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23 pages, 7043 KB

Open AccessArticle

BiNeXt-SMSMVL: A Structure-Aware Multi-Scale Multi-View Learning Network for Robust Fundus Multi-Disease Classification

by Hongbiao Xie, Mingcheng Wang, Lin An, Yaqi Wang, Ruiquan Ge and Xiaojun Gong

Electronics 2025, 14(23), 4564; https://doi.org/10.3390/electronics14234564 (registering DOI) - 21 Nov 2025

Multiple ocular diseases frequently coexist in fundus images, while image quality is highly susceptible to imaging conditions and patient cooperation, often manifesting as blurring, underexposure, and indistinct lesion regions. These challenges significantly hinder robust multi-disease joint classification. To address this, we propose a [...] Read more.

Multiple ocular diseases frequently coexist in fundus images, while image quality is highly susceptible to imaging conditions and patient cooperation, often manifesting as blurring, underexposure, and indistinct lesion regions. These challenges significantly hinder robust multi-disease joint classification. To address this, we propose a novel framework, BiNeXt-SMSMVL (Bilateral ConvNeXt-based Structure-aware Multi-scale Multi-view Learning Network), that integrates structural medical biomarkers with deep semantic image features for robust multi-class fundus disease recognition. Specifically, we first employ automatic segmentation to extract the optic disc/cup and vascular structures, calculating medical biomarkers such as vertical/horizontal cup-to-disc ratio (CDR), vessel density, and fractal dimension as structural priors for classification. Simultaneously, a ConvNeXt-Tiny backbone extracts multi-scale visual features from raw fundus images, enhanced by SENet channel attention mechanisms to improve feature representation. Architecturally, the model performs independent predictions on left-eye, right-eye, and fused binocular images, leveraging multi-view ensembling to enhance decision stability. Structural priors and image features are then fused for joint classification modeling. Experiments on public datasets demonstrate that our model maintains stable performance under variable image quality and significant lesion heterogeneity, outperforming existing multi-label classification methods in key metrics including F1-score and AUC. Also, our approach exhibits strong robustness, interpretability, and clinical applicability. Full article

(This article belongs to the Section Artificial Intelligence)

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19 pages, 5528 KB

Open AccessArticle

Research on Ultrasonic Guided Wave Damage Detection in Internally Corroded Pipes with Curved Random Surfaces

by Ying Li, Qinying Liang and Fu He

Appl. Sci. 2025, 15(23), 12372; https://doi.org/10.3390/app152312372 (registering DOI) - 21 Nov 2025

Abstract

To accurately simulate the progression of pipeline corrosion, this paper proposes a three-dimensional corrosion modeling method for curved random surfaces based on spatial frequency composition. It applies this method to the inner surface of layered pipelines to emulate both the morphological characteristics and [...] Read more.

To accurately simulate the progression of pipeline corrosion, this paper proposes a three-dimensional corrosion modeling method for curved random surfaces based on spatial frequency composition. It applies this method to the inner surface of layered pipelines to emulate both the morphological characteristics and the evolution of internal corrosion. Combined with ultrasonic guided wave technology, the approach enables quantitative assessment of internal corrosion in layered pipelines. First, trigonometric series expansion and nonlinear polynomial superposition are used to characterize the roughness and curvature of the corroded surface, respectively, establishing a mathematical model capable of accurately representing complex corrosion morphologies. Next, a COMSOL–ABAQUS co-modeling approach is employed to build a finite element model of a three-layer composite pipeline consisting of a steel pipe, an insulating layer, and an anti-corrosion layer, with curved random-surface corrosion on the inner surface of the steel pipe. Finally, a wavelet packet decomposition algorithm is applied to extract features from the guided wave echo signals, creating a damage index matrix to correlate the corrosion area with the damage index quantitatively. The results show that the damage index increases steadily with the corrosion area, confirming the effectiveness of the proposed method. This study provides an alternative technical approach for high-fidelity modeling and precise assessment of pipeline corrosion detection. Full article

(This article belongs to the Section Applied Physics General)

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11 pages, 3270 KB

Open AccessCommunication

The Inhibitory Effect of Hafnium Oxide on Grain Growth in Yttrium Aluminum Garnet Composite Fiber

by Ke Gai, Qian Wang, Ketian Guan, Xiaohu Li, Weisen Liu, Yuan Li, Hongwei Zhao and Tong Zhao

Materials 2025, 18(23), 5272; https://doi.org/10.3390/ma18235272 (registering DOI) - 21 Nov 2025

Abstract

Yttrium aluminum garnet (YAG, Y₃Al₅O₁₂) fibers are promising materials for high-power lasers and high-temperature structural materials, and it is anticipated that the improvement in the stability of grain size would extend their service life at high temperatures. [...] Read more.

Yttrium aluminum garnet (YAG, Y₃Al₅O₁₂) fibers are promising materials for high-power lasers and high-temperature structural materials, and it is anticipated that the improvement in the stability of grain size would extend their service life at high temperatures. In this work, YAG-HfO₂ composite ceramic fibers were obtained by the solution blow spinning of YAG-HfO₂ composite precursor and sintering in steam. The effect of HfO₂ on the crystal phase transition and grain growth of YAG-HfO₂ fibers was further studied by in situ X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), and Transmission Electron Microscope (TEM). The results show that the HfO₂ addition increased the crystallization temperature of the YAG phase from 900 °C to 950 °C and reduced the crystal size at 1400 °C from 41.9 nm to 31.8 nm. The HfO₂ grains were distributed at the boundary of YAG grains, which enabled the fiber to maintain its dense structure and uniform grain size even at 1500 °C, exhibiting excellent high-temperature grain size stability of composite fibers. Full article

(This article belongs to the Special Issue Advances in High-Temperature Ceramics and Refractory Materials)

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18 pages, 1060 KB

Open AccessArticle

Expression Analysis of JCAD and IL-33 in Gingival Cancer Tumor Angiogenesis

by Tatsuya Shirai, Yasumasa Kakei, Yumi Muraki, Tatsuya Nagano, Ratoe Suraya, Kaito Uryu, Daisuke Takeda, Manabu Shigeoka, Akira Kimoto, Takumi Hasegawa, Tetsuya Hara, Noriaki Emoto and Masaya Akashi

Cancers 2025, 17(23), 3732; https://doi.org/10.3390/cancers17233732 (registering DOI) - 21 Nov 2025

Abstract

Background: Tumor angiogenesis is a key step in oral squamous cell carcinoma (OSCC) development. Here, we evaluated the expression patterns of junctional cadherin 5-associated (JCAD), a pathological angiogenesis protein, and interleukin-33 (IL-33) in OSCC to investigate their roles in pathological angiogenesis. Methods [...] Read more.

Background: Tumor angiogenesis is a key step in oral squamous cell carcinoma (OSCC) development. Here, we evaluated the expression patterns of junctional cadherin 5-associated (JCAD), a pathological angiogenesis protein, and interleukin-33 (IL-33) in OSCC to investigate their roles in pathological angiogenesis. Methods: Wound healing assays were performed to evaluate pathological angiogenesis in JCAD knockout (JCAD-KO) mice. In human mandibular gingival SCC and lymph nodes specimens, the numbers of blood vessels positive for CD34 (a vascular endothelial cell marker), CD105 (a well-established tumor angiogenesis marker), JCAD, and IL-33 were counted. We also evaluated the effects of tumor necrosis factor-α (TNF-α) stimulation as a pro-angiogenic factor on human umbilical vein endothelial cells (HUVECs) with JCAD knockdown. Results: In JCAD-KO mouse skin, wound healing and angiogenesis were significantly disturbed. In the clinical samples, the number of microvessels in which CD105 and JCAD were expressed but intranuclear IL-33 expression was lost significantly increased in the intratumoral area compared with the normal area. JCAD knockdown restored the TNF-α-induced loss of intranuclear IL-33 expression in HUVECs. Conclusions: Our combined assessment of JCAD and IL-33 supports the evaluation of tumor angiogenesis in OSCC. JCAD is a potential target for controlling tumor angiogenesis mediated by TNF-α. Full article

(This article belongs to the Special Issue The Biomarkers of Oral Cancer)

21 pages, 7882 KB

Open AccessArticle

Unlocking Refractory Gold: Synergistic Pretreatment Strategies for High-Efficiency Thiosulfate Leaching

by Sepideh Javanshir, Lena Sundqvist Öqvist, Ida Strandkvist and Fredrik Engström

Processes 2025, 13(12), 3760; https://doi.org/10.3390/pr13123760 (registering DOI) - 21 Nov 2025

Abstract

This study evaluates four physicochemical pretreatments—ultra-fine grinding, roasting, alkaline pressure oxidation (POX), and oxidative ammoniacal pre-leaching—for improving gold extraction from a refractory sulfide concentrate produced trough flotation. The gold extraction by direct cyanidation is only ~48.6%, mainly due to the encapsulation of gold [...] Read more.

This study evaluates four physicochemical pretreatments—ultra-fine grinding, roasting, alkaline pressure oxidation (POX), and oxidative ammoniacal pre-leaching—for improving gold extraction from a refractory sulfide concentrate produced trough flotation. The gold extraction by direct cyanidation is only ~48.6%, mainly due to the encapsulation of gold by associated minerals. Ultra-fine grinding increased the BET surface area eight-fold but depressed gold dissolution from 74% to 18% due to accelerated thiosulfate decomposition and copper (I) passivation in the presence of a bigger surface area. Oxidative roasting at 750 °C converted pyrite–pyrrhotite to hematite without liberating additional gold, indicating limited benefit from thermal treatment. POX was conducted at 190 °C and 10 bar O₂ dissolved 33% of the solids and yielded only 26% of gold in a thiosulfate leaching step with 50% of the thiosulfate consumption. In contrast, a two-step oxidative ammoniacal conditioning (0.4 M NH₃ + 10 mM Cu²⁺ for 42 h) followed by thiosulfate leaching boosted gold extraction from 71% to 85% while cutting thiosulfate consumption from 48.4 to 29.0 kg t⁻¹. The results demonstrate that among the pretreatments investigated, oxidative ammoniacal pre-leaching provides the most effective and environmentally benign route to unlock encapsulated gold and enhance reagent efficiency for thiosulfate processing of refractory gold ore. Full article

(This article belongs to the Section Chemical Processes and Systems)

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18 pages, 5266 KB

Open AccessArticle

Severity-Regularized Deep Support Vector Data Description with Application to Intrusion Detection in Cybersecurity

by Taha J. Alhindi

Mathematics 2025, 13(23), 3741; https://doi.org/10.3390/math13233741 (registering DOI) - 21 Nov 2025

Abstract

Anomalies in real systems differ widely in impact, as such, missing a high-severity event can be far costlier and consequential than flagging a benign outlier. This paper introduces Severity-Regularized Deep Support Vector Data Description, an extention of deep support vector data description that [...] Read more.

Anomalies in real systems differ widely in impact, as such, missing a high-severity event can be far costlier and consequential than flagging a benign outlier. This paper introduces Severity-Regularized Deep Support Vector Data Description, an extention of deep support vector data description that incorporates severity for various anomaly types, reflecting the application-specific importance assigned to each type. The formulation retains the well-known deep support vector data description decision geometry and scoring system while allowing for specific control over the balance between false alarm rate and the prioritization of detecting anomalies with greater impact. In the proposed loss function, we introduce regularizing parameters that control the importance assign to each anomaly type. Experiments are carried out on a demanding simulated dataset and a real-world intrusion detection case study utilizing the Australian Defence Force Academy Linux Dataset. The results demonstrate the effectiveness of the proposed approach in detecting highly severe anomalies while maintaining competitive overall performance. Full article

(This article belongs to the Special Issue Advances in Algorithm Design and Machine Learning)

17 pages, 2073 KB

Open AccessArticle

Polystyrene Micro- and Nanoplastic Exposure Triggers an Activation and Stress Response in Human Astrocytes

by Sonia Kiran, Uvindu Thilanka, Yu Xue and Qing-Xiang Amy Sang

Int. J. Mol. Sci. 2025, 26(23), 11273; https://doi.org/10.3390/ijms262311273 (registering DOI) - 21 Nov 2025

Abstract

Recent evidence indicates the presence of micro- and nanoplastics in the human brain, with higher accumulation observed in patients with dementia. However, their mechanistic effects on the human brain at the cellular level remain underexplored. Astrocytes play a crucial role in repairing neurons [...] Read more.

Recent evidence indicates the presence of micro- and nanoplastics in the human brain, with higher accumulation observed in patients with dementia. However, their mechanistic effects on the human brain at the cellular level remain underexplored. Astrocytes play a crucial role in repairing neurons following injury. The dysfunction of these cells can lead to chronic inflammation, a hallmark of neurodegenerative diseases. Here, we investigated the cytotoxic responses of primary human astrocytes exposed to polystyrene particles of two representative sizes, 25 nm and 1 µm, at concentrations of 1 µg/mL and 5 µg/mL for 48 h. Flow cytometry and confocal microscopy revealed the accumulation of particles of both sizes within the cytoplasm. Functional assays revealed reduced cell viability and elevated lactate dehydrogenase release, indicating cytotoxic effects following microplastic exposure. Gene expression analysis showed significant upregulation of MAPK14 and SOD2, indicating oxidative stress activation, and increased expression of pro-inflammatory mediators IL-6, TNF-α, and NF-κB1. In parallel, GLUT1 transcripts and GLUT1-positive cell populations were markedly reduced, suggesting impaired glucose metabolism. Collectively, these findings demonstrate that microplastics disrupt astrocytic homeostasis by inducing oxidative, inflammatory, and metabolic disturbances, leading to a reactive yet metabolically compromised phenotype. This study demonstrates the cellular damage caused by microplastics in astrocytes, which may contribute to a cellular mechanism linking environmental pollutant exposure to adverse effects on human health. Full article

(This article belongs to the Section Molecular Nanoscience)

34 pages, 6240 KB

Open AccessArticle

Impacts of Urban Morphology, Climate, and Occupant Behavior on Building Energy Consumption in a Cold Region: An Agent-Based Modeling Study of Energy-Saving Strategies

by Peng Cui, Ran Ji, Jiaqi Lu, Zixin Guo and Yewei Zheng

Sustainability 2025, 17(23), 10447; https://doi.org/10.3390/su172310447 (registering DOI) - 21 Nov 2025

Abstract

Urban morphology, climate, and occupant behavior significantly affect urban building energy consumption. This study analyzed 200 example blocks with 4754 buildings in Harbin, China, a representative city with a severe cold climate, to calculate urban morphology and climate factors. A questionnaire was conducted [...] Read more.

Urban morphology, climate, and occupant behavior significantly affect urban building energy consumption. This study analyzed 200 example blocks with 4754 buildings in Harbin, China, a representative city with a severe cold climate, to calculate urban morphology and climate factors. A questionnaire was conducted to quantify the data on the energy use behaviors of building occupants. Linear and nonlinear methods were used to explore correlations between these three types of factors and energy consumption. An agent-based modeling (ABM) approach was applied to establish a city-scale energy consumption simulation model, and simulations of energy-saving scenarios were carried out to derive optimization strategies. Key findings include: (1) the living area is the most significant determinant of daily energy use intensity (EUI), contributing 24.42%; (2) the floor area ratio (FAR) most influences annual electricity EUI (30.55%), while building height (BH) has the largest impact on heating EUI (32.62%); and (3) altering urban morphology and climatic factors by one unit can, respectively, reduce energy consumption by up to 13.0 and 224.7 kWh/m² annually. Increasing energy-saving awareness campaigns can reduce household EUI by 30.6127 kWh/m². This study provides strategic recommendations for urban energy-saving planning in cold regions. Full article

(This article belongs to the Special Issue Urban Green Infrastructure for Heat Mitigation and Social Equity: Global Perspectives and Challenges)

18 pages, 3708 KB

Open AccessArticle

Modeling of High-Sand-Ratio and Low-Connectivity Reservoirs Based on Self-Attention Single-Image Generative Adversarial Network

by Xi Luo, Junbang Liu, Shaohua Li, Xinyi Qiu, Changsheng Lu and Shaojun Wang

Appl. Sci. 2025, 15(23), 12363; https://doi.org/10.3390/app152312363 (registering DOI) - 21 Nov 2025

Abstract

High sand-ratio and low-connectivity reservoirs are commonly developed in deep-water depositional environments. Well-developed muddy interlayers reduce reservoir connectivity and form multiple discrete sandbody units, thereby offering good potential for layered development. However, due to limited research and insufficient data, modeling such complex reservoir [...] Read more.

High sand-ratio and low-connectivity reservoirs are commonly developed in deep-water depositional environments. Well-developed muddy interlayers reduce reservoir connectivity and form multiple discrete sandbody units, thereby offering good potential for layered development. However, due to limited research and insufficient data, modeling such complex reservoir structures remains challenging. The existing multiple-point statistics (MPS) method can utilize limited training images for geological modeling, but under high sand-ratio conditions, it often produces models with excessively high connectivity, failing to accurately represent reservoir characteristics. To address this issue, this study proposes a self-attention-enhanced single-image generative adversarial network (SA-SinGAN). Based on the original 2D SinGAN, the method was extended to 3D modeling by incorporating a self-attention mechanism and trained layer by layer to capture multi-scale geological features. Experimental results show that the FID score of SA-SinGAN is 143.75, compared with 175.61 for the MPS method. In terms of average connectivity error, MPS yields 0.42, which is significantly higher than 0.13 for SA-SinGAN, while the average NTG error is similar. SA-SinGAN can more accurately reproduce the low-connectivity characteristics of reservoirs while maintaining randomness, outperforming MPS in modeling performance. This demonstrates the applicability of SA-SinGAN for modeling complex reservoirs. Full article

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23 pages, 10522 KB

Open AccessArticle

The Impact of Composite Alkali Activator on the Mechanical Properties and Enhancement Mechanisms in Aeolian Sand Powder–Aeolian Sand Concrete

by Haijun Liu and Yaohong Wang

Buildings 2025, 15(23), 4213; https://doi.org/10.3390/buildings15234213 (registering DOI) - 21 Nov 2025

Abstract

Against the backdrop of China’s Western Development Strategy, numerous infrastructure projects are being constructed in desert regions. Utilizing local aeolian sand (AS) as a raw material for concrete production offers significant cost-saving potential but is hindered by challenges such as limited applicability and [...] Read more.

Against the backdrop of China’s Western Development Strategy, numerous infrastructure projects are being constructed in desert regions. Utilizing local aeolian sand (AS) as a raw material for concrete production offers significant cost-saving potential but is hindered by challenges such as limited applicability and inadequate mechanical strength of the resulting concrete. To address these limitations, aeolian sand was ground into aeolian sand powder (ASP) and subjected to treatment with single alkali activators (NaOH, Na₂SiO₃) and a composite alkali activator (NaOH + Na₂SiO₃). The treated and untreated ASP was then used to replace 50% of cement by mass for the preparation of aeolian sand powder–aeolian sand concrete (ASPC). Mechanical performance tests and advanced characterization techniques (SEM, TG-DSC, XRD, FTIR, nanoindentation, and NMR) were employed to investigate the effects of different activators on the mechanical properties of ASPC and elucidate the underlying enhancement mechanisms. The results demonstrated that the composite activator outperformed its single-activator counterparts: ASPC-4-6 (incorporating 4% NaOH and 6% Na₂SiO₃) exhibited 16.3–23.1% higher compressive strength and 12.1–17.6% higher splitting tensile strength across all curing ages compared to plain ASPC. Under the influence of OH⁻ from the composite activator, ASP showed more pronounced reductions in potassium feldspar, montmorillonite, and SiO₂ content, accompanied by the formation of C-S-H gel—replacing the amorphous, water-absorbent N-A-S-H generated by single activators. The presence of highly polymerized hydration products and more stable potassium A-type zeolites in ASPC-4-6 led to a reduction in macropore volume, optimization of pore structure, and refinement of the aggregate–mortar inter-facial transition zone. These micro-structural improvements collectively contributed to the significant enhancement of mechanical properties. This study provides novel insights into the large-scale and multi-dimensional utilization of aeolian sand in concrete. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

20 pages, 1446 KB

Open AccessArticle

Synergistic Stabilization of Horseradish Peroxidase by Green-Synthesized Silver-Decorated Magnetite Nanoparticles Nanoparticles: Toward Sustainable Enzyme Technology

by Laila S. Alqarni, Yaaser Q. Almulaiky, Elham N. Bifari and Reda M. El-Shishtawy

Catalysts 2025, 15(12), 1098; https://doi.org/10.3390/catal15121098 (registering DOI) - 21 Nov 2025

Abstract

In this study, silver-decorated magnetite nanoparticles (Ag@Fe₃O₄) were synthesized via a green method using Brachychiton populneus leaf extract and employed as an efficient support matrix for immobilization of horseradish peroxidase (HRP). The biosynthesized nanocomposite exhibited magnetic properties that facilitated [...] Read more.

In this study, silver-decorated magnetite nanoparticles (Ag@Fe₃O₄) were synthesized via a green method using Brachychiton populneus leaf extract and employed as an efficient support matrix for immobilization of horseradish peroxidase (HRP). The biosynthesized nanocomposite exhibited magnetic properties that facilitated easy separation and reuse, while the silver loading imparted enhanced stability and potential antimicrobial activity. Comprehensive physicochemical characterizations, including XRD, FTIR, FESEM, EDX, BET, and VSM, confirmed the successful formation of Ag@Fe₃O₄ and effective enzyme loading. The immobilization yield of HRP on Ag@Fe₃O₄ reached 93%, and the immobilized enzyme showed improved tolerance toward temperature and pH variations, with an optimal pH of 7.5 and optimal temperature of 60 °C, compared to 7.0 and 50 °C for the free enzyme. Kinetic studies revealed a moderate increase in Km but maintained or slightly increased Vmax, indicating preserved catalytic efficiency. The immobilized enzyme demonstrated excellent reusability over 15 cycles (66% residual activity) and long-term storage stability (81% activity after 60 days at 4 °C). These enhancements are attributed to the protective microenvironment provided by the Ag@Fe₃O₄ matrix, which mitigates denaturation and leaching. This work highlights the potential of Ag@Fe₃O₄ as a sustainable and reusable platform for enzyme immobilization in biocatalytic applications, particularly in environmental remediation and industrial bioprocessing. Full article

(This article belongs to the Special Issue Green Chemistry and Catalysis, 2nd Edition)

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Graphical abstract

14 pages, 271 KB

Open AccessArticle

Breaking Down the Walls in Agnès Varda’s Mur Murs (1981) and Visages Villages (2016)

by Natalie Muñoz

Humanities 2025, 14(12), 227; https://doi.org/10.3390/h14120227 (registering DOI) - 21 Nov 2025

Abstract

What do images ask of the future, and what promises do we owe them? Reading Agnès Varda’s Mur Murs and Visages Villages with Derrida’s archive and de Certeau’s city-writing in mind, I treat Varda’s walls as contested palimpsests. Film overwrites and counter-inscribes surfaces, [...] Read more.

What do images ask of the future, and what promises do we owe them? Reading Agnès Varda’s Mur Murs and Visages Villages with Derrida’s archive and de Certeau’s city-writing in mind, I treat Varda’s walls as contested palimpsests. Film overwrites and counter-inscribes surfaces, yet it keeps undertexts legible. I set aside Michael Cramer’s divide between community murals and externally authored photomurals; rather than framing them as opposed projects, the films share one practice: collective inscription, archival method, shifting temporal sense. In Mur Murs, Varda’s camera lets living people eclipse their monumental doubles and turns trompe-l’œil and hushed voices into layers of the palimpsest that refuse closure. In Visages Villages, the larger-than-life portrait of the last remaining inhabitant of a former mining town and the colossal figures of dockworkers’ wives recenter overlooked lives while keeping their impermanence in view. Across both films, cinema becomes the archivable surface: framing, montage, and projection “write” the wall, preserving disappearance even as each screening adds a new layer. Varda practices a careful ethics of remembering that remains future-facing, aware of institutions, and shaped by reality, yet always keeping the walls of stucco, metal, glass, and rock open to re-reading and re-inscription. Full article

21 pages, 2417 KB

Open AccessArticle

Microstructure and Tribological Properties of Fe₄₀Mn₁₉Cr₂₀Ni₂₀Mo₁ High-Entropy Alloy Composite-Infiltrated by Aluminum–Nitrogen

by Zelin Huang, Xiangrong Zhang, Huijun Yang, Xi Jin, Min Zhang and Junwei Qiao

Lubricants 2025, 13(12), 509; https://doi.org/10.3390/lubricants13120509 (registering DOI) - 21 Nov 2025

Abstract

In the manufacturing sector, energy loss often stems mainly from wear. By improving the surface characteristics of alloys, we can substantially cut down on this kind of loss, which in turn boosts the efficiency of energy use. In this study, Fe₄₀Mn [...] Read more.

In the manufacturing sector, energy loss often stems mainly from wear. By improving the surface characteristics of alloys, we can substantially cut down on this kind of loss, which in turn boosts the efficiency of energy use. In this study, Fe₄₀Mn₁₉Cr₂₀Ni₂₀Mo₁ high-entropy alloy (HEA) with a face-centered cubic (FCC) structure was subjected to aluminum–nitrogen co-infiltration treatment via pack aluminizing and plasma nitriding, forming an aluminum–nitrogen co-infiltrated layer with a thickness of approximately 17 μm. An analysis was carried out on the microstructure, growth dynamics, and tribological behavior of the Al-N co-infiltrated layer across a broad temperature spectrum. The results showed that the surface hardness of the samples treated by aluminizing and Al-N co-infiltration reached 592 HV and 993 HV, respectively, which were significantly higher than that of the hot-rolled alloy (178 HV). The Al-N co-infiltrated HEA exhibited a low and stable friction coefficient as well as wear rate over a wide temperature range (20–500 °C), which was attributed to the formation of the Al-N co-infiltrated layer composed of AlN, CrN, and FeN phases. This study demonstrates that Al-N co-infiltration treatment is an effective surface modification technique, which can significantly enhance the hardness and tribological properties of high-entropy alloys over a wide temperature range. Full article

(This article belongs to the Special Issue Mechanical Properties and Wear Resistance of Multi-Component Alloys and Composites)

15 pages, 2058 KB

Open AccessArticle

Mycorrhizal Abundance and Its Interaction with Cereal Root Traits and Crop Productivity in Organically Managed Cereal/Legume Intercropping

by Agnė Veršulienė, Andrius Garbaras, Gražina Kadžienė, Arman Shamshitov and Monika Toleikienė

Plants 2025, 14(23), 3561; https://doi.org/10.3390/plants14233561 (registering DOI) - 21 Nov 2025

Abstract

Mixed cropping may positively affect soil fertility and soil biological activities, such as those related to mycorrhizal colonization intensity (M%), which plays a vital role in the plant nutrient cycle and can improve tolerance to drought and pathogens. This plant and soil fungi [...] Read more.

Mixed cropping may positively affect soil fertility and soil biological activities, such as those related to mycorrhizal colonization intensity (M%), which plays a vital role in the plant nutrient cycle and can improve tolerance to drought and pathogens. This plant and soil fungi symbiosis helps to reduce dependency on chemical fertilizers, promotes sustainable agricultural practices, and minimizes environmental impacts. However, field studies that clearly assess the effects of cereal/legume intercropping on mycorrhizal intensity and relate it to plant productivity, yield quality, and plant adaptation to climate change are lacking. This field experiment was conducted to assess the effects of cereals/legume intercropping on mycorrhizal colonization, and to explore its interaction with physical cereal root parameters and crop yield. Three main crops, spring barley, oat, and field pea, were grown as monocultures. For the spring barley and oat, the study also included two different fertilization levels (with and without organic fertilizers) and legume intercropping (field pea and red clover). The intercropping had a significant impact on spring barley and oat root length, diameter, and specific root length. The general average of root length and diameter was higher in oat–pea and barley–pea cropping systems. The most significant effect in root architecture parameters observed in red clover was when it was intercropped with barley or oat. The establishment of field pea intercrop significantly increased M% in spring barley and had a positive effect on the grain yields of both spring barley and oat. Meanwhile, red clover intercropping enhanced M% and grain yield in oats but had no such effect in barley. In both spring barley and oat, M% was positively correlated with grain yield. Full article

(This article belongs to the Collection Selected Papers from Lithuanian Research Centre for Agriculture and Forestry)

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23 pages, 1660 KB

Open AccessSystematic Review

Temporal and Contextual Variations in Job Satisfaction Between Physicians and Nurses: A Systematic Review and Meta-Analysis

by Nazerke Narymbayeva, Maksut Kamaliev, Konrad Tomasz Juszkiewicz, Kuralay Kanafyanova, Sholpan Aliyeva, Nadira Aitambayeva, Laila Nazarova, Sharapat Moiynbayeva, Akylbek Saktapov and Shnara Svetlanova

Healthcare 2025, 13(23), 3008; https://doi.org/10.3390/healthcare13233008 (registering DOI) - 21 Nov 2025

Abstract

Objectives: This systematic review and meta-analysis evaluated differences in job satisfaction scores between nurses and physicians, examining variation by (a) care setting (hospital, emergency department, outpatient, mixed), and (b) time period (pre-COVID, during COVID, post-COVID). Methods: We systematically searched PubMed, Scopus, [...] Read more.

Objectives: This systematic review and meta-analysis evaluated differences in job satisfaction scores between nurses and physicians, examining variation by (a) care setting (hospital, emergency department, outpatient, mixed), and (b) time period (pre-COVID, during COVID, post-COVID). Methods: We systematically searched PubMed, Scopus, ScienceDirect, Web of Science, and CINAHL for studies published between January 2020 and July 2025. Eligible studies reported mean and standard deviation values for job satisfaction among physicians and nurses in healthcare settings across the specified timeframes. Studies were excluded if they assessed other types of satisfaction or combined data across COVID periods. Pooled standardized mean difference (SMD) was calculated using random-effects models in R. Results: Before COVID-19, the SMD was −2.40 (95% CI −8.05 to 3.26; I² = 98%). During the pandemic, the estimate was 1.39 (95% CI −0.57 to 3.35; I² = 91.5%), and post-pandemic, it remained small (SMD = 0.29; 95% CI −1.63 to 2.22; I² = 95.8%). Emergency care during COVID showed a significant advantage for physicians (SMD = 0.29; 95% CI 0.05 to 0.52; I² = 0%). Post-COVID, mixed settings slightly favored physicians (SMD = 0.06), while primary care favored nurses (SMD = −0.30); subgroup differences were significant. Conclusions: The findings reveal that job satisfaction is not solely determined by professional role but is significantly influenced by temporal and contextual factors. Job satisfaction is shaped more by temporal and contextual factors than by professional role. While no consistent differences were observed pre-pandemic, emergency care favored physicians during COVID, and post-pandemic trends showed modest advantages for nurses in primary care and physicians in mixed settings. Due to the methodological limitations of this meta-analysis, including high heterogeneity, reliance on cross-sectional data, and very low/low certainty of evidence, these results should be interpreted with caution. Full article

(This article belongs to the Special Issue Innovating Care in the Post-Pandemic Era: Models, Leadership, and Technologies for the Future of Nursing)

14 pages, 1661 KB

Open AccessArticle

Scrutinizing Dark-Matter Scenarios with B → (K,

K^{*}

)

\bar{ν}

ν Decays

by Alexander Berezhnoy, Wolfgang Lucha and Dmitri Melikhov

Universe 2025, 11(12), 385; https://doi.org/10.3390/universe11120385 (registering DOI) - 21 Nov 2025

Abstract

Conceivable explanations of Belle-II measurements of a (surprising) excess of missing energy decays of the B meson to the K meson not covered by standard model neutrino–antineutrino pairs might be offered by additional contributions of dark matter fermion–antifermion pairs. Assuming the excessive missing-energy [...] Read more.

Conceivable explanations of Belle-II measurements of a (surprising) excess of missing energy decays of the B meson to the K meson not covered by standard model neutrino–antineutrino pairs might be offered by additional contributions of dark matter fermion–antifermion pairs. Assuming the excessive missing-energy events to be mediated by a (generic) scalar or vector boson, a simultaneous inspection of both the missing energy B decays into a pseudoscalar K meson or a vector

K^{*}

meson enables to gain information on the nature of any boson relating the standard-model and dark-matter sectors, irrespective of (unknown) dark-sector details. Upon availability of indispensable experimental data, most prominent among such insights might be the identification of the mediator spin from the differential B-meson decay widths. Full article

(This article belongs to the Section High Energy Nuclear and Particle Physics)

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23 pages, 5668 KB

Open AccessArticle

Life Cycle Sustainable Design Optimization of Building Structural Components: A Hybrid Approach Incorporating Genetic Algorithm and Machine Learning

by Xiaocun Zhang and Jingfeng Zhang

Sustainability 2025, 17(23), 10449; https://doi.org/10.3390/su172310449 (registering DOI) - 21 Nov 2025

Abstract

Optimization design is an effective strategy for reducing carbon emissions in building structures. Various exhaustive and metaheuristic methods have been proposed to optimize the carbon emissions of structural components, which has primarily focused on sustainable design during the construction phase. This study proposes [...] Read more.

Optimization design is an effective strategy for reducing carbon emissions in building structures. Various exhaustive and metaheuristic methods have been proposed to optimize the carbon emissions of structural components, which has primarily focused on sustainable design during the construction phase. This study proposes a hybrid approach for the life cycle sustainable design of reinforced concrete components, encompassing the material production, construction, carbonization, and end-of-life phases. The resistance of structural components was evaluated through time-dependent reliability indices, and surrogate models were developed using machine learning techniques. The surrogate models were subsequently integrated into a dual-objective genetic algorithm for life cycle sustainable design. Based on the proposed approach, numerical examples including a singly reinforced beam and a biaxially eccentric compressed column were analyzed. The minimum carbon emissions were optimized to 486.2 kg CO_2e and 307.8 kg CO_2e, respectively, representing a reduction of more than 10% compared to the original design. Moreover, parametric and comparative analyses were conducted to identify the key factors influencing life cycle sustainable design. The findings underlined the impact of design methods, system boundaries, and specific design variables such as material strengths and concrete cover depth. Overall, this study enhances the efficiency and applicability of sustainable design for structural components while considering life cycle impacts. Full article

(This article belongs to the Section Green Building)

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23 pages, 606 KB

Open AccessArticle

Psychosocial Resources and Emotional Support Needs in Women with Vulvodynia: A Lifespan Developmental and Biopsychosocial Perspective

by Valentina Lucia La Rosa and Elena Commodari

Behav. Sci. 2025, 15(12), 1600; https://doi.org/10.3390/bs15121600 (registering DOI) - 21 Nov 2025

Abstract

Vulvodynia is a chronic vulvar pain condition that can interfere with women’s developmental processes and overall well-being. Adopting a broader perspective of women’s health informed by lifespan developmental and biopsychosocial frameworks, this study examined psychosocial factors related to the psychological well-being of Italian [...] Read more.

Vulvodynia is a chronic vulvar pain condition that can interfere with women’s developmental processes and overall well-being. Adopting a broader perspective of women’s health informed by lifespan developmental and biopsychosocial frameworks, this study examined psychosocial factors related to the psychological well-being of Italian women with vulvodynia. Between December 2023 and December 2024, a total of 533 women diagnosed with vulvodynia completed an online survey. The survey included questions about sociodemographics and the illness, as well as validated measures of dyadic adjustment, social support, self-efficacy, perceived stress, and psychological well-being. Descriptive statistics, group comparisons, Pearson correlations, and hierarchical multiple regressions were performed. Nearly two-thirds of the women reported symptoms lasting over five years, and 44% experienced severe pain. Those with more intense pain, longer symptom duration, or delayed diagnosis reported lower well-being and higher stress. Satisfaction with treatment was linked to greater well-being. Psychological well-being was strongly correlated with social support, dyadic adjustment, and psychological resources. Regression analyses identified younger age, higher pain intensity, lower treatment satisfaction, reduced social support, lower self-efficacy, and greater stress as predictors of poorer psychological well-being. Vulvodynia should be considered a psychosocial and developmental challenge as well as a medical condition. These findings underscore the importance of viewing vulvodynia as not only a medical condition, but also a psychosocial and developmental challenge within women’s broader health trajectories, highlighting the need for interventions that address pain and provide structured emotional support to strengthen psychological and relational resources. Full article

(This article belongs to the Special Issue Providing Emotional Support for People with Chronic Diseases)

27 pages, 2768 KB

Open AccessArticle

Psychophysiological and Neurobiological Responses to Deception and Emotional Stimuli: A Pilot Study on the Interplay of Personality Traits and Perceived Stress

by Andrei Teodor Bratu, Gabriela Carmen Calniceanu, Florin Zamfirache, Gabriela Narcisa Prundaru, Cristina Dumitru and Beatrice Mihaela Radu

Brain Sci. 2025, 15(12), 1252; https://doi.org/10.3390/brainsci15121252 (registering DOI) - 21 Nov 2025

Abstract

Background/Objectives: Deception engages both emotional and cognitive processes, yet individual variability in these responses remains insufficiently understood. This study aimed to investigate how personality traits, perceived stress, and empathic distress shape psychophysiological and neurobiological responses during deception and emotional processing. Methods: Thirty [...] Read more.

Background/Objectives: Deception engages both emotional and cognitive processes, yet individual variability in these responses remains insufficiently understood. This study aimed to investigate how personality traits, perceived stress, and empathic distress shape psychophysiological and neurobiological responses during deception and emotional processing. Methods: Thirty healthy young adults completed a protocol combining a deception task with emotional stimulus exposure, while heart rate (HR), heart rate variability (HRV), and electroencephalographic (EEG) activity were continuously recorded. Participants were characterized using measures of Dark Triad traits, perceived stress (PSS-10), and empathic distress. Results: The results showed increased HR and reduced HRV during deceptive responses, reflecting heightened cognitive effort and autonomic arousal. In contrast, morally or socially evaluative stimuli were associated with right-frontal EEG asymmetry, suggesting engagement of emotional regulation processes. Cluster analysis revealed distinct reactivity profiles: individuals with high stress and empathic distress exhibited amplified autonomic activation and reduced cortical inhibition, whereas those with higher Machiavellianism and psychopathy displayed attenuated HR/HRV modulation and stable EEG patterns, suggestive of emotional detachment and adaptive inhibition. These findings suggest that deception is a dynamic, context-dependent process influenced by individual personality traits and stress-regulation capacities. Conclusions: The study offers valuable insights into the psychophysiological mechanisms underlying deceptive behavior, with meaningful implications for both forensic and affective neuroscience. Full article

(This article belongs to the Special Issue Advances in Emotion Processing and Cognitive Neuropsychology)

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24 pages, 1176 KB

Open AccessArticle

Field Testing of ADAS Technologies in Naturalistic Driving Conditions

by Adam Skokan

Vehicles 2025, 7(4), 135; https://doi.org/10.3390/vehicles7040135 (registering DOI) - 21 Nov 2025

Abstract

This paper evaluates Advanced Driver Assistance Systems (ADASs) in test scenarios derived from naturalistic driving and crash data, mapped to ISO 26262, ISO/PAS 21448 (SOTIF), and ISO 34502. From eight high-risk scenarios, it is validated for left turns across oncoming traffic on a [...] Read more.

This paper evaluates Advanced Driver Assistance Systems (ADASs) in test scenarios derived from naturalistic driving and crash data, mapped to ISO 26262, ISO/PAS 21448 (SOTIF), and ISO 34502. From eight high-risk scenarios, it is validated for left turns across oncoming traffic on a proving ground using a Škoda Superb iV against a soft Global Vehicle Target. ODD and spatiotemporal thresholds are parameterized and speed/acceleration profiles from GNSS/IMU data are analyzed. AEB and FCW performance varies across nominally identical runs, driven by human-in-the-loop variability and target detectability. In successful interventions, peak deceleration reached −0.64 g, meeting UNECE R152 criteria; in other runs, late detection narrowed TTC below intervention thresholds, leading to contact. Limitations in current protocols are identified and argue for scenario catalogs with realistic context (weather, surface, masking) and latency-aware metrics. The results motivate extending validation beyond standard tracks toward mixed methods linking simulation, scenario databases, and instrumented field trials. Full article

31 pages, 4352 KB

Open AccessArticle

Comparative Performance Evaluation of Wind Energy Systems Using Doubly Fed Induction Generator and Permanent Magnet Synchronous Generator

by Areeg Ebrahiem Elngar, Asmaa Sobhy Sabik, Ahmed Hassan Adel and Adel S. Nada

Wind 2025, 5(4), 31; https://doi.org/10.3390/wind5040031 (registering DOI) - 21 Nov 2025

Abstract

Wind energy has become a cornerstone of sustainable electricity generation, yet the reliable integration of wind energy conversion systems (WECSs) into modern grids remains challenged by dynamic variations in wind speed and stringent fault ride-through (FRT) requirements. Among the available technologies, the Doubly [...] Read more.

Wind energy has become a cornerstone of sustainable electricity generation, yet the reliable integration of wind energy conversion systems (WECSs) into modern grids remains challenged by dynamic variations in wind speed and stringent fault ride-through (FRT) requirements. Among the available technologies, the Doubly Fed Induction Generator (DFIG) and the Permanent Magnet Synchronous Generator (PMSG) dominate commercial applications; however, a comprehensive comparative assessment under diverse grid and fault scenarios is still limited. This study addresses this gap by systematically evaluating the performance of DFIG- and PMSG-based WECSs across three operating stages: (i) normal operation at constant speed, (ii) variable wind speed operation, and (iii) grid fault conditions including single-line-to-ground, line-to-line, and three-phase faults. To enhance fault resilience, a DC-link Braking Chopper is integrated into both systems, ensuring a fair evaluation of transient stability and compliance with low-voltage ride-through (LVRT) requirements. The analysis, performed using MATLAB/Simulink, focuses on active and reactive power, rotor speed, pitch angle, and DC-link voltage dynamics. The results reveal that PMSG exhibits smoother transient responses and lower overshoot compared to DFIG. Under fault conditions, the DC-link Braking Chopper effectively suppresses voltage spikes in both systems, with DFIG achieving faster reactive power recovery in line with grid code requirements, while PMSG ensures more stable rotor dynamics with lower oscillations. The findings highlight the complementary strengths of both technologies and provide useful insights for selecting appropriate WECS configurations to improve grid integration and fault ride-through capability. Full article

(This article belongs to the Topic Wind Energy in Multi Energy Systems)

42 pages, 5911 KB

Open AccessArticle

Analysing Disease Spread on Complex Networks Using Forman–Ricci Curvature

by Oladimeji Samuel Sowole, Nicola Luigi Bragazzi and Geminpeter A. Lyakurwa

Mathematics 2025, 13(23), 3742; https://doi.org/10.3390/math13233742 (registering DOI) - 21 Nov 2025

Abstract

Infectious-disease dynamics depend on heterogeneous contact structure, which classical homogeneous-mixing models such as SIR/SEIR cannot capture. We develop a curvature-informed network SIR framework that embeds Forman–Ricci curvature (FRC), a discrete topological descriptor of fragility and robustness, into per-edge transmission. We compute FRC on [...] Read more.

Infectious-disease dynamics depend on heterogeneous contact structure, which classical homogeneous-mixing models such as SIR/SEIR cannot capture. We develop a curvature-informed network SIR framework that embeds Forman–Ricci curvature (FRC), a discrete topological descriptor of fragility and robustness, into per-edge transmission. We compute FRC on undirected and directed Erdős–Rényi, Watts–Strogatz, Barabási–Albert, and Power–Law Cluster networks, and relate curvature to degree, clustering, and betweenness to identify structurally influential nodes and bridge edges. Using curvature-adjusted transmission, we simulate epidemics across topologies and infection rates, then validate predictively with a controlled “hidden-truth” benchmark: posterior-calibrated FRC models are compared with advanced centrality-weighted baselines (EdgeBetweenness, Degree, Eigenvector) under identical fit/holdout splits. On heterogeneous graphs (Barabási–Albert/Power–Law Cluster), FRC improves holdout Root Mean Squared Error (RMSE), peak-time accuracy, and final-size proximity. A compact sensitivity analysis over baseline transmission and clustering, with Partial Rank Correlation Coefficient (PRCC), shows these gains are robust across parameter regimes. Intervention ablations (cases averted vs. budget) further show that vaccinating high-curvature nodes and protecting extreme negative-curvature bridges can outperform EdgeBetweenness targeting at practical budgets. Directed networks exhibit sharper peaks and faster resolution, with strongly negative out-curvature marking putative exporters. In general, FRC provides a principled geometric signal that enhances network epidemic models and yields concrete, topology-aware guidance for targeted vaccination and community-bridge control. Full article

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14 pages, 264 KB

Open AccessArticle

Vaccine Hesitancy Toward Dengue Immunization Among Indonesian Office Workers: A Cross-Sectional Study of Perceptions, Barriers, and Trust Factors

by Theresia Santi, Ridwansyah Ridwansyah, Veli Sungono, Natalia Widjaya, Keinata Nabila Euqenekim, Cessya Prianyanta, Sri Rezeki S. Hadinegoro, Budi Setiabudiawan and Juandy Jo

Vaccines 2025, 13(12), 1178; https://doi.org/10.3390/vaccines13121178 (registering DOI) - 21 Nov 2025

Abstract

Background/Objectives: In the absence of specific antiviral therapy for dengue viral infection, vaccination remains the most effective preventive measure. Two dengue vaccines have been licensed in Indonesia; however, concerns regarding vaccine hesitancy persist. This study aimed to assess dengue vaccine hesitancy among Indonesian [...] Read more.

Background/Objectives: In the absence of specific antiviral therapy for dengue viral infection, vaccination remains the most effective preventive measure. Two dengue vaccines have been licensed in Indonesia; however, concerns regarding vaccine hesitancy persist. This study aimed to assess dengue vaccine hesitancy among Indonesian office workers, comprising healthcare and non-healthcare workers. Methods: A cross-sectional study with an online survey was conducted between February 1 and April 30, 2025. Eligible participants were adults (≥18 years) employed in office-based settings, including healthcare facilities. Questionnaires were disseminated through company management teams and included 37 items on demographic characteristics, vaccination intentions, and underlying motivations. Data were analyzed to identify determinants of vaccine hesitancy. Results: A total of 377 respondents participated, the majority of whom were from West Java (335; 88.9%). One-third of respondents reported uncertainty regarding dengue vaccination (33.4% “not sure”), which was paralleled by hesitancy to pay for vaccination (43.2% “not sure”). Multivariable logistic regression analysis identified five significant determinants of vaccine hesitancy, with willingness-to-pay emerging as the strongest factor (β coefficient = 2.024; OR = 7.57; 95% CI = 4.06–14.10; p-value < 0.01). Conclusions: Approximately one-third of the surveyed Indonesian office workers exhibited hesitancy toward dengue vaccination. Willingness-to-pay was the most influential determinant of vaccine acceptance. Targeted strategies to address financial concerns and improve confidence in dengue vaccination are essential for strengthening workforce protection and national preparedness against dengue outbreaks. Full article

(This article belongs to the Special Issue Global Immunization Inequities-Challenges and Solutions)

17 pages, 1996 KB

Open AccessArticle

AdhesionScore: A Prognostic Predictor of Breast Cancer Patients Based on a Cell Adhesion-Associated Gene Signature

by Catarina Esquível, Rogério Ribeiro, Ana Sofia Ribeiro, Pedro G. Ferreira and Joana Paredes

Cancers 2025, 17(23), 3731; https://doi.org/10.3390/cancers17233731 (registering DOI) - 21 Nov 2025

Abstract

Background: Aberrant or loss of cell adhesion drives invasion and metastasis, key hallmarks of cancer progression. In this work, we hypothesized that a gene signature related to cell adhesion could predict breast cancer prognosis. Methods: Highly variant genes were tested for association with [...] Read more.

Background: Aberrant or loss of cell adhesion drives invasion and metastasis, key hallmarks of cancer progression. In this work, we hypothesized that a gene signature related to cell adhesion could predict breast cancer prognosis. Methods: Highly variant genes were tested for association with overall survival using Cox regression. Adhesion-related genes were identified through gene ontology analysis and multivariate Cox regression, with AIC selection, defined the prognostic signature. The AdhesionScore was then calculated as a weighted sum of gene expression, with risk stratification assessed by Kaplan–Meier and log-rank tests. Results: We found that the AdhesionScore was a significant independent predictor of poor survival in three large independent datasets, as it provided a robust stratification of patient prognosis in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (HR: 2.65; 95% CI: 2.33–3.0, p = 2.34 × 10⁻⁵¹), The Cancer Genome Atlas (TCGA) (HR: 3.46; 95% CI: 2.35–5.09, p = 3.50 × 10⁻¹⁰), and the GSE96058 (HR: 2.83; 95% CI: 2.20–3.65, p = 6.29 × 10⁻¹⁶) datasets. The 5-year risk of death in the high-risk group was 32.41% for METABRIC, 27.8% for TCGA, and 17.54% for GSE96058 datasets. Consistently, HER2-enriched and triple-negative breast carcinomas (TNBC) cases showed higher AdhesionScores than luminal subtypes, indicating an association with aggressive tumor biology. Conclusions: We have developed, for the first time, a molecular signature based on cell adhesion, as well as an associated AdhesionScore that can predict patient prognosis in invasive breast cancer, with potential clinical application. We developed a novel adhesion-based molecular signature, the AdhesionScore, that robustly predicts prognosis in breast cancer across independent cohorts, highlighting its potential clinical utility for patient risk stratification. Full article

(This article belongs to the Special Issue Molecular Signatures of Therapy: Biomarkers Predicting Response and Relapse in Cancer)

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26 pages, 1215 KB

Open AccessArticle

The Impact of Digital–Real Economy Integration on Green Development Efficiency: Evidence from China’s Yangtze River Delta Urban Agglomeration

by Pengcheng Yin and Haolan Liao

Sustainability 2025, 17(23), 10448; https://doi.org/10.3390/su172310448 (registering DOI) - 21 Nov 2025

Abstract

Enhancing green development efficiency (GDE) is of great significance in achieving regional green transition. Against the backdrop of rapid advancements in digital technology, digital–real economy integration (DRI) opens a new avenue for enhancing GDE. This research develops a theoretical analytical framework to analyze [...] Read more.

Enhancing green development efficiency (GDE) is of great significance in achieving regional green transition. Against the backdrop of rapid advancements in digital technology, digital–real economy integration (DRI) opens a new avenue for enhancing GDE. This research develops a theoretical analytical framework to analyze the influence of DRI on GDE. It employs panel data from 41 cities in China’s Yangtze River Delta urban agglomeration (YRDUA) spanning from 2011 to 2023 to develop a series of econometric models that empirically examine the impact of DRI on GDE and its underlying mechanisms. Research has demonstrated that the degree of DRI varies by region across the YRDUA, with a pattern of decreasing from east to west. Empirical results confirm that DRI development significantly boosts GDE in the YRDUA. Mechanism tests reveal that DRI indirectly enhances GDE through industrial structure optimization, green technological progress, and resource allocation efficiency. Moderation effects indicate that industrial collaborative agglomeration (ICA) significantly amplifies DRI’s positive impact on GDE. Further analysis indicates that the positive impact of DRI on GDE is only significant in low-carbon pilot cities and non-resource-based cities. Moreover, ICA exhibits a single-threshold effect: when regional ICA exceeds 2.0048, DRI’s impact on GDE demonstrates diminishing marginal returns. These findings not only give a realistic roadmap for accomplishing regional green transformation but also offer empirical evidence for policymakers to make scientific policies, adapt to local conditions, and appropriately promote ICA. This approach fully leverages the benefits of DRI, thereby advancing the economy toward sustainable development. Full article

21 pages, 538 KB

Open AccessArticle

Students’ Use and Perception of Educational GenAI Chatbot in High School Computing: Insights from the Decomposed Theory of Planned Behavior

by Ean Teng Khor, Leta Chan and Peter Seow

Educ. Sci. 2025, 15(12), 1569; https://doi.org/10.3390/educsci15121569 (registering DOI) - 21 Nov 2025

Abstract

Generative Artificial Intelligence (GenAI) has gained mass popularity in education due to its versatility and convenience. It is particularly popular amongst younger students, who, as digital natives, are more receptive towards new technology. However, research on students’ attitudes and intentions towards using GenAI [...] Read more.

Generative Artificial Intelligence (GenAI) has gained mass popularity in education due to its versatility and convenience. It is particularly popular amongst younger students, who, as digital natives, are more receptive towards new technology. However, research on students’ attitudes and intentions towards using GenAI technology in their education mainly focuses on older age groups like university students. Utilizing the Decomposed Theory of Planned Behavior (DTPB) as a theoretical framework, this qualitative study interviewed 18 high school computing students to explore their perceptions and intentions to use an educational GenAI chatbot to learn programming and how these decisions may be influenced by individual differences in their academic abilities. Using an abductive approach in analyzing the interview data, the findings align with DTPB to describe students’ attitudes towards using GenAI chatbots in their studies. It also proposes a new construct, students’ perceived need to use GenAI technology, that may influence students’ attitude and intentions. Lastly, the study uncovers differences between students of varying academic abilities in their priorities when using GenAI chatbots that influence their subsequent attitudes. This study extends the user perceptions captured in the existing DTPB framework and suggests how individual factors like academic ability may shape attitudes differently. It also provides recommendations for integrating GenAI into the high school classroom. Full article

(This article belongs to the Special Issue Generative AI in Education: Current Trends and Future Directions)

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28 pages, 6267 KB

Open AccessArticle

Screening of Macadamia integrifolia Varieties Based on the Comparison of Seedling Adaptability and Quality Differences

by Xibin Zhang, Xu Li, Liangyi Zhao, Zhitao Yang, Chengping Luo, Fuyan Ma, Weifeng Zhao, Baoqiong Zhang, Wenxiu Yang, Xuehu Yang and Liangliang Sun

Biology 2025, 14(12), 1638; https://doi.org/10.3390/biology14121638 (registering DOI) - 21 Nov 2025

Abstract

Macadamia (Macadamia spp.), as a high-value cash crop, relies on varietal adaptability screening and quality optimization for enhanced industrial benefits. However, existing research has predominantly focused on the mature tree stage. Systematic studies on the physiological characteristics during the seedling stage and [...] Read more.

Macadamia (Macadamia spp.), as a high-value cash crop, relies on varietal adaptability screening and quality optimization for enhanced industrial benefits. However, existing research has predominantly focused on the mature tree stage. Systematic studies on the physiological characteristics during the seedling stage and comprehensive multi-indicator evaluations remain insufficient, limiting improved variety selection and industrial development. This study investigated three macadamia varieties (A4, A16, A203). We systematically measured leaf morphology, photosynthetic parameters, antioxidant enzyme activities, and free amino acid content at the seedling stage, combined with a comprehensive analysis of mature fruit morphology, mineral elements, amino acid composition, and pericarp phenolic compounds. The results indicated that at the seedling stage: A4 exhibited the highest SPAD value and CAT activity, significantly exceeding A16 and A203 by 137.14% and 139.82%, respectively, alongside the lowest MDA content, highlighting its superior stress resistance; A16 showed the highest Pn, Cleaf, and WUE, with total amino acid content being 38.09% and 18.79% higher than A4 and A203, respectively; A203 demonstrated the highest light energy utilization efficiency, significantly higher SOD activity compared to A16 and A203, and the lowest O²⁻ content. Regarding fruit quality: A16 kernels contained the highest total amino acids and umami amino acids, with sweet and aromatic amino acids also being significantly higher than in other varieties; A203 performed notably well in K, Mg, and Mn content, with medicinal amino acids accounting for over 70% of the total; A4 pericarp contained significantly higher levels of phenolic compounds, such as p-hydroxybenzoic acid, compared to A16 and A203, some exceeding 80%. Correlation analysis revealed a complex regulatory network among fruit traits, mineral elements, amino acids, and phenolics. In summary, A4, A16, and A203 possess respective advantages in high stress resistance, superior flavor quality, and high nutritional functionality. This study establishes a comprehensive “morphology–photosynthesis–antioxidant activity–amino acids–quality” evaluation system, providing a scientific basis for targeted breeding and whole-industry-chain development of macadamia. Full article

(This article belongs to the Special Issue Advances in Tropical and Subtropical Plant Ecology and Physiology)

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