MDPI - Publisher of Open Access Journals

23 pages, 3967 KiB

Open AccessArticle

Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest

by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris and Panagiotis Stefanidis

Atmosphere 2025, 16(7), 851; https://doi.org/10.3390/atmos16070851 (registering DOI) - 12 Jul 2025

Abstract

Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression [...] Read more.

Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression (SVR), Random Forest Regression (RFR), Gradient Boosting Regression (GBR), and K-Nearest Neighbors (KNN)—in predicting daily PET using limited meteorological data from a high-altitude in Central Greece. The ML models were trained and tested using easily available meteorological inputs—temperature, relative humidity, and extraterrestrial solar radiation—on a dataset covering 11 years (2012–2023). Among the tested configurations, RFR showed the best performance (R² = 0.917, RMSE = 0.468 mm/d, MAPE = 0.119 mm/d) when all the above-mentioned input variables were included, closely approximating FAO56–PM outputs. Results bring to light the potential of machine learning models to reliably estimate PET in data-scarce conditions, with RFR outperforming others, whereas the inclusion of the easily estimated extraterrestrial radiation parameter in the ML models training enhances PET prediction accuracy. Full article

(This article belongs to the Special Issue Observation and Modeling of Evapotranspiration)

► Show Figures

Figure 1

27 pages, 344 KiB

Open AccessArticle

Unveiling the Dual Mechanisms of Public Environmental Concern on Green Innovation Quality: The Interplay Between External Pressure and Internal Motivation

by Guomin Song and Fengyan Wang

Sustainability 2025, 17(14), 6398; https://doi.org/10.3390/su17146398 (registering DOI) - 12 Jul 2025

Abstract

Numerous studies have examined how environmental restrictions affect innovation behavior; however, there has not been enough research focused on how public environmental concerns affect green innovation. This paper utilizes panel data of 4607 Chinese A-share listed companies (29,877 firm-year observations) over the period [...] Read more.

Numerous studies have examined how environmental restrictions affect innovation behavior; however, there has not been enough research focused on how public environmental concerns affect green innovation. This paper utilizes panel data of 4607 Chinese A-share listed companies (29,877 firm-year observations) over the period of 2011–2022 and constructs a dual fixed-effects model to investigate the impact of public environmental concern (PEC) on green innovation quality. Furthermore, we explore the mechanisms underlying this influence through the lenses of external pressure and internal motivation, and the moderating effect of digital transformation. The findings reveal the following: (1) Public concern about environmental issues is positively correlated with the green innovation quality. For every 1% increase in PEC, the companies’ green innovation quality will increase by 0.013%. (2) PEC forces firms to improve the green innovation quality through pressure from institutional investors, while pushing firms to boost the green innovation quality by stimulating ESG performance. (3) Digital transformation reinforces the impact of PEC on the green innovation quality. (4) PEC is more sensitive to the impact of green innovation quality in high-tech and non-heavy-polluting companies, and the enhancement effect is more pronounced in the eastern and western districts. Besides expanding the insights into the factors influencing the green innovation quality, this study also gives pragmatic guidance for governments and companies to enhance the green innovation quality, address environmental challenges, and achieve sustainable development. Full article

(This article belongs to the Section Pollution Prevention, Mitigation and Sustainability)

► Show Figures

Figure 1

20 pages, 568 KiB

Open AccessArticle

Non-Parametric Inference for Multi-Sample of Geometric Processes with Application to Multi-System Repair Process Modeling

by Ömer Altındağ

Mathematics 2025, 13(14), 2260; https://doi.org/10.3390/math13142260 (registering DOI) - 12 Jul 2025

Abstract

The geometric process is a significant monotonic stochastic process widely used in the fields of applied probability, particularly in the failure analysis of repairable systems. For repairable systems modeled by a geometric process, accurate estimation of model parameters is essential. The inference problem [...] Read more.

The geometric process is a significant monotonic stochastic process widely used in the fields of applied probability, particularly in the failure analysis of repairable systems. For repairable systems modeled by a geometric process, accurate estimation of model parameters is essential. The inference problem for geometric processes has been well-studied in the case of single-sample data. However, multi-sample data may arise when the repair processes of multiple systems are observed simultaneously. This study addresses the non-parametric inference problem for geometric processes based on multi-sample data. Several non-parametric estimators are proposed using the linear regression method, and their asymptotic properties are established. In addition, test statistics are introduced to assess sample homogeneity and to evaluate the significance of the trend observed in the process. The performance of the proposed estimators is evaluated through a comprehensive simulation study under small-sample settings. An artificial data analysis is conducted to model the repair processes of multiple repairable systems using the geometric process. Furthermore, a real-world dataset consisting of multi-sample failure data from two shared memory processors of the Blue Mountain supercomputer is analyzed to demonstrate the practical applicability of the method in multi-sample failure data analysis. Full article

(This article belongs to the Section D1: Probability and Statistics)

► Show Figures

Figure 1

17 pages, 384 KiB

Open AccessArticle

The Detection Method of the Tobit Model in a Dataset

by El ouali Rahmani and Mohammed Benmoumen

Stats 2025, 8(3), 59; https://doi.org/10.3390/stats8030059 (registering DOI) - 12 Jul 2025

Abstract

This article proposes an extension of detection methods for the Tobit model by generalizing existing approaches from cases with known parameters to more realistic scenarios where the parameters are unknown. The main objective is to develop detection procedures that account for parameter uncertainty [...] Read more.

This article proposes an extension of detection methods for the Tobit model by generalizing existing approaches from cases with known parameters to more realistic scenarios where the parameters are unknown. The main objective is to develop detection procedures that account for parameter uncertainty and to analyze how this uncertainty affects the estimation process and the overall accuracy of the model. The methodology relies on maximum likelihood estimation, applied to datasets generated under different configurations of the Tobit model. A series of Monte Carlo simulations is conducted to evaluate the performance of the proposed methods. The results provide insights into the robustness of the detection procedures under varying assumptions. The study concludes with practical recommendations for improving the application of the Tobit model in fields such as econometrics, health economics, and environmental studies. Full article

► Show Figures

Figure 1

18 pages, 4285 KiB

Open AccessArticle

Application of a Phase-Change Material Heat Exchanger to Improve the Efficiency of Heat Pumps at Partial Loads

by Koharu Tani, Sayaka Kindaichi, Keita Kawasaki and Daisaku Nishina

Energies 2025, 18(14), 3694; https://doi.org/10.3390/en18143694 (registering DOI) - 12 Jul 2025

Abstract

Inverter-equipped heat pumps allow for increased energy efficiency. However, air conditioning (AC) systems often operate at low load ratios below where inverter control is effective, which reduces their energy efficiency. We developed an AC system that increases the apparent load ratio of the [...] Read more.

Inverter-equipped heat pumps allow for increased energy efficiency. However, air conditioning (AC) systems often operate at low load ratios below where inverter control is effective, which reduces their energy efficiency. We developed an AC system that increases the apparent load ratio of the heat pump by using a phase-change material (PCM). Cooling and heating experiments were conducted with a PCM heat exchanger, which comprised aluminum plates and fins filled with paraffinic PCM. The result indicated a high heat transfer coefficient of >70 W/(m²·K). A simplified numerical model of the PCM heat exchanger as a lumped constant system was created based on the experiment. The calculations generally reproduced the experimental results, with root mean squared errors of 0.39 K for cooling and 0.84 K for heating, confirming their accuracy. Simulations were then conducted to evaluate the energy performance of the proposed system for the cooling season. While low load operation accounted for 39% of the total AC time for a non-PCM system, it was reduced to 2.7% for the proposed system. The proposed system demonstrated load ratios of 50–60% for most of the season, achieving an energy reduction of 11.4% owing to the improved efficiency at partial load ratios. Full article

(This article belongs to the Section J1: Heat and Mass Transfer)

► Show Figures

Figure 1

33 pages, 1211 KiB

Open AccessReview

“My Bitch Is Empty!” an Overview of the Preconceptional Causes of Infertility in Dogs

by Juliette Roos-Pichenot and Maja Zakošek Pipan

Vet. Sci. 2025, 12(7), 663; https://doi.org/10.3390/vetsci12070663 (registering DOI) - 12 Jul 2025

Abstract

Infertility is a complex and common problem in reproductive medicine consultations. Three factors must be examined during the preconception phase: breeding management, the fertility of the bitch, and the fertility of the stud dog. Among these factors, improper breeding management remains the main [...] Read more.

Infertility is a complex and common problem in reproductive medicine consultations. Three factors must be examined during the preconception phase: breeding management, the fertility of the bitch, and the fertility of the stud dog. Among these factors, improper breeding management remains the main cause of reproductive failure, with accurate recognition of ovulation being crucial for successful mating. Artificial insemination allows for a thorough evaluation of semen quality compared to natural mating. In addition, genetic selection, nutritional factors, and reproductive health management can either impair or improve the fertility of females and males. Idiopathic infertility can occur in bitches, but it is important to rule out other possible causes first. In bitches with irregular estrus cycles, ovarian dysfunction and endocrine imbalances should be investigated. In bitches with regular cycles, uterine disorders such as cystic endometrial hyperplasia, endometritis or congenital anomalies may be the cause. Both mating-related and chronic endometritis are recognized as contributing factors to infertility. Infectious agents, particularly Brucella spp. and Mycoplasma spp., should also be evaluated, although interpretation of Mycoplasma test results requires caution. In males presenting with poor semen quality, potential causes include infectious diseases (with brucellosis always requiring exclusion), hormonal imbalances, and the impact of exogenous treatments. The article underscores the critical role of comprehensive diagnostic protocols, proactive health surveillance, and data-driven breeding strategies in systematically addressing this multifaceted challenge. Full article

(This article belongs to the Section Veterinary Reproduction and Obstetrics)

20 pages, 8459 KiB

Open AccessArticle

Membrane Processes for Remediating Water from Sugar Production By-Product Stream

by Amal El Gohary Ahmed, Christian Jordan, Eva Walcher, Selma Kuloglija, Reinhard Turetschek, Antonie Lozar, Daniela Tomasetig and Michael Harasek

Membranes 2025, 15(7), 207; https://doi.org/10.3390/membranes15070207 (registering DOI) - 12 Jul 2025

Abstract

Sugar production generates wastewater rich in dissolved solids and organic matter, and improper disposal poses severe environmental risks, exacerbates water scarcity, and creates regulatory challenges. Conventional treatment methods, such as evaporation and chemical precipitation, are energy-intensive and often ineffective at removing fine particulates [...] Read more.

Sugar production generates wastewater rich in dissolved solids and organic matter, and improper disposal poses severe environmental risks, exacerbates water scarcity, and creates regulatory challenges. Conventional treatment methods, such as evaporation and chemical precipitation, are energy-intensive and often ineffective at removing fine particulates and dissolved impurities. This study evaluates membrane-based separation as a sustainable alternative for water reclamation and sugar recovery from sugar industry effluents, focusing on replacing evaporation with membrane processes, ensuring high permeate quality, and mitigating membrane fouling. Cross-flow filtration experiments were conducted on a lab-scale membrane system at 70 °C to suppress microbial growth, comparing direct reverse osmosis (RO) of the raw effluent to an integrated ultrafiltration (UF)–RO process. Direct RO resulted in rapid membrane fouling. A tight UF (5 kDa) pre-treatment before RO significantly mitigated fouling and improved performance, enabling 28% water recovery and 79% sugar recovery, maintaining permeate conductivity below 0.5 mS/cm, sustaining stable flux, and reducing membrane blocking. Additionally, the UF and RO membranes were tested via SEM, EDS, and FTIR to elucidate the fouling mechanisms. Full article

(This article belongs to the Special Issue Emerging Superwetting Membranes: New Advances in Water Treatment)

► Show Figures

Figure 1

23 pages, 22555 KiB

Open AccessArticle

Citrate Transporter Expression and Localization: The Slc13a5^Flag Mouse Model

by Jan C.-C. Hu, Tian Liang, Hong Zhang, Yuanyuan Hu, Yasuo Yamakoshi, Ryuji Yamamoto, Chuhua Zhang, Hui Li, Charles E. Smith and James P. Simmer

Int. J. Mol. Sci. 2025, 26(14), 6707; https://doi.org/10.3390/ijms26146707 (registering DOI) - 12 Jul 2025

Abstract

The sodium–citrate cotransporter (NaCT) plays a crucial role in citrate transport during amelogenesis. Mutations in the SLC13A5 gene, which encodes the NaCT, cause early infantile epileptic encephalopathy 25 and amelogenesis imperfecta. We analyzed developing pig molars and determined that the citrate concentrations in [...] Read more.

The sodium–citrate cotransporter (NaCT) plays a crucial role in citrate transport during amelogenesis. Mutations in the SLC13A5 gene, which encodes the NaCT, cause early infantile epileptic encephalopathy 25 and amelogenesis imperfecta. We analyzed developing pig molars and determined that the citrate concentrations in secretory- and maturation-stage enamel are both 5.3 µmol/g, with about 95% of the citrate being bound to mineral. To better understand how citrate might enter developing enamel, we developed Slc13a5^Flag reporter mice that express NaCT with a C-terminal Flag-tag (DYKDDDDK) that can be specifically and accurately recognized by commercially available anti-Flag antibodies. The 24-base Flag coding sequence was located immediately upstream of the natural translation termination codon (TAG) and was validated by Sanger sequencing. The general development, physical activities, and reproductive outcomes of this mouse strain were comparable to those of the C57BL/6 mice. No differences were detected between the Slc13a5^Flag and wild-type mice. Tooth development was extensively characterized using dissection microscopy, bSEM, light microscopy, in situ hybridization, and immunohistochemistry. Tooth formation was not altered in any detectable way by the introduction of the Flag. The Slc13a5^Flag citrate transporter was observed on all outer membranes of secretory ameloblasts (distal, lateral, and proximal), with the strongest signal on the Tomes process, and was detectable in all but the distal membrane of maturation-stage ameloblasts. The papillary layer also showed positive immunostaining for Flag. The outer membrane of odontoblasts stained stronger than ameloblasts, except for the odontoblastic processes, which did not immunostain. As NaCT is thought to only facilitate citrate entry into the cell, we performed in situ hybridization that showed Ank is not expressed by secretory- or maturation-stage ameloblasts, ruling out that ANK can transport citrate into enamel. In conclusion, we developed Slc13a5^Flag reporter mice that provide specific and sensitive localization of a fully functional NaCT-Flag protein. The localization of the Slc13a5^Flag citrate transporter throughout the ameloblast membrane suggests that either citrate enters enamel by a paracellular route or NaCT can transport citrate bidirectionally (into or out of ameloblasts) depending upon local conditions. Full article

(This article belongs to the Special Issue Molecular Metabolism of Ameloblasts in Tooth Development)

► Show Figures

Figure 1

36 pages, 1452 KiB

Open AccessReview

A Beautiful Bind: Phage Display and the Search for Cell-Selective Peptides

by Babak Bakhshinejad and Saeedeh Ghiasvand

Viruses 2025, 17(7), 975; https://doi.org/10.3390/v17070975 (registering DOI) - 12 Jul 2025

Abstract

Phage display has advanced the discovery of peptides that selectively bind to a wide variety of cell surface molecules, offering new modalities to modulate disease-related protein–protein interactions (PPIs). These cell-binding peptides occupy a unique pharmaceutical space between small molecules and large biologics, and [...] Read more.

Phage display has advanced the discovery of peptides that selectively bind to a wide variety of cell surface molecules, offering new modalities to modulate disease-related protein–protein interactions (PPIs). These cell-binding peptides occupy a unique pharmaceutical space between small molecules and large biologics, and their growing popularity has opened up new avenues for targeting cell surface proteins that were previously considered undruggable. This work provides an overview of methods for identifying cell-selective peptides using phage display combinatorial libraries, covering in vitro, ex vivo, and in vivo biopanning approaches. It addresses key considerations in library design, including the peptide conformation (linear vs. cyclic) and length, and highlights examples of clinically approved peptides developed through phage display. It also discusses the on-phage chemical cyclization of peptides to overcome the limitations of genetically encoded disulfide bridges and emphasizes advances in combining next-generation sequencing (NGS) with phage display to improve peptide selection and analysis workflows. Furthermore, due to the often suboptimal binding affinity of peptides identified in phage display selections, this article discusses affinity maturation techniques, including random mutagenesis and rational design through structure–activity relationship (SAR) studies to optimize initial peptide candidates. By integrating these developments, this review outlines practical strategies and future directions for harnessing phage display in targeting challenging cell surface proteins. Full article

(This article belongs to the Special Issue The Application of Viruses to Biotechnology 3.0)

21 pages, 4285 KiB

Open AccessArticle

Federated Learning for Human Pose Estimation on Non-IID Data via Gradient Coordination

by Peng Ni, Dan Xiang, Dawei Jiang, Jianwei Sun and Jingxiang Cui

Sensors 2025, 25(14), 4372; https://doi.org/10.3390/s25144372 (registering DOI) - 12 Jul 2025

Abstract

Human pose estimation is an important downstream task in computer vision, with significant applications in action recognition and virtual reality. However, data collected in a decentralized manner often exhibit non-independent and identically distributed (non-IID) characteristics, and traditional federated learning aggregation strategies can lead [...] Read more.

Human pose estimation is an important downstream task in computer vision, with significant applications in action recognition and virtual reality. However, data collected in a decentralized manner often exhibit non-independent and identically distributed (non-IID) characteristics, and traditional federated learning aggregation strategies can lead to gradient conflicts that impair model convergence and accuracy. To address this, we propose the Federated Gradient Harmonization aggregation strategy (FedGH), which coordinates update directions by measuring client gradient discrepancies and integrating gradient-projection correction with a parameter-reconstruction mechanism. Experiments conducted on a self-constructed single-arm robotic dataset and the public Max Planck Institute for Informatics (MPII Human Pose Dataset) dataset demonstrate that FedGH achieves average Percentage of Correct Keypoints (PCK) of 47.14% and 66.31% across all keypoints, representing improvements of 1.82 and 0.36 percentage points over the Federated Adaptive Weighting (FedAW) method. On our self-constructed dataset, FedGH attains a PCK of 86.4% for shoulder detection, surpassing other traditional federated learning methods by 20–30%. Moreover, on the self-constructed dataset, FedGH reaches over 98% accuracy in the keypoint heatmap regression model within the first 10 rounds and remains stable between 98% and 100% thereafter. This method effectively mitigates gradient conflicts in non-IID environments, providing a more robust optimization solution for distributed human pose estimation. Full article

(This article belongs to the Section Sensors and Robotics)

► Show Figures

Figure 1

37 pages, 618 KiB

Open AccessSystematic Review

Interaction, Artificial Intelligence, and Motivation in Children’s Speech Learning and Rehabilitation Through Digital Games: A Systematic Literature Review

by Chra Abdoulqadir and Fernando Loizides

Information 2025, 16(7), 599; https://doi.org/10.3390/info16070599 (registering DOI) - 12 Jul 2025

Abstract

The integration of digital serious games into speech learning (rehabilitation) has demonstrated significant potential in enhancing accessibility and inclusivity for children with speech disabilities. This review of the state of the art examines the role of serious games, Artificial Intelligence (AI), and Natural [...] Read more.

The integration of digital serious games into speech learning (rehabilitation) has demonstrated significant potential in enhancing accessibility and inclusivity for children with speech disabilities. This review of the state of the art examines the role of serious games, Artificial Intelligence (AI), and Natural Language Processing (NLP) in speech rehabilitation, with a particular focus on interaction modalities, engagement autonomy, and motivation. We have reviewed 45 selected studies. Our key findings show how intelligent tutoring systems, adaptive voice-based interfaces, and gamified speech interventions can empower children to engage in self-directed speech learning, reducing dependence on therapists and caregivers. The diversity of interaction modalities, including speech recognition, phoneme-based exercises, and multimodal feedback, demonstrates how AI and Assistive Technology (AT) can personalise learning experiences to accommodate diverse needs. Furthermore, the incorporation of gamification strategies, such as reward systems and adaptive difficulty levels, has been shown to enhance children’s motivation and long-term participation in speech rehabilitation. The gaps identified show that despite advancements, challenges remain in achieving universal accessibility, particularly regarding speech recognition accuracy, multilingual support, and accessibility for users with multiple disabilities. This review advocates for interdisciplinary collaboration across educational technology, special education, cognitive science, and human–computer interaction (HCI). Our work contributes to the ongoing discourse on lifelong inclusive education, reinforcing the potential of AI-driven serious games as transformative tools for bridging learning gaps and promoting speech rehabilitation beyond clinical environments. Full article

(This article belongs to the Special Issue ICT, AI, and Assistive Technology for Accessible and Inclusive Education)

► Show Figures

Figure 1

29 pages, 5277 KiB

Open AccessArticle

DualHet-YOLO: A Dual-Backbone Heterogeneous YOLO Network for Inspection Robots to Recognize Yellow-Feathered Chicken Behavior in Floor-Raised House

by Yaobo Zhang, Linwei Chen, Hongfei Chen, Tao Liu, Jinlin Liu, Qiuhong Zhang, Mingduo Yan, Kaiyue Zhao, Shixiu Zhang and Xiuguo Zou

Agriculture 2025, 15(14), 1504; https://doi.org/10.3390/agriculture15141504 (registering DOI) - 12 Jul 2025

Abstract

The behavior of floor-raised chickens is closely linked to their health status and environmental comfort. As a type of broiler chicken with special behaviors, understanding the daily actions of yellow-feathered chickens is crucial for accurately checking their health and improving breeding practices. Addressing [...] Read more.

The behavior of floor-raised chickens is closely linked to their health status and environmental comfort. As a type of broiler chicken with special behaviors, understanding the daily actions of yellow-feathered chickens is crucial for accurately checking their health and improving breeding practices. Addressing the challenges of high computational complexity and insufficient detection accuracy in existing floor-raised chicken behavior recognition models, a lightweight behavior recognition model was proposed for floor-raised yellow-feathered chickens, based on a Dual-Backbone Heterogeneous YOLO Network. Firstly, DualHet-YOLO enhances the feature extraction capability of floor-raised chicken images through a dual-path feature map extraction architecture and optimizes the localization and classification of multi-scale targets using a TriAxis Unified Detection Head. Secondly, a Proportional Scale IoU loss function is introduced that improves regression accuracy. Finally, a lightweight structure Eff-HetKConv was designed, significantly reducing model parameters and computational complexity. Experiments on a private floor-raised chicken behavior dataset show that, compared with the baseline YOLOv11 model, the DualHet-YOLO model increases the mAP for recognizing five behaviors—pecking, resting, walking, dead, and inactive—from 77.5% to 84.1%. Meanwhile, it reduces model parameters by 14.6% and computational complexity by 29.2%, achieving a synergistic optimization of accuracy and efficiency. This approach provides an effective solution for lightweight object detection in poultry behavior recognition. Full article

(This article belongs to the Special Issue Key Technology Research and Applications of Agricultural Inspection Robots Based on Machine Vision and Artificial Intelligence)

► Show Figures

Figure 1

17 pages, 12090 KiB

Open AccessArticle

Multiomics Integration of Parkinson’s Disease Datasets Reveals Unexpected Roles of IRE1 in Its Pathology

by Bianka Alexandra Pasat, Matthieu Moncan, Eleftherios Pilalis, Afshin Samali, Aristotelis Chatziioannou and Adrienne M. Gorman

Int. J. Mol. Sci. 2025, 26(14), 6711; https://doi.org/10.3390/ijms26146711 (registering DOI) - 12 Jul 2025

Abstract

Parkinson’s disease (PD) is the second most common neurodegenerative disease. It primarily affects the motor system but is also associated with a range of cognitive impairments that can manifest early in disease progression, indicating its multifaceted nature. In this paper, we performed a [...] Read more.

Parkinson’s disease (PD) is the second most common neurodegenerative disease. It primarily affects the motor system but is also associated with a range of cognitive impairments that can manifest early in disease progression, indicating its multifaceted nature. In this paper, we performed a meta-analysis of transcriptomics and proteomics data using MultiOmicsIntegrator to gain insights into the post-transcriptional modifications and deregulated pathways associated with this disease. Our results reveal differential isoform usage between control and PD patient brain samples that result in enriched alternative splicing events, including an extended UTR length, domain loss, and the upregulation of non-coding isoforms. We found that Inositol-Requiring Enzyme 1 (IRE1) is active in PD samples and examined the role of its downstream signaling through X-box binding mRNA 1 (XBP1) and regulated IRE1-dependent decay (RIDD). We identified several RIDD candidates and showed that the enriched alternative splicing events observed are associated with RIDD. Moreover, in vitro mRNA cleavage assays demonstrated that OSBPL3, C16orf74, and SLC6A1 mRNAs are targets of IRE1 RNAse activity. Finally, a pathway enrichment analysis of both XBP1s and RIDD targets in the PD samples uncovered associations with processes such as immune response, oxidative stress, signal transduction, and cell–cell communication that have previously been linked to PD. These findings highlight a potential regulatory role of IRE in PD. Full article

(This article belongs to the Special Issue Multi-Omics Approaches to Disentangle Pathomechanisms in Neurological Disease)

25 pages, 1491 KiB

Open AccessReview

Toxicological Risk Assessment of Coffee Oil (Coffee Seed Oil and Spent Coffee Grounds Oil) as a Novel Food with Focus on Cafestol

by Bernadette Maier, Heike Franke, Steffen Schwarz and Dirk W. Lachenmeier

Molecules 2025, 30(14), 2951; https://doi.org/10.3390/molecules30142951 (registering DOI) - 12 Jul 2025

Abstract

Coffee oil derived from spent coffee grounds of Coffea arabica is considered a novel food in the European Union (EU), requiring pre-market approval supported by comprehensive toxicological data. The effects of coffee oil on human health, particularly on blood parameters and liver enzymes, [...] Read more.

Coffee oil derived from spent coffee grounds of Coffea arabica is considered a novel food in the European Union (EU), requiring pre-market approval supported by comprehensive toxicological data. The effects of coffee oil on human health, particularly on blood parameters and liver enzymes, have been investigated in several studies. This review article summarizes the available toxicological literature on coffee oil, including its bioactive diterpenes cafestol and kahweol, which are known for their potential health effects. Considering the different modes of action of these two diterpenes, moderate consumption of coffee oil may be considered safe for healthy adults. Based on the changes in serum values in humans, this review provides initial estimations of LOAEL, NOAEL, and ADI for these diterpenes. The findings suggest that an intake of 225 mg of coffee oil per day might be considered safe assuming that coffee oil contains about 0.4% diterpenes. In summary, the assessment based on the published data indicates that (i) the consumption of coffee oil contained in any type of prepared coffee appears to be safe because the homeostasis of lipid levels in the blood is not significantly affected, and (ii) a low consumption of coffee oil as such might be acceptable but would require a refined risk assessment considering the exposure levels of the intended food product, which must be provided for novel food approval procedures. Full article

(This article belongs to the Special Issue Food Sustainability: Promising By-Products for Valorization—2nd Edition)

► Show Figures

Figure 1

24 pages, 5551 KiB

Open AccessArticle

Global Validation of the Version F Geophysical Data Records from the TOPEX/POSEIDON Altimetry Satellite Mission

by Linda Forster, Jean-Damien Desjonquères, Matthieu Talpe, Shailen D. Desai, Hélène Roinard, François Bignalet-Cazalet, Philip S. Callahan, Josh K. Willis, Nicolas Picot, Glenn M. Shirtliffe and Thierry Guinle

Remote Sens. 2025, 17(14), 2418; https://doi.org/10.3390/rs17142418 (registering DOI) - 12 Jul 2025

Abstract

We present the validation of the latest version F Geophysical Data Records (GDR-F) for the TOPEX/POSEIDON (T/P) altimetry satellite mission. The GDR-F products represent a major evolution with respect to the preceding version B Merged Geophysical Data Records (MGDR-B) that were released more [...] Read more.

We present the validation of the latest version F Geophysical Data Records (GDR-F) for the TOPEX/POSEIDON (T/P) altimetry satellite mission. The GDR-F products represent a major evolution with respect to the preceding version B Merged Geophysical Data Records (MGDR-B) that were released more than two decades ago. Specifically, the numerical retracking of the altimeter waveforms significantly mitigates long-standing issues in the TOPEX altimeter measurements, such as drifts and hemispherical biases in the altimeter range and significant wave height. Additionally, GDR-F incorporates updated geophysical model standards consistent with current altimeter missions, improved sea state bias corrections, end-of-mission calibration for the microwave radiometer, and refined orbit ephemeris solutions. These enhancements notably decrease the variance of the Sea Surface Height Anomaly (SSHA) measurements, with along-track SSHA variance reduced by 26 cm² compared to MGDR-B and crossover SSHA variance lowered by 1 cm². GDR-F products also demonstrate improved consistency with Jason-1 measurements during their tandem mission phase, reducing the standard deviation of differences from 6 cm to 4 cm when compared to Jason-1 GDR-E data. These results confirm that GDR-F products offer a more accurate and consistent T/P data record, enhancing the quality of long-term sea level studies and supporting inter-mission altimetry continuity. Full article

► Show Figures

Figure 1

16 pages, 269 KiB

Open AccessArticle

Genetic Susceptibility in Sinusoidal Obstruction Syndrome/Veno-Occlusive Disease: A Case–Control Study

by Ioulia Mavrikou, Marta Castelli, Tasoula Touloumenidou, Zoi Bousiou, Evangelia-Evdoxia Koravou, Anna Vardi, Apostolia Papalexandri, Christos Demosthenous, Maria Koutra, Paschalis Evangelidis, Alkistis-Kyra Panteliadou, Ioannis Batsis, Dimitrios Chatzidimitriou, Emmanouil Nikolousis, Alessandro Rambaldi, Ioanna Sakellari and Eleni Gavriilaki

Int. J. Mol. Sci. 2025, 26(14), 6712; https://doi.org/10.3390/ijms26146712 (registering DOI) - 12 Jul 2025

Abstract

Sinusoidal Obstruction Syndrome/Veno-Occlusive Disease (SOS/VOD) is a severe complication of hematopoietic cell transplantation (HCT). Furthermore, emerging evidence suggests the potential role of complement activation and endothelial injury in SOS/VOD pathogenesis. In this study, we aimed to identify potential distinct pathogenic genetic variants between [...] Read more.

Sinusoidal Obstruction Syndrome/Veno-Occlusive Disease (SOS/VOD) is a severe complication of hematopoietic cell transplantation (HCT). Furthermore, emerging evidence suggests the potential role of complement activation and endothelial injury in SOS/VOD pathogenesis. In this study, we aimed to identify potential distinct pathogenic genetic variants between SOS/VOD and other endothelial injury syndromes following HCT, such as transplant-associated thrombotic microangiopathy (TA-TMA). For this aim, genomic DNA from 30 SOS/VOD patients and 30 controls with TA-TMA was analyzed. Using Next-Generation Sequencing (NGS), variants in complement-related genes (CFH, CFI, CFB, CFD, C3, CD55, C5, CD46, and thrombomodulin/THBD) and ADAMTS13 were examined. Out of 426 detected variants, 20 were classified as pathogenic. In SOS/VOD patients, variants were identified in ADAMTS13 (4), CFH (3), C3 (2), and CFB (1) genes. One of the variants has been recognized as the strongest genetic predictor of ADAMTS13 activity. Controls exhibited more variants in complement-related genes, particularly CFH, CFI, and C3. The genetic differences between SOS/VOD and TA-TMA highlight different pathogenic mechanisms, offering the potential for targeted risk assessment and therapy in HCT recipients. Full article

(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)

17 pages, 1016 KiB

Open AccessArticle

Design of Wideband Power Amplifier Using Improved Particle Swarm Optimization with Output Power and Efficiency Constraints

by Hanyue Wang, Yunqin Chen, Wa Kong, Jianwei Qi, Zhaowen Zheng and Jing Xia

Electronics 2025, 14(14), 2813; https://doi.org/10.3390/electronics14142813 (registering DOI) - 12 Jul 2025

Abstract

In order to expand the bandwidth of the power amplifier (PA), this paper proposes a PA optimization design method based on improved particle swarm optimization (PSO) with output power and efficiency as optimization objectives. Simulated annealing strategy and adaptive inertia weight are introduced [...] Read more.

In order to expand the bandwidth of the power amplifier (PA), this paper proposes a PA optimization design method based on improved particle swarm optimization (PSO) with output power and efficiency as optimization objectives. Simulated annealing strategy and adaptive inertia weight are introduced to PSO to achieve the global optimum and accelerate the convergence speed. Considering performance metrics of PA, such as the efficiency and output power, a piecewise objective function is formulated for wideband PA optimization design. For validation, a wideband PA operating at 0.5–4.3 GHz (fractional bandwidth of 158.3%) was designed and fabricated. Measured results show a saturated output power ranging from 39.7 to 42.4 dBm and an efficiency between 60.5 and 68.8% within the operating bandwidth. Full article

(This article belongs to the Section Microwave and Wireless Communications)

► Show Figures

Figure 1

15 pages, 285 KiB

Open AccessReview

Human (Face-to-Face) and Digital Innovation Platforms and Their Role in Innovation and Sustainability

by Amalya L. Oliver and Rotem Rittblat

Platforms 2025, 3(3), 12; https://doi.org/10.3390/platforms3030012 (registering DOI) - 12 Jul 2025

Abstract

This paper provides a comparative review of digital and human (face-to-face) innovation platforms and their roles in promoting innovation and sustainability. These platforms are particularly significant in advancing sustainability objectives as outlined in Sustainable Development Goal 17, (SDG17) which emphasizes the importance of [...] Read more.

This paper provides a comparative review of digital and human (face-to-face) innovation platforms and their roles in promoting innovation and sustainability. These platforms are particularly significant in advancing sustainability objectives as outlined in Sustainable Development Goal 17, (SDG17) which emphasizes the importance of knowledge and technology partnerships to address sustainability challenges, foster innovation, and enhance scientific collaboration. Through a systematic literature review of organizational and management research over the past decade, the study identifies key features, benefits, and limitations of each platform type. Digital platforms offer scalability, asynchronous collaboration, and data-driven innovation, yet face challenges such as trust deficits, cybersecurity risks, and digital inequality. In contrast, human (face-to-face) platforms facilitate trust, emotional communication, and spontaneous idea generation, but are limited in scalability and resource efficiency. By categorizing insights into thematic tables and evaluating implications for organizations, the paper highlights how the integration of both platform types can optimize innovation outcomes. The authors argue that hybrid models—combining the scalability and efficiency of digital platforms with the relational depth of human (face-to-face) platforms—offer a promising path toward sustainable innovation ecosystems. The paper concludes with a call for future empirical research on platform integration strategies and sector-specific applications. Full article

17 pages, 749 KiB

Open AccessArticle

Prognostic Role of TSH Within Euthyroid T2DM Patients with Retinopathy: A 3-Year Cohort Study

by Nilgun Tan Tabakoglu and Mehmet Celik

Diseases 2025, 13(7), 217; https://doi.org/10.3390/diseases13070217 (registering DOI) - 12 Jul 2025

Abstract

Background/Objectives: We aimed to determine how baseline TSH levels relate to clinical outcomes over a three-year follow-up in euthyroid patients with T2DR. Methods: This single-center retrospective cohort study included 363 euthyroid T2DR patients who were followed for three years after baseline TSH measurement. [...] Read more.

Background/Objectives: We aimed to determine how baseline TSH levels relate to clinical outcomes over a three-year follow-up in euthyroid patients with T2DR. Methods: This single-center retrospective cohort study included 363 euthyroid T2DR patients who were followed for three years after baseline TSH measurement. Patients were stratified into tertiles based on TSH values belonging to the standard clinical limits (0.35–4.50 mIU/L). Binary and multivariate logistic regression analyses, along with non-linear modeling, were used to evaluate the prognostic impact of TSH and its interaction with age on mortality. The study adhered to the STROBE guidelines. Results: In the first year of follow-up, Group 1 (TSH 0.35–1.24 mIU/L) had significantly higher rates of mortality and combined outcomes compared to Group 2 (TSH 1.24–1.94 mIU/L; p = 0.025 and p = 0.041, respectively). Group 2 had a lower risk (OR for mortality = 0.349, p = 0.004; OR for combined outcome = 0.358, p = 0.007). Between TSH and TSH tertiles, a non-linear, inverted U-shaped relationship was observed, with the lowest mortality risk near 2.0 mIU/L. A significant interaction between TSH and age was found for third-year mortality (p = 0.016). Conclusions: TSH values showed a non-linear association with outcomes in euthyroid T2DR patients. Group 2 was linked to the lowest risk. Given the significantly higher mortality and combined complications identified within Group 1, closer monitoring and individualized follow-up strategies may be warranted for these patients. Additionally, TSH’s impact on long-term mortality increased with age, supporting its use alongside age for risk stratification in T2DR. Full article

27 pages, 3121 KiB

Open AccessReview

A Critical Review of Membrane Distillation Using Ceramic Membranes: Advances, Opportunities and Challenges

by Francesca Alessandro and Francesca Macedonio

Materials 2025, 18(14), 3296; https://doi.org/10.3390/ma18143296 (registering DOI) - 12 Jul 2025

Abstract

Membrane distillation (MD) has attracted increasing attention as a thermally driven separation process for water purification, desalination, and wastewater treatment. Its primary advantages include high rejection of non-volatile solutes, compatibility with low-grade or waste heat sources, and operation at ambient pressure. Despite these [...] Read more.

Membrane distillation (MD) has attracted increasing attention as a thermally driven separation process for water purification, desalination, and wastewater treatment. Its primary advantages include high rejection of non-volatile solutes, compatibility with low-grade or waste heat sources, and operation at ambient pressure. Despite these benefits, large-scale implementation remains limited due to the lack of membrane materials capable of withstanding harsh operating conditions and maintaining their hydrophobic character. Polymeric membranes have traditionally been used in MD applications; however, their limited thermal and chemical stability compromises long-term performance and reliability. In contrast, ceramic membranes are emerging as a promising alternative, offering superior mechanical strength, chemical resistance, and thermal stability. Nevertheless, their broader adoption in MD is hindered by several challenges, including high thermal conductivity, surface wettability, high fabrication costs, and limited scalability. This review provides a critical assessment of current developments, key opportunities, and ongoing challenges associated with the use of ceramic membranes in MD. Particular emphasis is placed on advances in surface modification techniques and the emerging applications in advanced MD configurations. Full article

(This article belongs to the Special Issue Next-Generation Membranes for Enhanced Membrane Distillation Performance)

► Show Figures

Figure 1

25 pages, 85368 KiB

Open AccessArticle

SMA-YOLO: An Improved YOLOv8 Algorithm Based on Parameter-Free Attention Mechanism and Multi-Scale Feature Fusion for Small Object Detection in UAV Images

by Shenming Qu, Chaoxu Dang, Wangyou Chen and Yanhong Liu

Remote Sens. 2025, 17(14), 2421; https://doi.org/10.3390/rs17142421 (registering DOI) - 12 Jul 2025

Abstract

With special consideration for complex scenes and densely distributed small objects, this frequently leads to serious false and missed detections for unmanned aerial vehicle (UAV) images in small object detection scenarios. Consequently, we propose a UAV image small object detection algorithm, termed SMA-YOLO. [...] Read more.

With special consideration for complex scenes and densely distributed small objects, this frequently leads to serious false and missed detections for unmanned aerial vehicle (UAV) images in small object detection scenarios. Consequently, we propose a UAV image small object detection algorithm, termed SMA-YOLO. Firstly, a parameter-free simple slicing convolution (SSC) module is integrated in the backbone network to slice the feature maps and enhance the features so as to effectively retain the features of small objects. Subsequently, to enhance the information exchange between upper and lower layers, we design a special multi-cross-scale feature pyramid network (M-FPN). The C2f-Hierarchical-Phantom Convolution (C2f-HPC) module in the network effectively reduces information loss by fine-grained multi-scale feature fusion. Ultimately, adaptive spatial feature fusion detection Head (ASFFDHead) introduces an additional P2 detection head to enhance the resolution of feature maps to better locate small objects. Moreover, the ASFF mechanism is employed to optimize the detection process by filtering out information conflicts during multi-scale feature fusion, thereby significantly optimizing small object detection capability. Using YOLOv8n as the baseline, SMA-YOLO is evaluated on the VisDrone2019 dataset, achieving a 7.4% improvement in mAP@0.5 and a 13.3% reduction in model parameters, and we also verified its generalization ability on VAUDT and RSOD datasets, which demonstrates the effectiveness of our approach. Full article

(This article belongs to the Special Issue Advances in Computer Vision and Machine Learning Applications on Remote Sensing Images)

► Show Figures

Figure 1

29 pages, 4862 KiB

Open AccessArticle

Repurposed Antipsychotics as Potential Anticancer Agents: Clozapine Efficacy and Dopaminergic Pathways in Neuroblastoma and Glioblastoma

by Catarina Moura, Maria João Gouveia and Nuno Vale

Life 2025, 15(7), 1097; https://doi.org/10.3390/life15071097 (registering DOI) - 12 Jul 2025

Abstract

Neuro-oncology focuses on the diagnosis and treatment of brain tumors, which, despite their rarity, are associated with high mortality due to their invasiveness and limited treatment options. Emerging evidence suggests that dopamine (DA), a neurotransmitter crucial for cognitive and emotional processes, and its [...] Read more.

Neuro-oncology focuses on the diagnosis and treatment of brain tumors, which, despite their rarity, are associated with high mortality due to their invasiveness and limited treatment options. Emerging evidence suggests that dopamine (DA), a neurotransmitter crucial for cognitive and emotional processes, and its receptors may influence tumor growth and the tumor microenvironment. This study aimed to evaluate the potential anticancer effects of repurposed antipsychotic dopamine-targeting drugs (Clozapine, CLZ; Pimozide, PIM; Olanzapine, OLZ; and Risperidone, RIS) and antiemetic drugs (Domperidone, DOM; Droperidol, DRO) on neuroblastoma (SH-SY5Y) and glioblastoma (A172) cell lines, and to assess whether their efficacy is modulated by oxidative stress and DA synthesis. The drugs were first tested individually, followed by co-treatment with tyrosine (Tyr), a dopamine precursor, and hydrogen peroxide (H₂O₂), an inducer of oxidative stress. Additionally, drug activity was evaluated in the simultaneous presence of H₂O₂ and Tyr. CLZ exhibited the highest cytotoxicity in both cell lines, suggesting strong anticancer potential and also synergism among the different combinations, particularly in SH-SY5Y. Liquid chromatography of the extracellular medium showed greater Tyr consumption in SH-SY5Y compared to A172 cells, indicating a higher dependence on extracellular Tyr to mitigate drug- and/or stress-induced cytotoxicity. In summary, several of the repurposed antipsychotics demonstrated cytotoxic effects on central nervous system tumor cells, with CLZ showing the most promising activity, even under oxidative stress conditions. These findings support further investigation into dopamine-targeting drugs as potential therapeutic agents in neuro-oncology. Full article

(This article belongs to the Section Pharmaceutical Science)

► Show Figures

Figure 1

30 pages, 5062 KiB

Open AccessReview

State-of-the-Art Review of Studies on the Flexural Behavior and Design of FRP-Reinforced Concrete Beams

by Hau Tran, Trung Nguyen-Thoi and Huu-Ba Dinh

Materials 2025, 18(14), 3295; https://doi.org/10.3390/ma18143295 (registering DOI) - 12 Jul 2025

Abstract

Fiber-reinforced polymer (FRP) bars have great potential to replace steel bars in the design of reinforced concrete (RC) beams since they have numerous advantages such as high tensile strength and good corrosion resistance. Therefore, many studies including experiments and numerical simulations have focused [...] Read more.

Fiber-reinforced polymer (FRP) bars have great potential to replace steel bars in the design of reinforced concrete (RC) beams since they have numerous advantages such as high tensile strength and good corrosion resistance. Therefore, many studies including experiments and numerical simulations have focused on the behavior of FRP RC beams. In this paper, a comprehensive overview of previous studies is conducted to provide a thorough understanding about the behavior, the design, and the limitations of FRP RC beams. Particularly, experimental studies on FRP RC beams are collected and reviewed. In addition, the numerical analysis of FRP beams including the finite element (FE) analysis, the discrete element (DE) analysis, and artificial intelligence/machine learning (AI/ML) is summarized. Moreover, the international standards for the design of FRP RC beams are presented and evaluated. Through the review of previous studies, 93 tested specimens are collected. They can be a great source of reference for other studies. In addition, it has been found that the studies on the continuous beams and deep beams reinforced with FRP bars are still limited. In addition, more studies using DE analysis and AI/ML to analyze the response of FRP RC beams under loading conditions should be conducted. Full article

(This article belongs to the Section Construction and Building Materials)

► Show Figures

Figure 1

36 pages, 2939 KiB

Open AccessSystematic Review

A Systematic Review and Bibliometric Analysis for the Design of a Traceable and Sustainable Model for WEEE Information Management in Ecuador Based on the Circular Economy

by Marlon Copara, Angel Pilamunga, Fernando Ibarra, Silvia-Melinda Oyaque-Mora, Diana Morales-Urrutia and Patricio Córdova

Sustainability 2025, 17(14), 6402; https://doi.org/10.3390/su17146402 (registering DOI) - 12 Jul 2025

Abstract

The rapid increase in waste electrical and electronic equipment (WEEE) creates major environmental and governance issues in developing countries like Ecuador struggle because they with minimal formal collection and recycling rates. This research presents a potential sustainable management approach that tracks products through [...] Read more.

The rapid increase in waste electrical and electronic equipment (WEEE) creates major environmental and governance issues in developing countries like Ecuador struggle because they with minimal formal collection and recycling rates. This research presents a potential sustainable management approach that tracks products through their life cycles while following circular economy principles that include product extension and material extraction and waste minimization. A systematic literature review (SLR) using the PRISMA methodology combined with a bibliometric analysis found essential global strategies and technological frameworks and regulatory frameworks. The analysis of articles demonstrates that information management systems (IMSs) together with digital technologies and consistent regulations serve as essential elements for enhancing traceability and material recovery and formal recycling processes. A WEEE management IMS model was developed for the Ecuadorian market through an analysis of the findings; it follows a five-stage development process, starting from the technological infrastructure setup to complete data visualization integration. The proposed model is designed to enable public–private–community partnerships using digital tools that promote sustainable practices. The combination of circular strategies with traceability technologies and strong regulatory frameworks leads to improved WEEE governance, which supports sustainable system transitions in emerging economies. Full article

(This article belongs to the Special Issue Extrusion Technology and Engineering for Sustainability and Circular Economy)

► Show Figures

Figure 1

16 pages, 3260 KiB

Open AccessArticle

Rifaximin Attenuates Liver Fibrosis and Hepatocarcinogenesis in a Rat MASH Model by Suppressing the Gut–Liver Axis and Epiregulin–IL-8-Associated Angiogenesis

by Naoki Nishimura, Kosuke Kaji, Norihisa Nishimura, Junichi Hanatani, Tatsuya Nakatani, Masafumi Oyama, Akihiko Shibamoto, Yuki Tsuji, Koh Kitagawa, Shinya Sato, Tadashi Namisaki, Satoru Tamaoki and Hitoshi Yoshiji

Int. J. Mol. Sci. 2025, 26(14), 6710; https://doi.org/10.3390/ijms26146710 (registering DOI) - 12 Jul 2025

Abstract

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive liver disease linked to fibrosis and hepatocellular carcinoma (HCC). Gut-derived lipopolysaccharide (LPS) promotes hepatic inflammation, fibrosis, and angiogenesis through toll-like receptor 4 (TLR4) signaling. This study examined the effects of rifaximin, a non-absorbable, gut-targeted antibiotic, on [...] Read more.

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive liver disease linked to fibrosis and hepatocellular carcinoma (HCC). Gut-derived lipopolysaccharide (LPS) promotes hepatic inflammation, fibrosis, and angiogenesis through toll-like receptor 4 (TLR4) signaling. This study examined the effects of rifaximin, a non-absorbable, gut-targeted antibiotic, on MASH-related liver fibrosis and early hepatocarcinogenesis, with a focus on the LPS–epiregulin–IL-8–angiogenesis axis.MASH was induced in Fischer 344 rats using a choline-deficient, L-amino acid-defined high-fat diet (CDAHFD). Rifaximin (30 mg/kg/day) was orally administered for 12 weeks. Liver histology, gene expression, intestinal permeability, LPS levels, and angiogenic markers were evaluated. Rifaximin reduced hepatic inflammation, fibrosis, hydroxyproline content, and fibrogenic gene expression. The number and size of GST-P-positive preneoplastic lesions and proliferation-related genes were decreased. Portal LPS levels and Kupffer cell activation declined, with downregulation of Lbp, Cd14, Tlr4, and inflammatory cytokines. Rifaximin decreased hepatic epiregulin and IL-8 expression, attenuated CD34-positive neovascularization, and suppressed proangiogenic gene expression, accompanied by improved intestinal barrier function and reduced gut permeability. Rifaximin mitigates MASH progression by restoring gut barrier integrity, limiting LPS translocation, and inhibiting fibrogenic and angiogenic pathways. These results suggest its potential as a chemopreventive agent in MASH-related hepatocarcinogenesis. Full article

(This article belongs to the Special Issue Liver Diseases: From Molecular Basis to Potential Therapy)

► Show Figures

Figure 1

26 pages, 3702 KiB

Open AccessArticle

Research on Path Tracking Technology for Tracked Unmanned Vehicles Based on DDPG-PP

by Yongjuan Zhao, Chaozhe Guo, Jiangyong Mi, Lijin Wang, Haidi Wang and Hailong Zhang

Machines 2025, 13(7), 603; https://doi.org/10.3390/machines13070603 (registering DOI) - 12 Jul 2025

Abstract

Realizing path tracking is crucial for improving the accuracy and efficiency of unmanned vehicle operations. In this paper, a path tracking hierarchical control method based on DDPG-PP is proposed to improve the path tracking accuracy of tracked unmanned vehicles. Constrained by the objective [...] Read more.

Realizing path tracking is crucial for improving the accuracy and efficiency of unmanned vehicle operations. In this paper, a path tracking hierarchical control method based on DDPG-PP is proposed to improve the path tracking accuracy of tracked unmanned vehicles. Constrained by the objective of minimizing path tracking error, with the upper controller, we adopted the DDPG method to construct an adaptive look-ahead distance optimizer in which the look-ahead distance was dynamically adjusted in real-time using a reinforcement learning strategy. Meanwhile, reinforcement learning training was carried out with randomly generated paths to improve the model’s generalization ability. Based on the optimal look-ahead distance output from the upper layer, the lower layer realizes precise closed-loop control of torque, required for steering, based on the PP method. Simulation results show that the path tracking accuracy of the proposed method is better than that of the LQR and PP methods. The proposed method reduces the average tracking error by 94.0% and 79.2% and the average heading error by 80.4% and 65.0% under complex paths compared to the LQR and PP methods, respectively. Full article

(This article belongs to the Section Vehicle Engineering)

► Show Figures

Figure 1

Recent Articles

Open Access Journals

Highly Accessed Articles

Latest Books

News

Blog Posts

Topics

Selected Special Issues

Selected Collections

Journals by Subject

Further Information

Guidelines

MDPI Initiatives

Follow MDPI