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20 pages, 2705 KiB

Open AccessArticle

Temperature and Depth Sensor Based on Fiber Bragg Gratings with Temperature-Compensated Structure in Marine Environment

by Xinyu Zhao, Chenxi Wei, Lina Zeng, Lu Li, Shengjie Liu, Li Sun, Zaijin Li, Hao Chen, Guojun Liu, Yi Qu, Zichun Le, Yingchao Li, Lianhe Li and Lin Li

Coatings 2025, 15(7), 795; https://doi.org/10.3390/coatings15070795 (registering DOI) - 6 Jul 2025

Abstract

A fiber Bragg grating (FBG)-based ocean temperature and depth sensor structure is proposed. The pressure sensing section employs a secondary sensitization design comprising a piston and the polycarbonate buffer, while the temperature sensing section utilizes an FBG encapsulated within a metal silver tube, [...] Read more.

A fiber Bragg grating (FBG)-based ocean temperature and depth sensor structure is proposed. The pressure sensing section employs a secondary sensitization design comprising a piston and the polycarbonate buffer, while the temperature sensing section utilizes an FBG encapsulated within a metal silver tube, accompanied by a temperature compensation structure. Simulation analyses verify the enhanced sensitivity of the proposed configuration. By selecting suitable materials for the piston, metal tube, and polymer, and optimizing the dimensions of key components, the sensitivity of the bare FBG sensor is significantly improved through the combined effects of the piston, polymer, and metal tube. After optimization, the sensor exhibits a pressure sensitivity of 1.33 nm/MPa and a temperature sensitivity of 102.77 pm/°C, meeting the high-precision detection requirements for ocean temperature and depth sensing. The experimental results show that the temperature sensitivity is 109.9 pm/°C within the temperature range of −5~35 °C, and that the pressure sensitivity is 1.63 nm/MPa within the pressure range of 1~10 MPa. These results confirm that the sensor is well-suited for high-precision ocean temperature and depth measurements. Full article

(This article belongs to the Section Laser Coatings)

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17 pages, 10435 KiB

Open AccessArticle

Analysis and Optimization of Rotationally Symmetric Au-Ag Alloy Nanoparticles for Refractive Index Sensing Properties Using T-Matrix Method

by Long Cheng, Shuhong Gong and Paerhatijiang Tuersun

Nanomaterials 2025, 15(13), 1052; https://doi.org/10.3390/nano15131052 (registering DOI) - 6 Jul 2025

Abstract

Previous investigations devoted to non-spherical nanoparticles for biosensing have primarily addressed two hot topics, namely, finding nanoparticles with the best shape for refractive index sensing properties and the optimization of size parameters. In this study, based on these hot topics, Au-Ag alloy nanoparticles [...] Read more.

Previous investigations devoted to non-spherical nanoparticles for biosensing have primarily addressed two hot topics, namely, finding nanoparticles with the best shape for refractive index sensing properties and the optimization of size parameters. In this study, based on these hot topics, Au-Ag alloy nanoparticles with excellent optical properties were selected as the research object. Targeting rotationally symmetric Au-Ag alloy nanoparticles for biosensing applications, the complex media function correction model and T-matrix approach were used to systematically analyze the variation patterns of extinction properties, refractive index sensitivity, full width at half maximum, and figure of merit of three rotationally symmetric Au-Ag alloy nanoparticles with respect to the size of the particles and the Au molar fraction. In addition, we optimized the figure of merit to obtain the best size parameters and Au molar fractions for the three rotationally symmetric Au-Ag alloy nanoparticles. Finally, the range of dimensional parameters corresponding to a figure of merit greater than 98% of its maximum value was calculated. The results show that the optimized Au-Ag alloy nanorods exhibit a refractive index sensitivity of 395.2 nm/RIU, a figure of merit of 7.16, and a wide range of size parameters. Therefore, the optimized Au-Ag alloy nanorods can be used as high-performance biosensors. Furthermore, this study provides theoretical guidance for the application and preparation of rotationally symmetric Au-Ag alloy nanoparticles in biosensing. Full article

(This article belongs to the Special Issue Theoretical Calculation Study of Nanomaterials: 2nd Edition)

23 pages, 969 KiB

Open AccessArticle

Study on Multi-Objective Optimization of Construction of Yellow River Grand Bridge

by Jing Hu, Jinke Ji, Mengyuan Wang and Qingfu Li

Buildings 2025, 15(13), 2371; https://doi.org/10.3390/buildings15132371 (registering DOI) - 6 Jul 2025

Abstract

As an important transportation hub connecting the two sides of the Yellow River, the Yellow River Grand Bridge is of great significance for strengthening regional exchanges and promoting the high-quality development of the Yellow River Basin. However, due to the complex terrain, changeable [...] Read more.

As an important transportation hub connecting the two sides of the Yellow River, the Yellow River Grand Bridge is of great significance for strengthening regional exchanges and promoting the high-quality development of the Yellow River Basin. However, due to the complex terrain, changeable climate, high sediment concentration, long construction duration, complicated process, strong dynamic, and many factors affecting construction. It often brings many problems, including low quality, waste of resources, and environmental pollution, which makes it difficult to achieve the balance of multiple objectives at the same time. Therefore, it is very important to carry out multi-objective optimization research on the construction of the Yellow River Grand Bridge. This paper takes the Yellow River Grand Bridge on a highway as the research object and combines the concept of “green construction” and the national policy of “carbon neutrality and carbon peaking” to construct six major construction projects, including construction time, cost, quality, environment, resources, and carbon emission. Then, according to the multi-attribute utility theory, the objectives of different attributes are normalized, and the multi-objective equilibrium optimization model of construction time-cost-quality-environment-resource-carbon emission of the Yellow River Grand Bridge is obtained; finally, in order to avoid the shortcomings of a single algorithm, the particle swarm optimization algorithm and the simulated annealing algorithm are combined to obtain the simulated annealing particle swarm optimization (SA-PSO) algorithm. The multi-objective equilibrium optimization model of the construction of the Yellow River Grand Bridge is solved. The optimization result is 108 days earlier than the construction period specified in the contract, which is 9.612 million yuan less than the maximum cost, 6.3% higher than the minimum quality level, 11.1% lower than the maximum environmental pollution level, 4.8% higher than the minimum resource-saving level, and 3.36 million tons lower than the maximum carbon emission level. It fully illustrates the effectiveness of the SA-PSO algorithm for solving multi-objective problems. Full article

(This article belongs to the Section Construction Management, and Computers & Digitization)

30 pages, 1230 KiB

Open AccessArticle

Mathematical Model of Data Processing in a Personalized Search Recommendation System for Digital Collections

by Serhii Semenov, Wojciech Baran, Magdalena Andrzejewska, Maxim Pochebut, Inna Petrovska, Oksana Sitnikova, Marharyta Melnyk and Anastasiya Mekhovykh

Appl. Sci. 2025, 15(13), 7583; https://doi.org/10.3390/app15137583 (registering DOI) - 6 Jul 2025

Abstract

This paper presents a probabilistic-temporal modeling approach for analyzing data processing stages in a personalized recommendation system for digital heritage collections. The methodology is based on (Graphical Evaluation and Review Technique) GERT network formalism, which enables the representation of complex probabilistic workflows with [...] Read more.

This paper presents a probabilistic-temporal modeling approach for analyzing data processing stages in a personalized recommendation system for digital heritage collections. The methodology is based on (Graphical Evaluation and Review Technique) GERT network formalism, which enables the representation of complex probabilistic workflows with feedbacks and alternative branches. For each processing stage, corresponding GERT-schemes were developed, and equivalent transfer functions were derived. Using Laplace transform inversion techniques, probability density functions of processing time were recovered, followed by the calculation of key statistical metrics, including expectation, standard deviation, and quantiles. The results demonstrate that the proposed approach allows for detailed temporal performance evaluation, including the estimation of time exceedance probabilities at each stage. This provides a quantitative basis for optimizing recommendation system design and highlights the applicability of GERT-based modeling to intelligent data-driven services in the cultural domain. Full article

(This article belongs to the Special Issue Advanced Models and Algorithms for Recommender Systems)

19 pages, 2744 KiB

Open AccessArticle

Chaotic Behaviour, Sensitivity Assessment, and New Analytical Investigation to Find Novel Optical Soliton Solutions of M-Fractional Kuralay-II Equation

by J. R. M. Borhan, E. I. Hassan, Arafa Dawood, Khaled Aldwoah, Amani Idris A. Sayed, Ahmad Albaity and M. Mamun Miah

Mathematics 2025, 13(13), 2207; https://doi.org/10.3390/math13132207 (registering DOI) - 6 Jul 2025

Abstract

The implementation of chaotic behavior and a sensitivity assessment of the newly developed M-fractional Kuralay-II equation are the foremost objectives of the present study. This equation has significant possibilities in control systems, electrical circuits, seismic wave propagation, economic dynamics, groundwater flow, image and [...] Read more.

The implementation of chaotic behavior and a sensitivity assessment of the newly developed M-fractional Kuralay-II equation are the foremost objectives of the present study. This equation has significant possibilities in control systems, electrical circuits, seismic wave propagation, economic dynamics, groundwater flow, image and signal denoising, complex biological systems, optical fibers, plasma physics, population dynamics, and modern technology. These applications demonstrate the versatility and advantageousness of the stated model for complex systems in various scientific and engineering disciplines. One more essential objective of the present research is to find closed-form wave solutions of the assumed equation based on the

(\frac{G^{'}}{G^{'} + G + A})

-expansion approach. The results achieved are in exponential, rational, and trigonometric function forms. Our findings are more novel and also have an exclusive feature in comparison with the existing results. These discoveries substantially expand our understanding of nonlinear wave dynamics in various physical contexts in industry. By simply selecting suitable values of the parameters, three-dimensional (3D), contour, and two-dimensional (2D) illustrations are produced displaying the diagrammatic propagation of the constructed wave solutions that yield the singular periodic, anti-kink, kink, and singular kink-shape solitons. Future improvements to the model may also benefit from what has been obtained as well. The various assortments of solutions are provided by the described procedure. Finally, the framework proposed in this investigation addresses additional fractional nonlinear partial differential equations in mathematical physics and engineering with excellent reliability, quality of effectiveness, and ease of application. Full article

(This article belongs to the Special Issue Applications of Partial Differential Equations in Mathematical Physics, 2nd Edition)

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23 pages, 2022 KiB

Open AccessArticle

Impact of Slow-Forming Terraces on Erosion Control and Landscape Restoration in Central Africa’s Steep Slopes

by Jean Marie Vianney Nsabiyumva, Ciro Apollonio, Giulio Castelli, Elena Bresci, Andrea Petroselli, Mohamed Sabir, Cyrille Hicintuka and Federico Preti

Land 2025, 14(7), 1419; https://doi.org/10.3390/land14071419 (registering DOI) - 6 Jul 2025

Abstract

Large-scale land restoration projects require on-the-ground monitoring and evidence-based evaluation. This study, part of the World Bank Burundi Landscape Restoration and Resilience Project (in French: Projet de Restauration et de Résilience du Paysage du Burundi-PRRPB), examines the impact of slow-forming terraces on surface [...] Read more.

Large-scale land restoration projects require on-the-ground monitoring and evidence-based evaluation. This study, part of the World Bank Burundi Landscape Restoration and Resilience Project (in French: Projet de Restauration et de Résilience du Paysage du Burundi-PRRPB), examines the impact of slow-forming terraces on surface conditions and erosion in Isare (Mumirwa) and Buhinyuza (Eastern Depressions), Burundi. Slow-forming, or progressive, terraces were installed on 16 December 2022 (Isare) and 30 December 2022 (Buhinyuza), featuring ditches and soil bunds to enhance soil and water conservation. Twelve plots were established, with 132 measurement pins, of which 72 were in non-terraced plots (n_PT) and 60 were in terraced plots (PT). Monthly measurements, conducted until May 2023, assessed erosion reduction, surface conditions, roughness, and soil thickness. Terracing reduced soil loss by 54% in Isare and 9% in Buhinyuza, though sediment accumulation in ditches was excessive, especially in n_PT. Anti-erosion ditches improved surface stability by reducing slope length, lowering erosion and runoff. Covered Surface (CoS%) exceeded 95%, while Opened Surface (OS%) and Bare Surface (BS%) declined significantly. At Isare, OS% dropped from 97% to 80%, and BS% from 96% to 3% in PT. Similar trends appeared in Buhinyuza. Findings highlight PRRPB effectiveness in this short-term timeframe, and provide insights for soil conservation in steep-slope regions of Central Africa. Full article

(This article belongs to the Special Issue Vegetation Facing Environmental Changes in Terrestrial Systems: Research, Management and Education)

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12 pages, 582 KiB

Open AccessArticle

Urinary Inflammatory and Oxidative Stress Biomarkers as Indicators for the Clinical Management of Benign Prostatic Hyperplasia

by Yuan-Hong Jiang, Jimmy Lee, Hann-Chorng Kuo and Ya-Hui Wu

Int. J. Mol. Sci. 2025, 26(13), 6516; https://doi.org/10.3390/ijms26136516 (registering DOI) - 6 Jul 2025

Abstract

Oxidative stress and hypoxia-induced inflammation contribute to benign prostatic hyperplasia (BPH) progression. This study investigated the roles of urinary inflammatory and oxidative stress biomarkers in BPH patients. This prospective study enrolled 62 clinical BPH patients (33 treated medically, 29 surgically) and 20 controls. [...] Read more.

Oxidative stress and hypoxia-induced inflammation contribute to benign prostatic hyperplasia (BPH) progression. This study investigated the roles of urinary inflammatory and oxidative stress biomarkers in BPH patients. This prospective study enrolled 62 clinical BPH patients (33 treated medically, 29 surgically) and 20 controls. Symptom scores, uroflowmetry, and urinary biomarker levels were assessed at baseline and three months post-treatment. Before treatment, BPH patients exhibited elevated urinary levels of total antioxidant capacity (TAC), PGE2, IL-1β, and IL-6. Post-treatment, successful outcomes were reported in 63.6% of the medical treatment group and 86.2% of the surgical treatment group, with improvements in symptom scores and urinary flow rate, along with reductions in urinary 8-isoprostane, TAC, and IL-1β. Prior to treatment, voiding efficiency (VE) was negatively correlated with urinary IL-1β, IL-6, and IL-8 levels, while bladder wall thickness was positively correlated with TAC. After treatment, changes in VE were negatively correlated with changes in IL-1β, and changes in post-void residual urine were positively correlated with changes in IL-1β, IL-6, IL-8, and TNF-α. Urinary inflammatory and oxidative stress biomarkers may serve as non-invasive indicators of disease severity and treatment response in clinical BPH. Their significant correlations with clinical improvements underscore their potential utility in monitoring treatment efficacy. Full article

(This article belongs to the Special Issue Oxidative Stress and Inflammation in Health and Disease)

71 pages, 8428 KiB

Open AccessArticle

Bridging Sustainability and Inclusion: Financial Access in the Environmental, Social, and Governance Landscape

by Carlo Drago, Alberto Costantiello, Massimo Arnone and Angelo Leogrande

J. Risk Financial Manag. 2025, 18(7), 375; https://doi.org/10.3390/jrfm18070375 (registering DOI) - 6 Jul 2025

Abstract

In this work, we examine the correlation between financial inclusion and the Environmental, Social, and Governance (ESG) factors of sustainable development with the assistance of an exhaustive panel dataset of 103 emerging and developing economies spanning 2011 to 2022. The “Account Age” variable, [...] Read more.

In this work, we examine the correlation between financial inclusion and the Environmental, Social, and Governance (ESG) factors of sustainable development with the assistance of an exhaustive panel dataset of 103 emerging and developing economies spanning 2011 to 2022. The “Account Age” variable, standing for financial inclusion, is the share of adults owning accounts with formal financial institutions or with the providers of mobile money services, inclusive of both conventional and digital entry points. Methodologically, the article follows an econometric approach with panel data regressions, supplemented by Two-Stage Least Squares (2SLS) with instrumental variables in order to control endogeneity biases. ESG-specific instruments like climate resilience indicators and digital penetration measures are utilized for the purpose of robustness. As a companion approach, the paper follows machine learning techniques, applying a set of algorithms either for regression or for clustering for the purpose of detecting non-linearities and discerning ESG-inclusion typologies for the sample of countries. Results reflect that financial inclusion is, in the Environmental pillar, significantly associated with contemporary sustainability activity such as consumption of green energy, extent of protected area, and value added by agriculture, while reliance on traditional agriculture, measured by land use and value added by agriculture, decreases inclusion. For the Social pillar, expenditure on education, internet, sanitation, and gender equity are prominent inclusion facilitators, while engagement with the informal labor market exhibits a suppressing function. For the Governance pillar, anti-corruption activity and patent filing activity are inclusive, while diminishing regulatory quality, possibly by way of digital governance gaps, has a negative correlation. Policy implications are substantial: the research suggests that development dividends from a multi-dimensional approach can be had through enhancing financial inclusion. Policies that intersect financial access with upgrading the environment, social expenditure, and institutional reconstitution can simultaneously support sustainability targets. These are the most applicable lessons for the policy-makers and development professionals concerned with the attainment of the SDGs, specifically over the regions of the Global South, where the trinity of climate resilience, social fairness, and institutional renovation most significantly manifests. Full article

(This article belongs to the Special Issue Financial Inclusion Strategies: Emerging Trends and Global Perspectives)

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31 pages, 5414 KiB

Open AccessReview

Psychopharmacological Therapy Positively Modulates Disease Activity in Inflammatory Bowel Disease: A Systematic Review

by Federica Di Vincenzo, Antonio Maria D’Onofrio, Angelo Del Gaudio, Elena Chiera, Gaspare Filippo Ferrajoli, Francesco Pesaresi, Alessio Simonetti, Marianna Mazza, Georgios Demetrios Kotzalidis, Mauro Pettorruso, Giovanni Martinotti, Loris Riccardo Lopetuso, Antonio Gasbarrini, Gabriele Sani, Gionata Fiorino, Franco Scaldaferri and Giovanni Camardese

Int. J. Mol. Sci. 2025, 26(13), 6514; https://doi.org/10.3390/ijms26136514 (registering DOI) - 6 Jul 2025

Abstract

Depression, anxiety, and perceived stress are common comorbidities in patients with inflammatory bowel disease (IBD) and may negatively influence the disease course. Likewise, severe IBD may contribute to the development or worsening of psychiatric symptoms. Despite the established relevance of the gut–brain axis [...] Read more.

Depression, anxiety, and perceived stress are common comorbidities in patients with inflammatory bowel disease (IBD) and may negatively influence the disease course. Likewise, severe IBD may contribute to the development or worsening of psychiatric symptoms. Despite the established relevance of the gut–brain axis and frequent use of psychotropic medications in IBD patients, limited evidence exists regarding the effects of psychiatric treatments on gastrointestinal disease activity. Therefore, the aim of this systematic review is to evaluate the effectiveness of psychiatric therapies on gastrointestinal symptoms and disease activity in patients with IBD. The work was conducted in accordance with PRISMA guidelines. Searches were performed across PubMed, Web of Science, and Scopus up to July 2024. Eligible studies evaluated the effectiveness of psychiatric medications—including antidepressants, antipsychotics, anxiolytics, sedative-hypnotics, mood stabilizers, anticonvulsants, and others—on at least one gastrointestinal outcome in patients with IBD. Outcomes included changes in commonly used clinical and endoscopic scores for Crohn’s disease (CD) and ulcerative colitis (UC), number of bowel movements, stool consistency, presence of blood in stool, severity of abdominal pain, as well as in surrogate markers of disease activity following treatment. Out of 8513 initially identified articles, 22 studies involving 45,572 IBD patients met the inclusion criteria. Antidepressants, particularly bupropion, tricyclic antidepressants, selective serotonin reuptake inhibitors (SSRIs), venlafaxine, and duloxetine, were associated with improvements in IBD activity scores, including Crohn’s Disease Activity Index (CDAI) and Simple Endoscopic Score for Crohn’s Disease (SES-CD) for CD, Mayo score and Ulcerative Colitis Endoscopic Index of Severity (UCEIS) for UC. Case reports highlighted potential benefits of pregabalin and lithium carbonate, respectively, showed by the reduction in clinical and endoscopic score of disease activity for pregabalin and improvement of UC symptoms for lithium carbonate, while topiramate showed limited efficacy. Clonidine and naltrexone determined the reductions in clinical and endoscopic score of disease activity, including CDAI and Crohn’s disease endoscopy index severity score (CDEIS) for CD and Disease Activity Index (DAI) for UC. Despite the limited data and study heterogeneity, antidepressants, naltrexone, and clonidine were associated with improvements in IBD activity. Larger, prospective studies are needed to confirm the therapeutic potential of psychiatric medications in modulating IBD activity and to guide integrated clinical management. Full article

(This article belongs to the Section Molecular Immunology)

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29 pages, 1992 KiB

Open AccessArticle

An Efficient Sparse Twin Parametric Insensitive Support Vector Regression Model

by Shuanghong Qu, Yushan Guo, Renato De Leone, Min Huang and Pu Li

Mathematics 2025, 13(13), 2206; https://doi.org/10.3390/math13132206 (registering DOI) - 6 Jul 2025

Abstract

This paper proposes a novel sparse twin parametric insensitive support vector regression (STPISVR) model, designed to enhance sparsity and improve generalization performance. Similar to twin parametric insensitive support vector regression (TPISVR), STPISVR constructs a pair of nonparallel parametric insensitive bound functions to indirectly [...] Read more.

This paper proposes a novel sparse twin parametric insensitive support vector regression (STPISVR) model, designed to enhance sparsity and improve generalization performance. Similar to twin parametric insensitive support vector regression (TPISVR), STPISVR constructs a pair of nonparallel parametric insensitive bound functions to indirectly determine the regression function. The optimization problems are reformulated as two sparse linear programming problems (LPPs), rather than traditional quadratic programming problems (QPPs). The two LPPs are originally derived from initial L1-norm regularization terms imposed on their respective dual variables, which are simplified to constants via the Karush–Kuhn–Tucker (KKT) conditions and consequently disappear. This simplification reduces model complexity, while the constraints constructed through the KKT conditions—particularly their geometric properties—effectively ensure sparsity. Moreover, a two-stage hybrid tuning strategy—combining grid search for coarse parameter space exploration and Bayesian optimization for fine-grained convergence—is proposed to precisely select the optimal parameters, reducing tuning time and improving accuracy compared to a single-method strategy. Experimental results on synthetic and benchmark datasets demonstrate that STPISVR significantly reduces the number of support vectors (SVs), thereby improving prediction speed and achieving a favorable trade-off among prediction accuracy, sparsity, and computational efficiency. Overall, STPISVR enhances generalization ability, promotes sparsity, and improves prediction efficiency, making it a competitive tool for regression tasks, especially in handling complex data structures. Full article

16 pages, 1486 KiB

Open AccessArticle

Green Regenerative Bamboo Lignin-Based Epoxy Resin: Preparation, Curing Behavior, and Performance Characterization

by Jiayao Yang, Jie Fei and Xingxing Wang

Sustainability 2025, 17(13), 6201; https://doi.org/10.3390/su17136201 (registering DOI) - 6 Jul 2025

Abstract

The dependence of conventional epoxy resins on fossil fuels and the environmental and health hazards associated with bisphenol A (BPA) demand the creation of sustainable alternatives. Because lignin is a natural resource and has an aromatic ring skeleton structure, it could be used [...] Read more.

The dependence of conventional epoxy resins on fossil fuels and the environmental and health hazards associated with bisphenol A (BPA) demand the creation of sustainable alternatives. Because lignin is a natural resource and has an aromatic ring skeleton structure, it could be used as an alternative to fossil fuels. This study effectively resolved this challenge by utilizing a sustainable one-step epoxidation process to transform lignin into a bio-based epoxy resin. The results verified the successful synthesis of epoxidized bamboo lignin through systematic characterization employing Fourier transform infrared spectroscopy, hydrogen spectroscopy/two-dimensional heteronuclear single-quantum coherent nuclear magnetic resonance, quantitative phosphorus spectroscopy, and gel permeation chromatography. Lignin-based epoxy resins had an epoxy equivalent value of 350–400 g/mol and a weight-average molecular weight of 4853 g/mol. Studies on the curing kinetics revealed that polyetheramine (PEA-230) demonstrated the lowest apparent activation energy (46.2 kJ/mol), signifying its enhanced curing efficiency and potential for energy conservation. Mechanical testing indicated that the PEA-230 cured network demonstrated the maximum tensile strength (>25 MPa), whereas high-molecular-weight polyetheramine (PEA-2000) imparted enhanced elongation to the material. Lignin-based epoxy resins demonstrated superior heat stability. This study demonstrates the conversion of bamboo lignin into bio-based epoxy resins using a simple, environmentally friendly synthesis process, demonstrating the potential to reduce fossil resource use, efficiently use waste, develop sustainable thermosetting materials, and promote a circular bioeconomy. Full article

18 pages, 1520 KiB

Open AccessArticle

Transitioning to Cleaner Transport: Evaluating the Environmental and Economic Performance of ICE, HEVs, and PHEVs in Bangladesh

by MD Shiyan Sadik, Md Ishmam Labib and Asma Safia Disha

World Electr. Veh. J. 2025, 16(7), 380; https://doi.org/10.3390/wevj16070380 (registering DOI) - 6 Jul 2025

Abstract

The transportation sector in South Asia largely depends on internal combustion engine (ICE) vehicles, which are responsible for a large share of greenhouse gas (GHG) emissions, air pollution, and the increase in fuel prices. Although hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles [...] Read more.

The transportation sector in South Asia largely depends on internal combustion engine (ICE) vehicles, which are responsible for a large share of greenhouse gas (GHG) emissions, air pollution, and the increase in fuel prices. Although hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and fully electric vehicles (EVs) constitute promising alternatives, the rate of their implementation is low due to factors such as the high initial investment, the absence of the required infrastructure, and the reliance on fossil fuel-based electricity. This study is the first of its kind to examine Bangladesh’s drivetrain options in a comprehensive way, with in-depth real-world emission testing and economic analysis as the main tools of investigation into the environmental and economic feasibility of different technologies used in the vehicles available in Bangladesh, including lifecycle costs and infrastructure constraints. The study findings have shown that hybrid and plug-in hybrid vehicles are the best options, since they have moderate emissions and cost efficiency, respectively. Fully electric vehicles, however, face two main challenges: the overall lack of charging infrastructure and the overall high purchase prices. Among the evaluated technologies, PHEVs exhibited the lowest environmental and economic burden. The Toyota Prius PHEV emitted 98% less NOx compared to the diesel-powered Pajero Sport and maintained the lowest per-kilometer cost at BDT 6.39. In contrast, diesel SUVs emitted 178 ppm NOx and cost 22.62 BDT/km, reinforcing the transitional advantage of plug-in hybrid technology in Bangladesh’s context. Full article

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26 pages, 23702 KiB

Open AccessArticle

Study on the Influence and Mechanism of Mineral Admixtures and Fibers on Frost Resistance of Slag–Yellow River Sediment Geopolymers

by Ge Zhang, Huawei Shi, Kunpeng Li, Jialing Li, Enhui Jiang, Chengfang Yuan and Chen Chen

Nanomaterials 2025, 15(13), 1051; https://doi.org/10.3390/nano15131051 (registering DOI) - 6 Jul 2025

Abstract

To address the demands for resource utilization of Yellow River sediment and the durability requirements of engineering materials in cold regions, this study systematically investigates the mechanisms affecting the frost resistance of slag-Yellow River sediment geopolymers through the incorporation of mineral admixtures (silica [...] Read more.

To address the demands for resource utilization of Yellow River sediment and the durability requirements of engineering materials in cold regions, this study systematically investigates the mechanisms affecting the frost resistance of slag-Yellow River sediment geopolymers through the incorporation of mineral admixtures (silica fume and metakaolin) and fibers (steel fiber and PVA fiber). Through 400 freeze-thaw cycles combined with microscopic characterization techniques such as SEM, XRD, and MIP, the results indicate that the group with 20% silica fume content (SF20) exhibited optimal frost resistance, showing a 19.9% increase in compressive strength after 400 freeze-thaw cycles. The high pozzolanic reactivity of SiO₂ in SF20 promoted continuous secondary gel formation, producing low C/S ratio C-(A)-S-H gels and increasing the gel pore content from 24% to 27%, thereby refining the pore structure. Due to their high elastic deformation capacity (6.5% elongation rate), PVA fibers effectively mitigate frost heave stress. At the same dosage, the compressive strength loss rate (6.18%) and splitting tensile strength loss rate (21.79%) of the PVA fiber-reinforced group were significantly lower than those of the steel fiber-reinforced group (9.03% and 27.81%, respectively). During the freeze-thaw process, the matrix pore structure exhibited a typical two-stage evolution characteristic of “refinement followed by coarsening”: In the initial stage (0–100 cycles), secondary hydration products from mineral admixtures filled pores, reducing the proportion of macropores by 5–7% and enhancing matrix densification; In the later stage (100–400 cycles), due to frost heave pressure and differences in thermal expansion coefficients between matrix phases (e.g., C-(A)-S-H gel and fibers), interfacial microcracks propagated, causing the proportion of macropores to increase back to 35–37%. This study reveals the synergistic interaction between mineral admixtures and fibers in enhancing freeze–thaw performance. It provides theoretical support for the high-value application of Yellow River sediment in F400-grade geopolymer composites. The findings have significant implications for infrastructure in cold regions, including subgrade materials, hydraulic structures, and related engineering applications. Full article

(This article belongs to the Special Issue Nanomaterials and Nanotechnology in Civil Engineering)

24 pages, 5821 KiB

Open AccessArticle

Quantification of Flavonoid Contents in Holy Basil Using Hyperspectral Imaging and Deep Learning Approaches

by Apichat Suratanee, Panita Chutimanukul and Kitiporn Plaimas

Appl. Sci. 2025, 15(13), 7582; https://doi.org/10.3390/app15137582 (registering DOI) - 6 Jul 2025

Abstract

Holy basil (Ocimum tenuiflorum L.) is a medicinal herb rich in bioactive flavonoids with therapeutic properties. Traditional quantification methods rely on time-consuming and destructive extraction processes, whereas hyperspectral imaging provides a rapid, non-destructive alternative by analysing spectral signatures. However, effectively linking hyperspectral [...] Read more.

Holy basil (Ocimum tenuiflorum L.) is a medicinal herb rich in bioactive flavonoids with therapeutic properties. Traditional quantification methods rely on time-consuming and destructive extraction processes, whereas hyperspectral imaging provides a rapid, non-destructive alternative by analysing spectral signatures. However, effectively linking hyperspectral data to flavonoid levels remains a challenge for developing early detection tools before harvest. This study integrates deep learning with hyperspectral imaging to quantify flavonoid contents in 113 samples from 26 Thai holy basil cultivars collected across diverse regions of Thailand. Two deep learning architectures, ResNet1D and CNN1D, were evaluated in combination with feature extraction techniques, including wavelet transformation and Gabor-like filtering. ResNet1D with wavelet transformation achieved optimal performance, yielding an area under the receiver operating characteristic curve (AUC) of 0.8246 and an accuracy of 0.7702 for flavonoid content classification. Cross-validation demonstrated the model’s robust predictive capability in identifying antioxidant-rich samples. Samples with the highest predicted flavonoid content were identified, and cultivars exhibiting elevated levels of both flavonoids and phenolics were highlighted across various regions of Thailand. These findings demonstrate the predictive capability of hyperspectral data combined with deep learning for phytochemical assessment. This approach offers a valuable tool for non-destructive quality evaluation and supports cultivar selection for higher phytochemical content in breeding programs and agricultural applications. Full article

(This article belongs to the Special Issue Emerging Analytical Techniques in Food Industry and Agricultural Products)

24 pages, 9084 KiB

Open AccessArticle

Early-Strength Controllable Geopolymeric CLSM Derived by Shield Tunneling Muck: Performance Optimization and Hydration Mechanism of GGBFS–CS Systems

by Jiguo Liu, Jun Zhang, Xiaohui Sun, Shutong Dong and Silin Wu

Buildings 2025, 15(13), 2373; https://doi.org/10.3390/buildings15132373 (registering DOI) - 6 Jul 2025

Abstract

The large-scale reuse of shield tunneling muck remains a major challenge in urban construction. This study proposes a geopolymeric-controlled low-strength material (GC-CLSM) utilizing shield tunneling muck as the primary raw material and a novel alkali-activated binder composed of ground granulated blast-furnace slag (GGBFS) [...] Read more.

The large-scale reuse of shield tunneling muck remains a major challenge in urban construction. This study proposes a geopolymeric-controlled low-strength material (GC-CLSM) utilizing shield tunneling muck as the primary raw material and a novel alkali-activated binder composed of ground granulated blast-furnace slag (GGBFS) and carbide slag (CS). Emphasis is placed on early-age strength development and its underlying mechanisms, which were often overlooked in previous CLSM studies. Among the tested mixtures, a GGBFS:CS ratio of 80:20 yielded the best balance between early and long-term strength. Its 1-day UCS reached 1.18–1.75 MPa, representing a 6.3–23.6-fold increase over the low-CS reference (90:10), which achieved only 0.05–0.31 MPa. However, excessive CS content (e.g., 60:40) led to a significant reduction in the 28-day strength—up to nearly 50% compared with the 90:10 mix—due to impaired microstructural densification. Microstructural analyses (pore-solution pH, SEM, EDS, XRD, FTIR, LF-NMR) confirmed that higher CS levels enhanced early C–A–S–H gel formation by increasing OH⁻ and Ca²⁺ availability while compromising long-term structure. Additionally, the GC-CLSM system reduced carbon emissions by 68.6–70.3% per ton of treated shield tunneling muck compared with conventional cement-based CLSM. Overall, this study offers a sustainable and performance-driven approach for the valorization of shield tunneling muck, enabling the development of early-strength controllable, low-carbon CLSM for infrastructure applications. Full article

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

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23 pages, 3988 KiB

Open AccessArticle

Research on Equivalent One-Dimensional Cylindrical Modeling Method for Lead–Bismuth Fast Reactor Fuel Assemblies

by Jinjie Xiao, Yongfa Zhang, Song Li, Ling Chen, Jiannan Li and Cong Zhang

Energies 2025, 18(13), 3564; https://doi.org/10.3390/en18133564 (registering DOI) - 6 Jul 2025

Abstract

The lead-cooled fast reactor (LFR), a Generation IV nuclear system candidate, presents unique neutronic characteristics distinct from pressurized water reactors. Its neutron spectrum spans wider energy ranges with fast neutron dominance, exhibiting resonance phenomena across energy regions. These features require a fine energy [...] Read more.

The lead-cooled fast reactor (LFR), a Generation IV nuclear system candidate, presents unique neutronic characteristics distinct from pressurized water reactors. Its neutron spectrum spans wider energy ranges with fast neutron dominance, exhibiting resonance phenomena across energy regions. These features require a fine energy group structure for fuel lattice calculations, significantly increasing computational demands. To balance local heterogeneity modeling with computational efficiency, researchers across the world adopt fuel assembly equivalence methods using 1D cylindrical models through volume equivalence principles. This approach enables detailed energy group calculations in simplified geometries, followed by lattice homogenization for few-group parameter generation, effectively reducing whole-core computational loads. However, limitations emerge when handling strongly heterogeneous components like structural/control rods. This study investigates the 1D equivalence method’s accuracy in lead–bismuth fast reactors under various fuel assembly configurations. Through comprehensive analysis of material distributions and their equivalence impacts, the applicability of the one-dimensional equivalence approach to fuel assemblies of different geometries and material types is analyzed in this paper. The research further proposes corrective solutions for low-accuracy scenarios, enhancing computational method reliability. This paper is significant in its optimization of the physical calculation and analysis process of a new type of fast reactor component and has important engineering application value. Full article

(This article belongs to the Section B4: Nuclear Energy)

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28 pages, 4148 KiB

Open AccessArticle

A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification

by Lilu Wang, Yongqi Li, Haiyuan Liu and Taihui Liu

Sensors 2025, 25(13), 4224; https://doi.org/10.3390/s25134224 (registering DOI) - 6 Jul 2025

Abstract

Remaining Useful Life (RUL) prediction is a crucial task in predictive maintenance. Currently, gated recurrent networks, hybrid models, and attention-enhanced models used for predictive maintenance face the challenge of balancing prediction accuracy and model lightweighting when extracting complex degradation features. This limitation hinders [...] Read more.

Remaining Useful Life (RUL) prediction is a crucial task in predictive maintenance. Currently, gated recurrent networks, hybrid models, and attention-enhanced models used for predictive maintenance face the challenge of balancing prediction accuracy and model lightweighting when extracting complex degradation features. This limitation hinders their deployment on resource-constrained edge devices. To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. TBiGNet features an encoder–decoder architecture that outperforms traditional Transformer models by achieving over 15% higher accuracy while reducing computational load, memory access, and parameter size by more than 98%. In the encoder, we optimize the attention mechanism by integrating the individual linear mappings of queries, keys, and values into an efficient operation, reducing memory access overhead by 60%. Additionally, an adaptive feature pruning module is introduced to dynamically select critical features based on their importance, reducing redundancy and enhancing model accuracy by 6%. The decoder innovatively fuses two different types of features and leverages BiGRU to compensate for the limitations of the attention mechanism in capturing degradation features, resulting in a 7% accuracy improvement. Extensive experiments on the C-MAPSS dataset demonstrate that TBiGNet surpasses existing methods in terms of computational accuracy, model size, and memory access, showcasing significant technical advantages and application potential. Experiments on the C-MPASS dataset show that TBiGNet is superior to the existing methods in terms of calculation accuracy, model size and throughput, showing significant technical advantages and application potential. Full article

(This article belongs to the Section Intelligent Sensors)

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26 pages, 4277 KiB

Open AccessReview

Research Progress of Heat Damage Prevention and Control Technology in Deep Mine

by Yujie Xu, Liu Chen, Jin Zhang and Haiwei Ji

Sustainability 2025, 17(13), 6200; https://doi.org/10.3390/su17136200 (registering DOI) - 6 Jul 2025

Abstract

As mine mining extends to greater depths, the challenge of heat damage in high-temperature and high-humidity deep mines has emerged as a significant obstacle to the safe mining of deep mines. This paper reviews the causes of mine heat damage, evaluates heat damage [...] Read more.

As mine mining extends to greater depths, the challenge of heat damage in high-temperature and high-humidity deep mines has emerged as a significant obstacle to the safe mining of deep mines. This paper reviews the causes of mine heat damage, evaluates heat damage mechanisms, and explores deep mine cooling technologies. Traditional deep mine cooling technologies employ mechanical refrigeration to cool air. While these technologies can mitigate heat damage, they are associated with issues including high energy consumption, insufficient dehumidification, and significant cold loss. To address the high energy consumption and fully utilize geothermal resources, heat pump technology and combined cooling, heating, and power technology are employed to recover waste heat from deep mines, thereby achieving efficient mine cooling and energy utilization. To enhance the effectiveness of air dehumidification, the integration of deep dehumidification with mine cooling technology addresses the high humidity ratio in mine working faces. To enhance the refrigeration capacity of the system, liquid-phase-change refrigeration technology is employed to boost the refrigeration capacity. For the future development of deep mine cooling technology, this paper identifies four key directions: the integration of diverse technologies, collaboration cooling and geothermal mining, deep dehumidification and cooling, and intelligent control. Full article

(This article belongs to the Section Energy Sustainability)

19 pages, 1474 KiB

Open AccessArticle

Ripe-Detection: A Lightweight Method for Strawberry Ripeness Detection

by Helong Yu, Cheng Qian, Zhenyang Chen, Jing Chen and Yuxin Zhao

Agronomy 2025, 15(7), 1645; https://doi.org/10.3390/agronomy15071645 (registering DOI) - 6 Jul 2025

Abstract

Strawberry (Fragaria × ananassa), a nutrient-dense fruit with significant economic value in commercial cultivation, faces critical detection challenges in automated harvesting due to complex growth conditions such as foliage occlusion and variable illumination. To address these limitations, this study proposes Ripe-Detection, [...] Read more.

Strawberry (Fragaria × ananassa), a nutrient-dense fruit with significant economic value in commercial cultivation, faces critical detection challenges in automated harvesting due to complex growth conditions such as foliage occlusion and variable illumination. To address these limitations, this study proposes Ripe-Detection, a novel lightweight object detection framework integrating three key innovations: a PEDblock detection head architecture with depth-adaptive feature learning capability, an ADown downsampling method for enhanced detail perception with reduced computational overhead, and BiFPN-based hierarchical feature fusion with learnable weighting mechanisms. Developed using a purpose-built dataset of 1,021 annotated strawberry images (Fragaria × ananassa ‘Red Face’ and ‘Sachinoka’ varieties) from Changchun Xiaohongmao Plantation and augmented through targeted strategies to enhance model robustness, the framework demonstrates superior performance over existing lightweight detectors, achieving mAP50 improvements of 13.0%, 9.2%, and 3.9% against YOLOv7-tiny, YOLOv10n, and YOLOv11n, respectively. Remarkably, the architecture attains 96.4% mAP50 with only 1.3M parameters (57% reduction from baseline) and 4.4 GFLOPs (46% lower computation), simultaneously enhancing accuracy while significantly reducing resource requirements, thereby providing a robust technical foundation for automated ripeness assessment and precision harvesting in agricultural robotics. Full article

(This article belongs to the Section Precision and Digital Agriculture)

34 pages, 5767 KiB

Open AccessArticle

Approach to Semantic Visual SLAM for Bionic Robots Based on Loop Closure Detection with Combinatorial Graph Entropy in Complex Dynamic Scenes

by Dazheng Wang and Jingwen Luo

Biomimetics 2025, 10(7), 446; https://doi.org/10.3390/biomimetics10070446 (registering DOI) - 6 Jul 2025

Abstract

In complex dynamic environments, the performance of SLAM systems on bionic robots is susceptible to interference from dynamic objects or structural changes in the environment. To address this problem, we propose a semantic visual SLAM (vSLAM) algorithm based on loop closure detection with [...] Read more.

In complex dynamic environments, the performance of SLAM systems on bionic robots is susceptible to interference from dynamic objects or structural changes in the environment. To address this problem, we propose a semantic visual SLAM (vSLAM) algorithm based on loop closure detection with combinatorial graph entropy. First, in terms of the dynamic feature detection results of YOLOv8-seg, the feature points at the edges of the dynamic object are finely judged by calculating the mean absolute deviation (MAD) of the depth of the pixel points. Then, a high-quality keyframe selection strategy is constructed by combining the semantic information, the average coordinates of the semantic objects, and the degree of variation in the dense region of feature points. Subsequently, the unweighted and weighted graphs of keyframes are constructed according to the distribution of feature points, characterization points, and semantic information, and then a high-performance loop closure detection method based on combinatorial graph entropy is developed. The experimental results show that our loop closure detection approach exhibits higher precision and recall in real scenes compared to the bag-of-words (BoW) model. Compared with ORB-SLAM2, the absolute trajectory accuracy in high-dynamic sequences improved by an average of 97.01%, while the number of extracted keyframes decreased by an average of 61.20%. Full article

(This article belongs to the Special Issue Artificial Intelligence for Autonomous Robots: 3rd Edition)

15 pages, 4634 KiB

Open AccessArticle

Two-Dimensional Geometry Representation Learning-Based Construction Workers Activities Detection with Flexible IMU Solution

by Hainan Chen, Guiwen Liu and Jianjun Li

Buildings 2025, 15(13), 2372; https://doi.org/10.3390/buildings15132372 (registering DOI) - 6 Jul 2025

Abstract

Recognizing construction workers’ activities is essential for effective construction management. The complexity of construction sites and the varied, dynamic nature of workers’ actions make automatic monitoring of their behaviors challenging. This study introduces a flexible IMU solution to detect construction worker activities, aiming [...] Read more.

Recognizing construction workers’ activities is essential for effective construction management. The complexity of construction sites and the varied, dynamic nature of workers’ actions make automatic monitoring of their behaviors challenging. This study introduces a flexible IMU solution to detect construction worker activities, aiming to bypass the need for IMU devices to be rigidly attached to workers. The approach employs a 2D geometric representation algorithm that extracts features at the application level, independent of the IMU axes. Evaluations using the VTT-ConIoT public dataset for construction worker activities demonstrated that the proposed method performed effectively without fixed IMU attachments, enhancing practicality in real-world contexts. Full article

(This article belongs to the Special Issue Innovation in Construction and Project Management: Digital Technologies, Intelligent Systems, and Sustainable Solutions)

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13 pages, 633 KiB

Open AccessArticle

Compound Salt-Based Coagulants for Tofu Gel Production: Balancing Quality and Protein Digestibility

by Zhaolu Li, Sisi Zhang, Zihan Gao, Xinyue Guo, Ruohan Wang, Maoqiang Zheng and Guangliang Xing

Gels 2025, 11(7), 524; https://doi.org/10.3390/gels11070524 (registering DOI) - 6 Jul 2025

Abstract

Tofu quality is critically influenced by coagulants, though their impact on protein digestibility remains underexplored. This study aimed to investigate the effects of calcium sulfate (CaSO₄), magnesium chloride (MgCl₂), and their combination (CaSO₄ + MgCl₂) on [...] Read more.

Tofu quality is critically influenced by coagulants, though their impact on protein digestibility remains underexplored. This study aimed to investigate the effects of calcium sulfate (CaSO₄), magnesium chloride (MgCl₂), and their combination (CaSO₄ + MgCl₂) on the physicochemical properties and protein digestibility of tofu. Water-holding capacity, cooking loss, texture, protein composition, and protein digestibility were analyzed. The results showed that the CaSO₄ + MgCl₂ combination yielded a water-holding capacity of 99.16%, significantly higher than CaSO₄ tofu (93.73%) and MgCl₂ tofu (96.82%), while reducing cooking loss to 2.03% and yielding the highest hardness (897.27 g) and gumminess (765.72). Electrophoresis revealed distinct protein retention patterns, with MgCl₂ (0.6% w/v) forming denser gels that minimized protein leakage into soy whey. During in vitro digestion, MgCl₂-coagulated tofu exhibited superior soluble protein release (5.33 mg/mL after gastric digestion) and higher intestinal peptide (5.89 mg/mL) and total amino acid (123.06 μmol/mL) levels, indicating enhanced digestibility. Conversely, the CaSO₄ + MgCl₂combination showed delayed proteolysis in electrophoresis analysis. These findings demonstrate that coagulant selection directly modulates tofu’s texture, water retention, and protein bioavailability, with MgCl₂ favoring digestibility and the hybrid coagulant optimizing physical properties. This provides strategic insights for developing nutritionally enhanced tofu products. Full article

(This article belongs to the Special Issue Food Gel-Based Systems: Gel-Forming and Food Applications)

16 pages, 470 KiB

Open AccessArticle

Factors Associated with Acceptance of Vaccination Against Human Papillomavirus in eThekwini District of South Africa

by Phelele Bhengu, Charles S. Wiysonge, Patrick D. M. C. Katoto, Duduzile Ndwandwe, Sara Cooper, Sebenzile Bhengu, Akhona V. Mazingisa, Theresa Saber, Mandisi Sithole, Darian Smith, Lindiwe G. Tembe, Paul Kuodi and Muki S. Shey

Vaccines 2025, 13(7), 732; https://doi.org/10.3390/vaccines13070732 (registering DOI) - 6 Jul 2025

Abstract

Background: South Africa launched a school-based human papillomavirus (HPV) vaccination programme in 2014 and has achieved a national coverage of more than 80%. However, there is subnational variation in coverage, with eThekwini District in the province of KwaZulu-Natal having the lowest coverage at [...] Read more.

Background: South Africa launched a school-based human papillomavirus (HPV) vaccination programme in 2014 and has achieved a national coverage of more than 80%. However, there is subnational variation in coverage, with eThekwini District in the province of KwaZulu-Natal having the lowest coverage at 40%. Knowledge of the factors associated with vaccine acceptance in this district would inform tailored strategies to improve coverage, which could be extrapolated to similar settings. We conducted this cross-sectional study to assess the factors associated with HPV vaccine acceptance in eThekwini District. Methods: We used stratified random sampling to select caregivers of children aged 9–14 years in the district. We interviewed participants in April–May 2023 and employed bivariate and multivariate logistic regression models to assess the factors associated with HPV vaccine acceptance. Results: Of 793 individuals contacted, 713 (89.9%) participated. Most were women (86.1%) and had a mean age of 42.6 ± 11.6 years and secondary or lower education (83.8%). Most participants knew about the HPV vaccination programme (86.0%) and accepted HPV vaccination (93.5%). The latter includes 42.9% who had already vaccinated their daughters and 50.6% who were willing to allow their daughters to be vaccinated. A negligible proportion was either undecided (2.1%) or unwilling (4.4%) to accept HPV vaccination. Awareness of the programme (adjusted odds ratio [aOR] 5.22; 95% confidence interval [95%CI] 2.01–13.56), confidence in vaccine safety (aOR 19.69; 95%CI 5.86–66.15), and endorsement by religious leaders (aOR 5.06; 95%CI 1.56–16.45) were independent predictors of vaccine acceptance. Conclusions: Our findings highlight the critical role of the provision of information and education about the benefits and safety of HPV vaccination. Full article

(This article belongs to the Special Issue Vaccination Strategies and Population Immunity)

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17 pages, 2430 KiB

Open AccessArticle

Multimodal Navigation and Virtual Companion System: A Wearable Device Assisting Blind People in Independent Travel

by Jingjing Xu, Caiyi Wang, Yancheng Li, Xuantuo Huang, Meina Zhao, Zhuoqun Shen, Yiding Liu, Yuxin Wan, Fengrong Sun, Jianhua Zhang and Shengyong Xu

Sensors 2025, 25(13), 4223; https://doi.org/10.3390/s25134223 (registering DOI) - 6 Jul 2025

Abstract

Visual impairment or even loss seriously affects quality of life. Benefited by the rapid development of sound/laser detection, Global Positioning System (GPS)/Beidou positioning, machine vision and other technologies, the quality of life of blind people is expected to be improved through visual substitution [...] Read more.

Visual impairment or even loss seriously affects quality of life. Benefited by the rapid development of sound/laser detection, Global Positioning System (GPS)/Beidou positioning, machine vision and other technologies, the quality of life of blind people is expected to be improved through visual substitution technology. The existing visual substitution devices still have limitations in terms of safety, robustness, and ease of operation. The remote companion system developed here fully utilizes multimodal navigation and remote communication technologies, and the positioning and interaction functions of commercial mobile phones. Together with the accumulated judgment of backend personnel, it can provide real-time, safe, and reliable navigation services for blind people, helping them complete daily activities such as independent travel, circulation, and shopping. The practical results show that the system not only has strong operability and is easy to use, but also can provide users with a strong sense of security and companionship, making it suitable for promotion. In the future, this system can also be promoted for other vulnerable groups such as the elderly. Full article

(This article belongs to the Section Wearables)

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14 pages, 685 KiB

Open AccessArticle

Sex-Based Risk Evaluation in Acute Coronary Events—A Study Conducted on an Eastern-European Population

by Svetlana Mosteoru, Nilima Rajpal Kundnani, Abhinav Sharma, Roxana Pleava, Laura Gaita and Dan Ion Gaiță

Medicina 2025, 61(7), 1227; https://doi.org/10.3390/medicina61071227 (registering DOI) - 6 Jul 2025

Abstract

Background and Objectives: Cardiovascular (CV) diseases account for about 32% of deaths in women, with differing risk factors between women and men. Our study aimed to compare sex-related risk factors and comorbidities in patients at very high CV risk. Materials and Methods: We [...] Read more.

Background and Objectives: Cardiovascular (CV) diseases account for about 32% of deaths in women, with differing risk factors between women and men. Our study aimed to compare sex-related risk factors and comorbidities in patients at very high CV risk. Materials and Methods: We consecutively enrolled adult patients hospitalized for myocardial infarction or unstable angina at a tertiary referral center in western Romania between October 2016 and June 2017. A total of 299 adults underwent clinical and biochemical evaluations between 6 months and 2 years after their coronary event. We assessed patients’ specific characteristics, comorbidities, and risk factors. Results: Women made up only a quarter of the survey participants (74 women, 24.7%) and were generally older (63.32 ± 9.3 vs. 60.51 ± 9.3, p = 0.02) and more obese (31.20 ± 6.0 vs. 29.48 ± 4.9, p = 0.02). There were no significant differences in the prevalence of hypertension, diabetes, dyslipidemia, chronic kidney disease, or peripheral artery disease, though women had slightly higher rates for most comorbidities. Regarding smoking habits, both groups had high percentages of current and former smokers, with women being significantly less likely to smoke (20.9% vs. 44.6%, p = 0.003). Multivariable logistic regression adjusting for age, BMI, smoking status, diabetes, and eGFR revealed that sex was not a statistically significant independent predictor for myocardial infarction, PCI, or CABG. Conclusions: We observed that women with previous coronary events had a worse risk factor profile, while there were no significant sex differences in overall comorbidities. Risk factor control should be based on sex-specific prediction models. Full article

(This article belongs to the Section Cardiology)

25 pages, 2276 KiB

Open AccessArticle

Disagreements in Equivalent-Factor-Based Valuation of County-Level Ecosystem Services in China: Insights from Comparison Among Ten LULC Datasets

by Daiyi Song, Lizhou Wang, Yingge Wang, Bowen Zhao, Qi Jin and Jianxin Yang

Remote Sens. 2025, 17(13), 2320; https://doi.org/10.3390/rs17132320 (registering DOI) - 6 Jul 2025

Abstract

Valuation of ecosystem services (ESs) is crucial for understanding the benefits provided by ecosystems and informing sustainable management and policy decisions related to ecosystem protection. This study explores the disagreements in ecosystem service value (ESV) at the county level across China in 2020 [...] Read more.

Valuation of ecosystem services (ESs) is crucial for understanding the benefits provided by ecosystems and informing sustainable management and policy decisions related to ecosystem protection. This study explores the disagreements in ecosystem service value (ESV) at the county level across China in 2020 by comparing ten land cover datasets of varying resolutions from 500 to 10 m, using the equivalent factor method. Significant disagreements in ESV estimates are identified, revealing spatial heterogeneity and large inconsistencies among estimates from different datasets, even with high spatial resolution (10 m). Across all counties, the typical discrepancy in ESV estimates between any two datasets reaches 3503 CNY/ha, and the ESV estimates for each county show an average coefficient of variation (CV) of 0.186 across the ten datasets, indicating considerable inconsistency attributable to dataset selection. The results highlight that ESV evaluations based on the CLCD, Globeland30, and GLC-FCS30 datasets demonstrate higher consistency and reliability, making them suitable for regional ecosystem service valuation. Both the landscape configurations and the area disparities of different land types have significant impacts on ESV disagreement. This study provides valuable insights into the applicability of different datasets for ESV evaluation, thereby enhancing the reliability of ESV assessments and supporting informed decision making in ecosystem management. Full article

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