Advancing Open Science
Supporting academic communities
since 1996
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 

Recent Articles  

19 pages, 1587 KB  
Article
Transformer Attention-Guided Dual-Path Framework for Bearing Fault Diagnosis
by Saif Ullah, Wasim Zaman and Jong-Myon Kim
Appl. Sci. 2025, 15(23), 12431; https://doi.org/10.3390/app152312431 (registering DOI) - 23 Nov 2025
Abstract
Reliable bearing fault diagnosis plays an important role in maintaining the safety and performance of rotating machinery in industrial systems. Although deep learning models have achieved remarkable success in this field, their dependence on a single feature-extraction approach often restricts the diversity of [...] Read more.
Reliable bearing fault diagnosis plays an important role in maintaining the safety and performance of rotating machinery in industrial systems. Although deep learning models have achieved remarkable success in this field, their dependence on a single feature-extraction approach often restricts the diversity of learned representations and limits diagnostic accuracy. To overcome this limitation, this study proposes an attention-guided dual-path framework that integrates spatial and time–frequency feature learning with transformer-based classification for precise fault identification. In the proposed framework, vibration signals collected from an experimental bearing test rig are simultaneously processed through two complementary pipelines: one converts the signals into two-dimensional matrix images to extract spatial features, while the other transforms them into continuous wavelet transform (CWT) scalograms to capture fine-grained temporal and spectral information. The extracted features are fused through a lightweight transformer encoder with an attention mechanism that dynamically emphasizes the most informative representations. This fusion enables the model to effectively capture cross-domain dependencies and enhance discriminative capability. Experimental validation on an industrial vibration dataset demonstrates that the proposed model achieves 99.87% classification accuracy, outperforming conventional CNN and transformer-based approaches. The results confirm that integrating multi-domain features with attention-driven fusion significantly improves the robustness and generalization of deep learning models for intelligent bearing fault diagnosis. Full article
(This article belongs to the Special Issue Sustainable Reliability, Maintenance, and Fault Diagnosis Strategies for Mechanical and Manufacturing Systems)
38 pages, 25106 KB  
Article
A Two-Stage End-to-End Framework for Robust Scene Text Spotting with Self-Calibrated Detection and Contextual Recognition
by Yuning Cheng, Jinhong Huang, Io San Tai, Subrota Kumar Mondal, Tianqi Wang and Hussain Mohammed Dipu Kabir
Electronics 2025, 14(23), 4594; https://doi.org/10.3390/electronics14234594 (registering DOI) - 23 Nov 2025
Abstract
End-to-end scene text detection and recognition, which involves detecting and recognizing text in natural images, still faces significant challenges, particularly in handling text of arbitrary shapes, complex backgrounds, and computational efficiency requirements. This paper proposes a novel and viable end-to-end OCR framework that [...] Read more.
End-to-end scene text detection and recognition, which involves detecting and recognizing text in natural images, still faces significant challenges, particularly in handling text of arbitrary shapes, complex backgrounds, and computational efficiency requirements. This paper proposes a novel and viable end-to-end OCR framework that synergistically combines a powerful detection network with advanced recognition models. For text detection, we develop a method called Text Contrast Self-Calibrated Network (TextCSCN), which employs pixel-wise supervised contrastive learning to extract more discriminative features. TextCSCN addresses long-range dependency modeling and limited receptive field issues through self-calibrated convolutions and Global Convolutional Networks (GCNs). We further introduce an efficient Mamba-based bidirectional module for boundary refinement, enhancing both accuracy and speed. For text recognition, our framework employs a Swin Transformer backbone with Bidirectional Feature Pyramid Networks (BiFPNs) for optimized multi-scale feature extraction. We propose a Pre-Gated Contextual Attention Gate (PCAG) mechanism to effectively fuse visual and linguistic information while minimizing noise and uncertainty in multi-modal integration. Experiments on challenging benchmarks including TotalText and CTW1500 demonstrate the effectiveness of our approach. Our detection module achieves state-of-the-art performance with an F-score of 88.21% on TotalText, and the complete end-to-end system shows comparable improvements in recognition accuracy, establishing new benchmarks for scene text spotting. Full article
(This article belongs to the Special Issue Exploring Edge AI: Architectures, Algorithms, and the Role of Edge–Cloud Cooperation for Scalable AI Systems)
19 pages, 5316 KB  
Article
Disturbance Characteristics of Subsoiling in Paddy Soil Based on Smoothed Particle Hydrodynamics (SPH)
by Lei Liang, Qishuo Ding, Haiyan Zhang and Qi Liu
Agronomy 2025, 15(12), 2695; https://doi.org/10.3390/agronomy15122695 (registering DOI) - 23 Nov 2025
Abstract
Subsoiling is an important technology in conservation tillage. The disturbance characteristics of paddy soil were simulated by smoothed particle hydrodynamics (SPH) in this paper in order to explore the optimal tillage depth of paddy soil in a rice–wheat rotation area. Firstly, a subsoiling [...] Read more.
Subsoiling is an important technology in conservation tillage. The disturbance characteristics of paddy soil were simulated by smoothed particle hydrodynamics (SPH) in this paper in order to explore the optimal tillage depth of paddy soil in a rice–wheat rotation area. Firstly, a subsoiling experiment with five tillage depths was carried out by a self-made multi-functional in situ test-rig facility. Then, a three-layer-soil subsoiling model of a cultivated layer, plow pan, and subsoil layer was established based on the SPH method. Finally, the soil disturbance characteristics were analyzed from macroscopic and microscopic perspectives. The results showed that the average draft force in simulation was consistently lower than in the field, with a maximum error of 18.71%, and the field draft force fluctuated greatly. The soil block above the tine was not lifted up as a big block but broken into many small soil blocks and then lifted up, resulting in different displacements of the soil particles, but the relative position was unchanged from top to bottom. The particle displacements were concentrated above the tine, the stress was concentrated around the tine, while the velocity and acceleration were closely attached to the subsoiler. A “mole cavity” at 25 and 30 cm tillage depths existed at the bottom of the disturbance, which was consistent with the finding in the field. The disturbance area and specific draft were maximum and minimum at 20 cm tillage depth, respectively. These findings suggest that the optimal tillage depth was 20 cm for the rice–wheat rotation area. The results of the analysis provide a theoretical basis for the optimal design of subsequent subsoiling. Full article
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
►▼ Show Figures

Figure 1

15 pages, 1071 KB  
Article
Exploring the Role of CT-Based Delta-Radiomics in Unresectable Vulvar Cancer
by Abdulla Alzibdeh, Bara M. Hammadeh, Rahaf Alnajjar, Mohammad Abd Al-Raheem, Rima Mheidat, Alzahra’a Al Matairi, Mohamed Qamber, Hanan Almasri, Bayan Altalla’, Amal Al-Omari and Fawzi Abuhijla
Diagnostics 2025, 15(23), 2972; https://doi.org/10.3390/diagnostics15232972 (registering DOI) - 23 Nov 2025
Abstract
Background/Objectives: To explore the prognostic potential of gross tumor volume (GTV)-based delta-radiomic features from CT simulation scans in patients with locally advanced unresectable vulvar cancer. Methods: A total of 21 patients (between 2019 and 2024) undergoing definitive radiotherapy were included, with baseline and [...] Read more.
Background/Objectives: To explore the prognostic potential of gross tumor volume (GTV)-based delta-radiomic features from CT simulation scans in patients with locally advanced unresectable vulvar cancer. Methods: A total of 21 patients (between 2019 and 2024) undergoing definitive radiotherapy were included, with baseline and post-phase I (after 25 fractions) CT simulation scans analyzed. Radiomic features (n = 107) were extracted from GTVs using PyRadiomics, and delta features were calculated as the relative change between scans. A multi-step selection pipeline (univariable Cox screening (p < 0.10), correlation filtering, and Lasso–Cox) was applied for each endpoint: local control (LC), regional control, distant metastasis-free survival, progression-free survival, and overall survival (OS). Model discrimination was assessed via 500-iteration bootstrapped concordance index (C-index), and calibration was plotted at 24 months. Results: Median follow-up was 50.0 months. The 2-year LC and OS rates were 56.2% and 55.9%, respectively. Final multivariable models retained a sole texture Δ feature for LC (HR = 2.62, 95% CI = 1.05–6.52, p = 0.039; C-index = 0.748) and six Δ features for OS (C-index = 0.864). No features were retained for other endpoints. For LC, increased run-length non-uniformity after phase I predicted poorer control. For OS, increased texture/shape complexity predicted worse survival, whereas increased uniformity predicted better survival. Conclusions: CT-based delta-radiomic features, particularly shape and texture metrics, may predict LC and OS in unresectable vulvar cancer. Despite the small sample size, these findings highlight the potential for delta-radiomics as a noninvasive biomarker for risk stratification. Validation in larger cohorts and exploring potential in adaptive radiotherapy are warranted. Full article
(This article belongs to the Special Issue Medical Image Analysis and Machine Learning)
►▼ Show Figures

Figure 1

18 pages, 1342 KB  
Article
Kinematic Upper-Bound Analysis of Safety Performance for Precast 3D Composite Concrete Structure with Extended Mohr–Coulomb Criterion
by Taoxiang Feng, De Zhou and Qiang Chen
Appl. Sci. 2025, 15(23), 12429; https://doi.org/10.3390/app152312429 (registering DOI) - 23 Nov 2025
Abstract
This study develops a systematic kinematic upper-bound framework to evaluate the ultimate bearing capacity and failure mechanisms of prefabricated cast-in-place slab–wall joints in overlapped metro stations. Recognizing the complex shear–compression interaction in these critical structural nodes, a novel three-dimensional short-block shear failure model [...] Read more.
This study develops a systematic kinematic upper-bound framework to evaluate the ultimate bearing capacity and failure mechanisms of prefabricated cast-in-place slab–wall joints in overlapped metro stations. Recognizing the complex shear–compression interaction in these critical structural nodes, a novel three-dimensional short-block shear failure model is established based on the principle of energy balance. The analysis employs a modified Mohr–Coulomb strength criterion incorporating a finite tensile strength cut-off, enabling more accurate representation of cracking and tensile resistance effects. Analytical solutions are derived to predict the ultimate capacity and critical failure angle, followed by a comprehensive parametric analysis. The results reveal that cross-sectional dimensions dominate the bearing capacity, while the internal friction angle and tensile-to-compressive strength ratio significantly influence both the magnitude and mode of failure. A narrower load distribution width enhances capacity and reduces the optimal failure angle. Overall, the proposed 3D model provides a rigorous and efficient theoretical tool for the design optimization and safety assessment of prefabricated underground structures. Full article
(This article belongs to the Special Issue Slope Stability and Earth Retaining Structures—2nd Edition)
25 pages, 43287 KB  
Article
Document Image Verification Based on Paragraph Alignment and Subtle Change Detection
by Daoquan Li, Weifei Jia, Quanlin Yu and Zhaoxu Hu
Appl. Sci. 2025, 15(23), 12430; https://doi.org/10.3390/app152312430 (registering DOI) - 23 Nov 2025
Abstract
The digitization of paper documents enables rapid sharing and long-term preservation of information, making it a widely adopted approach for efficient document storage and management across various domains. However, the recent advances in image editing software pose an increasing threat to the integrity [...] Read more.
The digitization of paper documents enables rapid sharing and long-term preservation of information, making it a widely adopted approach for efficient document storage and management across various domains. However, the recent advances in image editing software pose an increasing threat to the integrity of document images. Comparing the input with the corresponding reference document image is a direct and effective approach to verification. Nevertheless, this task is challenging due to two key factors, namely, the need for efficient retrieval of the reference document images and the difficulty of detecting subtle content changes under the print–scan (PS) distortions. To address these challenges, this work proposes a document image verification scheme based on paragraph alignment and subtle change detection. It first extracts paragraph structural features from both input and reference document images to achieve efficient image retrieval and accurate paragraph alignment. Based on the alignment results, the proposed scheme employs contrastive learning to reduce the effect of PS distortions in extracting features from the input and reference document images. Finally, an additional verification step is introduced that significantly reduces the false positive detection by addressing the feature misalignment within the extracted paragraphs. To evaluate the proposed scheme, extensive experiments were conducted on databases constructed from public datasets, and various benchmark methods were compared. Experimental results show that the proposed scheme outperforms benchmark methods, achieving an accuracy score of 0.963. Full article
(This article belongs to the Topic Image Processing, Signal Processing and Their Applications)
15 pages, 7465 KB  
Article
Sensorless Payload Estimation of Serial Robots Using an Improved Disturbance Kalman Filter with a Variable-Parameter Noise Model
by Ruiqing Luo, Jianjun Yuan, Yimin He, Sheng Bao, Liang Du and Zhengtao Hu
Actuators 2025, 14(12), 568; https://doi.org/10.3390/act14120568 (registering DOI) - 23 Nov 2025
Abstract
The accurate estimation of the end-effector load force is essential in dynamic robotic scenarios, especially when the end-effector payload varies, to ensure safe and stable physical interaction among humans, robots, and environments. Currently, most applications still rely on payload calibration schemes, but existing [...] Read more.
The accurate estimation of the end-effector load force is essential in dynamic robotic scenarios, especially when the end-effector payload varies, to ensure safe and stable physical interaction among humans, robots, and environments. Currently, most applications still rely on payload calibration schemes, but existing calibration techniques often struggle to balance efficiency and accuracy. Moreover, current-based payload estimation methods, which are a commonly used and low-cost technique, face practical challenges such as non-negligible noise. To handle these issues, we propose a sensorless scheme based on a modified disturbance Kalman filter for accurately estimating the load force exerted on robots. Specifically, we introduce the dynamic model of robots that incorporates the nonlinear friction related to velocity and load. Subsequently, a generalized disturbance observer for the robot dynamics is adopted to avoid the measurement noise of joint acceleration. Considering the influence of friction and velocity on the noise parameters in the Kalman filter, a variable-parameter noise model is established. Finally, experimental results demonstrate that the proposed method achieves better performance in terms of accuracy, response, and overshoot suppression compared to the existing methods. Full article
(This article belongs to the Section Actuators for Robotics)
►▼ Show Figures

Figure 1

14 pages, 2958 KB  
Article
Dynamic Imprint and Recovery Mechanisms in Hf0.2Zr0.8O2 Anti-Ferroelectric Capacitors with FORC Characterization
by Yuetong Huo, Jianguo Li, Zeping Weng, Yaru Ding, Lijian Chen, Jiabin Qi, Yiming Qu and Yi Zhao
Electronics 2025, 14(23), 4593; https://doi.org/10.3390/electronics14234593 (registering DOI) - 23 Nov 2025
Abstract
The conventional static imprint effect in HfxZr1−xO2 (HZO) ferroelectric (FE) devices, which degrades data retention, is generally characterized by a shift in the hysteresis loop along the electric field axis. Unlike the static imprint effect, the dynamic imprint [...] Read more.
The conventional static imprint effect in HfxZr1−xO2 (HZO) ferroelectric (FE) devices, which degrades data retention, is generally characterized by a shift in the hysteresis loop along the electric field axis. Unlike the static imprint effect, the dynamic imprint effect emerges under dynamic electric fields or actual operating conditions, making the FE film exceptionally sensitive to switching pulse parameters and domain history. In HZO anti-ferroelectric (AFE) devices, this dynamic imprint effect alters the coercive field distribution associated with domain switching and poses a significant challenge to long-term stable device operation. This study systematically investigates the dynamic imprint effect and its recovery process using a comprehensive integration of first-order reversal curve (FORC) analysis, transient current-voltage (I-V), and polarization-voltage (P-V) characterization. By analyzing localized imprint behavior under sub-cycling conditions, mechanisms and recovery pathways of imprint in AFE devices are proposed. Finally, possible physics-based mechanisms describing imprint behaviors and recovery behaviors are discussed, providing insights for optimizing AFE memory technology performance and reliability. Full article
(This article belongs to the Special Issue Integration of Emerging Memory and Neuromorphic Architecture Chips)
11 pages, 1913 KB  
Article
The Frictional Impact with Rebound for 3D Printed Surfaces
by Ahmet Faruk Akhan and Dan Marghitu
Appl. Sci. 2025, 15(23), 12427; https://doi.org/10.3390/app152312427 (registering DOI) - 23 Nov 2025
Abstract
This research explores the oblique impact with rebound of a rigid rod and 3D-printed surfaces with varying infill ratios. A visco-elastic contact model is developed using normal impact experiments and then confirmed with oblique impact experiments. The force coefficients are determined using a [...] Read more.
This research explores the oblique impact with rebound of a rigid rod and 3D-printed surfaces with varying infill ratios. A visco-elastic contact model is developed using normal impact experiments and then confirmed with oblique impact experiments. The force coefficients are determined using a genetic algorithm. The impact on the polylactic acid surface is defined by a coefficient of restitution, coefficient of friction, and the coefficients of the contact force. The simulations demonstrate good compatibility with the experimental data. Full article
(This article belongs to the Special Issue Nonlinear Dynamics in Mechanical Engineering and Thermal Engineering)
13 pages, 2150 KB  
Article
Study on Atmospheric Boundary Layer Retrieval Method and Observation Data Analysis Based on Aerosol Lidar
by Chao Chen, Bingao Sui, Zhangjun Wang, Baoqing Sun, Hui Li, Xin Pan, Guoliang Shentu, Quanfeng Zhuang, Xianxin Li, Hao Chen and Wenbo Jiang
Atmosphere 2025, 16(12), 1323; https://doi.org/10.3390/atmos16121323 (registering DOI) - 23 Nov 2025
Abstract
The atmospheric boundary layer is the lowest part of the troposphere, directly influenced by the Earth’s surface. The boundary layer’s height is a critical parameter for weather forecasting, air quality monitoring, and climate modeling. Lidar has become a premier tool for continuous boundary [...] Read more.
The atmospheric boundary layer is the lowest part of the troposphere, directly influenced by the Earth’s surface. The boundary layer’s height is a critical parameter for weather forecasting, air quality monitoring, and climate modeling. Lidar has become a premier tool for continuous boundary layer height detection with its high spatial–temporal resolution. A multi-wavelength aerosol lidar with 355 nm, 532 nm, and 1064 nm has been developed and deployed for operational observations at the Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the multi-wavelength aerosol lidar are presented and the retrieval method of the boundary layer’s height is introduced. By comparing it with the data of the digital radiosonde, it is verified that the first normalized gradient of the range-corrected signal can more accurately retrieve the boundary layer’s height. The typical daily variation characteristics and influencing factors of urban boundary layer height are analyzed through observational examples and the monthly mean value of the boundary layer’s height in 2019 is acquired and analyzed. Full article
(This article belongs to the Special Issue Data Analysis and Algorithms for Aerosols Remote Sensing)
29 pages, 2593 KB  
Article
Ensemble Transfer Learning for Gastric Cancer Prediction Using Electronic Health Records in a Data-Scarce Single-Hospital Setting
by Hyon Hee Kim, Ji Yeon Han, Yae Bin Lim, Young Seo Lim, Seung-In Seo, Kyung Joo Lee and Woon Geon Shin
Appl. Sci. 2025, 15(23), 12428; https://doi.org/10.3390/app152312428 (registering DOI) - 23 Nov 2025
Abstract
Gastric cancer is a significant health concern in East Asia, where early risk prediction is critical for prevention. However, the scarcity of single-hospital electronic health records (EHRs) data limits the applicability and generalizability of machine learning models. To address this challenge, we propose [...] Read more.
Gastric cancer is a significant health concern in East Asia, where early risk prediction is critical for prevention. However, the scarcity of single-hospital electronic health records (EHRs) data limits the applicability and generalizability of machine learning models. To address this challenge, we propose an ensemble transfer learning framework for gastric cancer prediction using structured EHRs in a data-scarce single-hospital setting. Three base models, Support Vector Machine (SVM), Random Forest, and Deep Neural Network (DNN), were pretrained on a large-scale national dataset from the Republic of Korean National Health Insurance Service (NHIS) and fine-tuned on a smaller institutional dataset from Kangdong Sacred Heart Hospital (KSHH). These fine-tuned models were combined via stacking ensemble learning with logistic regression as a meta-learner. The proposed model achieved strong performance with precision 0.78, recall 0.92, F1-score 0.83, accuracy 0.91, and AUC 0.93. For interpretability, permutation feature importance and Shapley Additive Explanations (SHAP) were applied. Smoking status, gender, and hypertensive disorder were identified as key predictors consistent with previous studies. This study demonstrates the successful application of transfer learning to overcome data scarcity in single-hospital structured EHRs. Furthermore, our stacking ensemble strategy outperformed the individual fine-tuned models, offering a generalizable framework for gastric cancer prediction in data-scarce clinical settings. Full article
(This article belongs to the Special Issue Advances in Machine Learning for Healthcare Applications)
24 pages, 8438 KB  
Article
Cooling Performance of Night Ventilation and Climate Adaptation of Vernacular Buildings in the Turpan Basin with an Extremely Hot–Arid Climate
by Qingqing Han, Lei Zhang, Wuxing Zheng, Guochen Sang and Yiyun Zhu
Energies 2025, 18(23), 6135; https://doi.org/10.3390/en18236135 (registering DOI) - 23 Nov 2025
Abstract
This study investigates the cooling potential of night ventilation and the climate adaptability of local vernacular buildings in the Turpan basin, aiming to identify passive energy-saving design strategies. A rural building with an air-drying shelter was selected for summer indoor environment measurements (two [...] Read more.
This study investigates the cooling potential of night ventilation and the climate adaptability of local vernacular buildings in the Turpan basin, aiming to identify passive energy-saving design strategies. A rural building with an air-drying shelter was selected for summer indoor environment measurements (two stages: all-day window closure vs. night ventilation), and a numerical model was established to simulate the impacts of window-to-wall ratio and window shading projection factor on the indoor environment. Results indicate that night ventilation introduces cool outdoor air to replace indoor hot air, cools building components, improves thermal comfort, and reduces cooling energy demand. Without additional cooling technology, increasing the window-to-wall ratio lowers nighttime temperatures but increases Degree Discomfort Hours, while appropriately sized shading devices mitigate daytime overheating from larger windows. Benefiting from the high thermal storage capacity of earth-appressed walls, semi-underground rooms offer better comfort with lower temperatures and higher humidity; for aboveground rooms, orientation is critical due to intense solar radiation. The air-drying shelter reduces solar radiant heat absorption and inhibits convective/radiative heat transfer on the roof’s external surface, significantly lowering its temperature from noon to midnight. This leads to notable reductions in the roof’s internal surface temperature (1.02 °C in the sealed stage, 2.09 °C during night ventilation) and the average indoor temperature (1.70 °C). Full article
(This article belongs to the Special Issue Energy Efficiency and Thermal Performance in Buildings)
►▼ Show Figures

Figure 1

27 pages, 487 KB  
Article
Imperfect Demand Information Sharing Under Manufacturer Encroachment
by Beifen Wang and Zhibao Li
Systems 2025, 13(12), 1060; https://doi.org/10.3390/systems13121060 (registering DOI) - 23 Nov 2025
Abstract
The dual-channel structure resulted from manufacturer encroachment could alter the incentives of downstream retailer to ex ante communicate demand forecast. And different types of channel competition need to be investigated in this dual-channel information sharing scenario. This paper aims to investigate retailer’s ex [...] Read more.
The dual-channel structure resulted from manufacturer encroachment could alter the incentives of downstream retailer to ex ante communicate demand forecast. And different types of channel competition need to be investigated in this dual-channel information sharing scenario. This paper aims to investigate retailer’s ex ante imperfect demand information sharing strategy given that upstream manufacturer has set up direct sales channel (manufacturer encroachment). The imperfect information sharing means the demand information shared is uncertain and has some error relative to the real-world demand condition. It examines two types of channel competition: quantity competition and price competition. Additionally, this study discusses the encroaching manufacturer’s incentives for adjusting channel substitution. The paper adopts a stylized game theoretic model to describe interactions between retailer and the encroaching manufacturer. Contrary to conventional wisdom, the paper shows that under manufacturer encroachment, it is always possible for ex ante demand information sharing. Specifically, in the Cournot competition scenario where retailer channel and the encroaching manufacturer direct channel compete in quantity, the encroaching manufacturer could encourage demand information communication through side payment. Furthermore, in the Bertrand competition scenario, retailer may voluntarily share demand information. In addition, in either quantity or price competition, the encroaching manufacturer has incentives to adjust channel substitution for profit maximization. Full article
(This article belongs to the Section Supply Chain Management)
►▼ Show Figures

Figure 1

16 pages, 2690 KB  
Article
Silencing the Circadian Clock Genes Cycle and Clock Disrupts Reproductive–Metabolic Homeostasis but Does Not Induce Reproductive Diapause in Arma chinensis
by Junjie Chen, Qiaozhi Luo, Maosen Zhang, Zhuoling Lv, Meng Liu, Xiangchao Huang, Yuyan Li and Lisheng Zhang
Insects 2025, 16(12), 1192; https://doi.org/10.3390/insects16121192 (registering DOI) - 23 Nov 2025
Abstract
The circadian clock is a conserved timekeeping mechanism that enables organisms to anicipate and adapt to daily environmental cycles. While its role in photoperiodic diapause has been documented, its fundamental function in maintaining reproductive and metabolic homeostasis under favorable conditions remains less explored, [...] Read more.
The circadian clock is a conserved timekeeping mechanism that enables organisms to anicipate and adapt to daily environmental cycles. While its role in photoperiodic diapause has been documented, its fundamental function in maintaining reproductive and metabolic homeostasis under favorable conditions remains less explored, especially in biological control agents. This study investigates the functional roles of the core circadian clock genes Cycle (AcCyc) and Clock (AcClk) in the predatory bug Arma chinensis, focusing on their regulation of reproduction and metabolism under non-diapause conditions. We characterized these genes and analyzed their spatiotemporal expression under diapause and non-diapause conditions. Using RNA interference, we knocked down AcCyc and AcClk in non-diapausing females and evaluated phenotypic impacts on ovarian development, fecundity, and energy reserves. qPCR analyses delineated downstream effects on juvenile hormone (JH) signaling. Results showed that diapause altered AcCyc and AcClk expression rhythms. Their knockdown severely impaired reproduction, reducing ovarian size, vitellogenin expression, and egg production, while concurrently decreasing triglyceride levels indicating disrupted energy homeostasis. Mechanistically, gene silencing downregulated key JH pathway components, Methoprene-tolerant (Met) and Krueppel homolog 1 (Kr-h1). We conclude that AcCyc and AcClk are essential maintainers of reproductive–metabolic homeostasis, not merely diapause regulators. This reframes the clock’s role from a seasonal timekeeper to a central hub for daily physiological coordination, offering new insights for improving biocontrol agent production. Full article
(This article belongs to the Section Insect Molecular Biology and Genomics)
►▼ Show Figures

Figure 1

29 pages, 8374 KB  
Article
Cross-Domain Land Surface Temperature Retrieval via Strategic Fine-Tuning-Based Transfer Learning: Application to GF5-02 VIMI Imagery
by Peyman Heidarian, Hua Li, Zelin Zhang, Yumin Tan, Feng Zhao, Biao Cao, Yongming Du and Qinhuo Liu
Remote Sens. 2025, 17(23), 3803; https://doi.org/10.3390/rs17233803 (registering DOI) - 23 Nov 2025
Abstract
Accurate prediction of land surface temperature (LST) is critical for remote sensing applications, yet remains hindered by in situ data scarcity, limited input variables, and regional variability. To address these limitations, we introduce a three-stage strategic fine-tuning-based transfer learning (SFTL) framework that integrates [...] Read more.
Accurate prediction of land surface temperature (LST) is critical for remote sensing applications, yet remains hindered by in situ data scarcity, limited input variables, and regional variability. To address these limitations, we introduce a three-stage strategic fine-tuning-based transfer learning (SFTL) framework that integrates a large simulated dataset (430 K samples), in situ measurements from the Heihe and Huailai regions in China, and high-resolution imagery from the GF5-02 Visible and Infrared Multispectral Imager (VIMI). The key novelty of this study is the combination of large-scale simulation, an engineered humidity-sensitive feature, and multiple parameter-efficient tuning strategies—full, head, gradual, adapter, and low-rank adaptation (LoRA)—within a unified transfer-learning framework for cross-site LST estimation. In Stage 1, pre-training with 5-fold cross-validation on the simulated dataset produced strong baseline models, including Random Forest (RF), Light Gradient Boosting Machine (LGBM), Deep Neural Network (DNN), Transformer (TrF), and Convolutional Neural Network (CNN). In Stage 2, strategic fine-tuning was conducted under two cross-regional scenarios—Heihe-to-Huailai and Huailai-to-Heihe—and model transfer for tree-based learners. Fine-tuning achieved competitive in-domain performance while materially improving cross-site transfer. When trained on Huailai and tested on Heihe, DNN-gradual attained RMSE 2.89 K (R2 ≈ 0.96); when trained on Heihe and tested on Huailai, TrF-head achieved RMSE 3.34 K (R2 ≈ 0.94). In Stage 3, sensitivity analyses confirmed stability across IQR multipliers of 1.0–1.5, with <1% RMSE variation across models and sites, indicating robustness against outliers. Additionally, application to real GF5-02 VIMI imagery demonstrated that the best SFTL configurations aligned with spatiotemporal in situ observations at both sites, capturing the expected spatial gradients. Overall, the proposed SFTL framework—anchored in cross-validation, strategic fine-tuning, and large-scale simulation—outperforms the widely used Split-Window (SW) algorithm (Huailai: RMSE = 3.64 K; Heihe: RMSE = 4.22 K) as well as direct-training Machine Learning (ML) models, underscoring their limitations in modeling complex regional variability. Full article
(This article belongs to the Special Issue Spatio-Temporal Land Surface Temperature Retrieval Based on Ground-Based, Satellite Observations and Artificial Intelligence)
►▼ Show Figures

Figure 1

20 pages, 862 KB  
Review
Heparin Resistance in Cardiac Surgery with Cardiopulmonary Bypass: Mechanisms, Clinical Implications, and Evidence-Based Management
by Karina E. Rivera Jiménez, Yahaira M. Mamani Ticona, Giancarlo Gutierrez-Chavez, Cristian O. Astudillo, Edisson Calle, Giancarlo A. Torres Heredia, Dario S. Lopez Delgado, Oriana Rivera-Lozada and Joshuan J. Barboza
Medicina 2025, 61(12), 2088; https://doi.org/10.3390/medicina61122088 (registering DOI) - 23 Nov 2025
Abstract
Background: Unfractionated heparin (UFH) is the standard anticoagulant during cardiopulmonary bypass (CPB). A clinically relevant subset develops heparin resistance (HR)—failure to reach adequate anticoagulation with usual UFH—raising thrombotic risk and complicating perioperative care. Objectives: To synthesize contemporary evidence on the mechanisms, [...] Read more.
Background: Unfractionated heparin (UFH) is the standard anticoagulant during cardiopulmonary bypass (CPB). A clinically relevant subset develops heparin resistance (HR)—failure to reach adequate anticoagulation with usual UFH—raising thrombotic risk and complicating perioperative care. Objectives: To synthesize contemporary evidence on the mechanisms, clinical implications, and perioperative management of HR in adult cardiac surgery with CPB. Methods: This narrative review synthesizes contemporary evidence on the epidemiology, mechanisms, recognition, and management of HR in adult cardiac surgery with CPB, emphasizing clinically actionable points. Results: Incidence varies across centers and definitions. Mechanisms include antithrombin (AT) deficiency or consumption and AT-independent drivers such as systemic inflammation or sepsis, protein-loss states, thrombocytosis, hyperfibrinogenemia, obesity, prior heparin exposure, and drug interactions. Sole reliance on activated clotting time (ACT) may misestimate anticoagulant effect; anti–factor Xa (anti-Xa) assays or heparin titration systems improve assessment when available. Management is stepwise: UFH dose escalation; targeted AT supplementation (or fresh frozen plasma where concentrates are unavailable); and transition to direct thrombin inhibitors when HR persists or UFH is contraindicated. Protocolized pathways and multidisciplinary coordination reduce delays and adverse events. Conclusions: HR is a multifactorial, common challenge in CPB. Pre-bypass risk assessment, multimodal monitoring, and an algorithm prioritizing UFH optimization, AT repletion, and timely use of direct thrombin inhibitors provide a pragmatic framework to limit thrombosis and bleeding. Harmonized definitions and comparative trials remain priorities. Full article
(This article belongs to the Special Issue Recent Advances in Cardiovascular Surgery)
12 pages, 2004 KB  
Article
Fire-Enhanced Soil Carbon Sequestration in Wetlands: A 5000-Year Record from the Ussuri River, Northeast China
by Yan Zhao, Xinyuan He and Zhenqing Zhang
Atmosphere 2025, 16(12), 1322; https://doi.org/10.3390/atmos16121322 (registering DOI) - 23 Nov 2025
Abstract
Using high-resolution charcoal and TOC records from a sediment core collected in a coastal wetland along the middle reaches of the Ussuri River, the local fire history and carbon accumulation patterns were reconstructed for the past 5000 years. Results indicate that fire intensity [...] Read more.
Using high-resolution charcoal and TOC records from a sediment core collected in a coastal wetland along the middle reaches of the Ussuri River, the local fire history and carbon accumulation patterns were reconstructed for the past 5000 years. Results indicate that fire intensity remained relatively low and stable from 5000 to 1500 cal. yr BP, after which it increased markedly. This trend intensified over the past 400 years, likely due to rapid population growth and heightened anthropogenic disturbance. Regional fire frequency averaged approximately 3.1 fires per 1500 years, with notable peaks during 5000–4600 cal. yr BP, 3400–2400 cal. yr BP, and 1500 cal. yr BP to present. These high-fire intervals correspond closely to regional warm and dry climatic conditions, underscoring the strong influence of climate variability on fire activity. Carbon accumulation rates also showed a significant increase, rising from 0.11 g·kg−1·a−1 around 5000 years ago to 1.60 g·kg−1·a−1 in recent centuries. Importantly, a significant positive correlation was observed between fire regimes and carbon accumulation rates, suggesting that fires have potentially played a key role in enhancing long-term carbon sequestration in wetlands of this region. These findings highlight the complex interplay between fire, climate, and carbon dynamics in wetland ecosystems. Full article
(This article belongs to the Special Issue The Evolution of Climate and Environment in the Holocene)
14 pages, 3074 KB  
Article
Visual Localization and Policy Learning for Robotic Large-Diameter Peg-in-Hole Assembly Tasks
by Tao Liang, Dingrong Wang, Wenzhi Ma, Lei Zhang and Dongsheng Chen
Electronics 2025, 14(23), 4592; https://doi.org/10.3390/electronics14234592 (registering DOI) - 23 Nov 2025
Abstract
The conventional component assembly techniques employed in manufacturing industries typically necessitate laborious manual parameter calibration prior to system deployment, while existing vision-based control algorithms suffer from limited adaptability and inefficient learning capabilities. This paper presents a novel framework for automated large-diameter peg-in-hole assembly [...] Read more.
The conventional component assembly techniques employed in manufacturing industries typically necessitate laborious manual parameter calibration prior to system deployment, while existing vision-based control algorithms suffer from limited adaptability and inefficient learning capabilities. This paper presents a novel framework for automated large-diameter peg-in-hole assembly through convolutional network-based perception and reinforcement learning-driven control. Our methodology introduces three key innovations: (1) an enhanced deep segmentation architecture for precise identification and spatial localization of peg-end centroids, enabling accurate preliminary peg-in-hole; (2) a hybrid control strategy combining deep deterministic policy gradient (DDPG) reinforcement learning with classical control theory, augmented by real-time force feedback data acquisition; (3) systematic integration of visual–spatial information and haptic feedback for robust error compensation. Experimental validation on an industrial robotic platform demonstrates the method’s superior performance, achieving an Intersection over Union (IoU) score of 0.946 in peg segmentation tasks and maintaining insertion stability with maximum radial forces below 5.34 N during assembly operations. The proposed approach significantly reduces manual intervention requirements while exhibiting remarkable tolerance to positional deviations (±2.5 mm) and angular misalignments (±3°) commonly encountered in industrial assembly scenarios. Full article
(This article belongs to the Special Issue Intelligent Image and Video Processing: Quality, Compression and Vision Applications)
22 pages, 746 KB  
Review
Tracing Microplastics in the Human Body: From Detection to Disease Mechanisms
by Stefana Anastasia Talau, Mihaela Chialda, Cristian Ichim, Horatiu Dura and Ciprian Tanasescu
Diagnostics 2025, 15(23), 2971; https://doi.org/10.3390/diagnostics15232971 (registering DOI) - 23 Nov 2025
Abstract
Microplastics (MPs), defined as plastic particles <5 mm diameter, have become a growing public health concern. First identified in the aquatic environment in 2004 and later in air samples in 2015, airborne MPs display wide variations in shape and size, with fibres being [...] Read more.
Microplastics (MPs), defined as plastic particles <5 mm diameter, have become a growing public health concern. First identified in the aquatic environment in 2004 and later in air samples in 2015, airborne MPs display wide variations in shape and size, with fibres being the most common. These physical characteristics, together with others such as median aerodynamic diameter, influence how deeply they penetrate and where they deposit within the respiratory tract. Recent studies have confirmed the presence of MPs in nasal lavage fluid, bronchoalveolar lavage fluid, sputum, pleural fluid and lung tissue samples, with higher concentrations observed in older individuals, smokers and those with occupational exposure. Multiple polymer types have been identified, most frequently polypropylene, polyethylene and polyester. Experimental models demonstrate that MPs can induce inflammation, oxidative stress, mitochondrial dysfunction, microbiota alterations, fibrosis and carcinogenic changes, with toxicity generally increasing as particle size decreases. Despite the growing evidence of plastic toxicity, only a limited number of studies have examined MPs’ influence on the respiratory system, focusing mostly on polyester spheres, rather than fibres, which dominate real-world exposure. Current findings suggest MPs contribute to several pathophysiological processes and may play a role in respiratory disease. However, further research is needed to clarify the underlying mechanisms, long-term consequences and clinical relevance of these emerging pollutants. Full article
(This article belongs to the Special Issue Precise Diagnosis, Classification, and Monitoring of Pulmonary Diseases)
16 pages, 1295 KB  
Article
Color Stability of a Composite Containing Hydroxyapatite, Fluorine, and Silver Fillers After Artificial Aging
by Zofia Kula, Cristina Bettencourt Neves, Ana Bettencourt, Sara Oliveira and João Carlos Roque
Appl. Sci. 2025, 15(23), 12426; https://doi.org/10.3390/app152312426 (registering DOI) - 23 Nov 2025
Abstract
This work concerns composite materials containing hydroxyapatite, fluorine, and nanosilver fillers. These composites are intended for the reconstruction of lost hard tooth tissues. The aim of the work was to evaluate the color stability of a flow composite containing hydroxyapatite, fluorine, and silver [...] Read more.
This work concerns composite materials containing hydroxyapatite, fluorine, and nanosilver fillers. These composites are intended for the reconstruction of lost hard tooth tissues. The aim of the work was to evaluate the color stability of a flow composite containing hydroxyapatite, fluorine, and silver fillers after artificial thermal, chemical, and a combination of thermal and chemical aging processes. The samples were prepared from a commercial flow-type composite material (Arkona Flow Art, Niemcy, Poland) color A2 VITA (Vita Classical, Vita Zahnfabrick, Bad Sackingen, Germany) original and a modified composite material containing a filler additive of 2 wt.% hydroxyapatite powder containing fluorine (calcium fluoride) and nanosilver (n = 15). An Optishade (Style Italiano, Italy) colorimeter was used to measure color against a black background. Samples were submitted to thermal aging (T) using thermocycling equipment; to chemical aging (C) by immersion on artificial saliva at pH7, 37 °C; and to constant agitation or thermal–chemical aging using a combination of the previous two methods. The modified composite showed reduced color differences compared to the original composite. The results also show that thermal aging has a stronger influence on ΔE increase than chemical and combined aging, but only for the modified composite. Cumulative aging processes had an influence below the acceptability threshold for the modified composite. Full article
(This article belongs to the Special Issue Applied Biomaterials for Dental Implantology: Researches and Applications)
►▼ Show Figures

Figure 1

18 pages, 4087 KB  
Article
Aboveground Biomass Inversion Using DTM-Independent Crown Metrics from UAV Stereoscopic Imagery in the Greater and Lesser Khingan Mountains
by Qiang Wang, Yu Wang, Wenjian Ni, Tianyu Yu, Zhiyu Zhang, Peizhe Qin, Zongling Jiang, Xiaoling Yin and Jie Wang
Forests 2025, 16(12), 1765; https://doi.org/10.3390/f16121765 (registering DOI) - 23 Nov 2025
Abstract
The utilization of photography imagery captured using cameras mounted on unmanned aerial vehicles (UAVs) for aboveground biomass (AGB) inventory has seen rapid growth in recent years. Existing research has predominantly focused on utilizing spectral and textural features for biomass inversion. However, estimating the [...] Read more.
The utilization of photography imagery captured using cameras mounted on unmanned aerial vehicles (UAVs) for aboveground biomass (AGB) inventory has seen rapid growth in recent years. Existing research has predominantly focused on utilizing spectral and textural features for biomass inversion. However, estimating the AGB of trees remains a great challenge using stereoscopic imagery without the help of a digital terrain model (DTM). This study introduces five DTM-independent crown metrics using a digital surface model (DSM) and a canopy height model (CHM) derived from UAV stereoscopic imagery. The accuracy of the five metrics was evaluated against field measurements. The results indicate that the relationship between the crown cross-sectional area (CCSA) and AGB is stronger than that between tree height (TH) and AGB, with R2 = 0.62 and RMSE = 69.22 (kg/tree) for Larix gmelinii and R2 = 0.93 and RMSE = 142.06 (kg/tree) for Pinus sylvestris. Moreover, these DTM-independent crown metrics could be used to estimate the AGB of forests in the Greater and Lesser Khingan Mountain, with R2 = 0.77 and RMSE = 77.10 (kg/tree) for coniferous trees and R2 = 0.78 and RMSE = 72.46 (kg/tree) for all other trees. The results of this study demonstrate that UAV stereoscopic imagery can capture forest canopy information, and DTM-independent crown metrics can be used for AGB inversion where information on terrain under forest is unavailable. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
22 pages, 1317 KB  
Article
Diversified Crop Rotation Improves Soil Quality by Increasing Soil Organic Carbon in Long-Term Continuous Cotton Fields
by Qiuyu Ren, Jinbin Wang, Hang Qiao, Mingwei Du, Qiang Hu, Sumei Wan, Hongqiang Dong, Jialiang Zhang, Zhenlin Dong, Tiantian Li, Zhengjun Cui and Guodong Chen
Agronomy 2025, 15(12), 2698; https://doi.org/10.3390/agronomy15122698 (registering DOI) - 23 Nov 2025
Abstract
To explore the improvement effect of diversified crop rotation on soil quality in long-term continuous cotton fields (15 years), a field experiment was conducted in southern Xinjiang in 2024. With continuous cotton (C-C) as the control, four crop rotations, namely, cotton–maize (C-M), cotton–wheat [...] Read more.
To explore the improvement effect of diversified crop rotation on soil quality in long-term continuous cotton fields (15 years), a field experiment was conducted in southern Xinjiang in 2024. With continuous cotton (C-C) as the control, four crop rotations, namely, cotton–maize (C-M), cotton–wheat (C-W), cotton–soybean (C-S), and cotton–peanut (C-P), were set up. The results showed that compared with C-C, the soil organic carbon (SOC) treated by C-P and C-S increased significantly by 11.76% and 3.38%, respectively, and the easily oxidized organic carbon (EOC) increased by 45.18% and 37.15%, respectively. The dissolved organic carbon (DOC) treated with C-S increased by 14.36%, while C-M decreased by 10.98%. The carbon pool index (CPI) of C-P was the highest in the 0–20 cm soil layer, which was 13.00% higher than that of C-C. The β-1, 4-glucosidase (BGL) activity of C-C at 0–20 cm and 20–40 cm was 144.70–387.26% and 48.01%–71.32% higher than that of other treatments, respectively. The RuBisCo activity of C-P was 80.96% higher than that of C-C. The soil quality index was the highest for C-S, followed by C-P, which was 74.56% higher than that of C-C. In conclusion, the cotton–peanut rotation can effectively improve the soil quality of continuous cotton fields by increasing the organic carbon composition, enhancing the activity of carbon-fixing enzymes and bacterial diversity. Full article
(This article belongs to the Special Issue Innovations in Green and Efficient Cotton Cultivation)
47 pages, 7412 KB  
Review
Fluoride-Free MXene–Polymer Composites for Li-Metal and Li–S Batteries: Comparative Synthesis Methods, Integration Rules, Challenges, and Future Directions
by Truong Le Khang and Joonho Bae
Polymers 2025, 17(23), 3109; https://doi.org/10.3390/polym17233109 (registering DOI) - 23 Nov 2025
Abstract
MXene–polymer hybrids combine the high in-plane conductivity and rich surface chemistry of MXenes with the processability and mechanical tunability of polymers for lithium-metal and lithium–sulfur batteries. Most reported systems still rely on HF-etched MXenes, introducing F-rich terminations, safety and waste issues, and poorly [...] Read more.
MXene–polymer hybrids combine the high in-plane conductivity and rich surface chemistry of MXenes with the processability and mechanical tunability of polymers for lithium-metal and lithium–sulfur batteries. Most reported systems still rely on HF-etched MXenes, introducing F-rich terminations, safety and waste issues, and poorly controlled surfaces. This review instead centers on fluoride-free synthesis routes, benchmarks them against HF methods, and translates route–termination relationships into practical rules for choosing polymer backbones. We track the evolution from early linear hosts such as PEO- and PVDF-type polymers to polar nitrile or carbonyl matrices, crosslinked and ionogel networks, and emerging biopolymers and COF-type porous frameworks that are co-designed with MXene terminations to regulate ion transport, interfacial chemistry, and mechanical robustness. These chemistry–backbone pairings are linked to five scalable fabrication modes, including solution blending and film casting, in situ polymerization, surface grafting, layer-by-layer assembly, and electrospinning, and to roles as solid or quasi-solid electrolytes, artificial interphases, separator-like coatings, and electrode-facing architectures. Finally, we highlight key evidence gaps and reporting standards needed to de-risk scale-up of green MXene–polymer batteries. Full article
(This article belongs to the Special Issue Preparations and Applications of Polymer–MXenes Composites for Next Generation Energy Storage)
►▼ Show Figures

Figure 1

17 pages, 5337 KB  
Article
Thermal–Hydraulic Modeling and H∞ Control for Aero-Engine Fuel Metering Units
by Ke Wang, Yu Wang, Pengyuan Li, Di Wu, Lifeng Cui and Bin-Bin Hao
Aerospace 2025, 12(12), 1040; https://doi.org/10.3390/aerospace12121040 (registering DOI) - 23 Nov 2025
Abstract
Aero-engines operate across wide flight envelopes and harsh environments, requiring the fuel metering unit (FMU) to perform reliably over a broad temperature range. Fuel temperature fluctuations significantly modify viscosity and density, which in turn alter pressure distribution, flow behavior, and the dynamic response [...] Read more.
Aero-engines operate across wide flight envelopes and harsh environments, requiring the fuel metering unit (FMU) to perform reliably over a broad temperature range. Fuel temperature fluctuations significantly modify viscosity and density, which in turn alter pressure distribution, flow behavior, and the dynamic response of the metering spool. Based on the first law of thermodynamics and the control volume method, this study theoretically analyzes how these thermal effects influence FMU pressure, flow rate, and spool motion. A thermo-hydraulic FMU model is then developed in AMESim to capture the coupled pressure-flow-motion dynamics. Based on this model, a robust H∞ controller is designed using the mixed-sensitivity approach to compensate for the temperature-dependent degradation in system performance. Simulation results verify that the proposed model accurately reproduces the FMU dynamics under varying thermal conditions. Furthermore, compared with a conventional PI controller, the H∞ controller achieves precise spool displacement regulation over the wide temperature range of −10∘C to 50∘C, effectively mitigating the adverse effects induced by temperature variations. Full article
(This article belongs to the Section Aeronautics)
23 pages, 1677 KB  
Article
The Impact of Psyching-Up and Cognitive Challenges on Cognitive Performance and Well-Being in Adolescent Swimmers: A Randomized Controlled Trial
by Yasmine Dhaouadi, Riadh Khalifa and Antonella Muscella
Children 2025, 12(12), 1591; https://doi.org/10.3390/children12121591 (registering DOI) - 23 Nov 2025
Abstract
Background/Objectives: The integration of psychological techniques, such as psyching-up, into sports training has been increasingly explored for its potential to enhance athletic performance and cognitive function, especially in young athletes. This study aimed to examine the effects of combining psyching-up techniques with cognitive [...] Read more.
Background/Objectives: The integration of psychological techniques, such as psyching-up, into sports training has been increasingly explored for its potential to enhance athletic performance and cognitive function, especially in young athletes. This study aimed to examine the effects of combining psyching-up techniques with cognitive challenges on psychophysiological responses and visuo-auditory attention in adolescent competitive swimmers. Methods: A total of 48 male competitive swimmers were randomly assigned to three groups: the Psyching-Up and Cognitive Group (PCG), the Cognitive Training Group (CGT), and a Control Group (CG). The intervention involved ten training sessions, where the PCG received psyching-up techniques, while both the PCG and CGT participated in cognitive training tasks. Key assessments included cognitive performance tests (Bells Test, Trail Making Test Parts A and B, Go/No-Go Auditory Task), heart rate (%HR max), blood lactate levels, perceived exertion (RPE), and mood state (Total Mood Disturbance). Results: The PCG showed significant improvements in cognitive performance, with fewer omissions in the Bells Test (p = 0.041) and faster reaction times in the Trail Making Test (Part A, p = 0.002; Part B, p = 0.001). In the Go/No-Go Auditory Task, the PCG exhibited faster reaction times and a higher hit rate (p = 0.001). There were no significant differences in physiological responses, with %HR max and blood lactate levels showing stable trends across groups. However, the PCG reported significantly higher enjoyment (p < 0.001) and a reduction in Total Mood Disturbance (p < 0.001). Conclusions: Integrating psyching-up techniques with cognitive challenges positively impacts cognitive performance and psychological well-being in adolescent swimmers, without altering physiological responses. These findings highlight the potential of psychological interventions to enhance performance and overall athlete experience in youth sports training. Full article
(This article belongs to the Special Issue Advances in Adolescent Mental Health: Early Prevention and Intervention)
►▼ Show Figures

Figure 1

31 pages, 840 KB  
Article
Understanding Persistent Wage Disparities in Rural Colombia: Comparative Lessons from Latin America
by José Alejandro Moncada Aristizábal and Favio Cala Vitery
Soc. Sci. 2025, 14(12), 677; https://doi.org/10.3390/socsci14120677 (registering DOI) - 23 Nov 2025
Abstract
This research provides the first comprehensive analysis of the rural–urban wage gap in Colombia, with a focus on the coffee and cocoa sectors, over the past two decades. Using household survey microdata from 2001 to 2023 and international sources, we estimate wage differentials [...] Read more.
This research provides the first comprehensive analysis of the rural–urban wage gap in Colombia, with a focus on the coffee and cocoa sectors, over the past two decades. Using household survey microdata from 2001 to 2023 and international sources, we estimate wage differentials and apply econometric models—including Mincerian wage regressions and Blinder–Oaxaca decompositions. Results reveal a persistent and substantial wage gap: on average, rural coffee and cocoa workers earn roughly half as much as urban manufacturing workers. Even after controlling for education, experience, and other characteristics, a substantial share of the gap remains unexplained, indicating structural issues such as lower productivity, elevated levels of informality, and labor market segmentation in rural areas. Moreover, time-series evidence from the past two decades shows no significant convergence between rural and urban wages. Comparative analysis with Brazil, Mexico, and other Latin American countries highlights how policy interventions, such as rural social protection programs, labor formalization, and support for agricultural cooperatives, have helped narrow rural–urban wage disparities elsewhere. Drawing on these lessons, we discuss policy implications for Colombia and recommend measures to boost rural human capital, strengthen labor institutions, expand social safety nets, and promote rural economic development. These recommendations aim to gradually close the rural–urban wage divide, reduce rural poverty, and foster inclusive growth. Full article
(This article belongs to the Section Work, Employment and the Labor Market)
►▼ Show Figures

Figure 1

13 pages, 2013 KB  
Article
Preventive Effect of Epigallocatechin-3-Gallate on Postoperative Cognitive Dysfunction in Aged Rats via Modulation of Microglial Differentiation: An Experimental Animal Study
by Seung-Wan Hong, Liyun Piao, Eun-Hwa Cho, Eun-Hye Seo and Seong-Hyop Kim
Int. J. Mol. Sci. 2025, 26(23), 11326; https://doi.org/10.3390/ijms262311326 (registering DOI) - 23 Nov 2025
Abstract
This study evaluated the effect of epigallocatechin-3-gallate (EGCG), a flavonoid, on postoperative cognitive dysfunction by modulating microglial phenotype expression in aged rats following general anesthesia with isoflurane. Eighteen-month-old male Sprague–Dawley rats were randomly assigned to the EGCG and control groups. EGCG in distilled [...] Read more.
This study evaluated the effect of epigallocatechin-3-gallate (EGCG), a flavonoid, on postoperative cognitive dysfunction by modulating microglial phenotype expression in aged rats following general anesthesia with isoflurane. Eighteen-month-old male Sprague–Dawley rats were randomly assigned to the EGCG and control groups. EGCG in distilled water (DW) or DW alone was administered orally for 7 days before anesthesia. After anesthesia, cognitive function was assessed using the Y-maze test, and neuronal damage was evaluated histologically. Microglial activation and phenotype differentiation were also analyzed. At 24 h after anesthesia, the alternation ratio was significantly higher in the EGCG group than in the control group (70.00 ± 7.98% vs. 28.14 ± 11.52%, p < 0.001). The EGCG group exhibited reduced neuronal damage and microglial activation. Additionally, M1 phenotype activation was significantly lower (30.03 ± 7.73% vs. 51.00 ± 9.83%, p < 0.001), and M2 phenotype activation was significantly higher (17.61 ± 5.52% vs. 5.99 ± 2.46%, p < 0.001) in the EGCG group than in the control group. In summary, pre-anesthetic administration of EGCG modulated microglial phenotype differentiation, reduced neuronal damage, and improved postoperative cognitive function in aged rats following general anesthesia. Full article
(This article belongs to the Special Issue Updates on Synthetic and Natural Antioxidants)
More Articles...

Open Access Journals

► Browse by Indexing ► Browse by Subject ► Selected Journals
Explore All Journals...

Highly Accessed Articles

Latest Books

More Books and Reprints...

News

13 November 2025
MDPI is a Platinum Sponsor of the 2nd International Conference of Environmental Medicine in Chieti, Italy, 20–21 November 2025
13 November 2025
Meet Us at the 17th Canadian Science Policy Conference, 19–21 November 2025, Ottawa, Ontario
12 November 2025
MDPI Is a Sponsor for the 20th Munin Conference on Scholarly Publishing 2025, in Tromsø, Norway, 18–20 November 2025
More News & Announcements...

Blog Posts

More From Our Blog...

Topics

More Topics...
loading...

Selected Special Issues

Selected Collections

Back to TopTop