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Recent Articles  

19 pages, 940 KiB  
Article
Social Support and Environmental Factors for Older People Living in South Tyrol: A Multivariate Analysis
by Giulia Cavrini, Nadia Paone and Evan Tedeschi
Societies 2025, 15(5), 125; https://doi.org/10.3390/soc15050125 (registering DOI) - 5 May 2025
Abstract
Background and Aims: Current changes in family structures make the development of models for sustainably ensuring high-quality care for older people in the province of Bolzano–Bozen increasingly necessary to identify new solutions to address the needs of older people. This research project explores [...] Read more.
Background and Aims: Current changes in family structures make the development of models for sustainably ensuring high-quality care for older people in the province of Bolzano–Bozen increasingly necessary to identify new solutions to address the needs of older people. This research project explores support options that enable older individuals to live independently in their homes for as long as possible, based on data collected through a quantitative survey. Special attention is devoted to recent transformations in family dynamics, highlighting the urgency of rethinking care strategies for older people. Data and Methods: The study focuses on a sample of individuals aged 60 and older who reside in their own homes in South Tyrol. Data were collected through 536 interviews conducted in 2020, using a questionnaire administered in both German and Italian. A Latent Class Model (LCA) was used to identify latent categorical indicators, with each category representing a specific combination of factors derived from the data. Results: The findings underscore the critical role of eliminating architectural barriers, fostering social connections, and promoting volunteer activities as key factors in enhancing the quality of life and independence of older adults. Full article
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21 pages, 2660 KiB  
Review
Trends in Shoulder Arthroplasty: A Narrative Review of Predominant Indications and the Most Commonly Employed Implant Designs
by Paolo Fornaciari, Omid Jamei-Martel and Philippe Vial
J. Clin. Med. 2025, 14(9), 3186; https://doi.org/10.3390/jcm14093186 (registering DOI) - 5 May 2025
Abstract
Background: Over the past few decades, shoulder arthroplasty has evolved rapidly, driven by a growing demand for surgical solutions to degenerative, traumatic, and irreparable rotator cuff-related pathologies, particularly in an aging but increasingly active population. Objective: This narrative review aims to examine the [...] Read more.
Background: Over the past few decades, shoulder arthroplasty has evolved rapidly, driven by a growing demand for surgical solutions to degenerative, traumatic, and irreparable rotator cuff-related pathologies, particularly in an aging but increasingly active population. Objective: This narrative review aims to examine the main clinical indications and the most commonly used implant designs, highlighting differences in functional outcomes, complication rates, and revision rates between anatomic total shoulder arthroplasty (ATSA) and reverse total shoulder arthroplasty (RTSA). Methods: Articles published between 2011 and 2025 were selected through PubMed and the Australian Joint Replacement Registry reports from 2023 and 2024. The included studies comprised randomized controlled trials, systematic reviews, and meta-analyses involving adult patients treated for primary osteoarthritis, proximal humerus fractures, and massive irreparable rotator cuff tears. Results: ATSA remains the preferred option in younger patients with an intact rotator cuff, due to superior outcomes in mobility and prosthesis longevity. However, glenoid component loosening remains a significant limitation. Initially reserved for irreparable cuff tears and complex fractures, RTSA has seen a progressive expansion of its indications, offering lower revision rates and satisfactory functional results, particularly in elderly patients. Recent prosthetic innovations include stemless implants, augmented glenoid components, and convertible platforms. Conclusions: The choice between ATSA and RTSA should be individualized, based on patient-specific factors such as age, rotator cuff integrity, functional demands, and bone quality. Advances in implant materials and design, together with improved patient selection, have significantly enhanced clinical outcomes. Full article
(This article belongs to the Special Issue Trends and Prospects in Shoulder and Elbow Surgery)
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22 pages, 11622 KiB  
Article
Classification of Hacker’s Posts Based on Zero-Shot, Few-Shot, and Fine-Tuned LLMs in Environments with Constrained Resources
by Theodoros Giannilias, Andreas Papadakis, Nikolaos Nikolaou and Theodore Zahariadis
Future Internet 2025, 17(5), 207; https://doi.org/10.3390/fi17050207 (registering DOI) - 5 May 2025
Abstract
This paper investigates, applies, and evaluates state-of-the-art Large Language Models (LLMs) for the classification of posts from a dark web hackers’ forum into four cyber-security categories. The LLMs applied included Mistral-7B-Instruct-v0.2, Gemma-1.1-7B, Llama-3-8B-Instruct, and Llama-2-7B, with zero-shot learning, few-shot learning, and fine-tuning. The [...] Read more.
This paper investigates, applies, and evaluates state-of-the-art Large Language Models (LLMs) for the classification of posts from a dark web hackers’ forum into four cyber-security categories. The LLMs applied included Mistral-7B-Instruct-v0.2, Gemma-1.1-7B, Llama-3-8B-Instruct, and Llama-2-7B, with zero-shot learning, few-shot learning, and fine-tuning. The four cyber-security categories consisted of “Access Control and Management”, “Availability Protection and Security by Design Mechanisms”, “Software and Firmware Flaws”, and “not relevant”. The hackers’ posts were also classified and labelled by a human cyber-security expert, allowing a detailed evaluation of the classification accuracy per each LLM and customization/learning method. We verified LLM fine-tuning as the most effective mechanism to enhance the accuracy and reliability of the classifications. The results include the methodology applied and the labelled hackers’ posts dataset. Full article
(This article belongs to the Special Issue Generative Artificial Intelligence (AI) for Cybersecurity)
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12 pages, 2413 KiB  
Article
Bacillus Bio-Organic Fertilizer Altered Soil Microorganisms and Improved Yield and Quality of Radish (Raphanus sativus L.)
by Yingbin Qi, Zhen Wu, Yachen Wang, Rong Zhou, Liwang Liu, Yan Wang, Jiying Zhao and Fangling Jiang
Plants 2025, 14(9), 1389; https://doi.org/10.3390/plants14091389 - 5 May 2025
Abstract
Excessive use of fertilizers will not only cause the enrichment of soil N nutrients, soil secondary salinization, soil acidification, and an imbalance of the soil microbial community structure, but will also lead to the nitrate content of vegetables and the ground water exceeding [...] Read more.
Excessive use of fertilizers will not only cause the enrichment of soil N nutrients, soil secondary salinization, soil acidification, and an imbalance of the soil microbial community structure, but will also lead to the nitrate content of vegetables and the ground water exceeding the standard. The application of bio-organic fertilizer could reduce the amount of mineral fertilizer used. However, the effects of nitrogen reduced with different bio-organic fertilizers on soil chemical properties, microbial community structure, and the yield and quality of radish are not clear. In a field experiment, we designed six fertilization treatments: no fertilization (CK), conventional fertilization (T1), a total nitrogen reduction of 20% (T2), and a total nitrogen reduction of 20% with “No. 1”, “Seek” or “Jiajiapei” bio-organic fertilizers. The results showed that nitrogen reduction of 20% with Bacillus bio-organic fertilizer (N1) significantly increased the organic matter, pH, total nitrogen content, and the relative abundance of Bacillus and Streptomyce in the soil compared with T1. RDA analysis showed that the pH, organic matter content, invertase and fluorescein diacetate enzyme activity of the soil were significantly correlated with the soil microbial community structure. In addition, the yield and Vc content in radish were increased with the application of bio-organic fertilizers, while on the contrary, the nitrate and cellulose content were decreased, and the N1 treatment showed the best effect. Moreover, the yield had a significant positive correlation with Bacillus. Overall, nitrogen reduction with bio-organic fertilizers, especially full-effective “No. 1” enriched with Bacillus, could alter the soil microbial community structure and effectively improve soil fertility, which in turn enhanced the yield and quality of radish. An application of Bacillus bio-organic fertilizer was an effective strategy to improve soil quality and vegetable safety. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Soil Microbe Interactions in Vegetable Crops Under Abiotic Stress)
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21 pages, 10010 KiB  
Article
Agar Biopolymer as a Sustainable Alternative Binder to Enhance the Strength of Low-Plasticity Soil
by Mary Ann Adajar, Jomari Tan, Adriann Adriano, Sophia Bianca De Vera, John Vincent Manabat and Harumi Navarro
Polymers 2025, 17(9), 1253; https://doi.org/10.3390/polym17091253 (registering DOI) - 5 May 2025
Abstract
Low-plasticity silts (ML) found in Metro Manila, Philippines, characterized by low strength, stiffness, and bearing capacity, often require stabilization. Traditional methods using cement are associated with significant carbon emissions, causing environmental concerns. Sustainable materials such as agar biopolymers can be an alternative to [...] Read more.
Low-plasticity silts (ML) found in Metro Manila, Philippines, characterized by low strength, stiffness, and bearing capacity, often require stabilization. Traditional methods using cement are associated with significant carbon emissions, causing environmental concerns. Sustainable materials such as agar biopolymers can be an alternative to cement to improve the strength of fine-grained soils. A comparative study was conducted on ML samples treated with agar and cement at different concentrations (1%, 3%, 5%, and 7%) and subjected to varying curing periods (7, 21, 28, and 35 days) under air-dried conditions using Unconfined Compressive Strength (UCS) tests. Agar-treated samples generally exhibited higher UCS values than cement-treated samples across the tested concentrations and curing periods. Samples with 3% and 5% agar were significantly stronger than their cement-treated counterparts. The strength of agar-treated soils peaked at a 5% concentration and subsequently decreased at 7% agar, possibly due to a masking effect. SEM-EDS analysis revealed that a 5% agar concentration achieved a balanced microstructure with effective particle bonding, while higher concentrations led to diminished strength due to reduced mechanical interlocking from excessive biopolymer coverage. Subsequent statistical analysis also indicated significant improvement using agar versus cement-treated and untreated soils, especially at 5% agar. A predictive polynomial regression model demonstrated the influence of curing days and agar concentration on UCS, attaining R2 = 0.94 vs. experimental values. Using agar biopolymers presents a promising and potentially more sustainable approach to soil, highlighting the potential of utilizing a locally abundant resource for geotechnical engineering applications. Full article
(This article belongs to the Special Issue Advances in Biopolymer Materials: Properties, Processing, and Applications)
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28 pages, 1773 KiB  
Review
The Vaginal Microbiota, Human Papillomavirus, and Cervical Dysplasia—A Review
by Justė Kazlauskaitė, Guoda Žukienė, Vilius Rudaitis and Daiva Bartkevičienė
Medicina 2025, 61(5), 847; https://doi.org/10.3390/medicina61050847 - 5 May 2025
Abstract
Background and Objectives: The relationship between the vaginal microbiota, human papillomavirus infection (HPV), and cervical precancerous lesions is a critical area of research, as it influences both the progression of HPV-related diseases and potential treatment strategies. New evidence suggests that Lactobacillus crispatus dominance [...] Read more.
Background and Objectives: The relationship between the vaginal microbiota, human papillomavirus infection (HPV), and cervical precancerous lesions is a critical area of research, as it influences both the progression of HPV-related diseases and potential treatment strategies. New evidence suggests that Lactobacillus crispatus dominance in the microbiota may protect against HPV persistence and speed the elimination of HPV. This study aims to explore the relationship between the vaginal microbiota composition and HPV infection, focusing on the impact of these factors on the development of cervical precancerous lesions. Materials and Methods: A comprehensive literature review was conducted using the PubMed database, focusing on studies that analyzed the association between the vaginal microbiota and HPV infection in the context of cervical dysplasia. This study was primarily based on clinical data on HPV integration in women with low-grade squamous intraepithelial lesions (LSILs), high-grade squamous intraepithelial lesions (HSILs), and cervical cancer. Results: Different types of vaginal microbiota communities (CSTs) have different pathogenic or protective potential. Healthy women predominantly exhibited CST I, with Lactobacillus crispatus as the dominant microorganism. CST IV, associated with increased anaerobic bacteria, was most common in HSIL and cervical cancer patients. Statistical analysis revealed that bacterial vaginosis (BV) was significantly associated with HPV persistence, with studies reporting a 1.8–3.4-fold increased risk (p < 0.05) of persistent HR-HPV infection in BV-positive women. Conclusions: Our literature review suggests that the composition of the vaginal microbiota can modulate the local immune response, the expression of viral oncogenes, and the integrity of the epithelial barrier. Furthermore, certain bacterial genes or metabolic pathways can be associated with a favorable or unfavorable outcome of the disease. Analysis of the vaginal microbiota could serve as an additional risk assessment tool, helping to distinguish between regressing and progressive precancerous conditions. Full article
(This article belongs to the Special Issue Addressing the Changes and Innovations in the Treatment of Gynecological Cancers)
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21 pages, 1981 KiB  
Article
Enhanced Financial Fraud Detection Using an Adaptive Voted Perceptron Model with Optimized Learning and Error Reduction
by Muhammad Binsawad
Electronics 2025, 14(9), 1875; https://doi.org/10.3390/electronics14091875 - 5 May 2025
Abstract
Financial fraud detection is an important field in financial technology, and strong and effective machine learning (ML) models are needed to detect fraudulent transactions with high accuracy and reliability. Conventional fraud detection models, like probabilistic, instance-based, and tree-based models, tend to have high [...] Read more.
Financial fraud detection is an important field in financial technology, and strong and effective machine learning (ML) models are needed to detect fraudulent transactions with high accuracy and reliability. Conventional fraud detection models, like probabilistic, instance-based, and tree-based models, tend to have high error rates, class imbalance problems, and poor adaptability to changing fraud patterns. These issues call for sophisticated methods that improve predictive accuracy while being computationally efficient. To overcome these limitations, this research introduces the Voted Perceptron (VP) model, which utilizes an iterative learning process to dynamically adapt decision boundaries based on misclassified examples. In contrast to traditional models with static decision rules, the VP model constantly updates its weight parameters, thus providing better fraud detection abilities. The evaluation compares VP with state-of-the-art machine learning models, such as Average One Dependency Estimator (A1DE), K-nearest Neighbor (KNN), Naïve Bayes (NB), Random Tree (RT), and Functional Tree (FT), by using important performance metrics, like Mean Absolute Error (MAE), Root Mean Square Error (RMSE), True Positive Rate (TPR), recall, and accuracy. Experimental results show that VP outperforms its rivals significantly, yielding better fraud detection performance with low error rates and high recall. Furthermore, an ablation study confirms the influence of essential VP model elements on general classification performance. These results demonstrate VP to be an extremely effective model for detecting financial fraud, with enhanced flexibility towards evolving fraud patterns, and confirm the necessity for intelligent fraud detection mechanisms within financial organizations. Full article
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14 pages, 257 KiB  
Article
Depression and Anxiety Among Patients with Epilepsy: A Cross-Sectional Study in Saudi Arabia
by Mohammed A. Aljaffer, Ahmad H. Almadani, Ayedh H. Alghamdi, Anas A. Alalwan, Fay H. Albuqami, Khalid O. Altowaijri, Lujain A. Alkhalaf, Faisal A. Alazmi, Shahad F. Aljeri, Hadel H. Alhaluli and Bandar N. Aljafen
Brain Sci. 2025, 15(5), 484; https://doi.org/10.3390/brainsci15050484 - 5 May 2025
Abstract
Background: Epilepsy is a major neuropsychiatric disorder affecting many people worldwide, with depression and anxiety being common comorbidities that impact the quality of life (QoL). This study aims to examine depression and anxiety in epileptic patients at a tertiary care hospital, King Khalid [...] Read more.
Background: Epilepsy is a major neuropsychiatric disorder affecting many people worldwide, with depression and anxiety being common comorbidities that impact the quality of life (QoL). This study aims to examine depression and anxiety in epileptic patients at a tertiary care hospital, King Khalid University Hospital (KKUH), Riyadh, Saudi Arabia. It also aims to assess participants’ QoL and explore associated risk factors. Methods: This cross-sectional study enrolled 400 participants using a convenience sampling technique. The study tool consisted of a questionnaire, the Arabic version of the Hospital Anxiety and Depression Scale, and the Arabic version of the Quality of Life in Epilepsy Inventory. Results: The results revealed that 48.25% of the participants exhibited depression, and 39.75% exhibited anxiety. There was a statistically significant association between depression and educational level, employment status, history of psychiatric disorders, epilepsy duration, and all subscales of the Quality of Life in Epilepsy Inventory (QOLIE-31). There was also a statistically significant association between anxiety and educational level, employment status, history of psychiatric disorders, epilepsy duration, and all subscales of QOLIE-31. The mean overall QOLIE-31 score was 60.21 ± 20.19, with educational level and employment status, among other factors, being significantly associated with QOLIE-31. Conclusions: Depression and anxiety are prevalent among epileptic patients, requiring routine screening. Supporting education and employment among epileptic patients also appears to be crucial. Strategies to improve QoL among this population should be developed. Full article
(This article belongs to the Section Neuropsychiatry)
24 pages, 7959 KiB  
Article
Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking
by Ziqi Li, Dongyao Jia, Zihao He and Nengkai Wu
Appl. Sci. 2025, 15(9), 5119; https://doi.org/10.3390/app15095119 - 5 May 2025
Abstract
Multi-object tracking still faces significant challenges in complex conditions such as dense scenes, occlusion environments, and non-linear motion, especially regarding the detection and identity maintenance of small objects. To tackle these issues, this paper proposes a multi-modal fusion tracking framework that realizes high-precision [...] Read more.
Multi-object tracking still faces significant challenges in complex conditions such as dense scenes, occlusion environments, and non-linear motion, especially regarding the detection and identity maintenance of small objects. To tackle these issues, this paper proposes a multi-modal fusion tracking framework that realizes high-precision tracking in complex scenarios by collaboratively optimizing feature enhancement and motion prediction. Firstly, a multi-scale feature adaptive enhancement (MS-FAE) module is designed, integrating multi-level features and introducing a small object adaptive attention mechanism to enhance the representation ability for small objects. Secondly, a cross-frame feature association module (CFAM) is put forward, constructing a global semantic association network via grouped cross-attention and a memory recall mechanism to solve the matching difficulties in occlusion and dense scenes. Thirdly, a Dynamic Motion Model (DMM) is developed, enabling the robust prediction of non-linear motion based on an improved Kalman filter framework. Finally, a Bi-modal dynamic decision method (BDDM) is devised to fuse appearance and motion information for hierarchical decision making. Experiments conducted on multiple public datasets, including MOT17, MOT20, and VisDrone-MOT, demonstrate that this method remarkably improves tracking accuracy while maintaining real-time performance. On the MOT17 test set, it achieves 63.7% in HOTA, 61.4 FPS in processing speed, and 79.4% in IDF1, outperforming current state-of-the-art tracking algorithms. Full article
(This article belongs to the Topic Visual Computing and Understanding: New Developments and Trends)
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25 pages, 12677 KiB  
Article
Antioxidant Effect of Ethyl Acetate Fraction from Kaempferia galanga L.: Integrated Phytochemical Profiling, Network Analysis, and Experimental Validation
by Siyu Wang, Jianzhan Yang, Lei Cai, Haoxiang Li, Xiaodong Han, Bo Liu and Jianwei Wu
Antioxidants 2025, 14(5), 551; https://doi.org/10.3390/antiox14050551 - 5 May 2025
Abstract
Kaempferia galanga L. is well known for its use in medicinal and edible homologous application. Various diseases, including those related to oxidation, are commonly treated with it. However, its antioxidant effect is still lacking systematical study. We aimed to screen the most potential [...] Read more.
Kaempferia galanga L. is well known for its use in medicinal and edible homologous application. Various diseases, including those related to oxidation, are commonly treated with it. However, its antioxidant effect is still lacking systematical study. We aimed to screen the most potential antioxidant fraction of the crude ethanolic extract from K. galanga (KG) and evaluate its antioxidant activity and potential mechanism. The ethyl acetate fraction of ethanolic extract from K. galanga (KGEA) was chosen as the most potent antioxidant activity from all the fractions tested. UPLC-Q-TOF-MS/MS was used to determine 43 compounds in KGEA, and 25 potential bioactive compounds were identified by pharmacokinetic analysis. Network pharmacology revealed 174 overlapping targets of chemical and antioxidant targets, and the key targets were identified. Molecular docking and MD simulation revealed a strong binding affinity between the core compounds and their targets. In tests against DPPH and ABTS, KGEA exhibited potent radical scavenging activity. In H2O2-induced cells, KGEA could decrease reactive oxygen species (ROS) production; alleviate mitochondrial damage; promote the increase in antioxidant enzymes SOD, CAT, GSH-Px; and reduce the levels of MDA. Mechanistically, KGEA regulated PI3K/Akt and MAPK signaling pathways against oxidative damage. Moreover, in H2O2-induced zebrafish, KGEA attenuated ROS generation, cell death, lipid peroxidation, and increased SOD, CAT, GSH-Px activities; it also decreased MDA levels. The antioxidant properties of KGEA were demonstrated in vitro and in vivo, and it should be considered as an antioxidant agent for further profound study. Full article
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17 pages, 5559 KiB  
Article
Reconstruction of Cropland for the Rikaze Area of China Since the Tubo Dynasty (AD 655)
by Hongxia Pan, Qiong Chen, Zhilei Wu, Zemin Zhi, Wenguo Fang, Jiaqian Sun and Yanan Shi
Land 2025, 14(5), 994; https://doi.org/10.3390/land14050994 - 5 May 2025
Abstract
The reconstruction of cropland across historical periods offers valuable insights into the relationship between climate change and human–environment interactions. By extracting key demographic and tax revenue data from historical documents, we estimated cropland data during the Tubo, Yuan, Ming, and Qing dynasties for [...] Read more.
The reconstruction of cropland across historical periods offers valuable insights into the relationship between climate change and human–environment interactions. By extracting key demographic and tax revenue data from historical documents, we estimated cropland data during the Tubo, Yuan, Ming, and Qing dynasties for the Rikaze area in China. Subsequently, according to the characteristics of cropland fragmentation in the Rikaze area, we employed geographically weighted regression (GWR) to reconstruct the 1 km × 1 km cropland cover datasets across the four dynasties for the Rikaze area. The findings are as follows. The amount of cropland showed that the change in cropland in the Rikaze area in the four periods was extremely high, which reflects the great instability of cropland in the Rikaze area. Under the combined action of social unification, cropland production policies, and a suitable climate, the Tubo dynasty was the most significant period of cropland development in the Rikaze area, with the area of cropland reaching 591,927 mu. However, under the influence of the nomadic regime and harsh climate in the Yuan dynasty, the cropland area was sharply reduced, reaching only 18,338 mu. During the Ming and Qing dynasties, the cropland area increased steadily, reaching 200,000 mu and 547,000 mu, respectively. The spatial distribution of cropland shows that the cropland in the Rikaze area is mainly distributed in the middle reaches of the Yarlung Zangbo River, the middle and lower reaches of the Nianchu River, and the Pengqu River Valley. Counties and districts with better agricultural conditions, such as Jiangzi, Bailang, and Renbu, are the main concentration areas of cropland in the Rikaze area. The overall spatial distribution pattern of cropland shows fragmented distribution along rivers, highlighting the characteristics of valley cropland. The research in this paper represents the active exploration of the reconstruction of cropland distribution under complex terrain conditions. Full article
(This article belongs to the Section Land Systems and Global Change)
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13 pages, 3063 KiB  
Article
Exploring Factors Influencing Students’ Continuance Intention to Use E-Learning System for Iraqi University Students
by Ahmed Rashid Alkhuwaylidee
Computers 2025, 14(5), 176; https://doi.org/10.3390/computers14050176 - 5 May 2025
Abstract
In the past years, the education sector has suffered from repeated epidemics and their spread, and COVID-19 is a good example of this. Therefore, the search for other educational methods has become necessary. Therefore, e-learning is one of the best methods to replace [...] Read more.
In the past years, the education sector has suffered from repeated epidemics and their spread, and COVID-19 is a good example of this. Therefore, the search for other educational methods has become necessary. Therefore, e-learning is one of the best methods to replace traditional education. In this study, we found it necessary to conduct a comprehensive st udy on the perceptions of Iraqi university students toward e-learning and the factors affecting its use by students’ interest in being used consistently to increase learning effectiveness and the influence of educational presentations. In this research, the Expectation−Confirmation Model was used as a framework, and SPSS v21 and AMOS v21 were used to analyze the questionnaire obtained from 360 valid samples. According to the findings, students’ perceptions of the usefulness of e-learning systems are influenced by factors such as system quality, content quality, and confirmation. In addition, the findings show that technical support has no effect on perceived usefulness. In addition, content quality, system quality, and technical support are three critical antecedents of confirmation. In addition, we found that satisfaction was positively affected by both confirmation and perceived usefulness. We also found that the continuance intention to use e-learning was positively affected by both satisfaction and perceived usefulness. Full article
(This article belongs to the Special Issue Present and Future of E-Learning Technologies (2nd Edition))
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13 pages, 4231 KiB  
Article
Stress Distribution in a Mandibular Kennedy Class I with Bilateral Implant-Assisted Removable Partial Denture: A Finite Element Analysis
by Dagny Ochoa-Escate, Freddy Valdez-Jurado, Romel Watanabe, Martha Pineda-Mejía, Edwin Antonio Córdova Huayanay, Maria Soledad Ventocilla Huasupoma, Marcos Herrera Cisneros, Giovanna Lujan Larreátegui, Angela Quispe-Salcedo, Doris Salcedo-Moncada and Jesús Julio Ochoa Tataje
Oral 2025, 5(2), 31; https://doi.org/10.3390/oral5020031 - 5 May 2025
Abstract
Objectives: This study evaluated the dental and alveolar bone stress distribution of a mandibular Kennedy Class I restored with a bilateral implant-assisted removable partial denture (IARPD) compared with a conventional removable partial denture (CRPD) through the application of finite element analysis (FEA). Methods: [...] Read more.
Objectives: This study evaluated the dental and alveolar bone stress distribution of a mandibular Kennedy Class I restored with a bilateral implant-assisted removable partial denture (IARPD) compared with a conventional removable partial denture (CRPD) through the application of finite element analysis (FEA). Methods: Kennedy Class I plaster models were made, including teeth from the lower left first premolar and lower right canine. The models were scanned, resin-based replicated and digitized. Using Solidworks software, internal hexagonal implants (10 mm × 4 mm) were virtually placed at the level of the first molars. Each model was grouped into a unit, and a load of 200 N was applied, simulating masticatory forces. Von Mises stress distributions were calculated via FEA for the vertical, diagonal and combined forces. Results: In the IARPD, the stress generated in the alveolar bone by the vertical (4.2 Mpa), diagonal (12.2 MPa) and combined forces (12.3 MPa) was lower than that of the CRPD (7 MPa, 26.3 MPa and 32 MPa, respectively). Similarly, at the lower central incisor, the IARPD generated less stress than the CRPD due to the action of the vertical, diagonal and combined forces. Conclusions: Our preliminary data suggest that bilateral implant placement may result in less stress on bone and teeth during rehabilitation with a Kennedy Class I IARPD, with different orientations of the forces applied. Full article
(This article belongs to the Collection Synthesis, Testing and Mechanical Behavior of Dental Biomaterials at Different Clinical Parameters)
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11 pages, 540 KiB  
Article
Production of High-Value-Added Biomass by Saccharomyces cerevisiae Using Lignocellulosic Substrate
by Anelise Christ-Ribeiro, Carolina da Silva Graça, Kelly Cristina Massarolo, Débora Pez Jaeschke and Leonor Almeida de Souza Soares
Fermentation 2025, 11(5), 257; https://doi.org/10.3390/fermentation11050257 - 5 May 2025
Abstract
The aim of this study was to increase the availability of high-value-added compounds by applying S. cerevisiae to rice bran substrates (whole and defatted). The substrates were subjected to solid-state fermentation with yeast (3% pp−1) and water (30%) for up to [...] Read more.
The aim of this study was to increase the availability of high-value-added compounds by applying S. cerevisiae to rice bran substrates (whole and defatted). The substrates were subjected to solid-state fermentation with yeast (3% pp−1) and water (30%) for up to 8 h at 30 °C. The fermentation of brown rice bran resulted in increased ash, protein, and fiber contents, while the fermentation of defatted rice bran led to higher lipid and fiber levels. Additionally, the fermentation process influenced the mineral profile. The phenolic compound content of the fermented brown rice bran increased over fermentation, reaching values of 1165 µg g−1 per sample. Brown rice bran fermented for 6 h yielded the best results in terms of nutrient and bioactive compound availability. Principal component analysis (PCA) revealed correlations between variables, suggesting that modifications could further enhance the availability of various compounds. Full article
(This article belongs to the Special Issue Current Trends in Bioprocesses for Waste Valorization)
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18 pages, 2944 KiB  
Article
Optimal Strategy for Grid Loss Reduction Under Electricity Transmission and Distribution Reform Considering Low-Carbon Benefits
by Weiwu Li, Qing Xu, Xinying Wang, Zhengying Liu, Tianshou Li and Dandan Zhang
Processes 2025, 13(5), 1406; https://doi.org/10.3390/pr13051406 - 5 May 2025
Abstract
Selecting grid loss reduction strategies is crucial for energy-saving transformations, particularly in the context of electricity transmission and distribution pricing reforms. The optimization of strategic selection is not easy due to the vast number of grid devices, which leads to a multitude of [...] Read more.
Selecting grid loss reduction strategies is crucial for energy-saving transformations, particularly in the context of electricity transmission and distribution pricing reforms. The optimization of strategic selection is not easy due to the vast number of grid devices, which leads to a multitude of possible strategy combinations. This paper presents an optimal model for selecting loss reduction strategies, aiming to minimize the sum of comprehensive investment costs and energy loss costs over the life cycle of the strategies. The energy loss costs include both direct expenses due to energy loss and indirect costs, namely, carbon emission penalties. The constraints include allowable voltage deviations, branch power transmission, the number of loss reduction measures, loss rates, and total investment limits. The model comprehensively considers both economic benefits and the social benefits of reduced carbon emissions. It can help companies better adapt to electricity transmission and distribution pricing reforms, reduce operational costs, and contribute to low-carbon development. Finally, the model is validated using the data provided by one provincial power grid company in China. The results show that the loss reduction reaches 13.9 MW and the reduced carbon emission per hour is 10.425 t. The proposed method is also compared with the enumeration method, which demonstrates its effectiveness and efficiency. Further research will be conducted on establishing functional relationships between electricity sales prices and line losses to incentivize companies to apply loss reduction measures under different pricing functions. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control in Energy Systems)
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22 pages, 679 KiB  
Article
Protocol for a Randomized Controlled Trial to Determine if Biomarkers Predict Response to a Pediatric Chronic Pain Symptom Management Program
by Rona L. Levy, Tasha B. Murphy, Margaret M. Heitkemper, Miranda A. L. van Tilburg, Ann R. McMeans, Jocelyn Chang, Cynthia Boutte, Katherine Lamparyk, Bruno P. Chumpitazi and Robert J. Shulman
J. Clin. Med. 2025, 14(9), 3185; https://doi.org/10.3390/jcm14093185 - 5 May 2025
Abstract
Background/Objectives: Disorders of gut–brain interaction (DGBI), characterized by chronic abdominal pain and significant disability, affect 15–20% of children and adults and continue into adulthood in ~60% of cases. Costs for adults reach USD 30 billion per year, yet effective management strategies are [...] Read more.
Background/Objectives: Disorders of gut–brain interaction (DGBI), characterized by chronic abdominal pain and significant disability, affect 15–20% of children and adults and continue into adulthood in ~60% of cases. Costs for adults reach USD 30 billion per year, yet effective management strategies are elusive. Studies support using cognitive behavioral therapy (CBT), but abdominal pain only improves in ~40% of patients. Dietary management (low FODMAP diet; LFD) has also shown promise but it is effective in only a similar percentage of patients. Studies suggest that biologic factors (biomarkers) contribute to CBT response. Similarly, gut microbiome composition appears to influence abdominal pain response to the LFD. However, no previous CBT trials in children or adults have measured these biomarkers, and it is unclear which patients respond best to CBT vs. LFD. Methods: Children aged 7–12 years with DGBIs (n = 200) will be categorized as having/not having Autonomic Nervous System imbalance and/or abnormalities in gut physiology. We will randomize these children to either CBT or a LFD to compare the effectiveness of these treatments in those with/without abnormal physiologic biomarkers. We hypothesize that CBT will be more effective in those without abnormal physiology and LFD will be more effective in children with abnormal physiology. Primary outcome measures include the following: (1) Symptom improvement (abdominal pain frequency/severity) and (2) improvement in health-related quality of life. Conclusions: This innovative multidisciplinary study is the first to identify physiological characteristics that may moderate the response to two different management strategies. Identification of these characteristics may reduce the burden of these disorders through timely application of the intervention most likely to benefit an individual patient. Full article
(This article belongs to the Section Gastroenterology & Hepatopancreatobiliary Medicine)
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18 pages, 3381 KiB  
Article
Sea Breeze-Driven Variations in Planetary Boundary Layer Height over Barrow: Insights from Meteorological and Lidar Observations
by Hui Li, Wei Gong, Boming Liu, Yingying Ma, Shikuan Jin, Weiyan Wang, Ruonan Fan, Shuailong Jiang, Yujie Wang and Zhe Tong
Remote Sens. 2025, 17(9), 1633; https://doi.org/10.3390/rs17091633 - 5 May 2025
Abstract
The planetary boundary layer height (PBLH) in coastal Arctic regions is influenced by sea breeze circulation. However, the specific mechanisms through which sea breeze affects PBLH evolution remain insufficiently explored. This study uses meteorological data, micro-pulse lidar (MPL) data, and sounding profiles from [...] Read more.
The planetary boundary layer height (PBLH) in coastal Arctic regions is influenced by sea breeze circulation. However, the specific mechanisms through which sea breeze affects PBLH evolution remain insufficiently explored. This study uses meteorological data, micro-pulse lidar (MPL) data, and sounding profiles from 2014 to 2021 to investigate the annual and polar day PBLH evolution driven by sea breezes in the Barrow region of Alaska, as well as the specific mechanisms. The results show that sea breeze events significantly suppress PBLH, especially during the polar day, when prolonged solar radiation intensifies the thermal contrast between land and ocean. The cold, moist sea breeze stabilizes the atmospheric conditions, reducing net radiation and sensible heat flux. All these factors inhibit turbulent mixing and PBLH development. Lidar and sounding analyses further reveal that PBLH is lower during sea breeze events compared to non-sea-breeze conditions, with the peak of its probability density distribution occurring at a lower PBLH range. The variable importance in projection (VIP) analysis identifies relative humidity (VIP = 1.95) and temperature (VIP = 1.1) as the primary factors controlling PBLH, highlighting the influence of atmospheric stability in regulating PBLH. These findings emphasize the crucial role of sea breeze in modulating PBL dynamics in the Arctic, with significant implications for improving climate models and studies on pollutant dispersion in polar regions. Full article
(This article belongs to the Special Issue Advanced Lidar Remote Sensing for Atmosphere, Vegetation, and Ocean Observations)
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11 pages, 1555 KiB  
Article
Deep Learning-Based Classification of Canine Cataracts from Ocular B-Mode Ultrasound Images
by Sanghyeon Park, Seokmin Go, Seonhyo Kim and Jaeho Shim
Animals 2025, 15(9), 1327; https://doi.org/10.3390/ani15091327 (registering DOI) - 4 May 2025
Abstract
Cataracts are a prevalent cause of vision loss in dogs, and timely diagnosis is essential for effective treatment. This study aimed to develop and evaluate deep learning models to automatically classify canine cataracts from ocular ultrasound images. A dataset of 3155 ultrasound images [...] Read more.
Cataracts are a prevalent cause of vision loss in dogs, and timely diagnosis is essential for effective treatment. This study aimed to develop and evaluate deep learning models to automatically classify canine cataracts from ocular ultrasound images. A dataset of 3155 ultrasound images (comprising 1329 No cataract, 614 Cortical, 1033 Mature, and 179 Hypermature cases) was used to train and validate four widely used deep learning models (AlexNet, EfficientNetB3, ResNet50, and DenseNet161). Data augmentation and normalization techniques were applied to address category imbalance. DenseNet161 demonstrated the best performance, achieving a test accuracy of 92.03% and an F1-score of 0.8744. The confusion matrix revealed that the model attained the highest accuracy for the No cataract category (99.0%), followed by Cortical (90.3%) and Mature (86.5%) cataracts, while Hypermature cataracts were classified with lower accuracy (78.6%). Receiver Operating Characteristic (ROC) curve analysis confirmed strong discriminative ability, with an area under the curve (AUC) of 0.99. Visual interpretation using Gradient-weighted Class Activation Mapping indicated that the model effectively focused on clinically relevant regions. This deep learning-based classification framework shows significant potential for assisting veterinarians in diagnosing cataracts, thereby improving clinical decision-making in veterinary ophthalmology. Full article
(This article belongs to the Topic AI, Deep Learning, and Machine Learning in Veterinary Science Imaging)
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10 pages, 1298 KiB  
Article
Energy Metabolism and Aerobic Respiratory Chain of Vitreoscilla sp. C1: Comparison with β-Proteobacteria
by Paul T. Nguyen, Yuyao Hu, Anne Caroline Mascarenhas dos Santos, Pingdong Liang, Benjamin C. Stark, Karina Tuz and Oscar Juárez
Microbiol. Res. 2025, 16(5), 94; https://doi.org/10.3390/microbiolres16050094 - 4 May 2025
Abstract
As the source of the first reported class of non-mammalian hemoglobin, Vitreoscilla sp. C1 is a historically important microorganism that has offered important clues to understanding how bacteria can thrive at low oxygen tension, with potential applications to wastewater and sludge bioengineering. However, [...] Read more.
As the source of the first reported class of non-mammalian hemoglobin, Vitreoscilla sp. C1 is a historically important microorganism that has offered important clues to understanding how bacteria can thrive at low oxygen tension, with potential applications to wastewater and sludge bioengineering. However, the processes that enable this bacterium to thrive in such environments remain unclear. In this study, we analyzed the published Vitreoscilla sp. C1 genome to predict the core metabolic pathways used by this microorganism to support cell growth under hypoxic conditions, compared them with the predicted metabolism of other important β-proteobacteria, and tested Vitreoscilla’s respiratory activity in vitro in the presence of various substrates and inhibitors. Vitreoscilla sp. C1 carries a functional Krebs cycle and the genes for a branched aerobic respiratory chain, minus the genes for complexes III and IV, and our results show that Vitreoscilla sp. C1 sugar metabolism is carried out through a unique pathway that shunts intermediaries from glycolysis, bypassing phosphofructokinase-I, into the non-oxidative section of the pentose phosphate pathway, reducing its oxygen dependency, which appears as an adaptation to the microaerophilic environment that this organism inhabits. Although Vitreoscilla sp. C1 features a simplified respiratory chain, experimental data demonstrate that all predicted branches are functional, with two main dehydrogenases and two terminal oxidases. Full article
(This article belongs to the Topic Redox in Microorganisms, 2nd Edition)
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19 pages, 957 KiB  
Article
Prognostic Value of Non-Traditional Lipid Indices for In-Hospital Mortality in Patients with Acute Coronary Syndromes
by Rustem Yilmaz, Kenan Toprak, Ahmet Karagoz, Osman Can Yontar, Melisa Ucar, Halil Ibrahim Kokcu, Berkant Ozturk, Enes Kaya, Mustafa Yilmaz and Ersoy Öz
Medicina 2025, 61(5), 846; https://doi.org/10.3390/medicina61050846 - 4 May 2025
Abstract
Background and Objectives: Acute coronary syndrome (ACS) is a life-threatening cardiovascular condition with high mortality rates, necessitating accurate and early risk assessment to optimize patient outcomes. While traditional lipid markers, such as low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), are widely used, [...] Read more.
Background and Objectives: Acute coronary syndrome (ACS) is a life-threatening cardiovascular condition with high mortality rates, necessitating accurate and early risk assessment to optimize patient outcomes. While traditional lipid markers, such as low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), are widely used, non-traditional lipid indices, including the lipoprotein combined index (LCI), atherogenic index of plasma (AIP), atherogenic index (AI), Castelli risk indices (CRI-I, CRI-II), and atherogenic combined index (ACI) may offer additional prognostic insights by reflecting the underlying atherogenic and inflammatory processes. This study aimed to assess the prognostic value of these non-traditional lipid indices, along with traditional lipid and biochemical markers, for in-hospital mortality in ACS patients. Materials and Methods: This retrospective observational study analyzed data from ACS patients admitted to the coronary care unit (CCU) between January 2019 and September 2024. A cohort of 920 patients was divided into survivor (n = 823, 89.46%) and non-survivor (n = 97, 10.54%) groups based on in-hospital mortality outcomes. Demographic, hematological, biochemical, and lipid profile data, including traditional and non-traditional lipid indices, were collected. Separate logistic regression models were developed for each index, adjusting for demographic and clinical variables in order to assess the independent predictive power of each non-traditional lipid index. Results: Significant differences were observed between survivor and non-survivor groups in terms of age, c-reactive protein (CRP), white blood cell count (WBC), hemoglobin (HGB), and creatinine levels (all p-values < 0.05). While traditional lipid markers, such as LDL-C and HDL-C, showed limited predictive value, non-traditional lipid indices demonstrated stronger associations. The highest Exp (Beta) values were observed for the CRI-II, AI, and CRI-I. An ROC analysis further confirmed that the CRI-II, AI, and CRI-I had the highest AUC values, with pairwise comparisons underscoring the CRI-II’s superior accuracy. These findings suggest that non-traditional lipid indices predict atherogenic risk better than traditional markers alone. Conclusions: Non-traditional lipid indices, particularly the CRI-I and II, AI, LCI, ACI, and AIP, were found to be significantly associated with in-hospital mortality in ACS patients. These indices may provide additional prognostic value beyond traditional lipid parameters; however, further prospective studies are needed to confirm their clinical utility. These results underscore the importance of integrating non-traditional lipid indices into routine risk assessments to improve mortality predictions and inform targeted interventions in high-risk ACS patients. Full article
(This article belongs to the Section Cardiology)
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8 pages, 272 KiB  
Article
Gestational Hydronephrosis: A Retrospective Analysis of the Clinical Outcomes of Ureteral Stent Placement Versus Conservative Treatment
by Dursun Baba, Engin Yurtçu, Burak Ayvacık, Yusuf Salih Küçük, Arda Taşkın Taşkıran, Mehmet Ali Özel, Ahmet Yıldırım Balık, Ekrem Başaran and Betül Keyif
Medicina 2025, 61(5), 845; https://doi.org/10.3390/medicina61050845 - 4 May 2025
Abstract
Background and Objectives: Gestational hydronephrosis (GH) is a physiological condition commonly observed during pregnancy, resulting from hormonal effects and mechanical compression of the ureters by the enlarging uterus. Although often asymptomatic, GH can cause urinary stasis, recurrent infections, and renal function impairment in [...] Read more.
Background and Objectives: Gestational hydronephrosis (GH) is a physiological condition commonly observed during pregnancy, resulting from hormonal effects and mechanical compression of the ureters by the enlarging uterus. Although often asymptomatic, GH can cause urinary stasis, recurrent infections, and renal function impairment in symptomatic cases. The optimal management of such cases remains controversial, especially regarding the role of ureteral stent placement. This study aimed to compare clinical outcomes—including renal function, inflammatory markers, and obstetric parameters—in pregnant women with symptomatic GH who underwent ureteral stent placement versus those managed conservatively. Materials and Methods: We conducted a retrospective cohort study at Düzce University Hospital between 2020 and 2024, including 40 pregnant women diagnosed with symptomatic GH. The patients were divided into the following two groups: those who received a ureteral stent (n = 20) and those who were managed with conservative treatment (n = 20). Conservative management included hydration therapy, acetaminophen-based analgesia, and close clinical monitoring. The parameters assessed included serum creatinine, estimated glomerular filtration rate (GFR), inflammatory markers (C-reactive protein, erythrocyte sedimentation rate, and white blood cell count), urinary findings, obstetric outcomes, and postpartum complications. Statistical significance was set at p < 0.05. Results: Gestational age at diagnosis was significantly higher in the stent group (29.1 ± 3.2 weeks) than in the non-stent group (27.1 ± 3.5 weeks; p = 0.045), possibly reflecting increased mechanical compression in later pregnancy. Renal function parameters (serum creatinine and GFR), inflammatory markers (CRP, ESR, and WBC count), and obstetric outcomes (birth weight, Apgar scores) showed no significant differences between groups (p > 0.05). Interestingly, gestational diabetes mellitus (GDM) was more prevalent in the non-stent group (20% vs. 5%; p = 0.042), although no significant differences were found in fasting glucose levels. Conclusions: Ureteral stent placement in symptomatic GH does not appear to significantly improve renal function or obstetric outcomes. However, it may provide symptom relief in select patients with persistent or severe discomfort. Given the limitations of retrospective data and a small sample size, further prospective studies with larger cohorts and quality-of-life assessments are warranted to optimize management strategies and enhance patient-centered care. Full article
(This article belongs to the Section Urology & Nephrology)
21 pages, 4436 KiB  
Article
Sustainability and Innovation: Incorporating Waste from Ophthalmic Lenses into Natural Rubber Composites
by José Afonso Rocha, Carlos Toshiyuki Hiranobe, Dener da Silva Souza, Samara da Silva Araújo, Márcia Ferreira Hiranobe, Guilherme Henrique Barros de Souza, Elmer Mateus Gennaro, Flávio Camargo Cabrera, Guilherme Pina Cardim, Michael Jones da Silva, Erivaldo Antônio da Silva, José Francisco Resende da Silva and Renivaldo José dos Santos
Recycling 2025, 10(3), 90; https://doi.org/10.3390/recycling10030090 - 4 May 2025
Abstract
This study investigates the recycling of ophthalmic lens waste (OLW) in the production of vulcanized natural rubber (NR) composites, aiming to promote sustainability and reduce costs. To this end, Vietnamese natural rubber and ophthalmic lens waste were used, varying the filler content from [...] Read more.
This study investigates the recycling of ophthalmic lens waste (OLW) in the production of vulcanized natural rubber (NR) composites, aiming to promote sustainability and reduce costs. To this end, Vietnamese natural rubber and ophthalmic lens waste were used, varying the filler content from 0 to 50 phr. Rheological tests demonstrated that the addition of OLW decreases the cure time. The crosslink density, assessed through the Flory–Rehner and Mooney–Rivlin methods, exhibited an increase with the incorporation of a reinforcement. Thermal and spectroscopic analyses demonstrated the thermal stability of the composites and the absence of chemical interactions between the polymer matrix and the OLW. Mechanical tests showed that the composites exhibit satisfactory tensile and tear resistance, although the filler primarily acts as a filler rather than a structural reinforcement. Thus, the incorporation of OLW in NR composites emerges as a viable alternative for the reuse of industrial waste, fostering more sustainable and efficient practices in the polymer industry. Full article
(This article belongs to the Special Issue Challenges and Opportunities in Plastic Waste Management)
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18 pages, 4774 KiB  
Article
Hydrothermal Carbonization of Biomass Waste for Solid Biofuel Production: Hydrochar Characterization and Its Application in Blast Furnace Injection
by Guangwei Wang, Junyi Wu, Haibo Li, Andrey Karasev, Xiaojun Ning and Chuan Wang
Recycling 2025, 10(3), 89; https://doi.org/10.3390/recycling10030089 - 4 May 2025
Abstract
Hydrothermal carbonization (HTC) technology converts biomass into a carbon-rich, oxygen-containing solid fuel. Most studies have focused on hydrochar produced under laboratory conditions, leaving a gap in understanding the performance of industrially produced hydrochar. This study comprehensively analyzes three types of industrially produced hydrochar [...] Read more.
Hydrothermal carbonization (HTC) technology converts biomass into a carbon-rich, oxygen-containing solid fuel. Most studies have focused on hydrochar produced under laboratory conditions, leaving a gap in understanding the performance of industrially produced hydrochar. This study comprehensively analyzes three types of industrially produced hydrochar for blast furnace (BF) injection. The results indicate that hydrochar has a higher volatile and lower fixed carbon content. It has a lower high heating value (HHV) than coal and contains more alkali matter. Nevertheless, hydrochar exhibits a better grindability and combustion performance than coal. Blending hydrochar with anthracite significantly enhances the combustion reactivity of the mixture. The theoretical conversion rate calculations reveal a synergistic effect between hydrochar and anthracite during co-combustion. Environmental benefit calculations show that replacing 40% of bituminous coal with hydrochar can reduce CO2 emissions by approximately 145 kg/tHM, which is equivalent to an annual reduction of 528 kton of CO2 and 208 kton of coal in BF operations. While industrially produced hydrochar meets BF injection requirements, its low ignition point and high explosivity necessitate the careful control of the blending ratio. Full article
(This article belongs to the Special Issue Biomass Revival: Rethinking Waste Recycling for a Greener Future)
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15 pages, 14645 KiB  
Data Descriptor
Tracking U.S. Land Cover Changes: A Dataset of Sentinel-2 Imagery and Dynamic World Labels (2016–2024)
by Antonio Rangel, Juan Terven, Diana-Margarita Córdova-Esparza, Julio-Alejandro Romero-González, Alfonso Ramírez-Pedraza, Edgar A. Chávez-Urbiola, Francisco. J. Willars-Rodríguez and Gendry Alfonso-Francia
Data 2025, 10(5), 67; https://doi.org/10.3390/data10050067 - 4 May 2025
Abstract
Monitoring land cover changes is crucial for understanding how natural processes and human activities such as deforestation, urbanization, and agriculture reshape the environment. We introduce a publicly available dataset covering the entire United States from 2016 to 2024, integrating six spectral bands (Red, [...] Read more.
Monitoring land cover changes is crucial for understanding how natural processes and human activities such as deforestation, urbanization, and agriculture reshape the environment. We introduce a publicly available dataset covering the entire United States from 2016 to 2024, integrating six spectral bands (Red, Green, Blue, NIR, SWIR1, and SWIR2) from Sentinel-2 imagery with pixel-level land cover annotations from the Dynamic World dataset. This combined resource provides a consistent, high-resolution view of the nation’s landscapes, enabling detailed analysis of both short- and long-term changes. To ease the complexities of remote sensing data handling, we supply comprehensive code for data loading, basic analysis, and visualization. We also demonstrate an example application—semantic segmentation with state-of-the-art models—to evaluate dataset quality and reveal challenges associated with minority classes. The dataset and accompanying tools facilitate research in environmental monitoring, urban planning, and climate adaptation, offering a valuable asset for understanding evolving land cover dynamics over time. Full article
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38 pages, 2567 KiB  
Article
Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction—Part 1: Spatiotemporal Characteristics
by Amarech Alebie Addisuu, Gizaw Mengistu Tsidu and Lenyeletse Vincent Basupi
Climate 2025, 13(5), 95; https://doi.org/10.3390/cli13050095 - 4 May 2025
Abstract
Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these models emphasize the distribution of precipitation within a month or season rather than the overall amount. To meet this requirement, a study applied three [...] Read more.
Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these models emphasize the distribution of precipitation within a month or season rather than the overall amount. To meet this requirement, a study applied three bias correction techniques—scaled distribution mapping (SDM), quantile distribution mapping (QDM), and QDM with a separate treatment for precipitation below and above the 95th percentile threshold (QDM95)—to daily precipitation data from eleven Coupled Model Intercomparison Project Phase 6 (CMIP6) models, using the Climate Hazards Group Infrared Precipitation with Station version 2 (CHIRPS) as a reference. This study evaluated the performance of all bias-corrected CMIP6 models over Southern Africa from 1982 to 2014 in replicating the spatial and temporal patterns of precipitation across the region against three observational datasets, CHIRPS, the Climatic Research Unit (CRU), and the Global Precipitation Climatology Centre (GPCC), using standard statistical metrics. The results indicate that all bias-corrected precipitation generally performs better than native model precipitation in replicating the observed December–February (DJF) mean and seasonal cycle. The probability density function (PDF) of the bias-corrected regional precipitation indicates that bias correction enhances model performance, particularly for precipitation in the range of 3–35 mm/day. However, both corrected and uncorrected models underestimate higher extremes. The pattern correlations of the bias-corrected precipitation with CHIRPS, the GPCC, and the CRU, as compared to the correlations of native precipitation with the three datasets, have improved from 0.76–0.89 to 0.97–0.99, 0.73–0.87 to 0.94–0.97, and 0.74–0.89 to 0.97–0.99, respectively. Additionally, the Taylor skill scores of the models for replicating the CHIRPS, GPCC, and CRU precipitation spatial patterns over Southern Africa have improved from 0.57–0.80 to 0.79–0.95, 0.55–0.76 to 0.80–0.91, and 0.54–0.75 to 0.81–0.91, respectively. Overall, among the three bias correction techniques, QDM consistently demonstrated better performance than both QDM95 and SDM across various metrics. The implementation of distribution-based bias correction resulted in a significant reduction in bias and improved the spatial consistency between models and observations over the region. Full article
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15 pages, 6083 KiB  
Article
Investigation of 1,3-Diketone and Nano-Copper Additives for Enhancing Boundary Lubrication Performance
by Jingsi Wang, Dezhi Teng, Jiawei Fan, Xi Zhang, Qihang Cui, Ke Li and Pay Jun Liew
J. Mar. Sci. Eng. 2025, 13(5), 912; https://doi.org/10.3390/jmse13050912 - 4 May 2025
Abstract
In this work, 1,3-diketone synthesized via the Claisen condensation method and nano-copper particles modified by the Brust–Schiffrin method were added into a commercial marine medium-speed diesel engine cylinder piston oil to evaluate their effects on boundary lubrication performance. Friction and wear tests conducted [...] Read more.
In this work, 1,3-diketone synthesized via the Claisen condensation method and nano-copper particles modified by the Brust–Schiffrin method were added into a commercial marine medium-speed diesel engine cylinder piston oil to evaluate their effects on boundary lubrication performance. Friction and wear tests conducted on CKS-coated piston ring and cast-iron cylinder liner samples demonstrated significant reductions in both friction and wear with the addition of 1,3-diketone and nano-copper particles. Compared to the original oil without additives, the friction force was reduced by up to 16.7%, while the wear of the piston ring and cylinder liner was decreased by up to 21.6% and 15.1% at 150 °C, respectively. A worn surface analysis indicated that the addition of 1,3-diketone and functionalized nano-copper particles influenced the depolymerization and tribo-chemical reactions of the anti-wear additive ZDDP (zinc dialkyldithiophosphate) in the original engine oil. This modification enhanced the oil’s anti-friction and anti-wear properties, offering valuable insights into the development of eco-friendly lubricants for energy-efficient systems. Full article
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