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15 pages, 2447 KB

Open AccessArticle

Investigation on Microstructure, Thermal Fatigue Resistance, and Tribological Behavior of Mo₂FeB₂-Based Cermet Coating on GCr15 Steel Substrate

by Hao Zhang, Yang Zhang, Lufan Jin, Binglin Zhang and Yu Zhang

Lubricants 2026, 14(1), 5; https://doi.org/10.3390/lubricants14010005 (registering DOI) - 23 Dec 2025

Abstract

In this study, a boride cladding layer with Mo₂FeB₂ hard phase was prepared on the GCr15 steel via plasma cladding. The phase composition, microstructure, thermal fatigue resistance, microhardness, and wear resistance of the boride cladding layer were investigated. The results [...] Read more.

In this study, a boride cladding layer with Mo₂FeB₂ hard phase was prepared on the GCr15 steel via plasma cladding. The phase composition, microstructure, thermal fatigue resistance, microhardness, and wear resistance of the boride cladding layer were investigated. The results revealed that the hard phases in the boride cladding layer were Mo₂FeB₂ and (Cr,Fe)₂₃(C,B)₆, while the binder phase consisted of α-Fe martensite. When the thermal fatigue times increased, the indentation crack length extended in a quadratic pattern, and the crack propagation rate increased. Crack propagation in the cladding layer occurred via both transgranular and intergranular modes. When the thermal fatigue temperature was below 600 °C, the cladding layer exhibited good thermal stability, and a reliable metallurgical bond was formed between the cladding layer and the GCr15 steel substrate. The microhardness of the cladding layer reached 1022.1 HV_0.5, approximately 2.6 times that of the GCr15 steel. The mass loss of the cladding layer increased with the increase in wear load and wear time. The wear of the cladding layer was mainly three-body abrasion wear, resulting from brittle spalling of the hard phase on the worn surface. This study demonstrates the potential of Mo₂FeB₂-based cladding layers for extending the service life of high-value industrial components. Full article

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17 pages, 1189 KB

Open AccessArticle

AI-Driven RF Fingerprinting for Secure Positioning Optimization in 6G Networks

by Ioannis A. Bartsiokas, Maria-Lamprini A. Bartsioka, Anastasios K. Papazafeiropoulos, Dimitra I. Kaklamani and Iakovos S. Venieris

Microwave 2026, 2(1), 1; https://doi.org/10.3390/microwave2010001 (registering DOI) - 23 Dec 2025

Abstract

Accurate user positioning in 6G networks is essential for next-generation mobile services. However, classical approaches such as time-difference-of-arrival (TDoA) remain vulnerable to dense multipath and NLoS conditions commonly found in indoor and industrial environments. This paper proposes an AI-driven RF fingerprinting framework that [...] Read more.

Accurate user positioning in 6G networks is essential for next-generation mobile services. However, classical approaches such as time-difference-of-arrival (TDoA) remain vulnerable to dense multipath and NLoS conditions commonly found in indoor and industrial environments. This paper proposes an AI-driven RF fingerprinting framework that leverages uplink channel state information (CSI) to achieve robust and privacy-preserving 2D localization. A lightweight convolutional neural network (CNN) extracts location-specific spectral–spatial fingerprints from CSI tensors, while a federated learning (FL) scheme enables distributed training across multiple gNBs without sharing raw channel data. The proposed integration of CSI tensor processing with FL and structured pruning is introduced as a novel solution for practical 6G edge positioning. To further reduce latency and communication costs, a structured pruning mechanism compresses the model by 40–60%, lowering the memory footprint with negligible accuracy loss. A performance evaluation in 3GPP-compliant indoor factory scenarios indicates a median positioning error below 1 m for over 90% of cases, significantly outperforming TDoA. Moreover, the compressed FL model reduces the FL communication load by ~38% and accelerates local training, establishing an efficient, secure, and deployment-ready positioning solution for 6G networks. Full article

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23 pages, 2239 KB

Open AccessArticle

SparseDroop: Hardware–Software Co-Design for Mitigating Voltage Droop in DNN Accelerators

by Arnab Raha, Shamik Kundu, Arghadip Das, Soumendu Kumar Ghosh and Deepak A. Mathaikutty

J. Low Power Electron. Appl. 2026, 16(1), 2; https://doi.org/10.3390/jlpea16010002 (registering DOI) - 23 Dec 2025

Abstract

Modern deep neural network (DNN) accelerators must sustain high throughput while avoiding performance degradation from supply voltage (VDD) droop, which occurs when large arrays of multiply–accumulate (MAC) units switch concurrently and induce high peak current (

I C C_{m a x}

) [...] Read more.

Modern deep neural network (DNN) accelerators must sustain high throughput while avoiding performance degradation from supply voltage (VDD) droop, which occurs when large arrays of multiply–accumulate (MAC) units switch concurrently and induce high peak current (

I C C_{m a x}

) transients on the power delivery network (PDN). In this work, we focus on ASIC-class DNN accelerators with tightly synchronized MAC arrays rather than FPGA-based implementations, where such cycle-aligned switching is most pronounced. Conventional guardbanding and reactive countermeasures (e.g., throttling, clock stretching, or emergency DVFS) either waste energy or incur non-trivial throughput penalties. We propose SparseDroop, a unified hardware-conscious framework that proactively shapes instantaneous current demand to mitigate droop without reducing sustained computing rate. SparseDroop comprises two complementary techniques. (1) SparseStagger, a lightweight hardware-friendly droop scheduler that exploits the inherent unstructured sparsity already present in the weights and activations—it does not introduce any additional sparsification. SparseStagger dynamically inspects the zero patterns mapped to each processing element (PE) column and staggers MAC start times within a column so that high-activity bursts are temporally interleaved. This fine-grain reordering smooths

I C C

trajectories, lowers the probability and depth of transient VDD dips, and preserves cycle-level alignment at tile/row boundaries—thereby maintaining no throughput loss and negligible control overhead. (2) SparseBlock, an architecture-aware, block-wise-structured sparsity induction method that intentionally introduces additional sparsity aligned with the accelerator’s dataflow. By co-designing block layout with the dataflow, SparseBlock reduces the likelihood that all PEs in a column become simultaneously active, directly constraining

I C C_{m a x}

and peak dynamic power on the PDN. Together, SparseStagger’s opportunistic staggering (from existing unstructured weight zeros) and SparseBlock’s structured, layout-aware sparsity induction (added to prevent peak-power excursions) deliver a scalable, low-overhead solution that improves voltage stability, energy efficiency, and robustness, integrates cleanly with the accelerator dataflow, and preserves model accuracy with modest retraining or fine-tuning. Full article

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29 pages, 5307 KB

Open AccessArticle

Regional Cooling and Peak-Load Performance of Naturally Ventilated Cavity Walls in Representative U.S. Climate Zones

by Ri Na, Abdulaziz Banawi and Behzad Abbasnejad

Architecture 2026, 6(1), 2; https://doi.org/10.3390/architecture6010002 (registering DOI) - 23 Dec 2025

Abstract

Naturally ventilated cavity walls (VCWs) retrofit conventional cavity walls with vents that enable buoyancy- or wind-driven airflow and reduce cooling loads during summer. When closed, they retain the thermal performance of traditional walls. Previous studies evaluated VCWs under steady-state conditions but did not [...] Read more.

Naturally ventilated cavity walls (VCWs) retrofit conventional cavity walls with vents that enable buoyancy- or wind-driven airflow and reduce cooling loads during summer. When closed, they retain the thermal performance of traditional walls. Previous studies evaluated VCWs under steady-state conditions but did not capture regional, transient solar heating effects. This study assesses VCW performance across major U.S. climate types using a transient 3D solar heating model for east-, south-, and west-facing façades in four representative cities. Simulated façade temperatures were validated using published measurements and then applied to a regression-based energy model to estimate cooling load reductions. Results show 30–40% savings for east/west façades and 10–20% for south façades, with monthly reductions exceeding 1.0 kWh/m² in all regions. On-peak savings (3–7 PM) were at least 1.5× off-peak values, indicating strong peak-shaving capability. Overall, VCWs offer a low-cost, climate-adaptive retrofit strategy that improves façade energy performance and reduces peak cooling demand. Full article

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13 pages, 503 KB

Open AccessArticle

Rapid Evaluation of Wet Gluten Content in Wheat Using Hyperspectral Technology Combined with Machine Learning Algorithms

by Yan Lai, Yan-Yan Li, Min Sha, Peng Li and Zheng-Yong Zhang

Foods 2026, 15(1), 41; https://doi.org/10.3390/foods15010041 (registering DOI) - 23 Dec 2025

Abstract

The development of rapid and intelligent methods is urgently needed for wheat quality evaluation. Using the prediction of wet gluten content as a case study, this work systematically investigated the performance of various machine learning algorithms and their optimization for content prediction, based [...] Read more.

The development of rapid and intelligent methods is urgently needed for wheat quality evaluation. Using the prediction of wet gluten content as a case study, this work systematically investigated the performance of various machine learning algorithms and their optimization for content prediction, based on hyperspectral data from the visible and near-infrared ranges of wheat grains and flour. The results revealed that the random forest regression (RFR) algorithm delivered the best predictive performance under two conditions: first, when applied directly to visible spectra; and second, when applied to fused visible and near-infrared spectral data. This held true for both grains and flour. Conversely, its direct application to NIR spectra alone yielded relatively worse performance. Following data optimization, the first-derivative (FD) visible spectra of wheat grains were smoothed using a Savitzky–Golay (SG) filter and subsequently used as input for the RFR model. This optimized approach achieved a coefficient of determination (r²) of 0.8579, a root mean square error (RMSE) of 0.0216, and a relative percent deviation (RPD) of 2.6978. Under the same conditions, for wheat flour, the corresponding values were 0.8383, 0.0231, and 2.5293, respectively. Similarly, for wheat flour, the RFR model was applied to the SG-filtered FD spectra derived from the fused visible and near-infrared data, yielding an r² of 0.8474, an RMSE of 0.0224, and an RPD of 2.6034. Under the same conditions, wheat grains yielded an r² of 0.8494, an RMSE of 0.0223, and an RPD of 2.6208. This efficient and rapid intelligent prediction scheme demonstrates considerable potential for the quality assessment and control of relevant food products. Full article

(This article belongs to the Section Food Analytical Methods)

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20 pages, 5873 KB

Open AccessArticle

A Deep Reinforcement Learning-Optimized Blood Flow Profile for Enhanced Oxygenation Efficiency in Membrane Oxygenators

by Junwen Yu, Yuan Liu, Huaiyuan Guo, Qingyang Cheng, Junlong Meng and Ming Yang

Membranes 2026, 16(1), 4; https://doi.org/10.3390/membranes16010004 (registering DOI) - 23 Dec 2025

Abstract

The membrane oxygenator serves as the core component of extracorporeal life support systems, and its gas exchange efficiency critically influences clinical outcomes. However, gas transfer is predominantly limited by the diffusion barrier within the blood-side boundary layer, where saturated red blood cells accumulate. [...] Read more.

The membrane oxygenator serves as the core component of extracorporeal life support systems, and its gas exchange efficiency critically influences clinical outcomes. However, gas transfer is predominantly limited by the diffusion barrier within the blood-side boundary layer, where saturated red blood cells accumulate. Current research focuses mainly on static approaches such as optimizing fiber bundle configuration to promote passive blood mixing or modifying material properties, which are fixed after fabrication. In contrast, dynamic blood flow control remains an underexplored avenue for enhancing oxygenator performance. This study proposes an active pulsatile flow control method that disrupts the boundary layer barrier by optimizing periodic flow profiles, thereby directly improving gas exchange. A deep reinforcement learning framework integrating proximal policy optimization and long short-term memory networks was developed to autonomously search for optimal flow waveforms under constant flow conditions. A simplified stacked-plate membrane oxygenator was specially designed as the experimental platform to minimize flow path interference. Experimental results demonstrate that the optimized pulsatile profile increases the oxygen transfer rate by

20.64 %

without compromising hemocompatibility. Full article

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17 pages, 496 KB

Open AccessArticle

Two-Dimensional Discrete Coupled Fractional Fourier Transform (DCFrFT)

by Asma Elshamy, Zeinab S. I. Mansour and Ahmed Zayed

Fractal Fract. 2026, 10(1), 7; https://doi.org/10.3390/fractalfract10010007 (registering DOI) - 23 Dec 2025

Abstract

The fractional Fourier transform is critical in signal processing and supports many applications. Signal processing is one notable application. Implementing the fractional Fourier transform requires discrete versions. As a result, defining a discrete coupled fractional Fourier transform (DCFrFT) is essential. This paper presents [...] Read more.

The fractional Fourier transform is critical in signal processing and supports many applications. Signal processing is one notable application. Implementing the fractional Fourier transform requires discrete versions. As a result, defining a discrete coupled fractional Fourier transform (DCFrFT) is essential. This paper presents a discrete version of the continuous, two-dimensional coupled fractional Fourier transform, which is not a tensor product of one-dimensional transforms. We examine the main characteristics of the operator and illustrate its relationship with the existing two-dimensional discrete fractional Fourier transforms. Examples help clarify the approach. Full article

(This article belongs to the Special Issue Recent Advances in Fractional Fourier Transforms and Applications, 2nd Edition)

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8 pages, 207 KB

Open AccessEditorial

Recent Advances in Anti-HCV, Anti-HBV and Anti-Flavivirus Agents

by Grigoris Zoidis

Viruses 2026, 18(1), 20; https://doi.org/10.3390/v18010020 (registering DOI) - 23 Dec 2025

Abstract

Viral infections have shaped human history since the earliest stages of civilization and continue to exert one of the greatest global pressures on health, socioeconomic stability, and public health infrastructures [...] Full article

(This article belongs to the Special Issue Recent Advances in Anti-HCV, Anti-HBV and Anti-flavivirus Agents)

15 pages, 2389 KB

Open AccessArticle

Evaluating the Suitability of Four Plant Functional Groups in Green Roofs Under Nitrogen Deposition

by Nan Yang, Hechen Li, Runze Wu, Yihan Wang, Meiyang Li, Lei Chen, Hongyuan Li and Guang Hao

Plants 2026, 15(1), 43; https://doi.org/10.3390/plants15010043 (registering DOI) - 23 Dec 2025

Abstract

The rapid urban expansion in the past few decades has resulted in a deficit of urban green space, and green roofs have become an effective way to expand urban green spaces. High nitrogen (N) deposition induced by urban development has threatened the health [...] Read more.

The rapid urban expansion in the past few decades has resulted in a deficit of urban green space, and green roofs have become an effective way to expand urban green spaces. High nitrogen (N) deposition induced by urban development has threatened the health and sustainability of plants. The aim of this study was to evaluate the responses of plant growth performance and aesthetic value to N deposition in green roofs. Eleven species from four plant functional groups were grown under control, low N addition, and high N addition conditions to assess the effects of N addition on their growth performance, aesthetic value, soil properties, and plant functional traits. Different plant functional groups exhibited distinct traits, and their response to N addition was different. Under high N addition, the growth performance of sod-forming graminoids and tall forbs decreased by 47.0% and 23.7%, and their aesthetic value decreased by 24.4% and 16.2%, respectively. Growth performance of plant functional groups was mainly determined by plant functional traits rather than soil properties. The poor growth performance and aesthetic value of sod-forming graminoids and tall forbs challenged their widespread use under high N addition. This study highlighted the importance of selecting environmentally adaptive species from the perspective of plant functional groups, especially in the context of future high N deposition. Full article

(This article belongs to the Special Issue Sustainable Plants and Practices for Resilient Urban Greening)

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10 pages, 1095 KB

Open AccessCommunication

Tapeworms in an Apex Predator: First Molecular Identification of Taenia krabbei and Taenia hydatigena in Wolves (Canis lupus) from Romania

by Maria Monica Florina Moraru, Ana-Maria Marin, Dan-Cornel Popovici, Azzurra Santoro, Adriano Casulli, Sorin Morariu, Marius Stelian Ilie, Violeta Igna and Narcisa Mederle

Pathogens 2026, 15(1), 18; https://doi.org/10.3390/pathogens15010018 (registering DOI) - 23 Dec 2025

Abstract

The wolf (Canis lupus) is an apex predator with high mobility and trophic plasticity, serving as a valuable indicator of helminth transmission at the wildlife–livestock interface. Given the ecological overlap between wolves and both wild and domestic ungulates in Romania, we [...] Read more.

The wolf (Canis lupus) is an apex predator with high mobility and trophic plasticity, serving as a valuable indicator of helminth transmission at the wildlife–livestock interface. Given the ecological overlap between wolves and both wild and domestic ungulates in Romania, we aimed to identify and molecularly characterize cestodes from wolves’ small intestines. Between November 2022 and June 2025, small intestines from nine wolves were collected across four Romanian counties, frozen, and examined using classical parasitology (macroscopic and microscopic) and molecular methods (PCR amplification and Sanger sequencing of mitochondrial cox1, nad1, and 12S rRNA fragments). Taeniids were detected in three (33.33%) out of nine tested individuals. Genetic analyses confirmed the presence of Taenia krabbei and Taenia hydatigena—species not previously reported in wolves from Romania. This study provides the first molecular evidence of T. krabbei and T. hydatigena in wolves from Romania, and likely Eastern Europe, indicating active transmission and underscoring the need for broader surveillance of hosts to clarify their ecology and regional dynamics within a One Health context. Full article

(This article belongs to the Special Issue Novel Insights into Animal Disease Ecology and Epidemiology Under One Health)

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17 pages, 2502 KB

Open AccessArticle

DPPH Measurement for Phenols and Prediction of Antioxidant Activity of Phenolic Compounds in Food

by Riku Kato, Chihiro Tada, Moeka Yamauchi, Yuto Matsumoto and Hiroaki Gotoh

Curr. Issues Mol. Biol. 2026, 48(1), 12; https://doi.org/10.3390/cimb48010012 (registering DOI) - 23 Dec 2025

Abstract

Consuming foods with high antioxidant capacity is considered beneficial to health, and predicting the antioxidant capacity of food components is important. In the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, multiple reactions occur simultaneously, and because the experimental conditions are not standardized across studies, quantitative prediction of [...] Read more.

Consuming foods with high antioxidant capacity is considered beneficial to health, and predicting the antioxidant capacity of food components is important. In the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, multiple reactions occur simultaneously, and because the experimental conditions are not standardized across studies, quantitative prediction of DPPH activity is difficult. In this study, we qualitatively and quantitatively predicted the DPPH activity of phenols in food using data obtained under unified experimental conditions and machine learning. We measured DPPH activity of 96 compounds to create a dataset comprising measurements of 274 compounds, including values previously reported by our laboratory. The classification model implemented using LightGBM showed high performance, achieving an accuracy of 0.88 and an F1 score of 0.86. The support vector regression model satisfied the Golbraikh–Tropsha criteria, with an R²_test of 0.70, RMSE_test of 0.44, q² of 0.61, and RMSE_validation of 0.46. Furthermore, the chemical validity of the prediction was confirmed by comparing the results of the machine learning model with those of previous studies. This method provides a basis for the quantitative prediction of DPPH activity of numerous phenolic compounds in foods and is expected to contribute to the elucidation of the antioxidant capacity of foods. Full article

(This article belongs to the Special Issue Mechanistic Insights into the Antioxidant Activity of Bioorganic Molecules: A Chemical Perspective)

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30 pages, 1997 KB

Open AccessReview

Electrochemical Choline Sensing: Biological Context, Electron Transfer Pathways and Practical Design Strategies

by Angel A. J. Torriero, Sarah M. Thiak and Ashwin K. V. Mruthunjaya

Biomolecules 2026, 16(1), 23; https://doi.org/10.3390/biom16010023 (registering DOI) - 23 Dec 2025

Abstract

Choline is a central metabolite that connects membrane turnover, neurotransmission, and one-carbon metabolism, and its reliable measurement across diverse biological matrices remains a significant analytical challenge. This review brings together biological context, electrochemical mechanisms, and device engineering to define realistic performance targets for [...] Read more.

Choline is a central metabolite that connects membrane turnover, neurotransmission, and one-carbon metabolism, and its reliable measurement across diverse biological matrices remains a significant analytical challenge. This review brings together biological context, electrochemical mechanisms, and device engineering to define realistic performance targets for choline sensors in blood, cerebrospinal fluid, extracellular space, and milk. We examine enzymatic sensor architectures ranging from peroxide-based detection to mediated electron transfer via ferrocene derivatives, quinones, and osmium redox polymers and assess how applied potential, oxygen availability, and film structure shape electron-transfer pathways. Evidence for direct electron transfer with choline oxidase is critically evaluated, with emphasis on the essential controls needed to distinguish true flavin-based communication from peroxide-related artefacts. We also examine bienzymatic formats that allow operation at low or negative bias and discuss strategies for matrix-matched validation, selectivity, drift control, and resistance to fouling. To support reliable translation, we outline reporting standards that include matrix-specific concentration ranges, reference electrode notation, mediator characteristics, selectivity panels, and access to raw electrochemical traces. By connecting biological requirements to mechanistic pathways and practical design considerations, this review provides a coherent framework for developing choline sensors that deliver stable, reproducible performance in real samples. Full article

(This article belongs to the Section Chemical Biology)

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13 pages, 1777 KB

Open AccessArticle

White Matter N-Acylphosphatidylserines (NAPSs) and Myelin Dysfunction in Late-Onset Alzheimer’s Disease (LOAD): A Pilot Study

by Paul L. Wood, Annika K. Lagos and Alexis R. Kastigar

Life 2026, 16(1), 22; https://doi.org/10.3390/life16010022 (registering DOI) - 23 Dec 2025

Abstract

Disruption of myelin in Alzheimer’s disease has been observed by various approaches including histology, proteomics, and white matter hyperintensities in T2 FLAIR images. Since lipids are essential myelin components, we aimed to monitor N-acylphosphatidylserines (NAPSs), unique brain lipids that are altered by neuronal [...] Read more.

Disruption of myelin in Alzheimer’s disease has been observed by various approaches including histology, proteomics, and white matter hyperintensities in T2 FLAIR images. Since lipids are essential myelin components, we aimed to monitor N-acylphosphatidylserines (NAPSs), unique brain lipids that are altered by neuronal stress. NAPS 52:1 (PS 36:1-N16:0) was the dominant NAPS in both gray and white matter. Relative levels of NAPS 52:1 were 2.5 times higher in the periventricular white matter (PVWM) than in the hippocampus and were reduced to approximately 50% of control in both brain regions in subjects with late-onset Alzheimer’s disease (LOAD). To monitor potential alterations in metabolic precursors of NAPS 52:1, we also measured the following: (1) phosphatidylcholine (PC) 36:1, which can undergo base exchange with N-acylserine (NASer) 16:0 to form NAPS 52:1; (2) phosphatidylserine (PS) 36:1, which can undergo N-acylation with palmitic acid (FA 16:0); and (3) diacylglycerol 36:1, which can be a precursor for both PC 36:1 and PS 36:1. These analyses found that only the relative levels of PS 36:1 were decreased and only in the PVWM. Next, we evaluated NASer 16:0, which can be released from NAPS 52:1 by phospholipase D. This is an N-acyl amino acid with neuroprotective properties. NASer 16:0 was found to be present at trace levels and could only be reliably monitored in the PVWM in which relative levels were decreased in LOAD subjects. In summary, reductions in NAPSs and NASer in the PVWM are lipid biomarkers of disruptions in myelin in LOAD. These data, in conjunction with our previous report of decrements in the levels of neocortical ether-PS in LOAD, suggest that these combined alterations in serine glycerophospholipid metabolism may contribute to neuronal dysfunction in dementia. Full article

(This article belongs to the Section Physiology and Pathology)

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23 pages, 931 KB

Open AccessReview

Artificial Intelligence and the Reconfiguration of Emotional Well-Being (2020–2025): A Critical Reflection

by Carlos Santiago-Torner, José-Antonio Corral-Marfil and Elisenda Tarrats-Pons

Societies 2026, 16(1), 6; https://doi.org/10.3390/soc16010006 (registering DOI) - 23 Dec 2025

Abstract

Between 2020 and 2025, rapid advances in artificial intelligence (AI) reshaped how individuals access emotional support, express feelings, and build interpersonal trust. This article offers a critical reflection—based on an analytical review of 40 peer-reviewed studies—on the psychosocial, ethical, and sociotechnical tensions that [...] Read more.

Between 2020 and 2025, rapid advances in artificial intelligence (AI) reshaped how individuals access emotional support, express feelings, and build interpersonal trust. This article offers a critical reflection—based on an analytical review of 40 peer-reviewed studies—on the psychosocial, ethical, and sociotechnical tensions that characterize AI-mediated emotional well-being. We document both opportunities (expanded access to support, personalization, and early detection) and risks (simulated empathy, affective dependence, algorithmic fatigue, and erosion of relational authenticity). Methodologically, we applied a three-phase critical review: exploratory reading, thematic clustering, and interpretive synthesis; sources were retrieved from Scopus, Web of Science and PsycINFO and filtered by relevance, methodological rigor, and topical fit. We propose a conceptual model integrating three interdependent levels—technological–structural, psychosocial–relational, and ethical–existential—and argue for a sociotechnical perspective that recognizes AI as a co-constitutive actor in emotional ecologies. The article closes with targeted research agendas and policy recommendations to foster human-centered AI that preserves emotional autonomy and equity. Full article

(This article belongs to the Special Issue Mental Health, Anxiety, and Emerging Technologies: Assessment, Social Implications, and Interventions)

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37 pages, 928 KB

Open AccessReview

The Xenopus Oocyte System: Molecular Dynamics of Maturation, Fertilization, and Post-Ovulatory Fate

by Ken-Ichi Sato

Biomolecules 2026, 16(1), 22; https://doi.org/10.3390/biom16010022 (registering DOI) - 23 Dec 2025

Abstract

The Xenopus oocyte has long served as a versatile and powerful model for dissecting the molecular underpinnings of reproductive and developmental processes. Its large size, manipulability, and well-characterized cell cycle states have enabled generations of researchers to illuminate key aspects of oocyte maturation, [...] Read more.

The Xenopus oocyte has long served as a versatile and powerful model for dissecting the molecular underpinnings of reproductive and developmental processes. Its large size, manipulability, and well-characterized cell cycle states have enabled generations of researchers to illuminate key aspects of oocyte maturation, fertilization, and early embryogenesis. This review provides an integrated overview of the cellular and molecular events that define the Xenopus oocyte’s transition from meiotic arrest to embryonic activation—or alternatively, to programmed demise if fertilization fails. We begin by exploring the architectural and biochemical landscape of the oocyte, including polarity, cytoskeletal organization, and nuclear dynamics. The regulatory networks governing meiotic resumption are then examined, with a focus on MPF (Cdk1/Cyclin B), MAPK cascades, and translational control via CPEB-mediated cytoplasmic polyadenylation. Fertilization is highlighted as a calcium-dependent trigger for oocyte activation. During fertilization in vertebrates, sperm-delivered phospholipase C zeta (PLCζ) is a key activator of Ca²⁺ signaling in mammals. In contrast, amphibian species such as Xenopus lack a PLCZ1 ortholog and instead appear to rely on alternative protease-mediated signaling mechanisms, including the uroplakin III–Src tyrosine kinase pathway and matrix metalloproteinase (MMP)-2 activity, to achieve egg activation. The review also addresses the molecular fate of unfertilized eggs, comparing apoptotic and necrotic mechanisms and their relevance to reproductive health. Finally, we discuss recent innovations in Xenopus-based technologies such as mRNA microinjection, genome editing, and in vitro ovulation systems, which are opening new avenues in developmental biology and translational medicine. By integrating classic findings with emerging frontiers, this review underscores the continued value of the Xenopus model in elucidating the fundamental processes of life’s origin. We conclude with perspectives on unresolved questions and future directions in oocyte and early embryonic research. Full article

(This article belongs to the Special Issue Gametogenesis and Gamete Interaction, 2nd Edition)

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17 pages, 3144 KB

Open AccessArticle

Integrated Analysis of Behavioral and Physiological Effects of Nano-Sized Carboxylated Polystyrene Particles on Daphnia magna Neonates and Adults: A Video Tracking-Based Improvement of Acute Toxicity Assay

by Silvia Rizzato, Antonella Giacovelli, Gregorio Polo, Fausto Sirsi, Anna Grazia Monteduro, Gayatri Udayan, Muhammad Ahsan Ejaz, Giuseppe Maruccio and Maria Giulia Lionetto

Biosensors 2026, 16(1), 10; https://doi.org/10.3390/bios16010010 (registering DOI) - 23 Dec 2025

Abstract

Nanoplastics pose significant environmental and public health risks, prompting the need for sensitive, cost-effective, and rapid assays for ecotoxicity assessment. The present work proposes the use of a portable smartphone-based platform to enhance traditional Daphnia magna acute toxicity assays by integrating behavior analysis [...] Read more.

Nanoplastics pose significant environmental and public health risks, prompting the need for sensitive, cost-effective, and rapid assays for ecotoxicity assessment. The present work proposes the use of a portable smartphone-based platform to enhance traditional Daphnia magna acute toxicity assays by integrating behavior analysis and heart rate measurements. The aim is to improve sensitivity in detecting toxic effects of nanoplastics. In particular, the study focused on nano-sized carboxylated polystyrene (PS) nanoparticles. Two variability factors that could influence biological effects of nanoplastics, the particle size and the age of the organisms, were considered. Results demonstrated that the application of the proposed integrated approach allowed the detection of early subtle effects such as a significant impact on the heart rate and behavior of Daphnia magna under short-term exposure to PS carboxylated nanoparticles. In particular, a stimulation of heart rate was observed for both neonates and adults either for 40 nm or 200 nm particles after 48 h exposure, presumably attributable to an interference of carboxylated PS NPs with adrenergic-type receptors. Behavioral alterations were detectable for 40 nm particles but not for 200 nm ones consisting of a decrease in velocity and alterations of trajectories. Obtained results demonstrated the suitability of the proposed smartphone platform for friendly and real-time integration of behavioral analysis with physiological outcome measurements during acute exposure of Daphnia magna to nano-sized carboxylated PS NPs, expanding the sensitivity of the traditional acute toxicity tests. It offers a novel, cost-effective, and field-applicable method for environmental monitoring of nanoparticle toxicity and impact. Full article

(This article belongs to the Section Environmental Biosensors and Biosensing)

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15 pages, 4555 KB

Open AccessArticle

Mechanistic and Kinetic Insights into the Interfacial Polymerization of Fluorine-Containing Polyarylate

by Lingli Li, Tiantian Li, Siyu Chen, Jintang Duan, Cailiang Zhang, Xueping Gu and Lianfang Feng

Polymers 2026, 18(1), 31; https://doi.org/10.3390/polym18010031 (registering DOI) - 23 Dec 2025

Abstract

The interfacial polymerization of fluorine-containing polyarylates (F-PAR) represents an important synthetic route for advanced polymeric materials. This work presents a comprehensive mechanistic investigation through integrated kinetic analysis and macromolecular characterization. The polymerization for both F-PAR and its non-fluorinated analogue (M-PAR) follows a two-stage, [...] Read more.

The interfacial polymerization of fluorine-containing polyarylates (F-PAR) represents an important synthetic route for advanced polymeric materials. This work presents a comprehensive mechanistic investigation through integrated kinetic analysis and macromolecular characterization. The polymerization for both F-PAR and its non-fluorinated analogue (M-PAR) follows a two-stage, second-order kinetic profile, with the F-PAR system exhibiting a lower initial rate constant. Kinetic modeling revealed a dynamic reaction locus, transitioning from the bulk organic phase to an indistinguishable regime. The fluorinated system exhibits distinct stage-dependent behavior: initial retardation due to fluorine-induced “nucleophilicity penalty” on bisphenol monomer followed by a kinetic crossover where the growth rate of F-PAR surpasses M-PAR through enhanced oligomer electrophilicity. The terminal stage reveals fundamental divergence, while flexible M-PAR chains sustain accelerated growth via efficient chain-chain coupling, rigid F-PAR chains reach a molecular weight plateau. The incorporation of fluorine enhances thermal stability and optical transparency due to the low polarizability of C-F bonds. This study provides a complete mechanistic roadmap of fluorine’s dynamic role in polymer architecture control. Full article

(This article belongs to the Section Polymer Processing and Engineering)

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14 pages, 3925 KB

Open AccessArticle

CDKN2B Inhibits Vascular Smooth Muscle Phenotypic Switching in Corpus Spongiosum Surrounding the Urethral Plate in Hypospadias

by Jiayao Huang, Zihan Xu, Jiacheng Huang, Xiaoqin Yin, Yichen Huang and Fang Chen

Biomedicines 2026, 14(1), 32; https://doi.org/10.3390/biomedicines14010032 (registering DOI) - 23 Dec 2025

Abstract

Objective: Phenotypic switching of vascular smooth muscle cells (VSMCs) in the corpus spongiosum may contribute to abnormal urethral development in hypospadias, but the underlying molecular regulators remain unclear. This study aimed to identify hub genes associated with VSMCs phenotypic switching in the corpus [...] Read more.

Objective: Phenotypic switching of vascular smooth muscle cells (VSMCs) in the corpus spongiosum may contribute to abnormal urethral development in hypospadias, but the underlying molecular regulators remain unclear. This study aimed to identify hub genes associated with VSMCs phenotypic switching in the corpus spongiosum using RNA sequencing and Weighted Gene Co-expression Network Analysis (WGCNA), and to functionally characterize the top candidate gene CDKN2B. Methods: Corpus spongiosum tissue samples were collected from seven patients with proximal hypospadias and five patients with urethral stricture (control group). The expression of the VSMCs contractile markers Calponin 1 and α-SMA, and the secretory marker OPN, was evaluated by qRT-PCR and Western blotting to assess VSMCs phenotypic state. RNA sequencing and Weighted Gene Co-expression Network Analysis (WGCNA) were performed to identify hub genes, which were then validated by qRT-PCR. Primary VSMCs were isolated from corpus spongiosum tissue and transduced with lentiviral vectors to either suppress or overexpress CDKN2B. Changes in VSMC marker expression and in key signaling pathways associated with phenotypic switching—specifically TGF/Smad and SRF/MYOCD—were analyzed using qRT-PCR and Western blotting. Results: In hypospadias tissue, the decreased expression of α-SMA and Calponin 1, together with increased OPN, indicated a shift in VSMCs from a contractile to a secretory phenotype. RNA-seq and WGCNA identified 11 differentially expressed genes, among which CDKN2B showed a marked downregulation in hypospadias samples. In control VSMCs, CDKN2B inhibition led to reduced α-SMA and Calponin 1, elevated OPN, and suppressed activity of TGF/Smad and SRF/MYOCD signaling. Conversely, CDKN2B overexpression in VSMCs from hypospadias samples restored α-SMA and Calponin 1 expression, decreased OPN, and enhanced TGF/Smad and SRF/MYOCD pathway activation. Conclusions: VSMCs in the corpus spongiosum surrounding the urethral plate in hypospadias undergo a transition from a contractile to a secretory phenotype. CDKN2B emerges from unbiased transcriptomic screening as a key hub gene and functions as a critical regulator of this process, maintaining the contractile phenotype by modulating canonical TGF/Smad and SRF/MYOCD signaling. The CDKN2B–TGF/Smad axis may represent a central pathway linking VSMC phenotypic switching to abnormal vascular remodeling in hypospadias. Full article

(This article belongs to the Section Cell Biology and Pathology)

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22 pages, 1055 KB

Open AccessReview

Revolutionizing Green Electricity Certificates: A Real-Time Traceability Framework for Credible Renewable Energy Attribution in China

by Jiayi He, Lingxi Xie, Hongtao Wang, Lili Tian, Li Zhang, Shenzhang Li, Yanjie Zhu, Yudou Gao and Zuyuan Huang

Energies 2026, 19(1), 67; https://doi.org/10.3390/en19010067 (registering DOI) - 23 Dec 2025

Abstract

The global transition towards a clean energy system underscores the critical role of Green Electricity Certificates (GECs), yet their effectiveness is often hampered by an inability to credibly trace environmental attributes from generation to consumption. This study provides a systematic review of technological [...] Read more.

The global transition towards a clean energy system underscores the critical role of Green Electricity Certificates (GECs), yet their effectiveness is often hampered by an inability to credibly trace environmental attributes from generation to consumption. This study provides a systematic review of technological pathways and policy implications for enhancing GEC markets through real-time electricity-carbon traceability, using China’s large-scale and rapidly evolving market as a central case. Through comparative international analysis and examination of China’s market data (2023–2025), we identified a severe oversupply of certificates and a reliance on policy-driven demand as core structural dilemmas. The aim of this study was to clarify how real-time traceability can fundamentally enhance the credibility, temporal precision, and policy applicability of GEC mechanisms, particularly under China’s rapid institutional reforms. The findings indicate that a fundamental transition towards hourly granularity in certificate issuance and matching is critical to enhance credibility, prevent double-counting, and enable high-value applications like 24/7 clean energy matching. Furthermore, deep integration between the GEC market and the carbon emission trading (CET) scheme is necessary to expand value propositions. We conclude that the synergistic integration of market design (mandatory quotas), cross-market coupling (GEC-carbon market linkage), and robust digital traceability represents the most effective pathway to transform GECs into a credible instrument for driving additional renewable energy consumption and supporting global carbon mitigation goals. Full article

(This article belongs to the Section F1: Electrical Power System)

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15 pages, 6063 KB

Open AccessArticle

Rubber-Induced Corrosion of Painted Automotive Steel: Inconspicuous Case of Galvanic Corrosion

by Kateryna Popova, Jan Švadlena and Tomáš Prošek

Corros. Mater. Degrad. 2026, 7(1), 2; https://doi.org/10.3390/cmd7010002 (registering DOI) - 23 Dec 2025

Abstract

Rubber components filled with carbon black are widely used in vehicles for sealing, preventing water ingress, and reducing vibration and aerodynamic noise. However, carbon particles increase the electrical conductivity of rubber. When a carbon-filled rubber part comes into contact with the metal car [...] Read more.

Rubber components filled with carbon black are widely used in vehicles for sealing, preventing water ingress, and reducing vibration and aerodynamic noise. However, carbon particles increase the electrical conductivity of rubber. When a carbon-filled rubber part comes into contact with the metal car body, it may act as a cathode, accelerating metal corrosion via galvanic coupling. This study combined volume resistivity and zero-resistance ammeter (ZRA) measurements, resistometric corrosion monitoring, and accelerated corrosion testing to assess the effect of rubber conductivity on the corrosion degradation of painted car body panels in defects. More conductive rubber induced a higher galvanic current and accelerated paint delamination from defects. Real-time monitoring confirmed an earlier onset of corrosion and higher corrosion rates for steel coupled with conductive rubber. These findings emphasize the importance of using low-conductive rubber with resistivity from 10⁴ Ω·m to minimize the risk of galvanic corrosion of the car body. Full article

(This article belongs to the Special Issue Atmospheric Corrosion, Surface Electrochemistry and Environmental Degradation of Materials: In Honor of Prof. Christofer Leygraf)

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28 pages, 1896 KB

Open AccessReview

SWAT Model and Drought Indices: A Systematic Review of Progress, Challenges and Opportunities

by Letícia Lopes Martins, Wander Araújo Martins, Maria Eduarda Cruz Ferreira, Jener Fernando Leite de Moraes, Édson Luis Bolfe and Gabriel Constantino Blain

Water 2026, 18(1), 41; https://doi.org/10.3390/w18010041 (registering DOI) - 23 Dec 2025

Abstract

Drought is a natural phenomenon that has significant environmental and socioeconomic impacts. Drought indices are fundamental tools for quantifying and monitoring this hazard. In regions where ground data are scarce, hydrological modeling offers an alternative for drought monitoring and developing early warning systems. [...] Read more.

Drought is a natural phenomenon that has significant environmental and socioeconomic impacts. Drought indices are fundamental tools for quantifying and monitoring this hazard. In regions where ground data are scarce, hydrological modeling offers an alternative for drought monitoring and developing early warning systems. This study conducted a systematic literature review, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, to analyze the integrated application of the SWAT (Soil and Water Assessment Tool) model and the use of drought indices. A total of 803 articles published between 2011 and 2025 were identified in the Scopus and Web of Science databases, of which 115 met the eligibility criteria and were included in the review. The analysis revealed significant advances in the use of SWAT for drought monitoring and prediction, including the development of indices and forecasting systems. However, notable gaps remain, particularly the limited use of advanced statistical methodologies (e.g., machine learning and non-stationarity analyses) and the lack of harmonization and standardization across indices. Overall, this review establishes SWAT as a robust tool to support drought management strategies, while highlighting substantial untapped potential. Future research addressing these gaps is essential to strengthen drought indices and improve operational warning systems. Full article

(This article belongs to the Section Hydrology)

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10 pages, 3832 KB

Open AccessArticle

Intertwined Electron–Electron Interactions and Disorder in the Metal–Insulator Phase Transition

by Martha Y. Suárez-Villagrán and Nikolaos Mitsakos

Appl. Sci. 2026, 16(1), 146; https://doi.org/10.3390/app16010146 (registering DOI) - 23 Dec 2025

Abstract

Quantum materials exhibit a rich dynamic of physical parameters, which, when combined, can lead to entirely different behaviors. These parameters constantly compete with each other, with the most influential parameters determining the state of the system. For example, in the case of metal–insulator [...] Read more.

Quantum materials exhibit a rich dynamic of physical parameters, which, when combined, can lead to entirely different behaviors. These parameters constantly compete with each other, with the most influential parameters determining the state of the system. For example, in the case of metal–insulator transitions, electron–electron interactions compete with the kinetic energy of the electrons and disorder. Understanding these complex dynamics is crucial for both fundamental physics and the development of novel technological applications, particularly given the role of disorder in tuning critical temperatures, a property with significant potential benefit in the fabrication of new devices where temperature requirements are still the bottleneck. In this article, properties of the Mott metal–insulator transition within disordered electron systems are explored using the disordered Hubbard model, the simplest Hamiltonian for capturing the metal–insulator transition. The model solutions are obtained using the self-consistent statistical dynamical mean-field theory (statDMFT). statDMFT incorporates local electronic correlation effects while allowing for Anderson localization due to disorder. Full article

(This article belongs to the Special Issue Quantum Phases and Metal–Insulator Transitions in Electron Systems)

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19 pages, 286 KB

Open AccessArticle

Republican Virtues: Merits and Morals in Polybius’ Constitutional Analysis of the Histories, Book 6

by Steele Brand

Histories 2026, 6(1), 1; https://doi.org/10.3390/histories6010001 (registering DOI) - 23 Dec 2025

Abstract

John Adams asserted that the historical summation of republican political thought can be found in one writer: Polybius of Megalopolis. More clearly than any other, Polybius articulated those qualities that define good statesmen and citizens and make republics strong and successful. This article [...] Read more.

John Adams asserted that the historical summation of republican political thought can be found in one writer: Polybius of Megalopolis. More clearly than any other, Polybius articulated those qualities that define good statesmen and citizens and make republics strong and successful. This article will examine this claim by bringing new historical analysis to Book 6 of Polybius’ Histories in order to identify the republican virtues important to Polybius. Polybius believed that Rome survived its early defeats in the Second Punic War and emerged triumphant over all of its enemies due to a unique combination of morals and merits that characterized good statesmen and strong republics. These extended deeper than political institutions and into the social fabric that bound the Roman people together and defined their relationships with one another, both in their homes as citizens and on campaign as soldiers. This article will work through Polybius’ analysis and show how Rome’s constitution used political institutions to suppress civic vices; armies in the field to cultivate civic service, sacrifice, and skill; military camps to shape public notions of duty, honor, and shame; and Roman families—as exemplified in public funerals—to habituate and showcase personal and civic virtues. Full article

13 pages, 4226 KB

Open AccessArticle

Multi-Center Validation of Artificial Intelligence-Based Video Analysis Platform for Automatic Evaluation of Swallowing Disorders

by Chang-Won Jeong, Dong-Wook Lim, Si-Hyeong Noh, Hee-Kyung Moon, Chul Park, Nayeon Ko and Min-Su Kim

Diagnostics 2026, 16(1), 45; https://doi.org/10.3390/diagnostics16010045 (registering DOI) - 23 Dec 2025

Abstract

Background: Videofluoroscopic swallow study (VFSS) is a key examination for assessing swallowing function. Although several artificial intelligence (AI) models for VFSS interpretation have shown high predictive accuracy through internal validations, AI models that have undergone external validation are rare. This study aims to [...] Read more.

Background: Videofluoroscopic swallow study (VFSS) is a key examination for assessing swallowing function. Although several artificial intelligence (AI) models for VFSS interpretation have shown high predictive accuracy through internal validations, AI models that have undergone external validation are rare. This study aims to develop an AI model that automatically diagnoses aspiration and penetration from VFSS videos and to evaluate the model’s performance through multicenter external validation. Methods: Among the 2343 VFSS videos collected, 309 cases of Q1-grade videos, which were free of artifacts and clearly showed the airway and vocal cords, were included in the internal validation dataset. The training, internal validation, and test datasets were divided in a 7:1:2 ratio, with 2012 images (aspiration = 532, penetration = 932, no airway invasion = 548) used for training. The AI model was developed and trained using You Only Look Once version 9, model c (YOLOv9_c). External validation of the AI model was conducted using 138 Q1 and Q2-grade VFSS videos from two different hospitals. Results: According to the internal validation, the YOLOv9_c model showed a training accuracy of 98.1%, a validation accuracy of 97.8%, and a test accuracy of 61.5%. From the confusion matrix analysis, the AI model’s diagnostic accuracy for aspiration in VFSS videos was 0.76 (AUC = 0.70), and for penetration, the diagnostic accuracy was 0.66 (AUC = 0.65). According to the external validation, the AI model demonstrated good performance in diagnosing aspiration (precision: 90.2%, AUC = 0.79) and penetration (precision: 78.3%, AUC = 0.80). The overall diagnostic accuracy of external validation for VFSS videos was 80.4%. Conclusions: We developed an AI model that automatically diagnoses aspiration and penetration when an entire VFSS video is input, and external validation showed good accuracy. In the future, to improve the performance of this AI model and facilitate its clinical application, research using training and validation with VFSS video data from more hospitals is needed. Full article

(This article belongs to the Special Issue Artificial Intelligence for Clinical Diagnostic Decision Making)

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17 pages, 4444 KB

Open AccessArticle

Study on the Interface Regulation Mechanism of Rejuvenators on Virgin and Aged Asphalt Based on Molecular Diffusion Theory

by Yanhai Yang, Zhili Chen, Xin Jin, Ye Yang and Chonghua Wang

Coatings 2026, 16(1), 17; https://doi.org/10.3390/coatings16010017 (registering DOI) - 23 Dec 2025

Abstract

To address the issue of inefficient interfacial diffusion between virgin asphalt and the aged asphalt in Reclaimed Asphalt Pavement (RAP), this study investigates how a rejuvenator improves the interfacial blending behavior and restores the functional properties of aged asphalt. Molecular dynamics (MD) simulations [...] Read more.

To address the issue of inefficient interfacial diffusion between virgin asphalt and the aged asphalt in Reclaimed Asphalt Pavement (RAP), this study investigates how a rejuvenator improves the interfacial blending behavior and restores the functional properties of aged asphalt. Molecular dynamics (MD) simulations were employed to construct aged asphalt–rejuvenator models with varying rejuvenator contents and to establish a bilayer dynamic model of the virgin-aged asphalt–rejuvenator diffusion system. The kinetic characteristics of the diffusion process were analyzed based on system density and relative concentration profiles, while the mean square displacement (MSD) and diffusion coefficients were calculated to elucidate the diffusion mechanism. The accuracy of the MD simulation results was validated using Fourier Transform Infrared Spectroscopy (FTIR) and Differential Scanning Calorimetry (DSC), and the regulatory mechanism of the rejuvenator on the interfacial diffusion between virgin and aged asphalt was revealed at the microscopic scale. The results demonstrated that the addition of the rejuvenator effectively promotes the blending and diffusion at the virgin-aged asphalt interface. Specifically, a 6% rejuvenator significantly improved the diffusion efficiency at elevated temperatures, optimized system density toward virgin asphalt properties, and achieved the most uniform molecular distribution, thereby facilitating balanced intermolecular interactions. Meanwhile, the regenerant effectively restored the aromatic fraction content, reduced polar functional groups such as sulfoxide, and significantly lowered the glass transition temperature (Tg), thereby enhancing the low-temperature crack resistance and overall mechanical performance of RAP. Full article

(This article belongs to the Special Issue Surface Treatments and Coatings for Asphalt and Concrete)

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43 pages, 7271 KB

Open AccessArticle

Effect of Olive Stone Biomass Ash Filler in Polylactic Acid Biocomposites on Accelerated Weathering Tests

by José Ángel Moya-Muriana, Francisco J. Navas-Martos, Sofía Jurado-Contreras, Emilia Bachino-Fagalde and M. Dolores La Rubia

Polymers 2026, 18(1), 30; https://doi.org/10.3390/polym18010030 (registering DOI) - 23 Dec 2025

Abstract

Polylactic acid (PLA) is a widely used bio-based polymer, although its application is limited by mechanical brittleness and low thermal resistance. PLA-based biocomposites reinforced with waste materials are gaining attention due to their sustainability, but their durability under degradation conditions remains a key [...] Read more.

Polylactic acid (PLA) is a widely used bio-based polymer, although its application is limited by mechanical brittleness and low thermal resistance. PLA-based biocomposites reinforced with waste materials are gaining attention due to their sustainability, but their durability under degradation conditions remains a key concern. In this work, PLA biocomposites containing 0, 1, and 3% wt. of Olive-stone Biomass Ash (OBA) were manufactured and characterized both (1) after manufacture and (2) after laboratory-accelerated weathering (including UV exposure, heat, and humidity). The results obtained were analyzed to evaluate the influence of ash incorporation on degradation resistance (measured through Carbonyl Indices, CI), mechanical properties (tensile strength), thermal (Thermogravimetric Analysis—Differential Scanning Calorimetry, TGA-DSC), structure (Fourier Transform Infrared Spectroscopy, FT-IR), morphology (Scanning Electron Microscopy, SEM) and appearance (colorimetry and gloss). Key quantitative findings include a 35% reduction in tensile strength for raw PLA after 1000 h weathering exacerbated to 48% and 50% with 1% and 3% OBA incorporation, respectively. Degradation indices showed increased hydroxyl formation, with HI values ranging from 0.38 to 2.80 for PLA, while for biocomposites HI rose up to 5.85 for PLA with 3% OBA. Subsequently, a solid-state reaction was model-fitted from experimental data obtained by means of TGA analysis for determining the kinetic triplet (pre-exponential factor, the activation energy, and the reaction mechanism). Finally, the Acceleration Factor (AF), which combines the effects of radiation, temperature, and humidity to predict long-term material performance, is addressed analytically. Full article

(This article belongs to the Special Issue From Biomass Fractionation to Final Biobased Polymer Nanocomposites in European Sustainable Biobased Nanomaterials Community (BIOMAC))

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