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30 pages, 2475 KiB

Open AccessArticle

Collaborative Scheduling of Yard Cranes, External Trucks, and Rail-Mounted Gantry Cranes for Sea–Rail Intermodal Containers Under Port–Railway Separation Mode

by Xuhui Yu and Cong He

J. Mar. Sci. Eng. 2025, 13(6), 1109; https://doi.org/10.3390/jmse13061109 - 2 Jun 2025

Abstract

The spatial separation of port yards and railway hubs, which relies on external truck drayage as a necessary link, hampers the seamless transshipment of sea–rail intermodal containers between ports and railway hubs. This creates challenges in synchronizing yard cranes (YCs) at the port [...] Read more.

The spatial separation of port yards and railway hubs, which relies on external truck drayage as a necessary link, hampers the seamless transshipment of sea–rail intermodal containers between ports and railway hubs. This creates challenges in synchronizing yard cranes (YCs) at the port terminal, external trucks (ETs) on the road, and rail-mounted gantry cranes (RMGs) at the railway hub. However, most existing studies focus on equipment scheduling or container transshipment organization under the port–railway integration mode, often overlooking critical time window constraints, such as train schedules and export container delivery deadlines. Therefore, this study investigates the collaborative scheduling of YCs, ETs, and RMGs for synchronized loading and unloading under the port–railway separation mode. A mixed-integer programming (MIP) model is developed to minimize the maximum makespan of all tasks and the empty-load time of ETs, considering practical time window constraints. Given the NP-hard complexity of this problem, an improved genetic algorithm (GA) integrated with a “First Accessible Machinery” rule is designed. Extensive numerical experiments are conducted to validate the correctness of the proposed model and the performance of the solution algorithm. The improved GA demonstrates a 6.08% better solution quality and a 97.94% reduction in computation time compared to Gurobi for small-scale instances. For medium to large-scale instances, it outperforms the adaptive large neighborhood search (ALNS) algorithm by 1.51% in solution quality and reduces computation time by 45.71%. Furthermore, the impacts of objective weights, equipment configuration schemes, port–railway distance, and time window width are analyzed to provide valuable managerial insights for decision-making to improve the overall efficiency of sea–rail intermodal systems. Full article

(This article belongs to the Special Issue Sustainable Maritime Transport and Port Intelligence)

13 pages, 1147 KiB

Open AccessArticle

Exploring Nanofiltration for Transport of Small Molecular Species for Application in Artificial Kidney Devices to Treat End-Stage Kidney Disease

by Haley Duncan, Christopher Newton, Jamie Hestekin, Christa Hestekin and Ira Kurtz

Membranes 2025, 15(6), 168; https://doi.org/10.3390/membranes15060168 - 2 Jun 2025

Abstract

End-stage renal disease occurs when there is permanent loss of the kidney’s ability to filter toxins from the blood. Due to the limited number of transplants, dialysis is currently the most common treatment, but it significantly limits a patient’s lifestyle and has significant [...] Read more.

End-stage renal disease occurs when there is permanent loss of the kidney’s ability to filter toxins from the blood. Due to the limited number of transplants, dialysis is currently the most common treatment, but it significantly limits a patient’s lifestyle and has significant side effects. One solution is an artificial kidney, but significant challenges remain in its development. One challenge is the separation of glucose from urea. Nanofiltration is ideal for this separation; however, there is little understanding of the important parameters for this separation under physiological conditions. In this study, operating parameters (pressure and temperature) as well as feed conditions (increased glucose/salt) were explored for their effects on the separation of glucose from urea in six commercial membranes. The rejection of monovalent and divalent ions was also characterized. While increasing pressure increased flux, it had little effect on metabolite rejection, except for glucose, which increased above 20 psi. Increasing temperature led to a slight increase in flux and a slight decrease in the rejection of divalent ions. Glucose rejection was sensitive to feed conditions, while urea rejection was less affected. Divalent ions were rejected more strongly than monovalent ions and were also more affected by feed conditions. Full article

(This article belongs to the Section Membrane Applications for Other Areas)

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26 pages, 1134 KiB

Open AccessReview

Nanomembranes as Eco-Friendly Instruments for Modern Food Processing, from Filtration to Packaging

by Simona Gavrilaș

Membranes 2025, 15(6), 167; https://doi.org/10.3390/membranes15060167 - 2 Jun 2025

Abstract

With the increasing demand for safe, high-quality, and sustainable food, nanomembranes have attracted significant interest as innovative solutions in food processing. They are extremely thin structures created from special materials that allow for the selective filtration of very small particles. In the food [...] Read more.

With the increasing demand for safe, high-quality, and sustainable food, nanomembranes have attracted significant interest as innovative solutions in food processing. They are extremely thin structures created from special materials that allow for the selective filtration of very small particles. In the food industry, such approaches are increasingly used for packaging and processing, as they can slow down food degradation and thus extend its shelf life. This article examines the potential of utilizing nanomembranes as ecological tools at various stages of the food chain, ranging from advanced filtration of food liquids to the development of smart and active packaging. This study reviews the recent research in the field, highlighting the applications developed and presenting targeted advantages and disadvantages. The developed applications primarily focus on extending the shelf life of products while also discussing their antioxidant and antibacterial attributes. By highlighting the latest applications and emerging research directions, this article underscores the pivotal role of nanomembranes in facilitating the transition to a modern, sustainable, and environmentally responsible food industry. However, current research faces several challenges. Most products are less biodegradable and, consequently, could harm the environment. Additionally, data on the long-term effects of these materials on human health, particularly when used in packaging that comes into direct contact with food, remain insufficient. Therefore, more sustainable solutions are needed, such as nanomembranes based on natural biopolymers. Further studies are required to assess their safety and real-world effectiveness under industrial conditions. Full article

(This article belongs to the Section Membrane Applications for Other Areas)

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9 pages, 1752 KiB

Open AccessCommunication

A Fiberglass-Cloth-Reinforced Perfluorosulfonic Acid Membrane

by Zhutao Zhang, Yiru Dou, Wen Zhang, Li Xu and Yuxin Wang

Membranes 2025, 15(6), 166; https://doi.org/10.3390/membranes15060166 - 2 Jun 2025

Abstract

Perfluorosulfonic acid (PFSA) membranes have found broad-ranging applications, owing to their high ionic conductivity and excellent chemical stability. However, membranes with higher mechanical strength, lower area-specific resistance, reduced swelling, less gas crossover and more affordable costs are desirable. Herein, we report on the [...] Read more.

Perfluorosulfonic acid (PFSA) membranes have found broad-ranging applications, owing to their high ionic conductivity and excellent chemical stability. However, membranes with higher mechanical strength, lower area-specific resistance, reduced swelling, less gas crossover and more affordable costs are desirable. Herein, we report on the fabrication of a fiberglass-cloth-reinforced PFSA membrane using a simple solution cast method. The breaking strength of the reinforced membrane has the potential to reach 81 MPa, which is about 6 times and 2.5 times that of its non-reinforced counterpart and the commercial Nafion 117 (N117) membrane, respectively. The area swelling ratio of the reinforced membrane is lowered to merely 3%, which is only about 1/12 that of N117, in water at 100 °C. Despite ionic conduction being hindered by the fiberglass cloth, the reinforced PFSA membrane shows an area-specific resistance of only 0.069 Ω·cm², which is 58% lower than that of N117, under 80 °C and 100% humidity. This research provides a promising technological pathway for the development of high-performance ionic conductive membranes. Full article

(This article belongs to the Section Membrane Fabrication and Characterization)

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12 pages, 3153 KiB

Open AccessCase Report

Improving Mobility: A Case Report on the Rehabilitation of a Gait Anomaly in an Asian Elephant at a Thai Elephant Conservation Center

by Siriphan Kongsawasdi, Kittichai Wantanajittikul, Therdchai Jivacate, Warangkhana Langkaphin, Saran Chansitthiwet, Petthisak Sombutputorn, Kittikul Namwongprom, Narueporn Kittisirikul, Siripat Khammesri and Taweepoke Angkawanish

Animals 2025, 15(11), 1632; https://doi.org/10.3390/ani15111632 - 2 Jun 2025

Abstract

This case report details the successful rehabilitation of a 31-year-old male Asian elephant (Elephas maximus) presenting with an abnormal left forelimb gait following chronic traumatic injury. The elephant exhibited a distinctive circumduction gait with a semicircular arc movement, characterized by limited [...] Read more.

This case report details the successful rehabilitation of a 31-year-old male Asian elephant (Elephas maximus) presenting with an abnormal left forelimb gait following chronic traumatic injury. The elephant exhibited a distinctive circumduction gait with a semicircular arc movement, characterized by limited flexion at the elbow and carpus, along with compensatory proximal shrugging during the swing phase. Diagnostic evaluations revealed joint space narrowing and ligament fibrosis, while biomechanical gait analysis using inertial measurement units highlighted significant asymmetries between affected and unaffected limbs. An interprofessional team developed a comprehensive rehabilitation protocol that integrated peripheral magnetic stimulation, task-specific therapeutic walking with adjustable obstacles, and progressive strengthening exercises. At the eight-week follow-up, improvements were observed in cross-correlation coefficients of limb movement and imaging assessments, indicating enhanced symmetry and structural improvements with reduced fibrosis. However, persistent discrepancies in elbow functions suggest that further targeted rehabilitation may be warranted. This report underscores the potential of a coordinated interprofessional approach to restore functional gait patterns in elephants and offers valuable insights for future rehabilitative strategies in managing complex musculoskeletal injuries in large mammals. Full article

(This article belongs to the Section Wildlife)

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21 pages, 307 KiB

Open AccessArticle

Effect of Dietary Addition of Blueberry (Vaccinium corymbosum) Powder on Fattening Performance, Meat Quality, Oxidative Stability and Storage Quality in Japanese Quails (Coturnix coturnix japonica)

by Shaistah Naimati, Sibel Canoğulları Doğan, Muhammad Umair Asghar and Qurat Ul Ain Sajid

Animals 2025, 15(11), 1633; https://doi.org/10.3390/ani15111633 - 2 Jun 2025

Abstract

This study was conducted to investigate the effects of dietary addition of blueberry (Vaccinium corymbosum) powder on the growth performance, meat quality, oxidative stability and cold storage quality of Japanese quails (Coturnix coturnix japonica). In this research, 480 quail [...] Read more.

This study was conducted to investigate the effects of dietary addition of blueberry (Vaccinium corymbosum) powder on the growth performance, meat quality, oxidative stability and cold storage quality of Japanese quails (Coturnix coturnix japonica). In this research, 480 quail chicks were divided into four experimental groups, and each experimental group was composed of four replicates, each containing 30 quail chicks. Commercial feed was used in the study, but BBP was added to the feed at levels of 0%, 1%, 2% and 4%. Results showed that dietary addition of blueberry powder did not affect body weight gain, feed consumption and feed conversion ratio (p > 0.05). No significant difference was observed between hot and cold carcass weights and carcass yield among carcass parameters (p > 0.05). However, significant differences were found among the blueberry-supplemented groups in terms of thigh, back and neck ratios (p < 0.05). In this study, it was determined that thiobarbituric acid (TBA), pH and peroxide values in breast meat samples kept at +4 °C for 1, 3, 5 and 7 days were lower in the blueberry-supplemented groups compared to the control group and these values decreased linearly as the supplement level increased (p < 0.05). The addition of blueberries to the quail diets resulted in similar L, a and b values in breast and thigh meat and skin among the groups (p > 0.05) except for the b value in thigh meat (p < 0.05). The findings obtained in this study revealed that although adding blueberries to the quail diet did not have a significant effect on performance, the antioxidant activity and phenolic substance content of the plant had a significant effect on increasing the shelf life of meat. It was concluded that blueberry could be used as a natural additive that may replace synthetic antioxidants. Full article

(This article belongs to the Special Issue Feed Additives in Animal Nutrition)

22 pages, 3437 KiB

Open AccessArticle

ECG Signal Analysis for Detection and Diagnosis of Post-Traumatic Stress Disorder: Leveraging Deep Learning and Machine Learning Techniques

by Parisa Ebrahimpour Moghaddam Tasouj, Gökhan Soysal, Osman Eroğul and Sinan Yetkin

Diagnostics 2025, 15(11), 1414; https://doi.org/10.3390/diagnostics15111414 - 2 Jun 2025

Abstract

Background: Post-traumatic stress disorder (PTSD) is a serious psychiatric condition that can lead to severe anxiety, depression, and cardiovascular complications if left untreated. Early and accurate diagnosis is critical. This study aims to develop and evaluate an artificial intelligence-based classification system using electrocardiogram [...] Read more.

Background: Post-traumatic stress disorder (PTSD) is a serious psychiatric condition that can lead to severe anxiety, depression, and cardiovascular complications if left untreated. Early and accurate diagnosis is critical. This study aims to develop and evaluate an artificial intelligence-based classification system using electrocardiogram (ECG) signals for the detection of PTSD. Methods: Raw ECG signals were transformed into time–frequency images using Continuous Wavelet Transform (CWT) to generate 2D scalogram representations. These images were classified using deep learning-based convolutional neural networks (CNNs), including AlexNet, GoogLeNet, and ResNet50. In parallel, statistical features were extracted directly from the ECG signals and used in traditional machine learning (ML) classifiers for performance comparison. Four different segment lengths (5 s, 10 s, 15 s, and 20 s) were tested to assess their effect on classification accuracy. Results: Among the tested models, ResNet50 achieved the highest classification accuracy of 94.92%, along with strong MCC, sensitivity, specificity, and precision metrics. The best performance was observed with 5-s signal segments. Deep learning (DL) models consistently outperformed traditional ML approaches. The area under the curve (AUC) for ResNet50 reached 0.99, indicating excellent classification capability. Conclusions: This study demonstrates that CNN-based models utilizing time–frequency representations of ECG signals can effectively classify PTSD with high accuracy. Segment length significantly influences model performance, with shorter segments providing more reliable results. The proposed method shows promise for non-invasive, ECG-based diagnostic support in PTSD detection. Full article

(This article belongs to the Special Issue Artificial Intelligence in Biomedical Diagnostics and Analysis 2024)

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18 pages, 1146 KiB

Open AccessArticle

Explainable Machine Learning in the Prediction of Depression

by Christina Mimikou, Christos Kokkotis, Dimitrios Tsiptsios, Konstantinos Tsamakis, Stella Savvidou, Lillian Modig, Foteini Christidi, Antonia Kaltsatou, Triantafyllos Doskas, Christoph Mueller, Aspasia Serdari, Kostas Anagnostopoulos and Gregory Tripsianis

Diagnostics 2025, 15(11), 1412; https://doi.org/10.3390/diagnostics15111412 - 2 Jun 2025

Abstract

Background: Depression constitutes a major public health issue, being one of the leading causes of the burden of disease worldwide. The risk of depression is determined by both genetic and environmental factors. While genetic factors cannot be altered, the identification of potentially reversible [...] Read more.

Background: Depression constitutes a major public health issue, being one of the leading causes of the burden of disease worldwide. The risk of depression is determined by both genetic and environmental factors. While genetic factors cannot be altered, the identification of potentially reversible environmental factors is crucial in order to try and limit the prevalence of depression. Aim: A cross-sectional, questionnaire-based study on a sample from the multicultural region of Thrace in northeast Greece was designed to assess the potential association of depression with several sociodemographic characteristics, lifestyle, and health status. The study employed four machine learning (ML) methods to assess depression: logistic regression (LR), support vector machine (SVM), XGBoost, and neural networks (NNs). These models were compared to identify the best-performing approach. Additionally, a genetic algorithm (GA) was utilized for feature selection and SHAP (SHapley Additive exPlanations) for interpreting the contributions of each employed feature. Results: The XGBoost classifier demonstrated the highest performance on the test dataset to predict depression with excellent accuracy (97.83%), with NNs a close second (accuracy, 97.02%). The XGBoost classifier utilized the 15 most significant risk factors identified by the GA algorithm. Additionally, the SHAP analysis revealed that anxiety, education level, alcohol consumption, and body mass index were the most influential predictors of depression. Conclusions: These findings provide valuable insights for the development of personalized public health interventions and clinical strategies, ultimately promoting improved mental well-being for individuals. Future research should expand datasets to enhance model accuracy, enabling early detection and personalized mental healthcare systems for better intervention. Full article

(This article belongs to the Special Issue The Future of Diagnostics: Exploring the Role of Artificial Intelligence in Medicine)

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13 pages, 3078 KiB

Open AccessArticle

Real-Time MR-Guided Lumbosacral Periradicular Injection Therapy Using a 0.55 T MRI System: A Phantom Study

by Saher Saeed, Jan Boriesosdick, Arwed Michael, Nina Pauline Haag, Julian Schreck, Denise Schoenbeck, Matthias Michael Woeltjen, Julius Henning Niehoff, Christoph Moenninghoff, Jan Borggrefe and Jan Robert Kroeger

Diagnostics 2025, 15(11), 1413; https://doi.org/10.3390/diagnostics15111413 - 2 Jun 2025

Abstract

Objective: The purpose of this study was to evaluate the accuracy and feasibility of magnetic resonance (MR)-guided periradicular nerve root injection therapy (PRT) using a 0.55 T magnetic resonance imaging (MRI) system with fast dynamic imaging in a phantom. Methods: Five radiologists with [...] Read more.

Objective: The purpose of this study was to evaluate the accuracy and feasibility of magnetic resonance (MR)-guided periradicular nerve root injection therapy (PRT) using a 0.55 T magnetic resonance imaging (MRI) system with fast dynamic imaging in a phantom. Methods: Five radiologists with varying levels of experience in PRT performed nine randomly assigned PRT procedures: three under MR guidance, three under CT guidance using a fully integrated laser navigation system, and three under conventional CT guidance, all on a specialized phantom of the lumbar spine. The PRTs were assessed by two experienced neuroradiologists with expertise in interventions, using a scale of 1–5, as follows: 5 = excellent to very good, 4 = good, 3 = satisfactory 2 = bad, 1 = very bad. The puncture time and total intervention time were noted. Results: All procedures were technically successful. The subjective evaluation of the PRTs showed similar results with a median of 5 for all three guidance systems. Additionally, there was no significant difference with respect to pure puncture time (the period after needle path determination) among all PRTs (Mean ± SD): MR-guided 178 ± 117 s, CT-guided with laser system 186 ± 73 s, and the conventional CT-guided 218 ± 91 s (p = 0.482). However, the total procedure time including planning images was significantly higher for MR-guided PRT (700 ± 182 s) compared to CT guidance with laser system (366 ± 85 s) and conventional CT guidance (358 ± 150 s; p = 0.012). Conclusions: Real-time MRI-guided lumbosacral periradicular injection therapy utilizing a 0.55 T MRI system is feasible with similar puncture times to CT guidance but consumes more intervention time due to the duration of planning sequences. Limitation: The study utilized a stationary phantom made of homogeneous material, which provides an incomplete representation of real tissue properties and motion complexity applied to human beings. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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19 pages, 1674 KiB

Open AccessArticle

Determination of the Stage of Periodontitis with 20 ng/mL Cut-Off aMMP-8 Mouth Rinse Test and Polynomial Functions in a Mobile Application

by Miika Penttala, Timo Sorsa, Julie Toby Thomas, Andreas Grigoriadis, Dimitra Sakellari, Vaibhav Sahni, Shipra Gupta, Pirjo Pärnänen, Tommi Pätilä and Ismo T. Räisänen

Diagnostics 2025, 15(11), 1411; https://doi.org/10.3390/diagnostics15111411 - 2 Jun 2025

Abstract

Background: We propose a framework for determining the stage of periodontitis in a personalized medicine context, building on our previously developed model for periodontitis detection. In this study, we improved the earlier model by incorporating additional components to form a comprehensive system for [...] Read more.

Background: We propose a framework for determining the stage of periodontitis in a personalized medicine context, building on our previously developed model for periodontitis detection. In this study, we improved the earlier model by incorporating additional components to form a comprehensive system for identifying both the presence and stage of periodontitis. Central to the home-use application is an active-matrix metalloproteinase-8 (aMMP-8) mouth rinse test (cut-off: 20 ng/mL), integrated with software delivered via a mobile application. Methods: First, using all the data, we modeled a single polynomial function to distinguish healthy and stage I periodontitis patients from stage II and III patients. Second, we used an already published periodontitis detection function to separate stage I patients from healthy patients. Third, one more function was created that divided stage II and III patients from each other. All functions were modeled by multiple logistic regression analysis from the patient data, which consisted of 149 adult patients visiting dental offices in Thessaloniki, Greece. Results: The complete model demonstrated a sensitivity of 95.8% (95% CI: 92.1–99.4%) and a specificity of 71.0% (95% CI: 55.0–86.9%) for detecting periodontitis. Among those identified with periodontitis, the correct stage was determined in 61.1% of cases, with stage-specific accuracies of 64.3% for stage I, 60.5% for stage II, and 60.9% for stage III. All testing was performed on patient data with which the complete model was formed. Conclusions: The results of this study showed that with sufficient data and using multiple logistic regression analysis, a model can be created to simultaneously identify the presence and stage of periodontitis. Overall, in the complete model generated, a mouth rinse aMMP-8 test result with a cut-off value of 20 ng/mL, Visible Plaque Index (VPI) and information of patient’s teeth number present were found to be important factors to determine the stage of periodontitis in a personalized medicine manner for everyone to use. Full article

(This article belongs to the Special Issue Advances in Diagnosis and Management of Oral Disorders)

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13 pages, 5084 KiB

Open AccessArticle

Comparative Ecotoxicological Effects of Cyanobacterial Crude Extracts on Native Tropical Cladocerans and Daphnia magna

by Cesar Alejandro Zamora-Barrios, Marcos Efrén Fragoso Rodríguez, S. Nandini and S. S. S. Sarma

Toxins 2025, 17(6), 277; https://doi.org/10.3390/toxins17060277 (registering DOI) - 2 Jun 2025

Abstract

Freshwater cyanobacterial harmful algal blooms (FCHABs) alter zooplankton communities, often adversely, through the production of cyanotoxins. While Daphnia magna is frequently used to evaluate the impact of toxicants, it is not commonly found in tropical waters; cladocerans from tropical and subtropical waterbodies should [...] Read more.

Freshwater cyanobacterial harmful algal blooms (FCHABs) alter zooplankton communities, often adversely, through the production of cyanotoxins. While Daphnia magna is frequently used to evaluate the impact of toxicants, it is not commonly found in tropical waters; cladocerans from tropical and subtropical waterbodies should be used in bioassays. Here, we evaluated the impact of crude cyanobacteria extracts on three common, native species (Daphnia laevis, Ceriodaphnia dubia, and Simocephalus vetulus) based on acute and chronic bioassays. We analyzed the toxicity of cyanobacterial consortium collected from Lake Zumpango, Mexico. The FCHAB was dominated by Planktothrix agardhii (1.16 × 10⁶ ind mL⁻¹). A series of freeze/thaw/sonification cycles at 20 kHz was used to extract the toxic metabolites and the concentration of dissolved microcystin-LR equivalents was measured using an ELISA immunological kit. S. vetulus was the most sensitive species, with a median lethal concentration of 0.43 compared to 1.19 µg L⁻¹ of D. magna at 48 h. S. vetulus was also the most sensitive in chronic evaluations, showing a negative rate of population increase (−0.10 d⁻¹) in experiments with 20% crude extract. Full article

(This article belongs to the Special Issue Prospective Studies on Harmful Cyanobacteria and Cyanotoxins)

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38 pages, 1212 KiB

Open AccessReview

Insights into the Development of Corrosion Protection Coatings

by Monmi Saikia, Trisha Dutta, Niteen Jadhav and Deep J. Kalita

Polymers 2025, 17(11), 1548; https://doi.org/10.3390/polym17111548 - 2 Jun 2025

Abstract

This review article focuses on providing an accumulated knowledge on state-of-the-art composite polymer coating technologies that are studied for corrosion protection. A specific focus has been given to epoxy resin-based composite systems, considering their wide use due to remarkable chemical resistance, excellent adhesion [...] Read more.

This review article focuses on providing an accumulated knowledge on state-of-the-art composite polymer coating technologies that are studied for corrosion protection. A specific focus has been given to epoxy resin-based composite systems, considering their wide use due to remarkable chemical resistance, excellent adhesion to substrate, thermal stability, and mechanical strength. The addition of various functional polymers to the epoxy matrix has spurred significant advancements in the prevention of corrosion. Light has been shed on the epoxy resin composite systems that are produced by blending with functional polymers like conductive polymers, hydrophobic polymers, etc., and nanofillers. In many cases, the formation of a passive layer at the metal/polymer interface was aided by the addition of such a functional polymer and nanofiller to the epoxy matrix. As a result, corrosive ions are prevented from penetrating by the physical barrier that composite coatings provide. Comparable blends of epoxy and polyamide, epoxy and polyester, and epoxy/poly(vinyl alcohol) and epoxy/polyurethane have superior adhesion, wear, barrier, and anticorrosion properties due to the fine dispersion of nanocarbon and inorganic nanoparticles. The several strategies used to prevent metals from corroding are covered in this review article. Full article

(This article belongs to the Special Issue Advances in Functional Polymer Coatings and Surfaces)

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18 pages, 326 KiB

Open AccessReview

Beyond Mosquitoes: A Review of Pediatric Vector-Borne Diseases Excluding Malaria and Arboviral Infections

by Giulia Carbone, Amina De Bona, Dragos Septelici, Alessandro Cipri, Andrea Nobilio and Susanna Esposito

Pathogens 2025, 14(6), 553; https://doi.org/10.3390/pathogens14060553 (registering DOI) - 2 Jun 2025

Abstract

Vector-borne diseases (VBDs) significantly impact global child health, with mosquito-transmitted infections like malaria and arboviruses accounting for a substantial portion of this burden. However, other arthropod-borne diseases—transmitted by vectors such as ticks, fleas, sand flies, lice, and triatomine bugs—also pose serious health risks [...] Read more.

Vector-borne diseases (VBDs) significantly impact global child health, with mosquito-transmitted infections like malaria and arboviruses accounting for a substantial portion of this burden. However, other arthropod-borne diseases—transmitted by vectors such as ticks, fleas, sand flies, lice, and triatomine bugs—also pose serious health risks to children worldwide. This review specifically excludes mosquito-borne diseases to concentrate on these less-discussed yet clinically important pediatric VBDs. We examine their clinical manifestations, diagnostic challenges, and treatment options, highlighting the unique vulnerabilities of children, including immature immune systems, behavioral factors, and communication barriers that can delay diagnosis. Additionally, we explore how environmental and anthropogenic factors, such as climate change and urbanization, are expanding the geographic range of these vectors, leading to the emergence of diseases like Lyme disease and leishmaniasis in new regions. By focusing on non-mosquito VBDs, this review aims to raise awareness and inform healthcare providers and public health practitioners about the comprehensive landscape of pediatric vector-borne diseases. Full article

(This article belongs to the Special Issue Emerging and Re-emerging Infections in Pediatrics)

22 pages, 607 KiB

Open AccessFeature PaperArticle

Quantitative Recurrence Properties in Some Irregular Sets for Beta Dynamical Systems

by Yuanyang Chang and Wenna Liu

Mathematics 2025, 13(11), 1850; https://doi.org/10.3390/math13111850 (registering DOI) - 2 Jun 2025

Abstract

Let

β > 1

be a real number and

T_{β} x = β x (m o d 1)

. This paper is concerned with the quantitative recurrence properties of the system [...] Read more.

Let

β > 1

be a real number and

T_{β} x = β x (m o d 1)

. This paper is concerned with the quantitative recurrence properties of the system

([0, 1], T_{β})

in some (refined) irregular sets. Specifically, let

α_{1}, α_{2} > 0

and

ψ : N \to (0, 1)

be a positive function; we define the set

E_{α_{1}, α_{2}}^{β} = \{x \in [0, 1) : \underset{n \to \infty}{lim inf} \frac{1}{n} S_{n} (x, β) = α_{1}, \underset{n \to \infty}{lim sup} \frac{1}{n} S_{n} (x, β) = α_{2}\},

and calculate the Hausdorff dimension of the set

E_{α_{1}, α_{2}}^{β} (ψ) : = \{x \in E_{α_{1}, α_{2}}^{β} : | T_{β}^{n} x - x | < ψ (n) i . m . n \in N\},

where

i . m .

stands for infinitely many. Consequently, the Hausdorff dimension of the set

{\hat{E}}^{β} (ψ) = \{x \in [0, 1) : lim_{n \to \infty} \frac{1}{n} S_{n} (x, β) does not exist, | T_{β}^{n} x - x | < ψ (n) i . m . n \in N\}

is also determined. Full article

16 pages, 679 KiB

Open AccessArticle

A Comprehensive Evaluation of the Impact of China’s Carbon Market on Carbon Emission Efficiency from the Total-Factor Perspective

by Ruirui Fang, Yue Ma and Lianyong Feng

Sustainability 2025, 17(11), 5101; https://doi.org/10.3390/su17115101 (registering DOI) - 2 Jun 2025

Abstract

Excessive carbon emission presents a considerable danger to the sustainability of global development. The carbon market, a crucial mechanism to cut carbon emissions, is gaining more attention from the Chinese government. In this study, provincial-level total-factor carbon emission efficiency in China is assessed, [...] Read more.

Excessive carbon emission presents a considerable danger to the sustainability of global development. The carbon market, a crucial mechanism to cut carbon emissions, is gaining more attention from the Chinese government. In this study, provincial-level total-factor carbon emission efficiency in China is assessed, and the influence of the national carbon market on this efficiency is examined. Through the introduction of the carbon market’s internal constraint mechanism, a novel perspective for analyzing the driving mechanism is constructed. Empirical findings indicate that the carbon market significantly improves total-factor carbon emission efficiency. Currently, the constraint mechanism acts as the primary driver of this improvement, while the role of the market-based mechanism remains underutilized. Mediation analysis suggests that the improvement is mainly achieved through adjustments in the energy structure; by contrast, neither technological innovation nor industrial restructuring exhibits a significant effect. The conclusions are crucial for a comprehensive understanding of China’s carbon market. Lastly, several recommendations are proposed. Full article

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27 pages, 680 KiB

Open AccessArticle

Human Capital Development and Public Health Expenditure: Assessing the Long-Term Sustainability of Economic Development Models

by Ngesisa Magida, Thobeka Ncanywa, Kin Sibanda and Abiola John Asaleye

Soc. Sci. 2025, 14(6), 351; https://doi.org/10.3390/socsci14060351 (registering DOI) - 2 Jun 2025

Abstract

This study investigates the role of public health expenditure on human capital development in South Africa to promote economic development. Despite extensive public health investments and economic reforms, persistent socioeconomic challenges such as poverty, unemployment, and inequality impede sustainable economic growth. This study [...] Read more.

This study investigates the role of public health expenditure on human capital development in South Africa to promote economic development. Despite extensive public health investments and economic reforms, persistent socioeconomic challenges such as poverty, unemployment, and inequality impede sustainable economic growth. This study uses an autoregressive distributed lag model, a vector error correction model (VECM), quantile regression, and Granger causality analysis to assess the relationship between fiscal health policies and human development. The findings confirm that government health spending significantly enhances human development in the short and long run, while unemployment and population growth exert adverse effects. VECM variance decomposition results indicate that the influence of public health expenditure remains persistent, though diminishing over time, with growing contributions from unemployment. Quantile regression shows the heterogeneous impact of health spending across different levels of economic development, emphasising its greater effectiveness at higher development stages. Causality analysis reveals a unidirectional relationship from public health expenditure to human development; this shows the need for sustained healthcare investment. The study calls for policies combining health spending with economic strategies to boost productivity, reduce inequality, and promote inclusive growth. Strengthening institutional efficiency and ensuring macroeconomic stability are crucial for maximising long-term human capital to promote sustainable development. Full article

(This article belongs to the Section Work, Employment and the Labor Market)

23 pages, 3552 KiB

Open AccessArticle

Low-Scalability Distributed Systems for Artificial Intelligence: A Comparative Study of Distributed Deep Learning Frameworks for Image Classification

by Manuel Rivera-Escobedo, Manuel de Jesús López-Martínez, Luis Octavio Solis-Sánchez, Héctor Alonso Guerrero-Osuna, Sodel Vázquez-Reyes, Daniel Acosta-Escareño and Carlos A. Olvera-Olvera

Appl. Sci. 2025, 15(11), 6251; https://doi.org/10.3390/app15116251 (registering DOI) - 2 Jun 2025

Abstract

Artificial intelligence has experienced tremendous growth in various areas of knowledge, especially in computer science. Distributed computing has become necessary for storing, processing, and generating large amounts of information essential for training artificial intelligence models and algorithms that allow knowledge to be created [...] Read more.

Artificial intelligence has experienced tremendous growth in various areas of knowledge, especially in computer science. Distributed computing has become necessary for storing, processing, and generating large amounts of information essential for training artificial intelligence models and algorithms that allow knowledge to be created from large amounts of data. Currently, cloud services offer products for running distributed data training, such as NVIDIA Deep Learning Solutions, Amazon SageMaker, Microsoft Azure, and Google Cloud AI Platform. These services have a cost that adapts to the needs of users who require high processing performance to perform their artificial intelligence tasks. This study highlights the relevance of distributed computing in image processing and classification tasks using a low-scalability distributed system built with devices considered obsolete. To this end, two of the most widely used libraries for the distributed training of deep learning models, PyTorch’s Distributed Data Parallel and Distributed TensorFlow, were implemented and evaluated using the ResNet50 model as a basis for image classification, and their performance was compared with modern environments such as Google Colab and a recent Workstation. The results demonstrate that even with low scalability and outdated distributed systems, comprehensive artificial intelligence tasks can still be performed, reducing investment time and costs. With the results obtained and experiments conducted in this study, we aim to promote technological sustainability through device recycling to facilitate access to high-performance computing in key areas such as research, industry, and education. Full article

(This article belongs to the Special Issue Distributed Computing Systems: Advances, Trends and Emerging Designs)

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33 pages, 9816 KiB

Open AccessArticle

The Influence of Attribution Style and Goal Accessibility on Health Beliefs and Exercise Willingness: Experimental Evidence from University Students

by Shuai Zhang and Chenglong Miao

Behav. Sci. 2025, 15(6), 763; https://doi.org/10.3390/bs15060763 (registering DOI) - 2 Jun 2025

Abstract

Although the benefits of regular physical activity are widely recognized, many university students fail to sustain consistent exercise behaviors. This phenomenon may be attributed to cognitive and motivational barriers, particularly perceptions of goal attainability and attribution styles, which are believed to significantly influence [...] Read more.

Although the benefits of regular physical activity are widely recognized, many university students fail to sustain consistent exercise behaviors. This phenomenon may be attributed to cognitive and motivational barriers, particularly perceptions of goal attainability and attribution styles, which are believed to significantly influence students’ health beliefs and intentions to engage in physical activity. This research aimed to examine the independent and combined effects of goal attainability and attribution style on Chinese university students’ health beliefs and willingness to exercise. The study also investigated how shifts in attribution style may influence these outcomes under different levels of goal attainability. Two between-subjects experiments were conducted. In Experiment 1 (N = 146), a 2 (goal attainability: high vs. low) × 2 (attribution style: internal vs. external) design was used. Participants were exposed to tailored exercise advertisements and completed standardized questionnaires measuring health beliefs and exercise intentions. Experiment 2 (N = 130) adopted a 2 (goal attainability: high vs. low) × 2 (attributional shift: external-to-internal vs. internal-to-external) design, utilizing visual priming and short video interventions to manipulate attributional orientation. In Experiment 1, both high goal attainability and internal attribution independently enhanced participants’ health beliefs and exercise willingness. A significant interaction effect was observed only for exercise willingness, with the highest intentions found in the high attainability × internal attribution group. In Experiment 2, shifting attribution from external to internal significantly increased both health beliefs and exercise willingness, while shifting from internal to external resulted in substantial decreases. An interaction effect was again found only for exercise willingness, suggesting that the effectiveness of attributional shift depended on goal attainability. By integrating the Health Belief Model with Attribution Theory, this study offers a deeper understanding of how cognitive and motivational factors influence exercise behavior, and provides a theoretical foundation for developing adaptive interventions. Full article

12 pages, 2188 KiB

Open AccessArticle

Creating Forested Wetlands for Improving Ecosystem Services and Their Potential Benefits for Rural Residents in Metropolitan Areas

by Zhuhong Huang, Yanwei Sun, Rong Sheng, Kun He, Taoyu Wang, Yingying Huang and Xuechu Chen

Water 2025, 17(11), 1682; https://doi.org/10.3390/w17111682 (registering DOI) - 2 Jun 2025

Abstract

Intensive farming in urban suburbs often causes habitat loss, soil erosion, wastewater discharge, and agricultural productivity decline, threatening long-term benefits for the local community. We developed a nature-based solution for sustainable land restoration by establishing “Green Treasure Island” (GTI). The aim of this [...] Read more.

Intensive farming in urban suburbs often causes habitat loss, soil erosion, wastewater discharge, and agricultural productivity decline, threatening long-term benefits for the local community. We developed a nature-based solution for sustainable land restoration by establishing “Green Treasure Island” (GTI). The aim of this study is to evaluate the ecological restoration effectiveness of GTI and explore its feasibility and replicability for future applications. The core eco-functional zone of GTI—a 7 hm² forested wetland—embedded a closed-loop framework that integrates land consolidation, ecological restoration, and sustainable land utilization. The forested wetland efficiently removed 65% and 74% of dissolved inorganic nitrogen and phosphorus from agricultural runoff, raised flood control capacity by 22%, and attracted 48 bird species. Additionally, this biophilic recreational space attracted over 3400 visitors in 2022, created green jobs, and promoted local green agricultural product sales. Through adaptive management and nature education activities, GTI evolved into a landmark that represents local natural–social characteristics and serves as a publicly accessible natural park for both rural and urban residents. This study demonstrates the feasibility of creating GTI for improving ecosystem services, providing a practical, low-cost template that governments and local managers can replicate in metropolitan rural areas worldwide to meet both ecological and development goals. Full article

(This article belongs to the Special Issue Ecohydrological Processes, Environmental Effects, and Integrated Regulation of Wetland Ecosystems, 3rd Edition)

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22 pages, 5581 KiB

Open AccessArticle

The Effect of Varying Durations of Post-Harvest Cryogenic Treatments on the Quality of Cabernet Sauvignon Wines

by Zhihao Deng, Guo Cheng, Wangze Li, Pengfei Yang, Kekun Zhang, Keqin Chen and Yulin Fang

Foods 2025, 14(11), 1972; https://doi.org/10.3390/foods14111972 (registering DOI) - 2 Jun 2025

Abstract

While cold chain transportation facilitates the utilization of wine grapes grown in remote mountainous areas, there is currently a lack of research on the impacts of different post-harvest temperatures on the quality of wine grapes. Therefore, three temperatures—room temperature (20 °C), chilled (4 [...] Read more.

While cold chain transportation facilitates the utilization of wine grapes grown in remote mountainous areas, there is currently a lack of research on the impacts of different post-harvest temperatures on the quality of wine grapes. Therefore, three temperatures—room temperature (20 °C), chilled (4 °C), and frozen (−20 °C)—were selected to study the effects of post-harvest low-temperature treatments. The results indicated that the contents of tartaric acid and total polyphenols in the resulting wines were higher after the grapes underwent freezing, while the opposite trend was observed for those stored at room temperature. The changes in color lightness of wines were inversely correlated with the changes in color saturation and red chromaticity, while the yellow chromaticity of wines fermented after storage exhibited a slight increase. Rutin and ferulic acid were identified as the characteristic monophenols that decreased post-storage, and heptanal emerged as the volatile compound that decreased similarly. Furthermore, the tannin contents of the resulting wines demonstrated a strong correlation with temperature: when grapes were chilled, they reached the highest level, presenting a decreasing trend over time. For low-temperature storage, 1-hexanol, ethyl caprylate, isopentyl acetate, and (Z)-2-heptenal were identified as characteristic volatile compounds under the different treatments. Overall, the choice of an appropriate chilling temperature for the post-harvest storage of grapes can ensure the quality characteristics of the produced wine. This study confirms the potential value of cold chain transportation for the effective utilization of wine grapes grown in remote areas. Full article

(This article belongs to the Special Issue Nutritional and Flavor Compounds in Fruit Wines)

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18 pages, 3221 KiB

Open AccessArticle

Foot-and-Mouth Disease Virus-like Particles Produced in E. coli as Potential Antigens for a Novel Vaccine

by Sang-Cheol Yu, In-Kyu Lee, Hyun-Seok Kong, Sung-Ho Shin, Sung-Yoon Hwang, Yu-Jin Ahn, Jong-Hyeon Park, Bong-Yoon Kim and Young-Cheon Song

Vet. Sci. 2025, 12(6), 539; https://doi.org/10.3390/vetsci12060539 (registering DOI) - 2 Jun 2025

Abstract

Foot-and-mouth disease virus (FMDV) continues to pose a significant threat to livestock health and the global agricultural economy, particularly in endemic regions of Asia, Africa, and the Middle East. Current vaccines based on chemically inactivated FMDV present several challenges, including biosafety risks, high [...] Read more.

Foot-and-mouth disease virus (FMDV) continues to pose a significant threat to livestock health and the global agricultural economy, particularly in endemic regions of Asia, Africa, and the Middle East. Current vaccines based on chemically inactivated FMDV present several challenges, including biosafety risks, high production costs, and limited effectiveness against emerging viral variants. To overcome these limitations, we developed virus-like particle (VLP) vaccines targeting FMDV serotypes O, A, and Asia1 using a recombinant Escherichia coli expression system. The resulting VLPs self-assembled into 25–30 nm particles with native-like morphology and antigenic properties, as confirmed by transmission electron microscopy, SDS-PAGE, and Western blot analysis. Immunogenicity was evaluated in mice and pigs using ELISA and virus neutralization tests (VNT), and protective efficacy was assessed through viral challenge studies. All VLPs induced strong serotype-specific antibody responses, with ELISA PI values exceeding 50% and significantly increased VNT titers after booster immunization. In mice, PD₅₀ values were 73.5 (A-type), 32.0 (O-type), and 55.7 (Asia1-type); in pigs, PD₅₀ values reached 10.6 (O-type) and 22.6 (Asia1-type). Notably, the vaccines induced robust immune responses even at lower antigen doses, suggesting the feasibility of dose-sparing formulations. These findings demonstrate that FMDV VLPs produced in E. coli are highly immunogenic and capable of eliciting protective immunity, highlighting their promise as safe, scalable, and cost-effective alternatives to conventional inactivated FMD vaccines. Full article

27 pages, 12274 KiB

Open AccessArticle

Mechanical Properties and Microstructure Damage of Limestone Concrete Under Triaxial Stress

by Kaide Liu, Songxin Zhao, Dingbo Wang, Wenping Yue, Chaowei Sun, Yu Xia and Qiyu Wang

Buildings 2025, 15(11), 1924; https://doi.org/10.3390/buildings15111924 (registering DOI) - 2 Jun 2025

Abstract

This study takes limestone crushed stone concrete as the research object and systematically investigates its mechanical property changes and microstructural damage characteristics under different confining pressures using triaxial compression tests, scanning electron microscope (SEM) tests, and digital image processing techniques. The results show [...] Read more.

This study takes limestone crushed stone concrete as the research object and systematically investigates its mechanical property changes and microstructural damage characteristics under different confining pressures using triaxial compression tests, scanning electron microscope (SEM) tests, and digital image processing techniques. The results show that, in terms of macro-mechanical properties, as the confining pressure increases, the peak strength increases by 192.66%, the axial peak strain increases by 143.66%, the elastic modulus increases by 133.98%, and the ductility coefficient increases by 54.61%. In terms of microstructure, the porosity decreases by 64.35%, the maximum pore diameter decreases by 75.69%, the fractal dimension decreases by 19.56%, and the interfacial transition zone cracks gradually extend into the aggregate interior. The optimization of the microstructure makes the concrete more compact, reduces stress concentration, and thereby enhances the macro-mechanical properties. Additionally, the failure characteristics of the specimens shift from diagonal shear failure to compressive flow failure. According to the Mohr–Coulomb strength criterion, the calculated cohesion is 6.96 MPa, the internal friction angle is 38.89°, and the breakage angle is 25.53°. A regression analysis established a quantitative relationship between microstructural characteristics and macro-mechanical properties, revealing the significant impact of microstructural characteristics on macro-mechanical properties. Under low confining pressure, early volumetric expansion and rapid volumetric strain occur, with microcracks mainly concentrated at the aggregate interface that are relatively wide. Under high confining pressure, volumetric expansion is delayed, volumetric strain increases slowly, and microcracks extend into the interior of the aggregate, becoming finer and more dispersed. Full article

(This article belongs to the Special Issue Advanced Research on Concrete Materials in Construction)

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18 pages, 3937 KiB

Open AccessArticle

Preliminary Evaluation of 3D-Printed Alginate/Gelatin Scaffolds for Protein Fast Release as Suitable Devices for Personalized Medicine

by Benedetta Ghezzi, Ruben Foresti, Luisa Pia Scialoia, Maddalena Botti, Arianna Mersanne, Fulvio Ratto, Francesca Rossi, Chiara Martini, Paolo Perini, Elda Favari and Antonio Freyrie

Biomedicines 2025, 13(6), 1365; https://doi.org/10.3390/biomedicines13061365 (registering DOI) - 2 Jun 2025

Abstract

Background/Objectives: Drug-coated balloons (DCBs) are emerging as a promising treatment for peripheral artery disease; however, current technologies lack flexibility in customizing drug release profiles and composition, limiting their therapeutic potential. This study aims to develop a Gelatin (Gel) and Sodium Alginate (Alg) bioink [...] Read more.

Background/Objectives: Drug-coated balloons (DCBs) are emerging as a promising treatment for peripheral artery disease; however, current technologies lack flexibility in customizing drug release profiles and composition, limiting their therapeutic potential. This study aims to develop a Gelatin (Gel) and Sodium Alginate (Alg) bioink loaded with apolipoprotein A-I (apoA-I) for controlled drug delivery by using additive manufacturing technologies. Methods: We developed and printed via rapid freeze prototyping (RFP) a Gel and Alg bioink loaded with different concentrations of apoA-I. Mechanical properties related to compressional and tensile forces have been studied, as well as the structural stability and active release from the 3D structure of apoA-I (cholesterol efflux assays). The biological behavior of HUVEC cells with and without ApoA-I was assessed by proliferation assay, metabolic activity analysis, and fluorescence imaging. Results: The 3D structures presented breakpoint stress values consistent with the mechanical requirements for integration within a DCB, and the ability to effectively promote cholesterol transport in J774 cells. Moreover, in vitro studies on HUVECs revealed that the scaffolds exhibited no cytotoxic effects, leading to increased ATP levels and enhanced metabolic activity over time, confirming the possibility to obtain RFP-printed Alg/Gel scaffolds able to provide a stable structure capable of controlled apoA-I release. Conclusions: These findings support the potential of Alg/Gel+apoA-I scaffolds as biocompatible drug delivery systems for vascular applications. Their ability to maintain structural integrity while enabling controlled biomolecular release positions them as promising candidates for personalized cardiovascular therapy, facilitating the rapid customization of bioprinted therapeutic platforms. Full article

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

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18 pages, 3956 KiB

Open AccessArticle

Comparative Analysis of Lab-Data-Driven Models for International Friction Index Prediction in High Friction Surface Treatment (HFST)

by Alireza Roshan and Magdy Abdelrahman

Appl. Sci. 2025, 15(11), 6249; https://doi.org/10.3390/app15116249 (registering DOI) - 2 Jun 2025

Abstract

High Friction Surface Treatments (HFSTs) are often utilized as a spot treatment to enhance selected areas with high friction demand rather than extended pavement sections and are helpful in increasing skid resistance and minimizing road accidents. A laboratory design approach was created to [...] Read more.

High Friction Surface Treatments (HFSTs) are often utilized as a spot treatment to enhance selected areas with high friction demand rather than extended pavement sections and are helpful in increasing skid resistance and minimizing road accidents. A laboratory design approach was created to assess the fundamental ideas behind the international friction index (IFI) concept and update the present IFI model parameters for HFST applications based on test findings to gain a better understanding of HFST performance. Two aggregate types in three sizes were tested under controlled polishing cycles. Friction and texture were measured using the Dynamic Friction Tester (DFT) and Circular Track Meter (CTM). Three physics-informed empirical models, including logarithmic, power law, and polynomial models, were selected to better represent texture effects, nonlinear scaling, and complex interactions between COF and MPD. Results show that friction performance varies with aggregate type, gradation, and polishing, and that traditional IFI parameters may not fully capture HFST behavior. Model refinements are suggested to better represent HFST surface characteristics with the lowest testing Root Mean Squared Error (RMSE) (0.049) and the highest predictive accuracy R² (0.821); the logarithmic model was found to be the best. Sensitivity analysis revealed that IFI predictions are more sensitive to COF (ΔIFI: 14.3–17.7%) than MPD (ΔIFI: 1.5–6.0%) across all models. These results demonstrate how these models can improve HFST design and performance assessment while providing useful information for enhancing road safety. This process is a useful tool for evaluating HFST friction resistance in a lab setting since it calculates HFST skid resistance using results measured in the lab. Full article

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17 pages, 550 KiB

Open AccessArticle

Identification and Estimation in Linear Models with Endogeneity Through Time-Varying Volatility

by Shih-Tang Hwu

Mathematics 2025, 13(11), 1849; https://doi.org/10.3390/math13111849 (registering DOI) - 2 Jun 2025

Abstract

This paper proposes a novel control function approach to identify and estimate linear models with endogenous variables in the absence of valid instrumental variables. The identification strategy exploits time-varying volatility to address the multicollinearity problem that arises in conventional control function methods when [...] Read more.

This paper proposes a novel control function approach to identify and estimate linear models with endogenous variables in the absence of valid instrumental variables. The identification strategy exploits time-varying volatility to address the multicollinearity problem that arises in conventional control function methods when instruments are weak. We establish the identification conditions and show that the proposed method is

\sqrt{T}

-consistent and asymptotically normal. We apply the proposed approach to estimate the elasticity of intertemporal substitution, a key parameter in macroeconomics. Using quarterly data on aggregate stock returns across eleven countries, we find that the data exhibit substantial time variation in volatility, supporting the identifying assumptions. The proposed method yields confidence intervals that are broadly consistent with the general findings in the literature and are substantially narrower than those obtained using weak-instrument robust methods. Full article

(This article belongs to the Special Issue Mathematical Finance: Statistical Inference, Stochastic Modeling, and Advanced Algorithms)

18 pages, 3247 KiB

Open AccessArticle

Ageing Mediterranean Bluefin Tuna: A Comparative Study Between Dorsal Fin Spines and Vertebrae

by Niki Milatou and Persefoni Megalofonou

Fishes 2025, 10(6), 260; https://doi.org/10.3390/fishes10060260 (registering DOI) - 2 Jun 2025

Abstract

This study estimated the age and growth of reared Atlantic bluefin tuna by analyzing two calcified structures: the caudal vertebrae and the dorsal fin spines. The aim was to compare the two ageing methods. A total of 613 dorsal fin spines and 613 [...] Read more.

This study estimated the age and growth of reared Atlantic bluefin tuna by analyzing two calcified structures: the caudal vertebrae and the dorsal fin spines. The aim was to compare the two ageing methods. A total of 613 dorsal fin spines and 613 vertebrae were aged, with each pair of calcified structures derived from the same individual fish. The age of each fish was determined from the number of visible growth bands on the structures. The estimated ages ranged from 4 to 20 years for dorsal fin spines and from 5 to 17 years for caudal vertebrae. Both calcified structures were demonstrated to be suitable for ageing bluefin tuna. The percent agreement between the two methods was high in medium-sized fish but lower in larger fish. Additionally, the results showed a tendency to estimate fewer years in vertebrae than in dorsal fin spines for fish older than 11 years. For the samples where no bias was found between the two ageing methods (N = 215), the von Bertalanffy growth model was fitted to the mean lengths at estimated ages, with the growth parameters determined as follows: L_∞ = 372.3 cm, k = 0.075 yr⁻¹, and t₀ = −1.292 yr. This research makes a novel contribution to the field by conducting a direct, large-scale comparison of age estimates derived from two different calcified structures, addressing a notable gap in the literature and offering critical insights into the consistency and reliability of ageing methods used in stock assessment. Full article

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