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28 pages, 1142 KB

Open AccessArticle

Attitudinal Indicator Model for Disability Inclusion in Higher Education: Advancing Sustainable Development Goals in El Salvador

by Carlos Alberto Echeverría Mayorga and Marta Irene Flores Polanco

Sustainability 2025, 17(22), 10379; https://doi.org/10.3390/su172210379 (registering DOI) - 20 Nov 2025

Abstract

This study validates an empirical model of attitudinal indicators to assess the inclusion of students with physical motor disabilities in higher education. Grounded in the tripartite model of attitude and framed within the social model of disability, the research employed the SACIE-R scale [...] Read more.

This study validates an empirical model of attitudinal indicators to assess the inclusion of students with physical motor disabilities in higher education. Grounded in the tripartite model of attitude and framed within the social model of disability, the research employed the SACIE-R scale to measure emotional, cognitive, and behavioral predispositions among 384 faculty members from private universities in El Salvador, selected through stratified sampling. Exploratory factor analysis (EFA) identified three latent dimensions—concerns and general attitudes, inclusive feelings, and cognitive–affective tension—explaining 56.36% of the variance, with strong reliability (Cronbach’s α = 0.876). Chi-square tests revealed significant attitudinal differences by age, sex, training, and institutional affiliation. The resulting model translates latent predispositions into observable indicators of inclusive teaching competencies, providing a diagnostic and evaluative tool for higher education institutions. Beyond the Salvadoran context, the framework demonstrates potential scalability across Latin American systems with comparable socio-educational conditions. Importantly, the model contributes to the Sustainable Development Goals (SDG 4, SDG 10, and SDG 16) by supporting inclusive and equitable quality education, reducing structural inequalities, and informing governance policies grounded in human rights. Findings highlight persistent attitudinal barriers and limited faculty preparedness, underscoring the need for sustainable institutional strategies. This research advances the debate on educational sustainability by linking faculty attitudes to long-term policy development, capacity-building, and institutional accountability. Full article

(This article belongs to the Special Issue Innovation and Sustainability in Inclusive Education)

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23 pages, 3971 KB

Open AccessArticle

Evaluation of an Efficient Ring-Based Total Order Protocol in a Fairness-Controlled Environment

by Agbaeze Ejem, Cosmas Ifeanyi Nwakanma, Ejem Agwu Ejem and Juliet Nnenna Odii

Digital 2025, 5(4), 64; https://doi.org/10.3390/digital5040064 (registering DOI) - 20 Nov 2025

Abstract

Crash-tolerant systems rely on total order protocols to ensure consistent request execution across replicated servers. The Logical Clock and Ring (LCR) protocol employs a ring-based, leaderless design that provides a high throughput but suffers latency inefficiencies under a high message concurrency due to [...] Read more.

Crash-tolerant systems rely on total order protocols to ensure consistent request execution across replicated servers. The Logical Clock and Ring (LCR) protocol employs a ring-based, leaderless design that provides a high throughput but suffers latency inefficiencies under a high message concurrency due to its use of vector clocks and a fixed last-process rule for ordering concurrent messages. This paper presents the Daisy Chain Total Order Protocol (DCTOP), an enhanced version of LCR that integrates Lamport logical clocks for message sequencing and introduces dynamic last-process identification based on sender activity to accelerate message stabilisation and delivery. A modified fairness-control mechanism further balances message distribution among processes. The simulation results show that the DCTOP achieves an over 40% latency reduction compared to LCR while maintaining the same fairness and throughput across various cluster configurations. Full article

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17 pages, 3850 KB

Open AccessArticle

Traceable and Biocompatible Carbon Dots from Simple Precursors: A Pre-Deployment Safety Baseline

by Christian Silva-Sanzana, Plinio Innocenzi, Luca Malfatti, Federico Fiori, Francisca Blanco-Herrera, Juan Hormazabal, María Victoria Gangas, Oscar Diaz and Iván Balic

Agrochemicals 2025, 4(4), 20; https://doi.org/10.3390/agrochemicals4040020 (registering DOI) - 20 Nov 2025

Abstract

Carbon dots (CDs) are promising for agro-environmental applications; however, clear connections between synthesis, photophysical properties, size, and biosafety are often not well established. In this study, we map these relationships for glucose–arginine CDs (GA-CDs). By using microwave and hydrothermal routes at precursor ratios [...] Read more.

Carbon dots (CDs) are promising for agro-environmental applications; however, clear connections between synthesis, photophysical properties, size, and biosafety are often not well established. In this study, we map these relationships for glucose–arginine CDs (GA-CDs). By using microwave and hydrothermal routes at precursor ratios of 1:3, 1:9, and 1:15, we produced sub-10 nm nanoparticles (analyzed by dynamic light scattering and atomic force microscopy) that exhibit tunable absorption and emission properties, as well as surface properties (demonstrated through UV–Vis spectroscopy, 3D photoluminescence, and FTIR analysis). The hydrothermal 1:9 condition yielded the narrowest size distribution and red-shifted photoluminescence. Across biological models spanning plants, insects, plant-growth-promoting bacteria (PGPR), and human cells, GA-CDs were well tolerated, with no adverse changes detected in plant stress markers, aphid feeding behavior or fecundity, or PGPR growth. In A549 cells, viability remained stable up to a concentration of 0.125 mg mL⁻¹, while exposure to 0.5 mg mL⁻¹ reduced viability, establishing a practical operating range. These results provide a clearer picture of how the structure and properties of carbon dots derived from arginine and glucose are correlated to their safety. The GA-CDs are, therefore, useful, and traceable tools for agro-environmental research. The findings support their use as biocompatible nanomaterials for studying interactions among plants, insects, and microbes in agriculture. Full article

(This article belongs to the Section Fungicides and Bactericides)

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23 pages, 7595 KB

Open AccessArticle

Multiscale Coronary Arterial Network Generation and Hemodynamics Using Patient-Specific Fractional Myocardial Blood Volume

by Mostafa Mahmoudi, Arutyun Pogosyan, Amirhossein Arzani and Kim-Lien Nguyen

Bioengineering 2025, 12(11), 1274; https://doi.org/10.3390/bioengineering12111274 (registering DOI) - 20 Nov 2025

Abstract

Ischemic heart disease (IHD) is the leading cause of death worldwide. Although 90% of the intramyocardial blood volume resides in the microvasculature, clinical imaging methods cannot visualize the microvascular coronary network in vivo, and non-invasive hemodynamic estimates overlook patient-specific microcirculatory contributions. Herein, we [...] Read more.

Ischemic heart disease (IHD) is the leading cause of death worldwide. Although 90% of the intramyocardial blood volume resides in the microvasculature, clinical imaging methods cannot visualize the microvascular coronary network in vivo, and non-invasive hemodynamic estimates overlook patient-specific microcirculatory contributions. Herein, we present a multiscale framework to extend the epicardial coronary tree and generate 1D microvascular networks in the myocardium based on ferumoxytol-enhanced magnetic resonance coronary imaging and fractional myocardial blood volume (fMBV) maps. Synthetic arterial networks were constructed from MRI data belonging to three swine, four healthy volunteers, and one IHD patient using a modified multistage, adaptive constrained constructive optimization approach. Hemodynamic simulations were performed in synthetic arterial networks. Morphological parameters were compared with empirical models. In 126 arterial networks (n = 6000 terminal segments per subject per seed; six seeds per coronary vessel), the morphometry was strongly correlated with empirical data (r > 0.87), with low variability (CoV < 0.01) across multiple rounds of network simulations. Mixed-effects models and a Dynamic Time Warping analysis confirmed robustness and repeatability. In the IHD patient, simulated arterial networks (n = 15) reproduced tissue-dependent morphological and functional signatures consistent with coronary autoregulation in scar and hypoperfused tissues. The findings establish an early potential for patient-specific microvascular network synthesis and hemodynamic simulations from MRI data. Full article

(This article belongs to the Section Biomedical Engineering and Biomaterials)

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14 pages, 607 KB

Open AccessArticle

Shear Bond Strength of Biointeractive Restorative Materials to NeoMTA Plus and Biodentine

by Zübeyde Uçar Gündoğar, Gül Keskin and Merve Yaman Küçükersen

Polymers 2025, 17(22), 3070; https://doi.org/10.3390/polym17223070 (registering DOI) - 20 Nov 2025

Abstract

Background: The bonding compatibility between calcium silicate-based bioceramic cements and restorative materials is critical for long-term success in pediatric dentistry. This study compared the shear bond strength (SBS) of contemporary biointeractive restorative materials to two widely used bioceramics, NeoMTA Plus (NM) and Biodentine [...] Read more.

Background: The bonding compatibility between calcium silicate-based bioceramic cements and restorative materials is critical for long-term success in pediatric dentistry. This study compared the shear bond strength (SBS) of contemporary biointeractive restorative materials to two widely used bioceramics, NeoMTA Plus (NM) and Biodentine (BD). Methods: Eighty acrylic resin blocks with standardized cavities were filled with either NM or BD (n = 40 each) and subdivided into four restorative groups: nanohybrid composite (Filtek Ultimate), giomer (Beautifil II), bioactive restorative (Activa BioActive Restorative), and high-viscosity glass ionomer cement (Fuji IX GP Extra) (n = 10 each). All restorations followed a standardized etch-and-bond protocol. SBS was measured using a universal testing machine, and failure modes were assessed under a stereomicroscope. Data were analyzed using one-way ANOVA and Tukey’s HSD (p < 0.05). Results: BD exhibited significantly higher SBS values than NM (p < 0.001). In the BD group, Filtek Ultimate and Beautifil II achieved the highest and statistically comparable SBS, outperforming Activa BioActive Restorative and Fuji IX GP Extra (p < 0.05). In the NM group, no significant differences were found among materials. Adhesive failures predominated in NM (85%), while BD showed more cohesive failures (50%). Conclusions: Biodentine demonstrated superior bonding stability to restorative materials, with composite resin and giomer performing best. Giomer’s bioactivity and ion release make it a viable alternative to composite resin in suitable clinical contexts. Full article

(This article belongs to the Special Issue Polymers in Restorative Dentistry: 2nd Edition)

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Graphical abstract

66 pages, 9255 KB

Open AccessReview

Recent Advances in Polymer-Coated Metal and Metal Oxide Nanoparticles: From Design to Promising Applications

by Refia Atik, Rafiqul Islam, Melissa Ariza Gonzalez, Pailinrut Chinwangso and T. Randall Lee

Nanomaterials 2025, 15(22), 1744; https://doi.org/10.3390/nano15221744 (registering DOI) - 20 Nov 2025

Abstract

The integration of polymer coatings with metal and metal oxide nanoparticles represents a significant advancement in nanotechnology, enhancing the stability, biocompatibility, and functional versatility of these materials. These enhanced properties make polymer-coated nanoparticles key components in a wide range of applications, including biomedicine, [...] Read more.

The integration of polymer coatings with metal and metal oxide nanoparticles represents a significant advancement in nanotechnology, enhancing the stability, biocompatibility, and functional versatility of these materials. These enhanced properties make polymer-coated nanoparticles key components in a wide range of applications, including biomedicine, catalysis, environmental remediation, electronics, and energy storage. The unique combination of polymeric materials with metal and metal oxide cores results in hybrid structures with superior performance characteristics, making them highly desirable for various technological innovations. Polymer-coated metal and metal oxide nanoparticles can be synthesized through various methods, such as grafting to, grafting from, grafting through, in situ techniques, and layer-by-layer assembly, each offering distinct control over nanoparticle size, shape, and surface functionality. The distinctive contribution of this review lies in its systematic comparison of polymer-coating synthesis approaches for different metal and metal oxide nanoparticles, revealing how variations in polymer architecture and surface chemistry govern their stability, functionality, and application performance. The aim of this paper is to provide a comprehensive overview of the current state of research on polymer-coated nanoparticles, including metals such as gold, silver, copper, platinum, and palladium, as well as metal oxides like iron oxide, titanium dioxide, zinc oxide, and aluminum oxide. This review highlights their design strategies, synthesis methods, characterization approaches, and diverse emerging applications, including biomedicine (e.g., targeted drug delivery, gene delivery, bone tissue regeneration, imaging, antimicrobials, and therapeutic interventions), environmental remediation (e.g., antibacterials and sensors), catalysis, electronics, and energy conversion. Full article

(This article belongs to the Collection Metallic and Metal Oxide Nanohybrids and Their Applications)

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Graphical abstract

13 pages, 289 KB

Open AccessArticle

Persistence in Stock Returns: Robotics and AI ETFs Versus Other Assets

by Fekria Belhouichet, Guglielmo Maria Caporale and Luis Alberiko Gil-Alana

J. Risk Financial Manag. 2025, 18(11), 655; https://doi.org/10.3390/jrfm18110655 (registering DOI) - 20 Nov 2025

Abstract

This paper examines the long-memory properties of the returns of exchange-traded funds (ETFs) that provide exposure to companies operating in the fields of artificial intelligence (AI) and robotics listed on the US market, along with other assets such as the WTI crude oil [...] Read more.

This paper examines the long-memory properties of the returns of exchange-traded funds (ETFs) that provide exposure to companies operating in the fields of artificial intelligence (AI) and robotics listed on the US market, along with other assets such as the WTI crude oil price (West Texas Intermediate), Bitcoin, the S&P 500 index, 10-year US Treasury bonds, and the VIX volatility index. The data frequency is daily and covers the period from 1 January 2023 to 23 June 2025. The adopted fractional integration framework is more general and flexible than those previously used in related studies and allows for a detailed assessment of the degree of persistence in returns. The results indicate that all return series exhibit a high degree of persistence, regardless of the error structure assumed, and that, in general, a linear model adequately captures their dynamics over time. These findings suggest that newly developed AI- and robotics-themed ETFs do not provide investors with additional hedging or diversification benefits compared to more traditional assets, nor do they create new challenges for policymakers concerned with financial stability. Full article

(This article belongs to the Section Economics and Finance)

15 pages, 1774 KB

Open AccessArticle

Soil and Environmental Consequences of Spring Flooding in the Zhabay River Floodplain (Akmola Region)

by Madina Aitzhanova, Sayagul Zhaparova, Manira Zhamanbayeva and Assem Satimbekova

Sustainability 2025, 17(22), 10378; https://doi.org/10.3390/su172210378 (registering DOI) - 20 Nov 2025

Abstract

Floods increasingly threaten semiarid regions, yet their long-term soil ecological impacts remain underdocumented. This study quantifies the hydrologic change and flood-induced soil transformation on the Zhabay River floodplain (Akmola, Kazakhstan) using integrated field, laboratory, and remote sensing data. Gauge records (2012–2024) were analyzed; [...] Read more.

Floods increasingly threaten semiarid regions, yet their long-term soil ecological impacts remain underdocumented. This study quantifies the hydrologic change and flood-induced soil transformation on the Zhabay River floodplain (Akmola, Kazakhstan) using integrated field, laboratory, and remote sensing data. Gauge records (2012–2024) were analyzed; inundation was mapped from a 0.30 m DEM (Digital Elevation Model) merging SRTM (Shuttle Radar Topography Mission), Landsat 8/Sentinel 2, and UAV (Unmanned Aerial Vehicle) photogrammetry (NDWI (Normalized Difference Water Index) > 0.28) and validated with 54 in situ depths (MAE (Mean Absolute Error) 0.17 m). Soil samples collected before and after floods were analyzed for texture, bulk density, pH, Eh, macronutrients, and heavy metals. Annual maxima increased by 0.08 m yr⁻¹, while extreme floods became more frequent. Thresholds of ≥0.5 m depth and >7 days duration marked compaction onset, whereas >1 m and ≥12 days produced maximum organic carbon loss and Zn/Ni enrichment. The combination of high-resolution DEMs, ROC (Receiver Operating Characteristic) analysis, and soil microbial monitoring provides new operational indicators of soil degradation for Central Asian steppe floodplains. Findings contribute to SDG 13 (Climate Action) and SDG 15 (Life on Land) by linking flood resilience assessment with sustainable land-use planning. Full article

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24 pages, 8096 KB

Open AccessArticle

Diversity and Selection of Superior Algarrobos (Neltuma pallida) Phenotypes in the Natural Dry Forests of Peru for Sustainable Conservation and Genetic Improvement

by Sebastian Casas-Niño, Juan Rodrigo Baselly-Villanueva, Evelin Judith Salazar-Hinostroza, Sheyla Yanett Chumbimune-Vivanco, William Nauray, Nery Tirabante-Terrones, Max Ramirez Rojas and Flavio Lozano-Isla

Diversity 2025, 17(11), 802; https://doi.org/10.3390/d17110802 (registering DOI) - 20 Nov 2025

Abstract

Neltuma pallida (algarrobo) is a keystone species of the Peruvian dry forest whose persistence is threatened by overexploitation and habitat degradation, making its conservation and genetic improvement a national priority. This study aimed to identify outstanding phenotypes of N. pallida through phenotypic characterization [...] Read more.

Neltuma pallida (algarrobo) is a keystone species of the Peruvian dry forest whose persistence is threatened by overexploitation and habitat degradation, making its conservation and genetic improvement a national priority. This study aimed to identify outstanding phenotypes of N. pallida through phenotypic characterization in the regions of Piura and Tumbes in northern Peru. A stratified random sampling design was applied, establishing forest plots in 13 localities and evaluating 631 adult individuals. Dendrometric and phenotypic traits were recorded together with physiographic, climatic, and edaphic variables obtained from soil analyses and geographic information systems. Phenotypic differentiation among populations was assessed using the index

P_{S T}

, which quantifies between- and within-population variance components. High morphological variability was detected across populations, with significant differences in tree height, diameter, and fruit production, largely explained by environmental heterogeneity, particularly soil fertility and organic matter. The

P_{S T}

values, ranging from 0.83 to 0.98, revealed strong phenotypic divergence among populations, suggesting adaptive differentiation rather than neutral variation. Eight superior individuals were identified as potential candidates for inclusion in a germplasm bank to support breeding and restoration programs. This study provides a scientific basis for the sustainable management and conservation of N. pallida in the arid ecosystems. Full article

(This article belongs to the Section Biodiversity Conservation)

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21 pages, 447 KB

Open AccessArticle

Enhancing Intrusion Detection for IoT and Sensor Networks Through Semantic Analysis and Self-Supervised Embeddings

by Yanshen Liu and Yinfeng Guo

Sensors 2025, 25(22), 7074; https://doi.org/10.3390/s25227074 (registering DOI) - 20 Nov 2025

Abstract

As cyber threats continue to grow in complexity and sophistication, the need for advanced network and sensor security solutions has never been more urgent. Traditional intrusion detection methods struggle to keep pace with the sheer volume of network traffic and the evolving nature [...] Read more.

As cyber threats continue to grow in complexity and sophistication, the need for advanced network and sensor security solutions has never been more urgent. Traditional intrusion detection methods struggle to keep pace with the sheer volume of network traffic and the evolving nature of attacks. In this paper, we propose a novel machine learning-driven Intrusion Detection System (IDS) that improves intrusion detection through a comprehensive analysis of multidimensional data. Transcending traditional feature extraction methods, the system introduces geospatial context features and self-supervised semantic features that provide rich contextual information for enhanced threat identification. The system’s performance is validated on a carefully curated dataset from China Mobile, containing over 100 K records, achieving an impressive 98.5% accuracy rate in detecting intrusions. The results highlight the effectiveness of ensemble learning methods and underscore the system’s potential for real-world deployment, offering a significant advancement in the development of intelligent cybersecurity tools that can adapt to the ever-changing landscape of cyber threats. Furthermore, the proposed framework is extensible to IoT and wireless sensor networks (WSNs), where resource constraints and new attack surfaces demand lightweight yet semantically enriched IDS solutions. Full article

(This article belongs to the Special Issue Sensor Networks and Communication with AI)

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13 pages, 245 KB

Open AccessArticle

High Prevalence of Food Insecurity and Associated Risk Factors in Chilean and Immigrant Women from South-Central Chile

by Alejandra Rodríguez-Fernández, Juana María Delgado-Saborit, Paula Carrasco, Gabriela Cormick, Marcela Ruiz-de la Fuente and Eduard Maury-Sintjago

Foods 2025, 14(22), 3973; https://doi.org/10.3390/foods14223973 (registering DOI) - 20 Nov 2025

Abstract

Food insecurity (FI) is a major public health problem that disproportionately affects women, especially if they are migrants. In Chile, there is limited data on how gender and migration status intersect to explain vulnerability to FI. A cross-sectional analytical study was conducted among [...] Read more.

Food insecurity (FI) is a major public health problem that disproportionately affects women, especially if they are migrants. In Chile, there is limited data on how gender and migration status intersect to explain vulnerability to FI. A cross-sectional analytical study was conducted among 2124 women of childbearing age (1062 Chilean and 1062 immigrants) residing in south-central Chile. Biosociodemographic variables were collected through a structured questionnaire, and FI was assessed using the Household Food Insecurity Access Scale (HFIAS). Multivariate logistic regression models were applied to estimate risk factors using odds ratios (OR). Overall, 39.2% of women experienced some degree of FI, with prevalence significantly higher among immigrants (49%) compared to Chileans (29%). Severe FI was twice as frequent in immigrant women (18.1% vs. 9.2%). The risk factor of FI in the total sample included immigrant status (OR = 2.61; 95% CI: 2.15–3.17), low socioeconomic status (OR = 2.25; 1.77–2.87), having children (OR = 1.82; 1.49–2.23), being head of household (OR = 1.53; 1.25–1.87), not having a job (OR = 1.27; 1.02–1.58), and suffering from depression (OR = 2.11; 1.66–2.67). Subgroup analyses confirmed similar determinants in both groups, with not having a job being relevant mainly for immigrants and age acting as a protective factor among Chileans. FI is highly prevalent among women in south-central Chile, particularly among immigrants. Structural determinants such as socioeconomic status, having children, being the head of the household, and depression increase vulnerability. Policies must integrate gender and migration perspectives, promoting access to adequate food, employment, childcare, and mental health support. Full article

(This article belongs to the Topic Food Security and Healthy Nutrition)

24 pages, 2693 KB

Open AccessArticle

Multi-Objective Optimal Partitioning of Active Distribution Networks Integrating Consideration of Load Balancing and Solution Efficiency of Parallel Optimization

by Qing Ge, Yuezhou Xia, Qi Li, Ling Zeng, Zhangbin Huang and Chuanjie Lin

Processes 2025, 13(11), 3740; https://doi.org/10.3390/pr13113740 (registering DOI) - 20 Nov 2025

Abstract

To address the optimization challenges arising from the large-scale integration of distributed energy resources into active distribution networks, this paper proposes a multi-objective optimization partitioning method that balances system security/stability with parallel computing efficiency. To address the limitations of existing partitioning approaches, particularly [...] Read more.

To address the optimization challenges arising from the large-scale integration of distributed energy resources into active distribution networks, this paper proposes a multi-objective optimization partitioning method that balances system security/stability with parallel computing efficiency. To address the limitations of existing partitioning approaches, particularly their neglect of parallel computing efficiency and poor adaptability to the radial topology of distribution networks, a three-objective optimization model is constructed. This model incorporates reactive power–voltage control, load balancing, and power balance constraints, while introducing partition scale constraints and connectivity constraints. The NSGA-III algorithm is employed to solve the Pareto front, and an optimal compromise solution is obtained using a fuzzy membership function. A partition adjustment strategy ensures topological connectivity. Validation on 10 kV distribution networks with 47-node, 124-node, and 300-node systems demonstrates that this method achieves reasonable reactive power–voltage partitioning, ensures intra-partition power balance and load balancing, and exhibits significant advantages over traditional methods. Full article

(This article belongs to the Special Issue Analysis and Optimization Control of Active Distribution Networks and Smart Grids)

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22 pages, 344 KB

Open AccessReview

First-Generation Biofuels vs. Energy Security: An Overview of Biodiesel and Bioethanol

by Renata Marks-Bielska, Stanisław Bielski, Krystyna Kurowska and Anna Zielińska-Chmielewska

Energies 2025, 18(22), 6055; https://doi.org/10.3390/en18226055 (registering DOI) - 20 Nov 2025

Abstract

Energy agriculture is one of the ways of producing clean energy. Crop production constitutes the basis for the sustainable profitability of agriculture, and agricultural products are traded on two markets: the food market and the energy market. This article reviews the literature on [...] Read more.

Energy agriculture is one of the ways of producing clean energy. Crop production constitutes the basis for the sustainable profitability of agriculture, and agricultural products are traded on two markets: the food market and the energy market. This article reviews the literature on the conditions influencing biofuel production, with the aim of identifying the arguments supporting its expansion and the challenges associated with large-scale production. The study employs quantitative and qualitative desk research methods, the method of deduction, analysis and synthesis, the comparative method, and the expert method. Widespread application of biofuels requires a broader range of non-food raw materials (such as lignocellulosic biomass) and the advancement of conversion technologies used in bioethanol and biodiesel production. The main goal of ecofriendly energy generation should be to increase the energy output while minimizing environmental impacts. The findings from the literature review were collected, identified, and described as objectively as possible. The conclusions drawn are based on the authors’ findings and expert opinions. The future of biofuels depends on the optimal choice of raw materials that ensure the highest production efficiency, low costs, and reduced emissions of harmful atmospheric pollutants. Thus, intensification of agricultural production of non-food crops (lignocellulosic biomass) for energy generation may lead to irreversible changes in the environment. Full article

(This article belongs to the Special Issue Biomass and Waste Valorization for Biofuel and Bioproducts Production)

17 pages, 1438 KB

Open AccessArticle

Stochastic Cost Estimation in Transportation Infrastructure Projects Using Monte Carlo Simulation and Correlated Risk Variables

by Gerber Zavala, Victor Ariza Flores, Ricardo Santos and Jaime Blas Cano

Future Transp. 2025, 5(4), 176; https://doi.org/10.3390/futuretransp5040176 (registering DOI) - 20 Nov 2025

Abstract

Peru faces critical challenges in the development and maintenance of its national road infrastructure, comprising over 32,000 km, of which only 26% are classified as being in good condition. This infrastructural deficit significantly elevates logistics costs and undermines national competitiveness, particularly in key [...] Read more.

Peru faces critical challenges in the development and maintenance of its national road infrastructure, comprising over 32,000 km, of which only 26% are classified as being in good condition. This infrastructural deficit significantly elevates logistics costs and undermines national competitiveness, particularly in key sectors such as agriculture and mining. In this context, improving the accuracy and reliability of cost estimation in road infrastructure projects is imperative to optimize resource allocation and mitigate the risk of cost overruns. This study proposes a stochastic cost estimation framework that integrates Monte Carlo simulation with correlation matrices, enabling the modeling of uncertainty and the complex interdependencies among critical cost drivers. The methodology was applied to the Oyon Ambo highway in Peru. Historical input cost databases were analyzed to define probabilistic distributions, and correlation coefficients were employed to represent the dependencies between variables such as material prices, labor productivity, and equipment efficiency. The stochastic model produced probabilistic cost forecasts with associated confidence intervals and quantified risk exposure. The findings demonstrate that the proposed integrated approach significantly enhances the precision and robustness of cost estimates, providing project managers and decision-makers with a rigorous, data-driven tool for risk-informed budgeting and strategic financial planning in complex infrastructure projects. Full article

(This article belongs to the Special Issue Machine Learning for Sustainable Planning and Modelling in Future Smart Transportation System)

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20 pages, 2061 KB

Open AccessArticle

Assessing Short-Term Temporal Variability of CO₂ Emission and Soil O₂ Influx in Tropical Pastures and Regenerating Forests

by Wanderson Benerval De Lucena, Kleve Freddy Ferreira Canteral, Maria Elisa Vicentini, Daniele Fernanda Zulian, Renato Paiva De Lima, Mario Luiz Teixeira De Moraes, Maurício Roberto Cherubin, Carlos Eduardo Pellegrino Cerri, Alan Rodrigo Panosso and Newton La Scala Jr.

Appl. Sci. 2025, 15(22), 12302; https://doi.org/10.3390/app152212302 (registering DOI) - 20 Nov 2025

Abstract

Soil respiration, the exchange of gases between soil and the atmosphere (O₂ consumption and CO₂ production), plays a key role in ecosystem functioning and climate regulation. This study investigated the short-term temporal variability of soil CO₂ emissions and O₂ [...] Read more.

Soil respiration, the exchange of gases between soil and the atmosphere (O₂ consumption and CO₂ production), plays a key role in ecosystem functioning and climate regulation. This study investigated the short-term temporal variability of soil CO₂ emissions and O₂ influx and their relationship with tropical climate conditions and soil attributes in the Cerrado region, Selvíria, MS, Brazil. Soil CO₂ emissions were measured using the LI-8100 portable system, while soil O₂ influx was estimated by linear interpolation of O₂ variation inside the chamber using a UV Flux 25% (ultraviolet light) sensor. Soil temperature and moisture were measured simultaneously in three land use types: pasture (~11 years) and reforested areas with native species and eucalyptus (~35 years). Soils were classified as Oxisoils according to Soil Taxonomy. Significant short-term temporal variability was observed in CO₂ emissions (mean 3.2 ± 0.5 µmol m⁻² s⁻¹), O₂ influx (mean 1.8 ± 0.3 mg O₂ m⁻² s⁻¹), soil temperature and moisture across the land use types. Pasture areas exhibited the lowest CO₂ emission rates, associated with improved soil attributes (soil organic matter, sum of bases and pH) due to management practices, while reforested areas showed overlapping soil respiration patterns and higher temporal variability. Principal component analysis revealed strong coupling between O₂ influx and CO₂ emission in reforested soils. These findings highlight the influence of land use on short-term soil respiration dynamics and underscore the importance of sustainable pasture management and reforestation in the Brazilian Cerrado. The results also support public policies aimed at restoring degraded pastures, reducing deforestation and burning, and enhancing soil carbon sequestration to mitigate climate change. Full article

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21 pages, 3033 KB

Open AccessArticle

Spatio-Temporal Patterns and Decoupling Analysis of Land Use-Related Carbon Emissions in Jilin Province

by Wenwen Lv and Yan Liu

Sustainability 2025, 17(22), 10377; https://doi.org/10.3390/su172210377 (registering DOI) - 20 Nov 2025

Abstract

Land use change is a key driver of regional carbon emissions. Understanding the mechanisms through which regional land use changes influence carbon emissions, as well as their spatiotemporal evolution, is of great significance for the optimization of land use structure and the formulation [...] Read more.

Land use change is a key driver of regional carbon emissions. Understanding the mechanisms through which regional land use changes influence carbon emissions, as well as their spatiotemporal evolution, is of great significance for the optimization of land use structure and the formulation of low-carbon policies. This study, based on land use data and socio-economic data from 2002 to 2022, combines decoupling analysis models with carbon carrying capacity assessment frameworks to systematically analyze the dynamic evolution of carbon emissions from land use in Jilin Province. The results show the following: (1) From 2002 to 2022, the cultivated land area in Jilin Province remained stable and accounted for the largest proportion; the areas of water bodies and construction land expanded, while forest, grassland, and unutilized land continued to decline. (2) Total carbon emissions exhibited a “growth-stabilization-slight decline” trend, with construction land contributing the most to emissions. Spatially, carbon emissions were concentrated in the central region with Changchun at its core. (3) The overall carbon ecological carrying capacity of Jilin Province showed a fluctuating upward trend, with notable differences in carbon ecological carrying capacity across cities. (4) Cultivated land showed the highest correlation with carbon emissions, followed by woodland. The decoupling relationship between carbon emissions and economic development exhibited phase fluctuations, evolving from weak decoupling to strong decoupling and then transitioning back to weak negative decoupling. Therefore, it is recommended that effective measures be adopted to curb the excessive expansion of construction land, enhance ecological carbon sink functions, and facilitate the transformation of cultivated land from a carbon source to a carbon sink. This will promote the efficient and green utilization of land resources, advance the synergistic progress of economic development and environmental protection, and achieve the goal of regional sustainable development. Full article

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12 pages, 578 KB

Open AccessArticle

Organic Fertilization vs. the Quality of Basil Raw Material

by Katarzyna Dzida, Karolina Pitura and Anna Król

Agronomy 2025, 15(11), 2656; https://doi.org/10.3390/agronomy15112656 (registering DOI) - 19 Nov 2025

Abstract

Basil (Ocimum basilicum L.) is one of the most widely cultivated herbal plants, valued in the food and pharmaceutical industries for its abundance of bioactive compounds, and also as an ornamental plant. The contents of its bioactive compounds are strongly influenced by [...] Read more.

Basil (Ocimum basilicum L.) is one of the most widely cultivated herbal plants, valued in the food and pharmaceutical industries for its abundance of bioactive compounds, and also as an ornamental plant. The contents of its bioactive compounds are strongly influenced by both environmental and anthropogenic factors, among which fertilization plays a key role. This study aimed to evaluate the effects of different application doses (5, 10, 15, and 20 g·dm⁻³ of substrate) of an organic fertilizer (granulated cattle manure) on the fresh biomass yield and quality of two basil varieties: lemon basil and cinnamon basil. The applied manure doses significantly affected the fresh biomass yield of O. basilicum L. Both basil variety and fertilizer dose were found to determine the content of L-ascorbic acid and nitrates in the plants. Increasing manure doses resulted in higher contents of N, P, and K, as well as decreased contents of Ca and Mg in plants of both varieties. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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28 pages, 3332 KB

Open AccessArticle

An Optimization-Based Aggregation Approach with Triangular Intuitionistic Fuzzy Numbers in High-Dimensional Multi-Attribute Decision-Making

by Yanshan Qian, Junda Qiu, Jiali Tang, Qi Liu, Chuanan Li and Senyuan Chen

Information 2025, 16(11), 1010; https://doi.org/10.3390/info16111010 (registering DOI) - 19 Nov 2025

Abstract

We address information fusion and spatial structure modeling in high-dimensional fuzzy multi-attribute decision-making by proposing a novel framework that couples Triangular Intuitionistic Fuzzy Numbers (TIFNs) with the Plant Growth Simulation Algorithm (PGSA). The method first maps the triangular intuitionistic fuzzy information of experts [...] Read more.

We address information fusion and spatial structure modeling in high-dimensional fuzzy multi-attribute decision-making by proposing a novel framework that couples Triangular Intuitionistic Fuzzy Numbers (TIFNs) with the Plant Growth Simulation Algorithm (PGSA). The method first maps the triangular intuitionistic fuzzy information of experts on each evaluation scheme into high-dimensional spatial points to realize the structured expression of decision-making information. Subsequently, the PGSA is used to perform dynamic global optimization search on the high-dimensional point cloud to determine the optimal set point and realize the intelligent aggregation of heterogeneous fuzzy data from multiple sources. The algorithm breaks through the limitation of traditional linear aggregation on the portrayal of information spatial distribution and is able to improve the accuracy and consistency of decision-making results in high-dimensional complex environments. The experimental results show that the method in this paper outperforms the mainstream aggregation methods in a number of evaluation indexes such as weighted Hamming distance, correlation, information energy and correlation coefficient. The proposed model provides a new technical path for intelligent solution and theory expansion of high-dimensional fuzzy decision-making problems. Full article

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33 pages, 10093 KB

Open AccessArticle

Exploring the Agromorphological Profiles of the Cacao (Theobroma cacao L.) Collection from the INIA Germplasm Bank in the Amazonas Region, Peru

by José Jesús Tejada-Alvarado, Nuri Carito Vilca-Valqui, Luis Alberto Montenegro-Acuña, Jhimy Andy Parco-Quinchori and Elizabeth Fernandez

Plants 2025, 14(22), 3536; https://doi.org/10.3390/plants14223536 (registering DOI) - 19 Nov 2025

Abstract

Cacao is a strategic crop in Peru due to its significant socioeconomic impact, driving extensive efforts to collect, characterize, and conserve its genetic diversity. This study aimed to establish phenotypic criteria to differentiate and structure the Cacao Amazonas Perú (CAP) germplasm, thereby providing [...] Read more.

Cacao is a strategic crop in Peru due to its significant socioeconomic impact, driving extensive efforts to collect, characterize, and conserve its genetic diversity. This study aimed to establish phenotypic criteria to differentiate and structure the Cacao Amazonas Perú (CAP) germplasm, thereby providing a foundation for selection and breeding programs. A total of 113 accessions from the INIA Germplasm Bank were evaluated over two consecutive growing seasons using 33 quantitative and 18 qualitative agromorphological descriptors. Data were analyzed through univariate and multivariate approaches. The results revealed substantial phenotypic variability, with coefficients of variation reaching up to 37.5% for fruit-related quantitative traits, all exhibiting high heritability values (>60%). Principal component analysis indicated that the first two components explained 29.3% of the total variance, primarily influenced by fruit and seed descriptors. Hierarchical clustering analysis identified eight phenotypic groups; one cluster exhibited high seed mass and a favorable pod index (17.63), while another showed the highest seed index (1.55 g) and the greatest intragroup distance (7.54). This comprehensive characterization highlights accessions with superior agronomic and bioactive potential, providing a robust framework for parental selection, core collection development, and targeted breeding strategies to enhance cacao competitiveness and resilience under changing climatic conditions. Full article

(This article belongs to the Special Issue Characterization and Conservation of Vegetable Genetic Resources)

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26 pages, 4060 KB

Open AccessReview

A Research Review of Rolling Bearing Turbocharger Modeling and System Characteristics

by Zhiheng Yu, Zhiyong Zhang, Jinrui Pu, Qi Xue, Yuanhao Li and Tianyou Wang

Machines 2025, 13(11), 1066; https://doi.org/10.3390/machines13111066 (registering DOI) - 19 Nov 2025

Abstract

In recent years, due to the growing imbalance between energy consumption and available resources, as well as strict CO₂ emission regulations, turbochargers have become increasingly important in applications such as automobiles, ships, and aerospace. Turbochargers can effectively increase the intake volume of [...] Read more.

In recent years, due to the growing imbalance between energy consumption and available resources, as well as strict CO₂ emission regulations, turbochargers have become increasingly important in applications such as automobiles, ships, and aerospace. Turbochargers can effectively increase the intake volume of engine cylinders, improving fuel combustion efficiency and engine power. In order to meet the growing demand for more energy-efficient, lower-carbon-emission systems, it is necessary to design more compact, efficient, durable, and affordable supercharging systems. Compared with traditional floating ring bearings, rolling bearing turbochargers have become a greater focus of research due to their excellent transient performance, low friction loss, and strong load-bearing capacity. Due to the large number of components, complex structure, lightweight high-load rotor, complicated operating conditions, and unclear nonlinear vibration mechanism of rolling bearing turbochargers, it is necessary to establish a refined model to clarify how factors such as bearing and squeeze film damper parameters and rotor operating parameters affect the system response. Therefore, this study reviews relevant research in this field from the perspectives of modeling and system characteristics and points out directions for future research. Full article

(This article belongs to the Section Turbomachinery)

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13 pages, 968 KB

Open AccessArticle

Differential Soil Organic Carbon Accumulation Patterns Following Cropland-to-Grassland Conversion in Non-Saline and Saline–Alkali Soils

by Jinglei Zhang, Shanshan Bai, Chunlin Jia, Lele Kang, Yuxue Zhang, Cong Guan, Jinhong Zhang, Daniel Horacio Basigalup, Bo Wu and Guoliang Wang

Agriculture 2025, 15(22), 2393; https://doi.org/10.3390/agriculture15222393 (registering DOI) - 19 Nov 2025

Abstract

Agricultural expansion and intensification generally lead to a depletion in soil organic carbon (SOC). While converting cropland to grassland is a recognized strategy for SOC accumulation, the patterns of SOC accumulation under different grassland types and soil conditions remain unclear. This study evaluated [...] Read more.

Agricultural expansion and intensification generally lead to a depletion in soil organic carbon (SOC). While converting cropland to grassland is a recognized strategy for SOC accumulation, the patterns of SOC accumulation under different grassland types and soil conditions remain unclear. This study evaluated the long-term effects of two perennial grasses—alfalfa (a legume) and switchgrass (a non-legume)—on SOC composition, specifically lignin phenols and amino sugars, in non-saline and saline–alkali soils, using a conventional wheat–maize rotation as a control. Our results showed that both alfalfa and switchgrass significantly enhanced SOC content compared to a wheat–maize rotation, but their accumulation pathways differed between non-saline and saline–alkali soils. In non-saline soils, increases in both lignin phenols and amino sugars (muramic acid and glucosamine) were observed under both perennial grasses. In saline–alkali soils, however, the accumulation was primarily driven by glucosamine. While no significant difference was observed in amino sugars content between the two grasses, switchgrass showed significantly higher lignin phenols content than alfalfa under saline–alkali conditions. This indicated that litter quality regulated the accumulation of plant-derived C in saline–alkali environments, but has no significant impact on the accumulation of microbial-derived C. These findings elucidate the divergent mechanisms that drive SOC sequestration following cropland-to-grassland conversion in contrasting non-saline and saline–alkali soils, highlight the dominant role of microbial processes in SOC accumulation following such conversion. Full article

(This article belongs to the Section Agricultural Soils)

19 pages, 7236 KB

Open AccessArticle

Study of the Particle Breakage Characteristics of Coral Sand Under the Effect of Freezing–Seepage Coupling

by Jie Zhou, Xiangzhen Kong, Huade Zhou, Chao Ban, Chengjun Liu and Jun Hu

Appl. Sci. 2025, 15(22), 12301; https://doi.org/10.3390/app152212301 (registering DOI) - 19 Nov 2025

Abstract

In the development and construction of the South China Sea (SCS), coral sand is a kind of common natural construction material. Sanya submarine tunnel is the first application of artificial ground freezing (AGF) in the SCS. Since the tunnel is located at an [...] Read more.

In the development and construction of the South China Sea (SCS), coral sand is a kind of common natural construction material. Sanya submarine tunnel is the first application of artificial ground freezing (AGF) in the SCS. Since the tunnel is located at an estuary, high-velocity seepage will have a significant influence on the particle characteristics of coral sand under freezing conditions. Therefore, taking coral sand from the SCS as the research object, the one-dimensional soil column unidirectional freezing test, particle sieving test, and scanning electron microscope (SEM, Hitachi High-Tech Corporation, Tokyo, Japan) test were carried out to investigate the particle breakage and temperature variation characteristics of coral sand under the coupling effect of freezing and seepage. The results show that under the coupling effect of freezing and seepage, coral sand particle breakage was significant. Under none-seepage and 0.5 m/d seepage velocity, the proportion of particles in the 0.5–2 mm size range in the frozen and phase transition zones decreased, while the proportion in the 0.125–0.5 mm size range increased. Through SEM analysis, the coupling effect of freezing and seepage caused serious damage to coral sand particles. Intense freezing could cause coral sand particles to break, while strong seepage could increase the roundness of particles. Seepage would affect the freezing rate and the final stabilization of the freezing temperature; when the seepage velocity was small (0–1.2 m/d), the impact of seepage was not obvious, and when seepage rate was larger (3 m/d), the impact throughout the entire freezing process both reduced the freezing rate and increased the final stabilization of the temperature. This study can provide a reference basis for the research on particle characteristics of coral sand under the coupling effect of freezing and seepage and for engineering and construction in the SCS. Full article

(This article belongs to the Section Civil Engineering)

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33 pages, 5476 KB

Open AccessArticle

Improvement of Energy Performance of Glass Furnaces Using Modelling and Optimization Techniques

by Onur Kodak, Miraç Burak Kaya, Farshid Sadeghi-Khaneghah, Emre Dumankaya, Gizem Yumru Alanat, Levent Kılıç, Neşet Arzan and Alp Er S. Konukman

Processes 2025, 13(11), 3739; https://doi.org/10.3390/pr13113739 (registering DOI) - 19 Nov 2025

Abstract

Glass furnaces are a key component of the energy-intensive glass industry. Therefore, optimization of their energy performance is crucial for both economic and environmental sustainability. This study focused on optimizing the performance of an electric-boosted natural gas glass furnace. For this purpose, firstly, [...] Read more.

Glass furnaces are a key component of the energy-intensive glass industry. Therefore, optimization of their energy performance is crucial for both economic and environmental sustainability. This study focused on optimizing the performance of an electric-boosted natural gas glass furnace. For this purpose, firstly, raw operational data were collected from a glass furnace. Next, reconciled data were obtained via a modelling process, data reconciliation, and gross error detection to establish a reliable dataset. Two linear regression models were developed and tested using both raw and reconciled data and compared with each other. The constrained optimization problem was constructed using a linear regression model and other process constraints and solved via the interior-point method to minimize specific energy consumption. The findings indicate that the reconciled data-based linear regression model yielded more reliable results. The specific energy consumption can be reduced to a minimum of 3660.088 kJ/kg-glass under an optimal setpoint for raw material, cullet, water, raw material temperature, electric boosting, and fuel. Furthermore, the analysis reveals that energy performance is enhanced with increased glass production and greater utilization of electric boosting. These results emphasize that the integrated statistical modelling approach provides valuable and actionable insights for energy performance improvements in the glass industry. Full article

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

45 pages, 3378 KB

Open AccessReview

Advances in Cytotoxicity Testing: From In Vitro Assays to In Silico Models

by Barbara Ziemba

Int. J. Mol. Sci. 2025, 26(22), 11202; https://doi.org/10.3390/ijms262211202 (registering DOI) - 19 Nov 2025

Abstract

Cytotoxicity testing remains a cornerstone of modern toxicology, providing critical insight into how chemicals and drugs affect cell viability and function. Classical colorimetric assays such as MTT, LDH release, and neutral red uptake established the methodological basis of in vitro toxicology and continue [...] Read more.

Cytotoxicity testing remains a cornerstone of modern toxicology, providing critical insight into how chemicals and drugs affect cell viability and function. Classical colorimetric assays such as MTT, LDH release, and neutral red uptake established the methodological basis of in vitro toxicology and continue to serve as regulatory benchmarks. However, their limited mechanistic depth and physiological relevance have prompted the field to evolve towards more predictive and human-centred approaches. Recent advances in high-content imaging, flow cytometry, and real-time impedance analysis have transformed cytotoxicity testing into a multiparametric discipline capable of detecting adaptive and sub-lethal cellular responses. Parallel progress in computational toxicology has introduced in silico models—QSAR, machine learning, and physiologically based pharmacokinetic (PBPK) modelling—that enable quantitative in vitro–in vivo extrapolation (QIVIVE). The integration of these computational tools with 3D organoids, organ-on-chip systems, and stem cell-based models allows for cross-validation between predictive simulations and experimental evidence, enhancing mechanistic interpretation and translational accuracy. Together, these developments underpin New Approach Methodologies (NAMs) and Integrated Approaches to Testing and Assessment (IATA), marking the transition from descriptive assays to predictive, mechanism-anchored frameworks that bridge in silico prediction with in vitro and in vivo validation—advancing both biomedical research and regulatory toxicology. Full article

(This article belongs to the Collection Latest Review Papers in Molecular Toxicology)

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25 pages, 1371 KB

Open AccessArticle

Development of an Ergonomic Additively Manufactured Modular Saddle for Rehabilitation Cycling

by Alberto Iglesias Calcedo, Chiara Bregoli, Valentina Abbate, Marta Mondellini, Jacopo Fiocchi, Gennaro Rollo, Cristina De Capitani, Marino Lavorgna, Marco Sacco, Andrea Sorrentino, Ausonio Tuissi, Carlo Alberto Biffi and Alfredo Ronca

Materials 2025, 18(22), 5242; https://doi.org/10.3390/ma18225242 (registering DOI) - 19 Nov 2025

Abstract

This work reports the design, fabrication, and validation of a modular ergonomic saddle for rehabilitation cycling, developed through a combined additive manufacturing approach. The saddle consists of a metallic support produced by Laser Powder Bed Fusion (LPBF) in AISI 316L stainless steel and [...] Read more.

This work reports the design, fabrication, and validation of a modular ergonomic saddle for rehabilitation cycling, developed through a combined additive manufacturing approach. The saddle consists of a metallic support produced by Laser Powder Bed Fusion (LPBF) in AISI 316L stainless steel and a polymeric ergonomic covering fabricated via Selective Laser Sintering (SLS) using thermoplastic polyurethane (TPU). A preliminary material screening between TPU and polypropylene (PP) was conducted, with TPU selected for its superior elastic response, energy dissipation, and more favourable SLS processability, as confirmed by thermal analyses. A series of gyroid lattice configurations with varying cell sizes and wall thicknesses were designed and mechanically tested. Cyclic testing under both stress- and displacement-controlled conditions demonstrated that the configuration with 8 mm cell size and 0.3 mm wall thickness provided the best balance between compliance and stability, showing minimal permanent deformation after 10,000 cycles and stable force response under repeated displacements. Finite Element Method (FEM) simulations, parameterized using experimentally derived elastic and density data, correlated well with the mechanical results, correlated with the mechanical results, supporting comparative stiffness evaluation. Moreover, a cost model focused on the customizable TPU component confirmed the economic viability of the modular approach, where the metallic base remains a reusable standard. Finally, the modular saddle was fabricated and successfully mounted on a cycle ergometer, demonstrating functional feasibility. Full article

(This article belongs to the Special Issue Additive Manufacturing and Forming Technologies of Alloy: Mechanical Properties and Microstructure Evaluation)

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15 pages, 1224 KB

Open AccessArticle

Low-Temperature RF Magnetron Sputtering of TiW Thin Films: Effects of the Bulk Plasma Characteristics on Film Growth

by Chiyun Bang, Chang Yeong Ji and Ju-Hong Cha

Appl. Sci. 2025, 15(22), 12300; https://doi.org/10.3390/app152212300 (registering DOI) - 19 Nov 2025

Abstract

TiW thin films with superior surface properties were deposited at room temperature using RF magnetron sputtering under low-temperature process conditions. The correlation between bulk plasma characteristics and thin-film properties was investigated as a function of applied RF power (200–600 W) and process pressure [...] Read more.

TiW thin films with superior surface properties were deposited at room temperature using RF magnetron sputtering under low-temperature process conditions. The correlation between bulk plasma characteristics and thin-film properties was investigated as a function of applied RF power (200–600 W) and process pressure (1–10 mTorr). Plasma potential and ion density were measured using a Langmuir probe, while deposition rate, surface roughness, sheet resistance, and crystallinity were evaluated. Increasing the applied RF power simultaneously increased plasma potential and ion density, enhancing ion bombardment energy at both the target and substrate, which improved sputtering efficiency and deposition rate. Under low-temperature deposition, thermal stress induced by differences in thermal expansion between the film and substrate was minimal. However, limited surface diffusion of adatoms caused incomplete coalescence of nucleation islands, adversely affecting film crystallinity. Refractory metals such as tungsten exhibit strong dependence of residual stress and microstructure on deposition conditions, highlighting the importance of plasma and process parameters on TiW film properties. When RF power was increased, the enhancement in deposition rate outweighed the effect of increased ion energy, leading to tensile stress from void formation dominating over compressive stress induced by high-energy ions. This also contributed to increased grain size and reduced sheet resistance. In contrast, variations in process pressure had minor effects on plasma characteristics, resulting in limited changes in the deposited film properties. Full article

(This article belongs to the Special Issue Plasma Applications in Material Processing)

20 pages, 2180 KB

Open AccessSystematic Review

Emotional Functioning as a Dimension of Quality of Life in Breast Cancer Survivors: A Systematic Review and Meta-Analysis

by Iryna Makhnevych, Mussab Ibrahim Mohamed Fadl Elseed, Ibrahim Mohamed Ahmed Musa and Yauhen Statsenko

Cancers 2025, 17(22), 3707; https://doi.org/10.3390/cancers17223707 (registering DOI) - 19 Nov 2025

Abstract

Background: As survival rates among breast cancer (BC) patients continue to rise, Emotional Functioning (EF)—has become increasingly clinically relevant; however, researchers have yet to fully characterize its long-term, dynamic trajectories following surgery. This systematic review and meta-analysis aimed to (1) characterize the [...] Read more.

Background: As survival rates among breast cancer (BC) patients continue to rise, Emotional Functioning (EF)—has become increasingly clinically relevant; however, researchers have yet to fully characterize its long-term, dynamic trajectories following surgery. This systematic review and meta-analysis aimed to (1) characterize the longitudinal trajectories of EF after BC surgery and (2) examine the moderating effects of surgical modality and age. Methods: We conducted this systematic review and meta-analysis in accordance with PRISMA 2020 guidelines. We synthesized data from studies published between 2000 and 2024 that assessed EF using the EORTC QLQ-C30 at multiple post-surgical time points. Using multilevel random-effects meta-analytic models, we examined EF trajectories across 116 effect sizes derived from 40 studies, and evaluated time, surgical modality (breast-conserving surgery (BCS), mastectomy (MA), mastectomy with immediate reconstruction (Mx + IR) and age group as moderators. Results: The overall pooled estimate for EF was 73.44 (95% CI: 70.29–76.58, p < 0.001). Time since surgery significantly influenced EF: scores were lowest during the initial 6 months (66.82, 95% CI: 59.75–73.89), peaked at 7–15 months (77.86, 95% CI: 74.51–81.22) and 31–54 months (77.52, 95% CI: 70.44–84.59), and showed lower values at 16–30 months (72.58, 95% CI: 61.45–83.72) and 55–72 months (69.81, 95% CI: 64.08–75.54). Surgical modality significantly shaped these trajectories (p = 0.013). The overall pooled estimate for EF was 73.44 (95% CI: 70.29–76.58, p < 0.001). Time since surgery significantly influenced EF: scores were lowest during the initial 6 months (66.82, 95% CI: 59.75–73.89), peaked at 7–15 months (77.86, 95% CI: 74.51–81.22) and 31–54 months (77.52, 95% CI: 70.44–84.59), and showed lower values at 16–30 months (72.58, 95% CI: 61.45–83.72) and 55–72 months (69.81, 95% CI: 64.08–75.54). Surgical modality significantly shaped these trajectories (p = 0.013). The BCS group showed a significant inverted-U trajectory in EF scores, with a positive linear slope (β = 1.22, SE = 0.50, p = 0.046) and a small negative quadratic term (β = −0.02, SE = 0.01, p = 0.046), indicating initial improvement followed by decline. A similar pattern was observed for MA, where the linear term (β = 1.19, SE = 0.51, p = 0.054) and quadratic curvature (β = −0.02, SE = 0.01, p = 0.054) suggested an early rise with subsequent decline. In contrast, Mx + IR displayed a high intercept (β = 71.46, SE = 4.46, p < 0.001) but no significant trajectory over time (p = 0.582), indicating stability. The 45–60 year group demonstrated a significant inverted-U trajectory in EF scores, with a positive linear coefficient (β = 0.87, SE = 0.38, p = 0.067) and a negative quadratic coefficient (β = −0.01, SE = 0.01, p = 0.067), suggesting an early rise in emotional functioning followed by a subsequent decline. Participants <45 years also showed a significant inverted-U pattern, starting from a moderately high baseline (β = 67.56, SE = 4.26, p < 0.001) with a positive linear slope (β = 0.82, SE = 0.34, p = 0.051) and a negative quadratic curvature (β = −0.01, SE = 0.01, p = 0.051). In contrast, the >60 year group reported the highest baseline scores (β = 75.60, SE = 5.18, p < 0.001) with no significant trajectory, indicating overall stability. These findings confirm that EF follows a significant inverted-U trajectory (p < 0.001) and is influenced by time, surgical modality, and age. Full article

(This article belongs to the Section Systematic Review or Meta-Analysis in Cancer Research)

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