMI z-score, weekly chores and parental divorce were the strongest predictors: children who did chores had a slightly larger increase in BMI z-score in the intervention group compared with controls (MD = 0.15, 95% CI: −0.03, 0.33), while children with divorced parents showed a smaller increase (MD = −0.19, 95% CI: −0.69, 0.31). These results align with evidence that low-intensity activity has limited impact on obesity outcomes and that children with compounded vulnerability may respond differently to tailored interventions. Even when overall effects are small, machine learning approaches can identify potential predictors of heterogeneous intervention effects, supporting the design of future targeted interventions aimed at reducing inequalities. Full article

(This article belongs to the Section Computational Biology, Bioinformatics, and Biomedical Data Science)

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28 pages, 3999 KB

Open AccessArticle

Microstructure Evolution and Phase Formation in WC-TiC-TaC-HfC(-ZrC) High-Entropy Carbide Systems During Mechanical Activation and Spark Plasma Sintering

by Igor Yu Buravlev, Aleksey O. Lembikov, Anton A. Belov, Saveliy M. Pisarev, Ekaterina A. Ponomareva, Erkhan S. Kolodeznikov, Nikita S. Ogorodnikov, Anastasia A. Buravleva, Aleksandr N. Fedorets, Oleg O. Shichalin and Eugeniy K. Papynov

J. Compos. Sci. 2025, 9(12), 647; https://doi.org/10.3390/jcs9120647 (registering DOI) - 1 Dec 2025

Abstract

In this study, medium- and high-entropy carbide systems with compositions WC-TiC-TaC-HfC and WC-TiC-TaC-HfC-ZrC were successfully synthesized via a combination of mechanical activation (using high-energy ball milling, HEBM) and spark plasma sintering (SPS) at 1900 °C. Investigation of the SPS consolidation kinetics revealed that [...] Read more.

In this study, medium- and high-entropy carbide systems with compositions WC-TiC-TaC-HfC and WC-TiC-TaC-HfC-ZrC were successfully synthesized via a combination of mechanical activation (using high-energy ball milling, HEBM) and spark plasma sintering (SPS) at 1900 °C. Investigation of the SPS consolidation kinetics revealed that both systems undergo single-stage active densification via a solid-state sintering mechanism within the temperature range of 1316–1825 °C. The introduction of ZrC into the five-component system led to a 22% decrease in the maximum shrinkage rate (from 0.9 to 0.7 mm·min⁻¹), which is attributed to the manifestation of a sluggish diffusion effect, characteristic of high-entropy systems. X-ray diffraction analysis of the consolidated samples confirmed the formation of predominantly single-phase high-entropy solid solutions (W-Ti-Ta-Hf)C and (W-Ti-Ta-Hf-Zr)C with a NaCl-type cubic structure (space group Fm-3m) and lattice parameters of 4.4101 Å and 4.4604 Å, respectively. Energy-dispersive X-ray spectroscopy revealed a near-equimolar distribution of metallic components with deviations not exceeding ±1.9 at. %. The addition of ZrC increased the average crystallite size by 84.3% (from 83.6 to 153.1 nm). Both systems achieved comparable relative densities of ~91.75%; however, they exhibited differences in hardness distribution: the four-component system is characterized by a higher average microhardness (1860 HV), while the five-component system exhibits a higher macrohardness HV30 (2008.1). The established correlations between composition, phase formation, microstructure, and properties provide a fundamental basis for the targeted design of high-entropy carbide ceramics with tailored characteristics for high-temperature applications. Full article

(This article belongs to the Section Composites Manufacturing and Processing)

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29 pages, 3769 KB

Open AccessSystematic Review

Illuminating Industry Evolution: Reframing Artificial Intelligence Through Transparent Machine Reasoning

by Albérico Travassos Rosário and Joana Carmo Dias

Information 2025, 16(12), 1044; https://doi.org/10.3390/info16121044 (registering DOI) - 1 Dec 2025

Abstract

As intelligent systems become increasingly embedded in industrial ecosystems, the demand for transparency, reliability, and interpretability has intensified. This study investigates how explainable artificial intelligence (XAI) contributes to enhancing accountability, trust, and human–machine collaboration across industrial contexts transitioning from Industry 4.0 to Industry [...] Read more.

As intelligent systems become increasingly embedded in industrial ecosystems, the demand for transparency, reliability, and interpretability has intensified. This study investigates how explainable artificial intelligence (XAI) contributes to enhancing accountability, trust, and human–machine collaboration across industrial contexts transitioning from Industry 4.0 to Industry 5.0. To achieve this objective, a systematic bibliometric literature review (LRSB) was conducted following the PRISMA framework, analysing 98 peer-reviewed publications indexed in Scopus. This methodological approach enabled the identification of major research trends, theoretical foundations, and technical strategies that shape the development and implementation of XAI within industrial settings. The findings reveal that explainability is evolving from a purely technical requirement to a multidimensional construct integrating ethical, social, and regulatory dimensions. Techniques such as counterfactual reasoning, causal modelling, and hybrid neuro-symbolic frameworks are shown to improve interpretability and trust while aligning AI systems with human-centric and legal principles, notably those outlined in the EU AI Act. The bibliometric analysis further highlights the increasing maturity of XAI research, with strong scholarly convergence around transparency, fairness, and collaborative intelligence. By reframing artificial intelligence through the lens of transparent machine reasoning, this study contributes to both theory and practice. It advances a conceptual model linking explainability with measurable indicators of trustworthiness and accountability, and it offers a roadmap for developing responsible, human-aligned AI systems in the era of Industry 5.0. Ultimately, the study underscores that fostering explainability not only enhances functional integrity but also strengthens the ethical and societal legitimacy of AI in industrial transformation. Full article

(This article belongs to the Special Issue Advances in Information Studies)

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17 pages, 7634 KB

Open AccessArticle

CLSM-Guided Imaging to Visualize the Depth of Effective Disinfection in Endodontics

by Rebecca Mattern, Sarah Böcher, Gerhard Müller-Newen, Georg Conrads, Johannes-Simon Wenzler and Andreas Braun

Antibiotics 2025, 14(12), 1201; https://doi.org/10.3390/antibiotics14121201 (registering DOI) - 1 Dec 2025

Abstract

Background/Objectives: Important goals of endodontic treatment procedures are to effectively eliminate microorganisms from the root canal system and prevent reinfection. Despite advances in techniques, these goals continue to be difficult to achieve due to the complex anatomy of the root canal system and [...] Read more.

Background/Objectives: Important goals of endodontic treatment procedures are to effectively eliminate microorganisms from the root canal system and prevent reinfection. Despite advances in techniques, these goals continue to be difficult to achieve due to the complex anatomy of the root canal system and bacterial invasion into the dentinal tubules of the surrounding root dentin. This pilot study aimed to refine a confocal laser scanning microscopy (CLSM) model with LIVE/DEAD staining to quantitatively assess the depth of effective disinfection by endodontic disinfection measures. Methods: Thirty caries-free human teeth underwent standardized chemo-mechanical root canal preparation and were inoculated with Enterococcus faecalis. Following treatment, CLSM-guided imaging with LIVE/DEAD staining allowed for differentiation between vital and dead bacteria and quantification of the depth of effective disinfection. Results: An average depth of bacterial eradication of 450 µm for conventional and 520 µm for sonically activated irrigation (EDDY) could be observed with significant differences (p < 0.05) in the coronal and medial positions. Conclusions: The results indicated that sonically activated irrigation (EDDY) provided a more homogeneous (omnidirectional) irrigation pattern compared to conventional irrigation. The study highlights the importance of effective disinfection strategies in endodontics, emphasizing the need for further research on the depth of effective disinfection of endodontic disinfection measures and the optimization of disinfection protocols. Full article

(This article belongs to the Special Issue Antibacterial Treatment in Periodontal and Endodontic Therapy, 3rd Edition)

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32 pages, 3739 KB

Open AccessArticle

Operational Flexibility Assessment of Distributed Reserve Resources Considering Meteorological Uncertainty: Based on an End-to-End Integrated Learning Approach

by Chao Gao, Bin Wei, Yabin Chen, Fan Kuang, Pei Yong and Zixu Chen

Processes 2025, 13(12), 3870; https://doi.org/10.3390/pr13123870 (registering DOI) - 1 Dec 2025

Abstract

In the context of the rapid development of renewable energy and frequent extreme weather, accurate evaluation of the backup operation flexibility of multiple distributed resources is a prerequisite for improving the resilience of power systems. However, it is difficult to consider the detailed [...] Read more.

In the context of the rapid development of renewable energy and frequent extreme weather, accurate evaluation of the backup operation flexibility of multiple distributed resources is a prerequisite for improving the resilience of power systems. However, it is difficult to consider the detailed model of each distributed resource and evaluate its regulation ability in the operation of power systems because of the small number of distributed resources. Therefore, this paper first quantifies the capacity boundaries of distributed reserve resources on the power generation, load, and energy storage sides under different meteorological conditions through economic self-dispatching optimization and Minkowski aggregation methods. Subsequently, the maximum correlation–minimum redundancy (mRMR) principle and Granger causality test are combined to reduce the dimensionality of high-dimensional meteorological features. Finally, the stacking ensemble learning method is introduced to build an end-to-end modelling framework from multi-source weather input to reserve capability prediction. The results show that (1) the reserve capacity of multivariate distributed resources has significant intra-day and intra-day periodicity and seasonal differences; (2) the mRMR algorithm considering the Granger causality test can capture the correlation and causality between high-dimensional meteorological features and reserve capabilities, and the obtained features are more explanatory; (3) the average R² of the stacking model in both upper-reserve and lower-reserve predictions reaches 0.994. In terms of computational efficiency, the training time of the proposed model is 130.85 s for upper-reserve prediction and 133.71 s for lower-reserve prediction, which is significantly lower than that of conventional hybrid models while maintaining stable performance under extreme meteorological conditions such as high temperatures and strong winds; (4) compared with integration methods such as simple averaging and error weighting, the stacking integration strategy proposed in this paper remains stable in the mean and variance of prediction results, verifying its comprehensive advantages in structural design and performance integration. Full article

(This article belongs to the Special Issue Modeling, Optimization, and Control of Distributed Energy Systems)

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44 pages, 10191 KB

Open AccessArticle

Hyperspectral Imaging and Machine Learning for Automated Pest Identification in Cereal Crops

by Rimma M. Ualiyeva, Mariya M. Kaverina, Anastasiya V. Osipova, Alina A. Faurat, Sayan B. Zhangazin and Nurgul N. Iksat

Biology 2025, 14(12), 1715; https://doi.org/10.3390/biology14121715 (registering DOI) - 1 Dec 2025

Abstract

The spectral characteristics of harmful insect pests in wheat fields were characterised using hyperspectral imaging for the first time. The analysis of spectral profiles revealed that reflectance is determined by the structure of the insect’s chitin and the colouration of its body surface. [...] Read more.

The spectral characteristics of harmful insect pests in wheat fields were characterised using hyperspectral imaging for the first time. The analysis of spectral profiles revealed that reflectance is determined by the structure of the insect’s chitin and the colouration of its body surface. Insects with lighter or more vivid colours (white, yellow, or green) showed higher reflectance values compared to those with predominantly dark pigmentation. Reflectance was also influenced by the presence of wings, surface roughness, and the age of the insect. Each species exhibited distinct spectral patterns that allowed for differentiation not only from other insect species but also from the plant background. A classification model using PLS-DA was developed and demonstrated high accuracy in identifying 12 pest species, confirming the strong potential of hyperspectral imaging for species-level classification. The results validate the PLS-DA method for differentiating insects based on spectral characteristics and underscore the reliability of this approach for automated monitoring systems to detect phytophagous pests in crop fields. This technology could reduce insecticide use by 30–40% through targeted application. The research has both scientific and economic significance, laying the groundwork for integrating machine learning and computer vision into agricultural monitoring. It supports the advancement of precision farming and contributes to improved global food security. Full article

(This article belongs to the Section Bioinformatics)

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33 pages, 2738 KB

Open AccessArticle

Quantile Connectedness Between Stock Market Development and Macroeconomic Factors for Emerging African Economies

by Maroua Ben Salem, Naif Alsagr, Samir Belkhaoui and Sahbi Farhani

Int. J. Financial Stud. 2025, 13(4), 224; https://doi.org/10.3390/ijfs13040224 (registering DOI) - 1 Dec 2025

Abstract

This paper investigates the frequency dynamics of financial and macroeconomic connectedness by measuring tail-risk and uncertainty for two emerging African economies, namely Morocco and Tunisia, over the quarterly period Q2-2010 to Q4-2024. We employ a quantile connectedness approach, which, unlike traditional mean-based methods, [...] Read more.

This paper investigates the frequency dynamics of financial and macroeconomic connectedness by measuring tail-risk and uncertainty for two emerging African economies, namely Morocco and Tunisia, over the quarterly period Q2-2010 to Q4-2024. We employ a quantile connectedness approach, which, unlike traditional mean-based methods, leads to capturing asymmetries, tail-risk dependencies, and state-dependent spillovers, and to providing early warning signals of systemic stress and financial uncertainty. Our results reveal a stark divergence between the two stock markets in their roles in transmitting and absorbing shocks. The Moroccan stock market acts as a net transmitter, occasionally driving macroeconomic conditions and propagating uncertainty throughout the system. In contrast, the Tunisian stock market acts as a net receiver, with macroeconomic fundamentals, particularly GDP and money supply. These findings highlight how structural differences in emerging markets affect the transmission of shocks and offer actionable insights for policymakers, regulators, and investors to manage financial risks and uncertainty. Full article

(This article belongs to the Special Issue Risks and Uncertainties in Financial Markets)

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26 pages, 2310 KB

Open AccessSystematic Review

A Systematic Review of Intelligent Navigation in Smart Warehouses Using Prisma: Integrating AI, SLAM, and Sensor Fusion for Mobile Robots

by Domagoj Zimmer, Mladen Jurišić, Ivan Plaščak, Željko Barač, Hrvoje Glavaš, Dorijan Radočaj and Robert Benković

Eng 2025, 6(12), 339; https://doi.org/10.3390/eng6120339 (registering DOI) - 1 Dec 2025

Abstract

This systematic review focuses on intelligent navigation as a core enabler of autonomy in smart warehouses, where mobile robots must dynamically perceive, reason, and act in complex, human-shared environments. By synthesizing advancements in AI-driven decision-making, SLAM, and multi-sensor fusion, the study highlights how [...] Read more.

This systematic review focuses on intelligent navigation as a core enabler of autonomy in smart warehouses, where mobile robots must dynamically perceive, reason, and act in complex, human-shared environments. By synthesizing advancements in AI-driven decision-making, SLAM, and multi-sensor fusion, the study highlights how intelligent navigation architectures reduce operational uncertainty and enhance task efficiency in logistics automation. Smart warehouses, powered by mobile robots and AGVs and integrated with AI and algorithms, are enabling more efficient storage with less human labour. This systematic review followed PRISMA 2020 guidelines to systematically identify, screen, and synthesize evidence from 106 peer-reviewed scientific articles (including pri-mary studies, technical papers, and reviews) published between 2020–2025, sourced from Web of Science. Thematic synthesis was conducted across 8 domains: AI, SLAM, sensor fusion, safety, network, path planning, implementation, and design. The transition to smart warehouses requires modern technologies to automate tasks and optimize resources. This article examines how intelligent systems can be integrated with mathematical models to improve navigation accuracy, reduce costs and prioritize human safety. Real-time data management with precise information for AMRs and AGVs is crucial for low-risk operation. This article studies AI, the IoT, LiDAR, machine learning (ML), SLAM and other new technologies for the successful implementation of mobile robots in smart warehouses. Modern technologies such as reinforcement learning optimize the routes and tasks of mobile robots. Data and sensor fusion methods integrate information from various sources to provide a more precise understanding of the indoor environment and inventory. Semantic mapping enables mobile robots to navigate and interact with complex warehouse environments with high accuracy in real time. The article also analyses how virtual reality (VR) can improve the spatial orientation of mobile robots by developing sophisticated navigation solutions that reduce time and financial costs. Full article

(This article belongs to the Special Issue Interdisciplinary Insights in Engineering Research)

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15 pages, 1659 KB

Open AccessArticle

Simple Analytical Approximations for Donnan Ion Partitioning in Permeable Ion-Exchange Membranes Under Reverse Electrodialysis Conditions

by Antonio Ángel Moya

Membranes 2025, 15(12), 365; https://doi.org/10.3390/membranes15120365 (registering DOI) - 1 Dec 2025

Abstract

Reverse electrodialysis (RED) is a relatively recent technology for renewable energy harvesting from the interaction of river and seawater. This paper revisits the thermodynamic equilibrium governing the ionic transport processes through ion-exchange membranes (IEMs) under RED conditions and theoretically derives approximate analytical expressions [...] Read more.

Reverse electrodialysis (RED) is a relatively recent technology for renewable energy harvesting from the interaction of river and seawater. This paper revisits the thermodynamic equilibrium governing the ionic transport processes through ion-exchange membranes (IEMs) under RED conditions and theoretically derives approximate analytical expressions for the ionic concentrations at the inner boundaries of a permeable membrane with well-stirred baths. The equation for the Donnan ion partitioning at the membrane–solution interface, which is based on the equality of the electrochemical potential in the two phases, is analysed for binary salts with symmetric (1:1) and asymmetric (2:1) electrolytes, by considering bathing solutions with the equivalent concentrations 0.02 M in the dilute bath, and 0.5, 1, and 1.5 M in the concentrate one. Simple approximate analytical expressions exhibiting the evolution with the membrane fixed-charge concentration of the counter-ionic concentrations at the inner boundaries of the membrane, the concentration gradients inside the membrane, the total Donnan electric potential, and the ionic partitioning coefficients have been derived. The approximate generalised expressions for a general z₁:z₂ binary electrolyte are also presented for the first time. Full article

(This article belongs to the Special Issue Electrodialysis and Reverse Electrodialysis in Ion-Exchange Membrane Systems)

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13 pages, 8961 KB

Open AccessArticle

Fluorescence-Based Detection of KRAS Mutations in Genomic DNA Using Magnetic Bead-Coupled LDR Assay

by Chika Morimoto and Masahiko Hashimoto

Methods Protoc. 2025, 8(6), 142; https://doi.org/10.3390/mps8060142 (registering DOI) - 1 Dec 2025

Abstract

We previously developed a bead-coupled ligase detection reaction (LDR) assay that enables simple and rapid detection of single-nucleotide variations (SNVs) using synthetic oligonucleotide templates. In the present study, this approach was extended to genomic DNA extracted from colorectal cancer cell lines to evaluate [...] Read more.

We previously developed a bead-coupled ligase detection reaction (LDR) assay that enables simple and rapid detection of single-nucleotide variations (SNVs) using synthetic oligonucleotide templates. In the present study, this approach was extended to genomic DNA extracted from colorectal cancer cell lines to evaluate its applicability to clinically relevant samples. Targeting codon 12 of the KRAS gene, PCR-amplified products served as templates for bead-coupled LDR, and fluorescence excitation–emission matrix (EEM) analysis was employed for signal readout. The four fluorophores used in the assay exhibited distinct spectral properties, allowing their signals to be clearly resolved within the EEM profiles. This mapping provided characteristic fluorescence signatures that revealed the underlying genotypes, enabling not only the distinction between homozygous and heterozygous states but also the precise identification of allele compositions, as exemplified by G/A, T/T, G/G, and G/C in colorectal cancer cell lines. The single-tube workflow, integrating magnetic bead capture with fluorescence-based detection, demonstrated robustness, speed, and cost-effectiveness compared with conventional mutation detection methods. These findings confirm that the LDR–EEM platform can be successfully applied to genomic DNA analysis, underscoring its potential as an accessible and reliable tool for SNV detection in both research and diagnostic contexts. Full article

(This article belongs to the Section Molecular and Cellular Biology)

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19 pages, 624 KB

Open AccessArticle

Explanatory Factors of Materiality Disclosure in the Non-Financial Reporting of European Listed Companies

by Miguel Gomes, Fábio Albuquerque and Maria Albertina Barreiro Rodrigues

Account. Audit. 2025, 1(3), 12; https://doi.org/10.3390/accountaudit1030012 (registering DOI) - 1 Dec 2025

Abstract

This study analyses disclosures on materiality in non-financial information (NFI) reporting by examining their likely explanatory factors, including entities’ financial or structural characteristics, governance features, and contextual factors, grounded in a set of relevant theories. Based on archival research and content analysis, this [...] Read more.

This study analyses disclosures on materiality in non-financial information (NFI) reporting by examining their likely explanatory factors, including entities’ financial or structural characteristics, governance features, and contextual factors, grounded in a set of relevant theories. Based on archival research and content analysis, this study uses consolidated NFI reports from 2021 of entities listed in the main Euronext indices. The descriptive analysis reveals that while 71% of companies present a materiality matrix, only about half (50%) meet all eight criteria of materiality disclosure, with double materiality being addressed by just 16%. The regression results show that the level of materiality disclosure is significantly and positively associated only with the size of the board of directors, whereas other expected relationships, such as those with firm size, profitability, or debt, were not statistically significant, challenging traditional assumptions from stakeholders, agency, and positive accounting theories. These findings suggest that governance structures may play a more decisive role in transparency regarding materiality than the entities’ financial or structural characteristics. This research contributes to both the academic literature and practice by identifying explanatory factors and empirical patterns in materiality disclosure in NFI reporting, which may be relevant for standard-setting bodies, regulators, auditors, and stakeholders. Full article

(This article belongs to the Special Issue Rethinking ESG and CSR: Advancing Transparency and Integrity in Corporate Governance)

38 pages, 8524 KB

Open AccessArticle

Prediction of Compressive Strength of Carbon Nanotube Reinforced Concrete Based on Multi-Dimensional Database

by Ao Yan, Shengdong Zhang, Zhuoxuan Li, Peng Zhu and Yuching Wu

Buildings 2025, 15(23), 4349; https://doi.org/10.3390/buildings15234349 (registering DOI) - 1 Dec 2025

Abstract

The incorporation of carbon nanotubes (CNTs) enhances the mechanical properties of cement-based materials by inhibiting micro-crack propagation. Machine learning provides an efficient approach for predicting the compressive strength of CNT-reinforced concrete, yet existing studies often lack important features and rely on less adaptive [...] Read more.

The incorporation of carbon nanotubes (CNTs) enhances the mechanical properties of cement-based materials by inhibiting micro-crack propagation. Machine learning provides an efficient approach for predicting the compressive strength of CNT-reinforced concrete, yet existing studies often lack important features and rely on less adaptive models. To address these issues, a multi-dimensional database (429 experimental data points) covering 11 factors (including cement mix ratio, CNT morphology, and dispersion process) was constructed. A hierarchical model verification and optimization was conducted: traditional regression models (Multiple Linear Regression, Multiple Polynomial Regression (MPR), Multivariate Adaptive Regression Splines), mainstream model (Support Vector Regression (SVR)), and ensemble learning models (Random Forest, eXtreme Gradient Boosting (XGB), Light Gradient Boosting Machine optimized by Particle Swarm Optimization (PSO)/Bayesian Optimization (BO)) are trained, compared, and evaluated. MPR performs best (test set R² = 0.856) among traditional regression models, while SVR (test set R² = 0.824) is less accurate. The highest accuracy in ensemble models is achieved by the PSO-optimized XGB model, with R² = 0.910 (test set). PSO outperforms BO in optimization precision, while BO is much more efficient. Water–cement ratio, age, and sand–cement ratio are the primary influencing factors for strength. Among CNT parameters, the inner diameter has greater impact than the length and outer diameter. Optimal CNT parameters are CNT–cement mass ratio 0.1–0.3%, inner diameter ≥ 7.132 nm, and length 1–15 μm. Surfactant polycarboxylate can increase strength, while OH⁻ functional groups can decrease it. These findings, integrated into the high-precision PSO-XGB model, provide a powerful tool for optimizing the mix design of CNT-reinforced concrete, accelerating its development and application in the industry. Full article

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19 pages, 5499 KB

Open AccessArticle

Smart Crosswalks for Advancing Road Safety in Urban Roads: Conceptualization and Evidence-Based Insights from Greek Incident Records

by Maria Pomoni

Future Transp. 2025, 5(4), 180; https://doi.org/10.3390/futuretransp5040180 (registering DOI) - 1 Dec 2025

Abstract

Urban intersections are critical for pedestrian safety, as they usually account for high rates of traffic-related injury and fatalities. This study assesses smart crosswalks as an alternative approach to improve road safety that is inherently aligned with the development of intelligent transportation system [...] Read more.

Urban intersections are critical for pedestrian safety, as they usually account for high rates of traffic-related injury and fatalities. This study assesses smart crosswalks as an alternative approach to improve road safety that is inherently aligned with the development of intelligent transportation system technology. After a brief background on this technological advance, this study proceeds with the analysis of long-term crash records from Greek urban roads, concentrating on pedestrians’ behavior in incidents involving road crossing. Thereafter, challenges related to the adoption of an implementation framework are identified. The results confirmed the vulnerability of pedestrians, especially during cases with no specific crossing areas, based on a considerable number of available recorded crashes from a publicly available Greek database. Substantial reductions over the analysis period (i.e., years 2005–2022) in pedestrian-based incidents with injuries and fatalities at a rate of 44% and 52%, respectively, provide evidence-based insights that infrastructural interventions like improved crosswalk design can be translated into measurable benefits for pedestrian safety. Key factors toward a wider applicability framework for even safer interventions through smart crosswalks include maintenance strategies, user education, and systematic integration of funding into urban mobility plans. Full article

(This article belongs to the Special Issue Unfolding Road-Related Aspects of Modern Infrastructure in the Future Era of Road Transport)

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19 pages, 5153 KB

Open AccessTechnical Note

Assessment of Instrument Performance of the FY3E/JTSIM/DARA Radiometer Through the Analysis of TSI Observations

by Jean-Philippe Montillet, Wolfgang Finsterle, Ping Zhu, Margit Haberreiter, Silvio Koller, Daniel Pfiffner, Duo Wu, Xin Ye, Dongjun Yang, Wei Fang, Jin Qi and Peng Zhang

Remote Sens. 2025, 17(23), 3902; https://doi.org/10.3390/rs17233902 (registering DOI) - 30 Nov 2025

Abstract

Since the late 1970s, satellite missions have monitored Total Solar Irradiance (TSI), providing a long-term record of solar variability. The Digital Absolute Radiometer (DARA), onboard the Chinese Fengyun-3E (FY3E) spacecraft since 4 July 2021, contributes to extending this record. In this study, we [...] Read more.

Since the late 1970s, satellite missions have monitored Total Solar Irradiance (TSI), providing a long-term record of solar variability. The Digital Absolute Radiometer (DARA), onboard the Chinese Fengyun-3E (FY3E) spacecraft since 4 July 2021, contributes to extending this record. In this study, we evaluate the DARA observations in both World Radiometric Reference (WRR) and International System of Units (SI) scales. We compare these records with those from other instruments on different spacecraft (i.e., VIRGO/PMO6, TSIS-1/TIM) and with the co-located Solar Irradiance Absolute Radiometer (SIAR) on FY3E. A key finding is the identification and correction of an instrumental artifact: an issue in the thermal aperture model, linked to annual satellite maneuvers, repetitively introduced an artificial step of

0.15 \pm 0.05

Wm

^{- 2}

into the TSI measurements.A statistical analysis of the measurements in the SI scale shows that the mean value of the DARA TSI observations is approximately

1359.58

Wm

^{- 2}

(6-hourly rate), which is lower than the ones recorded by VIRGO/PMO6 (

1.82

Wm

^{- 2}

), TSIS-1/TIM (

2.90

Wm

^{- 2}

), and SIAR (

2.54

Wm

^{- 2}

). We estimate a degradation of ∼49 ppm over 46 months due to the exposure of the instrument to the (Extreme) Ultraviolet (UV/EUV) radiations. Finally, the corrected DARA observations are incorporated into the long-term TSI composite time series. Comparison with the PMOD/WRC composite shows only marginal differences (less than

0.015

Wm

^{- 2}

), confirming the consistency and reliability of including the new TSI product (i.e., JTSIM-DARAv1). Full article

(This article belongs to the Section Satellite Missions for Earth and Planetary Exploration)

38 pages, 1800 KB

Open AccessArticle

Critical Factors for the Application of InSAR Monitoring in Ports

by Jaime Sánchez-Fernández, Alfredo Fernández-Landa, Álvaro Hernández Cabezudo and Rafael Molina Sánchez

Remote Sens. 2025, 17(23), 3900; https://doi.org/10.3390/rs17233900 (registering DOI) - 30 Nov 2025

Abstract

Ports pose distinctive monitoring challenges due to harsh marine conditions, mixed construction typologies, and heterogeneous ground conditions. These factors complicate the routine use of satellite InSAR, especially when medium-resolution scatterers must be reliably attributed to specific assets for risk and asset management decisions. [...] Read more.

Ports pose distinctive monitoring challenges due to harsh marine conditions, mixed construction typologies, and heterogeneous ground conditions. These factors complicate the routine use of satellite InSAR, especially when medium-resolution scatterers must be reliably attributed to specific assets for risk and asset management decisions. In current practice, persistent and distributed scatterer (PS/DS) points are often interpreted in map view without an explicit positional uncertainty model or systematic linkage to three-dimensional infrastructure geometry. We present an end-to-end Differential InSAR framework tailored to large ports that fuses medium-resolution Sentinel-1 Level 2 Co-registered Single-Look Complex (L2-CSLC) stacks with high-resolution airborne LiDAR at the post-processing stage. For the Port of Bahía de Algeciras (Spain), we process 123 Sentinel-1A/B images (2020–2022) in ascending and descending geometry using PS/DS time-series analysis with ETAD-like timing corrections and RAiDER tropospheric/ionospheric mitigation. LiDAR is then used to (i) derive look-specific shadow/layover masks and (ii) perform a whitening-transformed nearest-neighbor association that assigns PS/DS points to LiDAR points under an explicit range–azimuth–cross-range (RAC) uncertainty ellipsoid. The RAC standard deviations

(σ_{r}, σ_{a}, σ_{c})

are derived from the effective CSLC range/azimuth resolution and from empirical height correction statistics, providing a geometry- and data-informed prior on positional uncertainty. Finally, we render dual-geometry red–green composites (ascending to R, descending to G; shared normalization) on the LiDAR point cloud, enabling consistent inspection in plan and elevation. Across asset types, rigid steel/concrete elements (trestles, quay faces, and dolphins) sustain high coherence, small whitened offsets, and stable backscatter in both looks; cylindrical storage tanks are bright but exhibit look-dependent visibility and larger cross-range residuals due to height and curvature; and container yards and vessels show high amplitude dispersion and lower temporal coherence driven by operations. Overall, LiDAR-assisted whitening-based linking reduces effective positional ambiguity and improves structure-specific attribution for most scatterers across the port. The fusion products, geometry-aware linking plus three-dimensional dual-geometry RGB, enhance the interpretability of medium-resolution SAR and provide a transferable, port-oriented basis for integrating deformation evidence into risk and asset management workflows. Full article

18 pages, 1687 KB

Open AccessArticle

Zinc Fertilization Enhances Growth, Yield, and Zinc Use Efficiency of Rice (Oryza sativa L. cv. Chai Nat 1) in Contrasting Soil Textures

by Benjapon Kunlanit, Tanapon Siritrakulsak, Ratanaporn Poosathit, Tuan Vu Dinh and Patma Vityakon

Agronomy 2025, 15(12), 2779; https://doi.org/10.3390/agronomy15122779 (registering DOI) - 30 Nov 2025

Abstract

Efficient nutrient management is vital to sustaining rice production in the sandy soils of Northeast Thailand, where zinc (Zn) deficiency and low organic matter often constrain yield. This study evaluated the effects of Zn fertilization on the growth, yield, and Zn use efficiency [...] Read more.

Efficient nutrient management is vital to sustaining rice production in the sandy soils of Northeast Thailand, where zinc (Zn) deficiency and low organic matter often constrain yield. This study evaluated the effects of Zn fertilization on the growth, yield, and Zn use efficiency (ZUE) of rice (Oryza sativa L. cv. Chai Nat 1) grown under greenhouse conditions in contrasting soil textures (loamy sand and clay). Four Zn rates were applied: 0, 5, 10, and 15 kg ZnSO₄·7H₂O ha⁻¹ (0, 0.013, 0.026, and 0.039 g ZnSO₄·7H₂O pot⁻¹). Clay soil, with higher organic matter, nitrogen, and available Zn, supported greater vegetative growth, biomass, and yield than loamy sand. Zinc fertilization significantly increased plant height, tiller number, chlorophyll content, biomass, panicle number, grain number, and filled grain weight. Yield improvement in loamy sand was associated mainly with reproductive efficiency, whereas in clay it was driven by vegetative vigor, biomass accumulation, and Zn uptake. Thousand-grain weight was not affected by Zn. ZUE peaked at 5 kg ha⁻¹ in loamy sand and 10 kg ha⁻¹ in clay, with clay showing a greater overall increase in ZUE across Zn rates and loamy sand exhibiting diminishing returns at higher application rates, reflecting differences in Zn availability and retention capacity. Correlation, PCA, and SEM analyses confirmed soil-specific yield mechanisms. Overall, Zn fertilization improved rice productivity and tissue Zn concentration, with optimal rates differing by soil texture. These findings highlight the importance of site-specific Zn management in enhancing yield, nutrient efficiency, and biofortification in rice-based systems of Northeast Thailand. Full article

(This article belongs to the Special Issue Advancements in Fertilization Strategies and Soil Health for Rice and Wheat Cultivation)

36 pages, 7526 KB

Open AccessArticle

Versatile FourierTransform Spectrometer Model for Earth Observation Missions Validated with In-Flight Systems Measurements

by Tom Piekarski, Christophe Buisset, Anne Kleinert, Felix Friedl-Vallon, Arnaud Heliere, Julian Hofmann, Ljubiša Babić, Micael Dias Miranda, Tobias Guggenmoser, Daniel Lamarre, Flavio Mariani, Felice Vanin and Ben Veihelmann

Remote Sens. 2025, 17(23), 3903; https://doi.org/10.3390/rs17233903 (registering DOI) - 30 Nov 2025

Abstract

Fourier-transform spectrometers (FTSs) are cornerstone instruments in Earth observation space missions, effectively monitoring atmospheric gases in missions such as Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), and Infrared Atmospheric Sounding Interferometer (IASI). It will also be the core instrument of Meteosat Third Generation—Sounding [...] Read more.

Fourier-transform spectrometers (FTSs) are cornerstone instruments in Earth observation space missions, effectively monitoring atmospheric gases in missions such as Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), and Infrared Atmospheric Sounding Interferometer (IASI). It will also be the core instrument of Meteosat Third Generation—Sounding (MTG-S) and the future Earth Explorer (EE) mission Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM). Building on this legacy, the European Space Agency (ESA) has developed an FTS instrument and an inverse model designed to estimate the radiometric and spectral performance from a set of instrumental parameters. The model and its validation using in-flight measurements of the FTS instrument Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA)-Lite are described in this paper. The results indicate that the difference between the model predictions and the measured signal is less than 2% relative to the average of the measurements. Moreover, we can correctly predict the instrument’s radiometric gain and offset and reconstruct a scientific science spectrum. This model can be utilised effectively to evaluate the radiometric performance of future FTS missions. Full article

22 pages, 1335 KB

Open AccessArticle

Determination of Bioactive Compounds, Antioxidant Capacity, Safety Assessment, and Antimicrobial Effect of Tristerix corymbosus Extracts

by Katia Fernández Moreno, Gabriela Maturana, Sofía Blanco-Haros, Ulises Norambuena-Jopia, Gabriela Valenzuela-Barra, María Carolina Zúñiga-López and Jessica Bravo Garrido

Molecules 2025, 30(23), 4610; https://doi.org/10.3390/molecules30234610 (registering DOI) - 30 Nov 2025

Abstract

Quitral (Tristerix corymbosus), a Chilean and Argentine parasitic mistletoe, is traditionally used by Mapuche natives to treat stomach ulcers, nervous disorders, and cholesterol reduction, although scientific support is scarce. Methanolic and chloroform extracts from its leaves and stems were prepared. Chemical [...] Read more.

Quitral (Tristerix corymbosus), a Chilean and Argentine parasitic mistletoe, is traditionally used by Mapuche natives to treat stomach ulcers, nervous disorders, and cholesterol reduction, although scientific support is scarce. Methanolic and chloroform extracts from its leaves and stems were prepared. Chemical analysis included antioxidant capacity assays (ORAC-FL and DPPH) and chromatographic determinations. The antimicrobial activity was tested against nine bacteria and two yeast strains. Additionally, cytotoxicity (hemolysis) and toxicity (against Caenorhabditis elegans) assays were performed. The results revealed that the methanolic leaf extracts had the highest ORAC-FL value, with DPPH assays showing solvent-dependent differences. Thirty-one compounds were tentatively identified, of which 61% were phenolic compounds, primarily flavonoids like quercetin and its derivatives. Antimicrobial results showed activity against Gram-positive bacteria (Staphylococcus aureus, Listeria monocytogenes, Bacillus cereus, and Enterococcus faecalis), but not against yeast Candida guillermondii and Candida tropicalis. Methanolic extracts induced dose-dependent erythrocyte hemolysis, while chloroform extracts showed no relevant cytotoxicity. Toxicity against Caenorhabditis elegans was also dose-dependent for methanolic extracts; leaf extract reduced survival at 50 mg mL⁻¹ after 24 h. These findings partially validate some traditional uses, highlight the importance of solvent polarity in extraction and biological effects, and establish quitral as a flavonoid source. Full article

(This article belongs to the Special Issue Advances in Natural Products and Their Biological Activities—2nd Edition)

18 pages, 6301 KB

Open AccessArticle

Improving the Friction-Wear Properties and Wettability of Titanium Through Microstructural Changes Induced by Laser Surface Treatment

by Agnieszka Twardowska and Łukasz Ślusarczyk

Materials 2025, 18(23), 5410; https://doi.org/10.3390/ma18235410 (registering DOI) - 30 Nov 2025

Abstract

In this study, a surface treatment of Ti grade 1 was carried out in air with the use of a Yb-fiber laser to increase the friction-wear properties tested in dry contact with α-Al₂O₃. The laser surface treated specimens clearly [...] Read more.

In this study, a surface treatment of Ti grade 1 was carried out in air with the use of a Yb-fiber laser to increase the friction-wear properties tested in dry contact with α-Al₂O₃. The laser surface treated specimens clearly differ in their surface roughness and wettability, coefficient of friction and resistance to wear, compared to untreated specimens. The microstructure changes induced by laser treatment were investigated using confocal scanning electron microscopy with chemical composition analysis by energy-dispersive spectroscopy, and phase composition by X-ray spectroscopy. It was found that laser surface treatment caused the formation of titanium oxide layers with TiO₂ (rutile, anatase and brookite) as the main constituent, while in the subsurface areas a partial transformation of α-Ti to β-Ti or α’-Ti was thermally induced. Specimens containing β-Ti or α’-Ti in the subsurface area and anatase or brookite in the top layer were characterized by two times lower friction coefficient values and 10 times lower volume wear index Wv in comparison to untreated Ti grade 1. Results clearly confirmed the beneficial effect of laser surface treatment on friction-wear properties of Ti grade 1, but the selection of laser processing parameters was crucial both for resistance to abrasive wear and wettability. Full article

(This article belongs to the Special Issue Evaluation of the Surface Topography, Abrasive Processing, and Precision Machining Technology and Applications)

22 pages, 5738 KB

Open AccessArticle

Riveting Quality Improvement Mechanism of 2A10 Aluminum Alloy with Compound Feed Rates

by Deyi Zou, Weijun Liu and Zewei Yuan

Metals 2025, 15(12), 1326; https://doi.org/10.3390/met15121326 (registering DOI) - 30 Nov 2025

Abstract

The riveting process is conventionally performed at a constant feed rate, overlooking the distinct deformation mechanisms inherent in its successive stages. This study introduces a novel compound feed rate approach to enhance the riveting quality of 2A10 aluminum alloy countersunk head rivets. A [...] Read more.

The riveting process is conventionally performed at a constant feed rate, overlooking the distinct deformation mechanisms inherent in its successive stages. This study introduces a novel compound feed rate approach to enhance the riveting quality of 2A10 aluminum alloy countersunk head rivets. A three-dimensional finite element model, validated experimentally, was developed to simulate the riveting process, segmented into three stages: free upsetting, hole wall interference, and driven head formation. An orthogonal experimental design was employed to investigate the effects of varying feed rates (1, 5, 10 mm/s) within these stages on key quality metrics: interference distribution, uniformity, and driven head geometry. Results demonstrate that increasing the feed rate reduces average interference but increases the driven head diameter, revealing a stage-dependent influence. A multi-objective optimization framework, integrating gray relational analysis with the entropy weighting method, was applied to balance these competing objectives. The optimal compound feed rate scheme of 10-1-10 mm/s (for the three stages, respectively) was identified. This optimized scheme improved interference uniformity by 1%, increased the critical shank-end interference (Point H) by 10.9%, and enhanced driven head dimensions compared to conventional constant-rate riveting. Full article

26 pages, 3717 KB

Open AccessArticle

Promising Anticancer Activity of Novel Hydroxyethyloxy and Bromo derivatives of Curcumin and Its Complexes with BF₂

by Eduard Potapskyi, Dawid Łażewski, Julian Myszkiewicz, Gabriela Korzańska, Joanna Kuźmińska, Łukasz Popenda, Artur Korzański, Agnieszka Zgoła-Grześkowiak, Agnieszka Gielara-Korzańska, Karolina Chmaj-Wierzchowska, Nataliya Finiuk, Yuliia Kozak, Iryna Ivasechko, Rostyslav Stoika, Roman Lesyk and Marcin Wierzchowski

Molecules 2025, 30(23), 4609; https://doi.org/10.3390/molecules30234609 (registering DOI) - 30 Nov 2025

Abstract

Curcumin has long been used for health purposes and is currently attracting significant research interest. In this study, we present a series of curcumin derivatives featuring structural modifications, including methoxy groups, short alcohol chains, and bromine atoms. The cytotoxic activity of the compounds [...] Read more.

Curcumin has long been used for health purposes and is currently attracting significant research interest. In this study, we present a series of curcumin derivatives featuring structural modifications, including methoxy groups, short alcohol chains, and bromine atoms. The cytotoxic activity of the compounds obtained was tested against BA/F3 wt, BA/F3 del52, BA/F3 ins5, K562, Jurkat, HCT-116, and MDA-MB-231 cell lines and non-cancerous Balb/3T3 fibroblast lines. The most promising compounds 2a, 6a, and 9a demonstrated anticancer activity comparable to that of doxorubicin, while exhibiting toxicity toward fibroblasts similar to natural curcumin. In addition, thanks to microscopic fluorescence analysis, a mechanism of action was proposed for the most active compounds against the HCT-116 cell line. Some compounds exhibit moderate or strong proapoptotic activity, while others are characterized by cytostatic activity. Studied compounds demonstrated the DNA-intercalation ability and increased the content of cellular ROS in treated HCT-116 cells. Full article

23 pages, 5423 KB

Open AccessArticle

Identification and Evolutionary Characteristics of Regional Landscapes in the Context of Rural Revitalization: A Case of Dujiangyan Irrigation District, China

by Haopeng Huang and Qingjuan Yang

Land 2025, 14(12), 2356; https://doi.org/10.3390/land14122356 (registering DOI) - 30 Nov 2025

Abstract

As a UNESCO World Heritage Site, the Dujiangyan Irrigation District is a key area for Chengdu’s rural revitalisation. However, as the plan progresses, issues have emerged, including loss of traditional features, cultural heritage, and landscape degradation. Within the framework of “landscape information collection—landscape [...] Read more.

As a UNESCO World Heritage Site, the Dujiangyan Irrigation District is a key area for Chengdu’s rural revitalisation. However, as the plan progresses, issues have emerged, including loss of traditional features, cultural heritage, and landscape degradation. Within the framework of “landscape information collection—landscape information processing—landscape information output”, the study utilized literature review, field surveys, and remote sensing interpretation to collect data for the years 2000, 2010, and 2020 as time slices. A system of landscape characteristic elements was then built to identify the types of landscape characteristics. The types were determined, and a systematic analysis of the regional landscape’s evolution was conducted. The results indicated that the types of landscape characteristics were classified as follows: Urban Settlement Landscape (8.70–16.10%), Low-Hill Forest Landscape (1.82–3.47%), Village Woodland-Grove Landscape (15.89–44.23%), and Idyllic Agricultural Landscape (36.20–73.59%). Over the last two decades, there has been a steady increase in Urban Settlement Landscape, a slow overall growth trend in Low-Hill Forest Landscape, a rapid growth trend in Village Woodland-grove Landscape, and a rapid decline in Idyllic Agricultural Landscape. Among these, built-up land dominates Urban Settlement Landscape evolution; forest land shapes Low-Hill Forest Landscape; cultivated and built-up land influence Village Woodland-grove Landscape; and cultivated land drives Idyllic Agricultural Landscape changes. Based on the changes observed, the study explored the impact of relevant policies on the landscape characteristics of the study area. Policies for urban-rural integration have encouraged the networked growth of settlement landscapes, creating a system with several centres. Both ecological and economic gains have resulted from forestry practices. Policies that safeguard farmhouse forests have made multifunctional transformation easier. Large-scale farming and ecological agriculture are now linked in a zone established by agricultural modernisation strategies. The study offers scientific references for the protection of regional landscapes and the construction of rural living environments in the irrigation area. Full article

26 pages, 9350 KB

Open AccessArticle

Population Structure and Climate Effects on Geckobia Infestation in Ptyodactylus Geckos from Israel and West Bank, with Descriptions of G. parva sp. nov. and G. inermis sp. nov

by Monika Fajfer-Jakubek and Bożena Sikora

Animals 2025, 15(23), 3461; https://doi.org/10.3390/ani15233461 (registering DOI) - 30 Nov 2025

Abstract

Scale mites of the genus Geckobia (Pterygosomatidae) are highly specialized permanent parasites of geckos, but their diversity and ecology in arid environments remain poorly understood. We examined 1135 museum specimens of Ptyodactylus geckos collected from 1965 to 1991 across Israel and the West [...] Read more.

Scale mites of the genus Geckobia (Pterygosomatidae) are highly specialized permanent parasites of geckos, but their diversity and ecology in arid environments remain poorly understood. We examined 1135 museum specimens of Ptyodactylus geckos collected from 1965 to 1991 across Israel and the West Bank’s Mediterranean–desert climate gradient to investigate environmental effects on Geckobia mite distributions and population structure. We analyzed prevalence, intensity, population structure, and seasonal patterns across three climate zones using standard parasitological methods and Köppen–Geiger climate classification. We describe two new species, Geckobia inermis sp. nov. and G. parva sp. nov., from Ptyodactylus puiseuxi and provide the first descriptions of previously unknown life stages: the male and nymphchrysalis of G. squameum and the imagochrysalis and larva of G. bochkovi. We report P. oudrii as a new host for G. synthesys and address taxonomic confusion regarding northern Israeli host populations following recent phylogenetic revisions of Ptyodactylus. Only 37 hosts were infected (3.26% prevalence), with a significant female bias in G. squameum populations. Most mites (94.6%) concentrated in the tympanum, where we documented a “double skin plug”, closing the ear opening and creating favorable microenvironments for mite survival. The results demonstrate climate as the primary factor structuring mite distributions: environmental filtering showed systematic prevalence decline from Mediterranean zones (4.3%) to desert-edge areas (1.1%), representing a 3.9-fold gradient that exceeded host species effects by 5.2-fold. Populations exhibited phenological plasticity, with Mediterranean mites peaking in winter versus spring activity in semi-arid zones. These findings reveal how climate constrains ectoparasite persistence in arid systems, with implications for understanding parasite responses to environmental change. Full article

(This article belongs to the Section Ecology and Conservation)

17 pages, 2522 KB

Open AccessArticle

Reutilizing Flavonoids from Agricultural By-Products for In Situ Generation and Immobilization of AgNPs on Silk Towards Coloration, Antimicrobial and Anti-UV Functions

by Wei Chen, Yijie Yue, Xiaoqi Zhou, Jingyu Sun, Leyang Chen, Xiaoyan Hu and Yuyang Zhou

Materials 2025, 18(23), 5409; https://doi.org/10.3390/ma18235409 (registering DOI) - 30 Nov 2025

Abstract

The utilization of agro-byproducts for textile dyeing and finishing is strongly suggested to meet sustainability and cost-efficiency objectives. Despite recently proliferating studies, three major issues hinder the industrialization of such a technique: identifying reasonable bio-resources, ensuring compatibility between agro-byproducts and textile substrates, and [...] Read more.

The utilization of agro-byproducts for textile dyeing and finishing is strongly suggested to meet sustainability and cost-efficiency objectives. Despite recently proliferating studies, three major issues hinder the industrialization of such a technique: identifying reasonable bio-resources, ensuring compatibility between agro-byproducts and textile substrates, and achieving satisfactory color depth, functionality, and durability. This research introduces an approach that forms and fixes silver nanoparticles (AgNPs) on silk using three representative flavonoids (FLs)—Quercetin (QUE), Baicalin (BAI), and Rutin (RUT)—through a single-step in situ bio-reduction. Results demonstrate that FLs-synthesized AgNPs@silk generates attractive spectra of hues, varying from pale cream-brown to deep golden-brown. Using an equivalent quantity of FLs, the color intensity of silk descends in QUE-Ag@silk > BAI-Ag@silk > RUR-Ag@silk, due to the decreasing reactivity and binding affinity of FLs to silk. SEM reveals uniformly distributed spherical AgNPs in dimensions between 20 and 40 nm on silk and the dimension inversely correlates with FLs concentration while being directly proportional to silver nitrate. The modified silk exhibits remarkable antimicrobial performance (>98% pathogen elimination) and exceptional wash resistance (>90% reduction both of E. coli and S. aureus after ten cycles of washing). Additionally, the FLs-synthesized AgNPs provide silk with superior UV shielding capability. This study stems from environmental awareness and sustainable production of AgNPs by FLs, ready for developing hygienic and therapeutic textile materials. Full article

(This article belongs to the Special Issue Functional Textiles: Fabrication, Processing and Applications)

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