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24 pages, 7420 KB

Open AccessArticle

Horizontal Vibration of the Coupled Rope–Car–Rail System in High-Speed Elevators Under Building Sway Excitation

by Wen Wang, Jiang Qian, Yunyang Wang and Benkun Tan

Buildings 2025, 15(19), 3608; https://doi.org/10.3390/buildings15193608 - 8 Oct 2025

Horizontal vibrations in high-speed elevators induced by building sway degrade ride comfort and compromise operational safety. Developing an accurate and robust dynamic model is essential for effective vibration control. To address this, this study develops a comprehensive dynamic model of the coupled traction [...] Read more.

Horizontal vibrations in high-speed elevators induced by building sway degrade ride comfort and compromise operational safety. Developing an accurate and robust dynamic model is essential for effective vibration control. To address this, this study develops a comprehensive dynamic model of the coupled traction rope–car–guide shoe–guide rail system under multi-support excitations, incorporating nonlinear contact between the guide shoe and rail, guide rail vibration characteristics, and the time-varying length of traction rope. Using this model, the dynamic responses of the system under stationary and operating conditions are analyzed in detail. The results demonstrate that the proposed model accurately captures the dynamic behavior of the coupled system. In addition, the traction rope’s dynamics are a dominant factor in the system’s response, particularly when the elevator is stationary at a landing, producing a resonant condition with the building sway. Furthermore, a strong coupling between vertical motion and horizontal vibration is identified, which significantly amplifies the system response. By linking elevator dynamics with the sway characteristics of high-rise buildings, this work provides a robust analytical framework for predicting the dynamic response of high-speed elevators due to building sway and contributes to the safety assessment of high-rise reinforced concrete (RC) structures. Full article

(This article belongs to the Special Issue Safety Assessment and Structural Analysis of Reinforced Concrete Buildings)

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21 pages, 2543 KB

Open AccessArticle

The Modulatory Effect of tDCS Onset Timing in Alleviating Vigilance Decrement

by Zelin Pan, Yang Chen, Shanghong Wu and Tiansheng Xia

Brain Sci. 2025, 15(10), 1085; https://doi.org/10.3390/brainsci15101085 - 8 Oct 2025

Abstract

Vigilance refers to a sustained attentional state enabling the detection of specific but unpredictable changes in the external environment. This state typically declines rapidly over time. A deterioration in vigilance can lead to serious errors or accidents in both occupational and special scenarios, [...] Read more.

Vigilance refers to a sustained attentional state enabling the detection of specific but unpredictable changes in the external environment. This state typically declines rapidly over time. A deterioration in vigilance can lead to serious errors or accidents in both occupational and special scenarios, rendering vigilance intervention a critical area of interest for researchers. Transcranial direct current stimulation (tDCS) has shown promise in mitigating vigilance decrement. However, the timing of such interventions may yield differential effects, a question that remains unresolved in the literature. The present study examines the possibility of using the average power in the low alpha frequency band (alpha-1) as an Electroencephalography-based index of vigilance to identify a candidate entry point for tDCS application that may enhance efficacy, and further explores how the timing of tDCS influences vigilance outcomes. In the pilot experiment, we determined the timing for guiding tDCS based on the average power of the low alpha frequency band (alpha-1) from five participants, which was identified as the third stage of the experiment. The validity of this timing has been verified in subsequent independent samples with a larger size. In the formal experiment, ninety-nine participants were randomly assigned to three groups, receiving early intervention, late intervention, or a no-stimulus control, and completed a 20 min visual modification of the Bakan Task. The early-stimulated group (n = 33) received anodal stimulation (2 mA) on the right posterior parietal cortex during the first 8 min of the test (0–8 min), the late-stimulated group (n = 33) received stimulation on the same location during the middle 8 min of the test (8–16 min), while the blank control group (n = 33) received no stimulation. Results indicated that the late-stimulated group (8–16 min of stimulation), for which alpha-1 power guided the tDCS onset timing, was associated with a greater attenuation of vigilance decrement compared to the early-stimulated group (0–8 min of stimulation). Both groups demonstrated significant differences in vigilance during the first stage following stimulation. Full article

(This article belongs to the Special Issue Neuroimaging and Biomarker-Guided Neuromodulation: Advances in Personalized Brain and Autonomic Stimulation)

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30 pages, 8109 KB

Open AccessArticle

Content-Adaptive Reversible Data Hiding with Multi-Stage Prediction Schemes

by Hsiang-Cheh Huang, Feng-Cheng Chang and Hong-Yi Li

Sensors 2025, 25(19), 6228; https://doi.org/10.3390/s25196228 - 8 Oct 2025

Abstract

:With the proliferation of image-capturing and display-enabled IoT devices, ensuring the authenticity and integrity of visual data has become increasingly critical, especially in light of emerging cybersecurity threats and powerful generative AI tools. One of the major challenges in such sensor-based systems [...] Read more.

:With the proliferation of image-capturing and display-enabled IoT devices, ensuring the authenticity and integrity of visual data has become increasingly critical, especially in light of emerging cybersecurity threats and powerful generative AI tools. One of the major challenges in such sensor-based systems is the ability to protect privacy while maintaining data usability. Reversible data hiding has attracted growing attention due to its reversibility and ease of implementation, making it a viable solution for secure image communication in IoT environments. In this paper, we propose reversible data hiding techniques tailored to the content characteristics of images. Our approach leverages subsampling and quadtree partitioning, combined with multi-stage prediction schemes, to generate a predicted image aligned with the original. Secret information is embedded by analyzing the difference histogram between the original and predicted images, and enhanced through multi-round rotation techniques and a multi-level embedding strategy to boost capacity. By employing both subsampling and quadtree decomposition, the embedding strategy dynamically adapts to the inherent characteristics of the input image. Furthermore, we investigate the trade-off between embedding capacity and marked image quality. Experimental results demonstrate improved embedding performance, high visual fidelity, and low implementation complexity, highlighting the method’s suitability for resource-constrained IoT applications. Full article

(This article belongs to the Special Issue Data Security Approaches for Autonomous Systems, IoT, and Smart Sensing Systems)

23 pages, 53656 KB

Open AccessArticle

ProposalLaneNet: Sparse High-Quality Proposal-Driven Efficient Lane Detection

by Baowang Chen, Liufeng Tao, Wenjie Zhao and Dengfeng Li

Appl. Sci. 2025, 15(19), 10803; https://doi.org/10.3390/app151910803 - 8 Oct 2025

Abstract

Lane detection is one of the key technologies for local map construction, and it is also a challenging task in intelligent driving, where various computer vision-based methods have been applied to address this issue. However, these methods often suffer from redundancy issues due [...] Read more.

Lane detection is one of the key technologies for local map construction, and it is also a challenging task in intelligent driving, where various computer vision-based methods have been applied to address this issue. However, these methods often suffer from redundancy issues due to the sparse and narrow structure of the lane lines, and full generalization to lane detection needs more effort. To solve these problems, we propose a stepwise positive guidance strategy that utilizes the visually presented lane structure characteristics, which are inspired by the reference points in the DETR-Family methods. This strategy guides the network detection from the reference points to the reference lanes, improving the accuracy of the detection process. Moreover, we propose a new multi-scale feature fusion strategy that directly performs feature fusion on high-quality proposals. This approach differs from traditional object detection models using the Feature Pyramid Network (FPN). It fully uses the sparsity of lanes and reduces the network’s redundant computation. We proposed ProposalLaneNet, which takes full advantage of the lanes’ structure and sparse distribution characteristics. Significant improvements in speed and accuracy have been achieved by our method, enabling it to reach the state-of-the-art performance on the popular datasets CULane and TuSimple. Our method can be used as a new detection paradigm for lane detection. Full article

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11 pages, 1312 KB

Open AccessArticle

Comparing Heart Rate and Heart Rate Reserve for Accurate Energy Expenditure Prediction Against Direct Measurement

by Yongsuk Seo, Yunbin Lee and Dae Taek Lee

Int. J. Environ. Res. Public Health 2025, 22(10), 1539; https://doi.org/10.3390/ijerph22101539 (registering DOI) - 8 Oct 2025

Abstract

This study developed and validated simplified, individualized heart rate (HR)-based regression models to predict energy expenditure (EE) during treadmill exercise without direct VO2 calibration, addressing the need for more practical and accurate methods that overcome limitations of existing predictions and facilitate precise EE [...] Read more.

This study developed and validated simplified, individualized heart rate (HR)-based regression models to predict energy expenditure (EE) during treadmill exercise without direct VO2 calibration, addressing the need for more practical and accurate methods that overcome limitations of existing predictions and facilitate precise EE estimation outside specialized laboratory conditions. Energy expenditure was measured by assessing oxygen uptake (VO₂) using a portable gas analyzer and predicted across three treadmill protocols: Bruce, Modified Bruce, and Progressive Speed. These protocols were selected to capture a wide range of exercise intensities and improve the accuracy of heart rate-based EE predictions. The six models combined heart rate, heart rate reserve (HRres), and demographic variables (sex, age, BMI, resting HR) using the Enter method of multiple regression, where all variables were included simultaneously to enhance the real-world applicability of the energy expenditure predictions. All models showed high accuracy with R² values between 0.80 and 0.89, and there were no significant differences between measured and predicted energy expenditure (p ≥ 0.05). HRres-based models outperformed others at submaximal intensities and remained consistent across sex, weight, BMI, and resting HR variations. By incorporating individual resting and maximal HR values, HRres models offer a personalized, physiologically relevant estimation method. These results support integrating HRres-based EE prediction into wearable devices to improve accessible and precise monitoring of physiological energy metabolism. Full article

(This article belongs to the Section Exercise and Health-Related Quality of Life)

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15 pages, 1227 KB

Open AccessReview

Rational Design of Self-Healing Hydrogel with High Mechanical Strength and Self-Healing Efficiency: A Short Review

by Xiaogang Yu, Jinxin Huang, Fang Yang and Jinbo Li

Gels 2025, 11(10), 807; https://doi.org/10.3390/gels11100807 (registering DOI) - 8 Oct 2025

Abstract

Self-healing hydrogels, a novel class of “smart” hydrogels, possess the ability to autonomously restore their network structure and mechanical properties following damage through the reconnection of a fractured three-dimensional network via reversible interactions. This characteristic enhances their safety and durability, exhibiting significant potential [...] Read more.

Self-healing hydrogels, a novel class of “smart” hydrogels, possess the ability to autonomously restore their network structure and mechanical properties following damage through the reconnection of a fractured three-dimensional network via reversible interactions. This characteristic enhances their safety and durability, exhibiting significant potential in biomedicine. The key determinants of self-healing hydrogels are their mechanical strength and healing efficiency. Ideally, these hydrogels exhibit both high mechanical strength and good healing efficiency. Nevertheless, an inverse relationship between the mechanical strength and self-healing efficiency of self-healing hydrogels typically exists. Thus, research is currently focused on the development of self-healing hydrogels that combine good biocompatibility, high mechanical strength, and good self-healing efficiency. This review focuses on the research progress that is being made regarding the mechanical properties and self-healing capabilities of self-healing hydrogels, where we aim to achieve a balance between self-healing performance and mechanical strength. We outline the evaluation methods for assessing self-healing performance, followed by providing a summary of recent advancements in the mechanical strength and self-healing efficiency of external-stimulus-triggered self-healing hydrogels and autonomous self-healing hydrogels. Finally, we address the challenges and prospects for the future development of self-healing hydrogels. Full article

(This article belongs to the Special Issue Biobased Gels for Drugs and Cells)

18 pages, 1722 KB

Open AccessArticle

Transformation of Phytoplankton Communities in the High Arctic: Ecological Properties of Species

by Larisa Pautova, Vladimir Silkin, Marina Kravchishina and Alexey Klyuvitkin

Diversity 2025, 17(10), 703; https://doi.org/10.3390/d17100703 (registering DOI) - 8 Oct 2025

Abstract

During the 84th cruise of the R/V Akademik Mstislav Keldysh in August 2021, patterns of phytoplankton composition transformation were revealed along a northward gradient. The study involved three transects in the Fram Strait and adjacent Arctic waters: a southern transect (from the Barents [...] Read more.

During the 84th cruise of the R/V Akademik Mstislav Keldysh in August 2021, patterns of phytoplankton composition transformation were revealed along a northward gradient. The study involved three transects in the Fram Strait and adjacent Arctic waters: a southern transect (from the Barents Sea shelf to the Greenland shelf), a middle transect across the Fram Strait, and a northern transect along the ice edge. Ten species of diatoms and eleven of dinoflagellates were identified, and their ecological preferences were characterized by determining the minimum, maximum, mean, and median values for abundance, biomass, depth of the biomass maximum, salinity, temperature, and the concentrations and ratios of nitrogen, phosphorus, and silicon. Significant gradients in temperature, salinity, silicon, and nitrogen concentrations were recorded along the south–north direction in the study area. The phytoplankton community responds to these changing factors through restructuring. Dinoflagellates predominantly dominate the southern and middle transects, whereas large diatoms make a substantial contribution to the phytoplankton biomass in the northern transect. Diatom biomass is determined by nitrogen concentration. The dependence of dinoflagellate biomass on that of small flagellates confirms the importance of mixotrophic nutrition. A hypothesis is proposed that the most probable criterion for the selective selection of diatoms northward is the half-saturation constant for nitrogen uptake, while for dinoflagellates, it is temperature. Full article

(This article belongs to the Section Marine Diversity)

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28 pages, 5254 KB

Open AccessArticle

IoT-Enabled Fog-Based Secure Aggregation in Smart Grids Supporting Data Analytics

by Hayat Mohammad Khan, Farhana Jabeen, Abid Khan, Muhammad Waqar and Ajung Kim

Sensors 2025, 25(19), 6240; https://doi.org/10.3390/s25196240 (registering DOI) - 8 Oct 2025

Abstract

The Internet of Things (IoT) has transformed multiple industries, providing significant potential for automation, efficiency, and enhanced decision-making. The incorporation of IoT and data analytics in smart grid represents a groundbreaking opportunity for the energy sector, delivering substantial advantages in efficiency, sustainability, and [...] Read more.

The Internet of Things (IoT) has transformed multiple industries, providing significant potential for automation, efficiency, and enhanced decision-making. The incorporation of IoT and data analytics in smart grid represents a groundbreaking opportunity for the energy sector, delivering substantial advantages in efficiency, sustainability, and customer empowerment. This integration enables smart grids to autonomously monitor energy flows and adjust to fluctuations in energy demand and supply in a flexible and real-time fashion. Statistical analytics, as a fundamental component of data analytics, provides the necessary tools and techniques to uncover patterns, trends, and insights within datasets. Nevertheless, it is crucial to address privacy and security issues to fully maximize the potential of data analytics in smart grids. This paper makes several significant contributions to the literature on secure, privacy-aware aggregation schemes in smart grids. First, we introduce a Fog-enabled Secure Data Analytics Operations (FESDAO) scheme which offers a distributed architecture incorporating robust security features such as secure aggregation, authentication, fault tolerance and resilience against insider threats. The scheme achieves privacy during data aggregation through a modified Boneh-Goh-Nissim cryptographic scheme along with other mechanisms. Second, FESDAO also supports statistical analytics on metering data at the cloud control center and fog node levels. FESDAO ensures reliable aggregation and accurate data analytical results, even in scenarios where smart meters fail to report data, thereby preserving both analytical operation computation accuracy and latency. We further provide comprehensive security analyses to demonstrate that the proposed approach effectively supports data privacy, source authentication, fault tolerance, and resilience against false data injection and replay attacks. Lastly, we offer thorough performance evaluations to illustrate the efficiency of the suggested scheme in comparison to current state-of-the-art schemes, considering encryption, computation, aggregation, decryption, and communication costs. Moreover, a detailed security analysis has been conducted to verify the scheme’s resistance against insider collusion attacks, replay attack, and false data injection (FDI) attack. Full article

(This article belongs to the Section Internet of Things)

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15 pages, 4472 KB

Open AccessArticle

Numerical Simulation and Microstructure Examination of a Low-Alloy Structural Steel for Laser Transformation Hardening Treatment

by Peiyu He, Liming Qian, Junnan Ren and Yun Wang

Photonics 2025, 12(10), 992; https://doi.org/10.3390/photonics12100992 (registering DOI) - 8 Oct 2025

Abstract

The surface treated by laser phase transformation hardening exhibits superior hardness, enhanced wear resistance, and refined grain structure. In this study, both single-track and two-track laser phase transformation hardening processes were numerically simulated, with the simulation accuracy being verified experimentally. Furthermore, the optimal [...] Read more.

The surface treated by laser phase transformation hardening exhibits superior hardness, enhanced wear resistance, and refined grain structure. In this study, both single-track and two-track laser phase transformation hardening processes were numerically simulated, with the simulation accuracy being verified experimentally. Furthermore, the optimal overlap rate for laser two-track overlay was predicted based on the simulation results. An S355J2G3 metal block specimen was used as a case, numerical simulations of the phase transformation coupled with the temperature field on the specimen’s surface under laser irradiation were carried out using SYSWELD2019 software. The surface temperature distribution and the evolution of phase volume fractions were analyzed. Additionally, the changes in the temperature field within the softening zone and the distribution of tempering structures resulting from two-track laser overlay were examined. The discrepancy between experimental and simulated results for the hardening layer width was approximately 10%, while the error rates for the hardening layer depth and the tempering softening zone were below 5% and 10%, respectively. Based on simulations conducted with varying overlap rates, the flatness metric produces the best results at 50% overlap under these laser processing parameters. Full article

(This article belongs to the Section Lasers, Light Sources and Sensors)

22 pages, 609 KB

Open AccessArticle

Risk Factors for Treatment Failure of Drug-Susceptible Pulmonary Tuberculosis in Lithuania over 22 Years

by Karolina Kėvelaitienė, Roma Puronaitė, Valerija Edita Davidavičienė, Birutė Nakčerienė and Edvardas Danila

Medicina 2025, 61(10), 1805; https://doi.org/10.3390/medicina61101805 (registering DOI) - 8 Oct 2025

Abstract

Background and Objectives: This study aimed to evaluate the treatment outcomes of adults with pulmonary drug-susceptible tuberculosis (DS-TB) in Lithuania over 22 years, and to examine associations between treatment outcomes, various risk factors, and temporal trends. Materials and Methods: A retrospective [...] Read more.

Background and Objectives: This study aimed to evaluate the treatment outcomes of adults with pulmonary drug-susceptible tuberculosis (DS-TB) in Lithuania over 22 years, and to examine associations between treatment outcomes, various risk factors, and temporal trends. Materials and Methods: A retrospective cohort analysis was conducted using data from the National Tuberculosis Information System from 2000 to 2021. A total of 18,697 adult patients with DS-TB were included. Patients were grouped into three time periods: Period I (2000–2007), Period II (2008–2015), and Period III (2016–2021). Treatment outcomes were categorized as successful (treatment completed with recovery) or unsuccessful (patients who encountered treatment failure, died during treatment, or converted to drug-resistant tuberculosis). Associations with individual risk factors, including smoking, alcohol use, comorbidities, and sociodemographic variables, were analyzed. Results: Treatment success rates improved steadily across the study periods: 82.3% in Period I, 84.4% in Period II, and 87.6% in Period III. Mortality rates declined over time but remained substantial: 17.1%, 15.2%, and 12.0% in Periods I, II, and III, respectively. Non-lethal treatment failures decreased slightly (0.6%, 0.4%, and 0.4%). Multivariate analysis identified significant associations between treatment failure and multiple risk factors, including low BMI, male gender, unemployment, homelessness, smoking, alcohol and substance use, and comorbid conditions such as cancer, cardiovascular disease, chronic lung disease, diabetes mellitus, HIV, and renal failure. Conclusions: Treatment outcomes for DS-TB in Lithuania have improved over the past two decades; however, certain modifiable risk factors—such as low BMI, homelessness, substance use, and comorbidities—remain strongly linked to treatment failure. To further improve outcomes, targeted interventions such as nutritional support, housing programs, and integrated addiction services should be prioritized for high-risk groups within national TB control efforts. Full article

(This article belongs to the Section Pulmonology)

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21 pages, 2048 KB

Open AccessArticle

Micro-Platform Verification for LiDAR SLAM-Based Navigation of Mecanum-Wheeled Robot in Warehouse Environment

by Yue Wang, Ying Yu Ye, Wei Zhong, Bo Lin Gao, Chong Zhang Mu and Ning Zhao

World Electr. Veh. J. 2025, 16(10), 571; https://doi.org/10.3390/wevj16100571 (registering DOI) - 8 Oct 2025

Abstract

Path navigation for mobile robots critically determines the operational efficiency of warehouse logistics systems. However, the current QR (Quick Response) code path navigation for warehouses suffers from low operational efficiency and poor dynamic adaptability in complex dynamic environments. This paper introduces a deep [...] Read more.

Path navigation for mobile robots critically determines the operational efficiency of warehouse logistics systems. However, the current QR (Quick Response) code path navigation for warehouses suffers from low operational efficiency and poor dynamic adaptability in complex dynamic environments. This paper introduces a deep reinforcement learning and hybrid-algorithm SLAM (Simultaneous Localization and Mapping) path navigation method for Mecanum-wheeled robots, validated with an emphasis on dynamic adaptability and real-time performance. Based on the Gazebo warehouse simulation environment, the TD3 (Twin Deep Deterministic Policy Gradient) path planning method was established for offline training. Then, the Astar-Time Elastic Band (TEB) hybrid path planning algorithm was used to conduct experimental verification in static and dynamic real-world scenarios. Finally, experiments show that the TD3-based path planning for mobile robots makes effective decisions during offline training in the simulation environment, while Astar-TEB accurately completes path planning and navigates around both static and dynamic obstacles in real-world scenarios. Therefore, this verifies the feasibility and effectiveness of the proposed SLAM path navigation for Mecanum-wheeled mobile robots on a miniature warehouse platform. Full article

(This article belongs to the Special Issue Research on Intelligent Vehicle Path Planning Algorithm)

26 pages, 5918 KB

Open AccessArticle

Autonomous Sewing Technology and System: A New Strategy by Integrating Soft Fingers and Machine Vision Technology

by Jinzhu Shen, Álvaro Ramírez-Gómez, Jianping Wang and Fan Zhang

Textiles 2025, 5(4), 45; https://doi.org/10.3390/textiles5040045 (registering DOI) - 8 Oct 2025

Abstract

The garment manufacturing industry, being labor-intensive, has long faced challenges in automating the sewing process due to the flexibility and deformability of fabrics. This study proposes a novel strategy for automated sewing by integrating soft fingers and machine vision technology. Firstly, leveraging the [...] Read more.

The garment manufacturing industry, being labor-intensive, has long faced challenges in automating the sewing process due to the flexibility and deformability of fabrics. This study proposes a novel strategy for automated sewing by integrating soft fingers and machine vision technology. Firstly, leveraging the flexibility and adjustability of soft fingers, combined with the motion characteristics of the sewing machine, a sewing model was established to achieve coordinated operation between the soft fingers and the sewing machine. Experimental results indicate that the fabric feeding speed and waiting time of the soft fingers are significantly correlated with the sewing speed and stitch density of the sewing machine, but not with the fabric properties. Secondly, machine vision technology was employed to inspect the quality of the sewn fabrics, achieving a classification accuracy of 97.84%. This study not only provides theoretical and technical support for the intelligent upgrading of the garment manufacturing industry but also lays the foundation for the automation of complex sewing processes such as quilting. Future research will further optimize the system’s performance and expand its applications in more complex sewing tasks. Full article

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26 pages, 2364 KB

Open AccessArticle

Dynamic Trajectory Planning for Automatic Grinding of Large-Curved Forgings Based on Adaptive Impedance Control Strategy

by Luping Luo, Kekang Qiu and Congchun Huang

Actuators 2025, 14(10), 487; https://doi.org/10.3390/act14100487 (registering DOI) - 8 Oct 2025

Abstract

In this paper, we proposed a novel method for grinding trajectory planning on large-curved forgings to improve grinding performance and grinding efficiency. Our method consists of four main steps. Firstly, we conducted simulations and analyses on the contact state and contact pressure between [...] Read more.

In this paper, we proposed a novel method for grinding trajectory planning on large-curved forgings to improve grinding performance and grinding efficiency. Our method consists of four main steps. Firstly, we conducted simulations and analyses on the contact state and contact pressure between the grinding tool and curved workpieces, and explored different grinding methods. Based on the Preston equation, a material removal model was established to analyze the grinding force. Secondly, we proposed an adaptive impedance control method based on grinding force analysis, which can control the contact force indirectly by adjusting the end position of the robot. To address the inability of impedance control to adjust impedance parameters in real time, a control strategy involving online estimation of environmental position and stiffness is adopted. Based on the Lyapunov asymptotic stability principle, an adaptive impedance control model is established, and the effectiveness of the adaptive algorithm is verified through simulation. Thirdly, Position correction is realized through gravity compensation of the grinding force and discretization of the impedance control model. Subsequently, a dynamic trajectory adjustment strategy is proposed, which integrates position correction for the current grinding point and position compensation for the next grinding point, to achieve the force control objective in the grinding process. Finally, a constant force grinding experiment was conducted on large-curvature blades using a robotic automatic grinding system. The grinding system effectively removed the knife marks on the blade surface, resulting in a surface roughness of 0.5146 µm and a grinding efficiency of approximately 0.89 cm²/s. The simulation and experimental results indicate that the smoothness and grinding efficiency of the blades are superior to the enterprise’s existing grinding technology, verifying the feasibility and effectiveness of our proposed method. Full article

(This article belongs to the Section Control Systems)

15 pages, 6511 KB

Open AccessArticle

Effect of B/N Doping on Enhanced Hydrogen Storage in Transition Metal-Modified Graphene: A First-Principles DFT Study

by Qian Nie, Lei Wang, Ye Chen and Zhengwei Nie

Materials 2025, 18(19), 4635; https://doi.org/10.3390/ma18194635 (registering DOI) - 8 Oct 2025

Abstract

Hydrogen energy is viewed as a promising green energy source because of its high energy density, abundant availability, and clean combustion results. Hydrogen storage is the critical link in a hydrogen economy. Using first-principles density functional theory calculations, this work explored the role [...] Read more.

Hydrogen energy is viewed as a promising green energy source because of its high energy density, abundant availability, and clean combustion results. Hydrogen storage is the critical link in a hydrogen economy. Using first-principles density functional theory calculations, this work explored the role of B and N in modulating the binding properties of transition metal-modified graphene. The hydrogen storage performance of Sc-, Ti-, and V-modified B-doped graphene was evaluated. Boron doping induces an electron-deficient state, enhancing interactions between transition metals and graphene. Sc, Ti, and V preferentially adsorbed at the carbon ring’s hollow site in B-doped graphene, with their binding energies being 1.87, 1.74, and 1.69 eV higher than those in pure graphene, respectively. These systems can stably adsorb up to 5, 4, and 4 H₂ molecules, with average adsorption energies of −0.528, −0.645, and −0.620 eV/H₂, respectively. The hydrogen adsorption mechanism was dominated by orbital interactions and polarization effects. Among the systems studied, Sc-modified B-doped graphene exhibited superior hydrogen storage characteristics, making it a promising candidate for reversible applications. Full article

(This article belongs to the Special Issue Advanced Nanomaterials for Gaseous Storage)

20 pages, 1059 KB

Open AccessArticle

Carob Pulp Flour as a Sustainable and Functional Ingredient in the Bakery: Effects of Leavening Typologies on Dough and Bread Properties

by Sebastiano Rosati, Ilenia Gaeta, Lucia Maiuro, Maria Carmela Trivisonno, Maria Cristina Messia and Elena Sorrentino

Life 2025, 15(10), 1571; https://doi.org/10.3390/life15101571 (registering DOI) - 8 Oct 2025

Abstract

Carob pulp flour (Ceratonia siliqua) is gaining attention as a sustainable ingredient with nutritional and functional potential. This study evaluated the partial replacement of soft wheat flour with 10% carob pulp flour in breadmaking, focusing on the role of different leavening [...] Read more.

Carob pulp flour (Ceratonia siliqua) is gaining attention as a sustainable ingredient with nutritional and functional potential. This study evaluated the partial replacement of soft wheat flour with 10% carob pulp flour in breadmaking, focusing on the role of different leavening strategies: commercial baker’s yeast (LB), a selected starter culture, Lactiplantibacillus plantarum SL31 and Saccharomyces cerevisiae SY17 (LI), and a type I sourdough (LS). Dough rheology, microbial dynamics, bread quality, acceptability, and shelf-life were assessed. Results showed that the inclusion of carob pulp flour enhances the nutritional profile while maintaining satisfactory technological performance. The leavening strategy strongly influenced the final products: breads made with commercial yeast displayed high volume and softness but were less stable during storage; LS breads achieved greater microbial stability but were limited by excessive acidity and reduced sensory acceptance; breads obtained with the selected starter culture offered the most balanced outcome, combining moderate structure with enhanced flavor and consumer preference. Overall, the findings demonstrate the feasibility of incorporating carob pulp flour into bakery products and highlight the potential of tailored starter cultures as a promising compromise between technological performance, sensory quality, and shelf-life. Future work should optimize fermentation approaches to further enhance consumer appeal and support industrial application. Full article

(This article belongs to the Section Life Sciences)

26 pages, 1369 KB

Open AccessArticle

Effects of Free and Conjugated Methionine on Growth, Meat Quality, Mineral Profile, and Shell Strength in Garden Snails (Cornu aspersum)

by Anna Rygało-Galewska, Klara Piotrowska, Magdalena Matusiewicz, Damian Bień, Monika Łukasiewicz-Mierzejewska, Zbigniew Skibko, Andrzej Borusiewicz and Tomasz Niemiec

Animals 2025, 15(19), 2922; https://doi.org/10.3390/ani15192922 (registering DOI) - 8 Oct 2025

Abstract

The present study examined the impact of adding methionine (Met) and its conjugated form (Met-Met) on Cornu aspersum snails. The primary focus was on the animals’ growth performance, the chemical composition of their carcass (whole body without the shell), the mineral profile, and [...] Read more.

The present study examined the impact of adding methionine (Met) and its conjugated form (Met-Met) on Cornu aspersum snails. The primary focus was on the animals’ growth performance, the chemical composition of their carcass (whole body without the shell), the mineral profile, and the mechanical properties of their shells. In two experiments conducted under controlled laboratory conditions, diets supplemented with varying levels of Met addition (0.3, 0.6, 1.4 g/kg feed) were used, and the effects of free methionine, Met-Met and their mixture (1.4 g/kg feed) were compared. The study incorporated measurements of body weight, shell width, and mortality of snails. Analyses encompassing protein, fat, sulphur amino acids, glutathione levels, oxidative stress indices (DPPH, TAC, TBARS), and macro- and micronutrient content of carcass and shells were conducted. The findings demonstrated that adding 1.4 g Met/kg feed significantly enhanced the shells’ weight gain (+56% vs. Control), shell weight (+56%) and crushing force (+135%). Furthermore, an increase in the Met content of the carcass was observed (+18%), along with elevated carcass Ca (+28%) and P (+30%) and higher shell Ca (+12%) and Zn (+87%), alongside reduced carcass Fe (−38%) and Cu (−19%). In Experiment II, the Met-Met group exhibited the highest carcass weight (+16% vs. Control), the greatest carcass-to-body weight ratio, and the highest proportion of mature individuals (+27%). Moreover, Met-Met supplementation improved Cu absorption and retention in the carcass (+19%). Also, the results suggest that the conjugated form of methionine may improve Cu absorption and storage in the carcass (+19%). The study’s findings indicate that methionine addition, especially in Met-Met form, can substantially impact the efficiency of C. aspersum farming, enhancing both the productivity outcomes and the quality of the product. That is particularly important in increasing the shell’s mechanical resistance and the carcass’s nutritional value. Full article

(This article belongs to the Section Animal Nutrition)

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31 pages, 15340 KB

Open AccessArticle

Integrative Description and Redescription of Black Fly (Diptera: Simuliidae) Species in the Simulium (Gomphostilbia) ceylonicum Species-Group from Thailand ^†

by Sorawat Thongsahuan, Kittipat Aupalee, Afham Yakoh, Domechai Kaewnoi, Wanchai Maleewong, Wichai Srisuka, Anchalee Wannasan, Atiporn Saeung and Hiroyuki Takaoka

Insects 2025, 16(10), 1034; https://doi.org/10.3390/insects16101034 (registering DOI) - 8 Oct 2025

Abstract

Utilizing the COI barcoding approach, cryptic diversity has previously been detected within the morphologically recognized Simulium (Gomphostilbia) trangense Jitklang, Kuvangkadilok, Baimai, Takaoka & Adler, 2008 and S. (G.) sheilae Takaoka & Davies, 1995, of the S. (G.) [...] Read more.

Utilizing the COI barcoding approach, cryptic diversity has previously been detected within the morphologically recognized Simulium (Gomphostilbia) trangense Jitklang, Kuvangkadilok, Baimai, Takaoka & Adler, 2008 and S. (G.) sheilae Takaoka & Davies, 1995, of the S. (G.) ceylonicum species-group. Here, an unknown black fly species belonging to the S. ceylonicum species-group from southern Thailand was discovered and described as a new species, S. (G.) sipoense sp. nov. In addition, S. (G.) trangense is herein fully redescribed based on specimens collected from its type locality. Based on an integrative taxonomic approach combining morphological and molecular data, the validity of the newly described S. sipoense sp. nov. and the redescribed S. trangense is confirmed. Comparative morphological characteristics and phylogenetic analysis, inferred from COI sequences, suggest that the new species is conspecific with the species redescribed as S. trangense, using specimens collected from Malaysia, and is morphologically and phylogenetically closely related to S. sheilae, particularly to the specimens from Indonesia. The redescribed S. trangense is genetically highly similar or even identical to the species that was apparently misidentified as S. sheilae from southern and western Thailand, and is morphologically very similar to the new species, from which it is clearly distinguished by the relative length of the female claw tooth, shape of the male ventral plate, and color of the larval body. A detailed information on the morphological characteristics separates the new species, and the redescribed S. trangense from all other known species of the same species-group in Thailand and neighboring countries is provided. Further studies are warranted to clarify the taxonomic status of several cryptic species recognized within the morphologically defined S. trangense and S. sheilae. Full article

(This article belongs to the Special Issue Diptera Diversity: Systematics, Phylogeny and Evolution)

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26 pages, 3383 KB

Open AccessArticle

Biomass Gasification for Waste-to-Energy Conversion: Artificial Intelligence for Generalizable Modeling and Multi-Objective Optimization of Syngas Production

by Gema Báez-Barrón, Francisco Javier Lopéz-Flores, Eusiel Rubio-Castro and José María Ponce-Ortega

Resources 2025, 14(10), 157; https://doi.org/10.3390/resources14100157 (registering DOI) - 8 Oct 2025

Abstract

Biomass gasification, a key waste-to-energy technology, is a complex thermochemical process with many input variables influencing the yield and quality of syngas. In this study, data-driven machine learning models are developed to capture the nonlinear relationships between feedstock properties, operating conditions, and syngas [...] Read more.

Biomass gasification, a key waste-to-energy technology, is a complex thermochemical process with many input variables influencing the yield and quality of syngas. In this study, data-driven machine learning models are developed to capture the nonlinear relationships between feedstock properties, operating conditions, and syngas composition, in order to optimize process performance. Random Forest (RF), CatBoost (Categorical Boosting), and an Artificial Neural Network (ANN) were trained to predict key syngas outputs (syngas composition and syngas yield) from process inputs. The best-performing model (ANN) was then integrated into a multi-objective optimization framework using the open-source Optimization & Machine Learning Toolkit (OMLT) in Pyomo. An optimization problem was formulated with two objectives—maximizing the hydrogen-to-carbon monoxide (H₂/CO) ratio and maximizing the syngas yield simultaneously, subject to operational constraints. The trade-off between these competing objectives was resolved by generating a Pareto frontier, which identifies optimal operating points for different priority weightings of syngas quality vs. quantity. To interpret the ML models and validate domain knowledge, SHapley Additive exPlanations (SHAP) were applied, revealing that parameters such as equivalence ratio, steam-to-biomass ratio, feedstock lower heating value, and fixed carbon content significantly influence syngas outputs. Our results highlight a clear trade-off between maximizing hydrogen content and total gas yield and pinpoint optimal conditions for balancing this trade-off. This integrated approach, combining advanced ML predictions, explainability, and rigorous multi-objective optimization, is novel for biomass gasification and provides actionable insights to improve syngas production efficiency, demonstrating the value of data-driven optimization in sustainable waste-to-energy conversion processes. Full article

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19 pages, 5136 KB

Open AccessArticle

An Accessible AI-Assisted Rehabilitation System for Guided Upper Limb Therapy

by Kevin Hou, Md Mahafuzur Rahaman Khan and Mohammad H. Rahman

Sensors 2025, 25(19), 6239; https://doi.org/10.3390/s25196239 (registering DOI) - 8 Oct 2025

Abstract

Conventional upper limb rehabilitation methods often encounter significant obstacles, including high costs, limited accessibility, and reduced patient adherence. Emerging technological solutions, such as telerehabilitation, virtual reality (VR), and wearable sensor-based systems, address some of these challenges but still face issues concerning supervision quality, [...] Read more.

Conventional upper limb rehabilitation methods often encounter significant obstacles, including high costs, limited accessibility, and reduced patient adherence. Emerging technological solutions, such as telerehabilitation, virtual reality (VR), and wearable sensor-based systems, address some of these challenges but still face issues concerning supervision quality, affordability, and usability. To overcome these limitations, this study presents an innovative and cost-effective rehabilitation system based on advanced computer vision techniques and artificial intelligence (AI). Developed using Python (3.11.5), the proposed system utilizes a standard webcam in conjunction with robust pose estimation algorithms to provide real-time analysis of patient movements during guided upper limb exercises. Instructional exercise videos featuring an NAO robot facilitate patient engagement and consistency in practice. The system generates instant quantitative feedback on movement precision, repetition accuracy, and exercise phase completion. The core advantages of the proposed approach include minimal equipment requirements, affordability, ease of setup, and enhanced interactive guidance compared to traditional telerehabilitation methods. By reducing the complexity and expense associated with many VR and wearable-sensor solutions, while acknowledging that some lower-cost and haptic-enabled VR options exist, this single-webcam approach aims to broaden access to guided home rehabilitation without specialized hardware. Full article

(This article belongs to the Section Biomedical Sensors)

18 pages, 3062 KB

Open AccessArticle

AMT Microjets Data Overall Evaluation Ratio at Different Operating Regimes

by Răzvan Marius Catană and Grigore Cican

Processes 2025, 13(10), 3200; https://doi.org/10.3390/pr13103200 (registering DOI) - 8 Oct 2025

Abstract

The paper presents a comprehensive evaluation of certain main parameters and the performance of microjet series models from the same engine manufacturer, AMT Netherlands, under various operating regimes. The study was performed through a percentage-based analysis of a series of actual values extracted [...] Read more.

The paper presents a comprehensive evaluation of certain main parameters and the performance of microjet series models from the same engine manufacturer, AMT Netherlands, under various operating regimes. The study was performed through a percentage-based analysis of a series of actual values extracted from a set of charts, from which a specific database was created. The database comprised data sourced from official specification sheets issued by the manufacturer. The studied engines shared the same technical turbomachinery design, comprising a single shaft, one centrifugal compressor rotor, one axial turbine rotor stage, and a convergent jet nozzle, but differed in thrust class, ranging from 167 to 1569 N. Parameter and performance ratios were calculated to analyze the variation patterns within each engine and across different engines. The study refers to the variation analysis of thrust, fuel flow, exhaust gas temperature, and specific fuel consumption relative to engine speed, from idle to maximum regime. It presents the actual percentage values alongside polynomial functions that characterize the variations in engine parameters through which the analysis can be conducted. Full article

(This article belongs to the Special Issue Fluid Dynamics and Thermodynamic Studies in Gas Turbine)

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17 pages, 3210 KB

Open AccessArticle

Comparison of Long-Term Oral Bacterial Flora Before and After Orthognathic Surgery in Surgical Orthodontic Treatment

by Rumi Matsumoto, Masahiro Takahashi, Kazuyoshi Hosomichi, Satoko Okuwaki, So Koizumi, Yu Hikita, Reina Hatanaka and Tetsutaro Yamaguchi

Dent. J. 2025, 13(10), 458; https://doi.org/10.3390/dj13100458 (registering DOI) - 8 Oct 2025

Abstract

Background/Objectives: Multi-bracket appliances are essential in surgical orthodontic treatment, and perioperative oral management during orthognathic surgery is critical. Thorough plaque control, appropriate use of antibiotics, and shortening of operative time have been reported to be effective in preventing postoperative infections and ensuring surgical [...] Read more.

Background/Objectives: Multi-bracket appliances are essential in surgical orthodontic treatment, and perioperative oral management during orthognathic surgery is critical. Thorough plaque control, appropriate use of antibiotics, and shortening of operative time have been reported to be effective in preventing postoperative infections and ensuring surgical success. As highly invasive orthognathic surgery involving osteotomy may influence the postoperative oral microbiota, this study aimed to investigate the characteristics of and clarify the changes occurring in the salivary oral microbiota after orthognathic surgery. Methods: The study included 14 patients (Group S; mean age 29.3 ± 9.8 years) who underwent surgical orthodontic treatment and 15 control patients (Group C; mean age 27.1 ± 8.7 years) who received orthodontic treatment alone. Salivary samples were analyzed via 16S rRNA gene sequencing, and the relative abundances of bacteria were evaluated using the Linear Discriminant Analysis Effect Size. Results: The prevalence of Neisseria, which is associated with early biofilm formation, decreased over time in both groups. In contrast, Streptococcus exhibited an increase in prevalence. In Group S, members of Pseudomonas, the family Saccharimonadaceae, and the order Rhizobiales showed increases at 5–8 months post-surgery. Conclusions: Surgical orthodontic treatment may influence the oral microbiota and promote colonization by opportunistic pathogens. Instructions regarding oral hygiene and appropriately timed professional cleaning interventions are critical in preventing such colonization. Longitudinal monitoring of the microbiota using metagenomic analysis may be useful for future perioperative management and guidance of oral hygiene. Full article

(This article belongs to the Special Issue Oral Microbiology and Related Research)

29 pages, 2358 KB

Open AccessReview

Research Progress on the Preparation and Properties of Graphene–Copper Composites

by Wenjie Liu, Xingyu Zhao, Hongliang Li and Yi Ding

Metals 2025, 15(10), 1117; https://doi.org/10.3390/met15101117 (registering DOI) - 8 Oct 2025

Abstract

The persistent conflict between strength and electrical conductivity in copper-based materials presents a fundamental limitation for next-generation high-performance applications. Graphene, with its unique two-dimensional architecture and exceptional intrinsic characteristics, has become a promising reinforcement phase for copper matrices. This comprehensive review synthesizes recent [...] Read more.

The persistent conflict between strength and electrical conductivity in copper-based materials presents a fundamental limitation for next-generation high-performance applications. Graphene, with its unique two-dimensional architecture and exceptional intrinsic characteristics, has become a promising reinforcement phase for copper matrices. This comprehensive review synthesizes recent advancements in graphene–copper composites (CGCs), focusing particularly on structural design innovations and scalable manufacturing approaches such as powder metallurgy, molecular-level mixing, electrochemical deposition, and chemical vapor deposition. The analysis examines pathways for optimizing key properties—including mechanical strength, thermal conduction, and electrical performance—while investigating the fundamental reinforcement mechanisms and charge/heat transport phenomena. Special consideration is given to how graphene morphology, concentration, structural quality, interfacial chemistry, and processing conditions collectively determine composite behavior. Significant emphasis is placed on interface engineering strategies, graphene alignment, consolidation control, and defect management to minimize electron and phonon scattering while improving stress transfer efficiency. The review concludes by proposing research directions to resolve the strength–conductivity paradox and broaden practical implementation domains, thereby offering both methodological frameworks and theoretical foundations to support the industrial adoption of high-performance CGCs. Full article

(This article belongs to the Special Issue Study on the Preparation and Properties of Metal Functional Materials)

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14 pages, 1659 KB

Open AccessArticle

Gastrointestinal Survivability of a BSH-Positive Lacticaseibacillus rhamnosus VB4 Strain and Its Effect on Bile Acid Deconjugation in a Dynamic In Vitro Gut Model

by Amanda Vaccalluzzo, Gianluigi Agolino, Alessandra Pino, Marianna Cristofolini, Davide Tagliazucchi, Alice Cattivelli, Cinzia Caggia, Lisa Solieri and Cinzia Lucia Randazzo

Nutrients 2025, 17(19), 3179; https://doi.org/10.3390/nu17193179 (registering DOI) - 8 Oct 2025

Abstract

Background: Bile salt hydrolase (BSH) is a key probiotic trait, as it facilitates both host metabolism and bacterial survival into the gastrointestinal tract (GIT), through bile acid (BA) deconjugation, keeping intestinal homeostasis. Objectives: The present study aims to investigate the viability [...] Read more.

Background: Bile salt hydrolase (BSH) is a key probiotic trait, as it facilitates both host metabolism and bacterial survival into the gastrointestinal tract (GIT), through bile acid (BA) deconjugation, keeping intestinal homeostasis. Objectives: The present study aims to investigate the viability of the Lacticaseibacillus rhamnosus VB4 strain and its effects on bile acid deconjugation during the gastrointestinal tract (GIT) passage, under a fed condition, using the in vitro SHIME^® (Simulator of the Human Intestinal Microbial Ecosystem) model. Methods: Gastric, small intestinal and colonic fractions were monitored and a fecal slurry from a healthy donor was inoculated into the colonic compartment to establish the intestinal microbiota. Samples were collected at the end of stomach, duodenum, jejunum, ileum phases, and colon after 0, 16 and 24 h. Strain survival was assessed by culturing method, and bsh gene expression was revealed by quantitative PCR (qPCR). In addition, UHPLC/HR-MS was performed to reveal the hypothetical changes in BAs profile after strain administration. Results: Good survivability of the VB4 strain in the upper GIT was revealed. Furthermore, VB4-inculated sample showed sustained expression of bsh in both the stomach/small intestine and colon fractions at all sampling times. Analysis of the BAs profile shown that the VB4 strain reduced the levels of the main conjugated BAs in the small intestine under fed condition and improved the deconjugation efficiency during colonic transit compared with the control. Conclusions: These findings highlight the survivability of L. rhamnosus VB4 strain inside the gut and its potential as biotherapeutic BAs-mediator candidate, demonstrating that transcriptomic and metabolomic approaches coupled to a dynamic in vitro gut model represent a robust tool for selection of a BSH-positive probiotic candidate. Full article

(This article belongs to the Topic News and Updates on Probiotics)

13 pages, 814 KB

Open AccessArticle

In Vitro Evaluation of Antimicrobial Effects of Endodontic Irrigants Containing Disodium Edetate and Chlorhexidine Gluconate, Octenidine Dihydrochloride, and Benzalkonium Bromide Against Intracanal Enterococcus faecalis

by Anna Siemińska, Katarzyna Kot, Ewa Marek, Agnieszka Chamarczuk, Magdalena Kaczała, Joanna Rasławska-Socha, Laurentia Schuster, Till Dammaschke, Liliana Szyszka-Sommerfeld and Mariusz Lipski

J. Clin. Med. 2025, 14(19), 7100; https://doi.org/10.3390/jcm14197100 (registering DOI) - 8 Oct 2025

Abstract

Background/Objectives: The objective of this in vitro study was to compare and evaluate the in vitro antimicrobial effectiveness of Endosal, Octenisolv, and Endoxal against intracanal Enterococcus faecalis. Methods: The study sample consisted of 84 extracted single-rooted human teeth, which were [...] Read more.

Background/Objectives: The objective of this in vitro study was to compare and evaluate the in vitro antimicrobial effectiveness of Endosal, Octenisolv, and Endoxal against intracanal Enterococcus faecalis. Methods: The study sample consisted of 84 extracted single-rooted human teeth, which were divided into seven groups (12 roots in each group): Group 1—Endoxal, Group 2—Octenisolv, Group 3—Endosal, Group 4—15% ethylenediaminetetraacetic acid (EDTA), Group 5—2% sodium hypochlorite (NaOCl), Group 6—0.9% sterile saline solution (NaCl), and one positive control group where no irrigant was used. The roots were sterilized within an autoclave for 30 min at 121 °C and then contaminated with E. faecalis bacteria, after instrumentation and removing the smear layer from canals. The root canals were irrigated using a side-vented needle, and then ISO size 40 H-file was used to obtain fine dentine chips. Aliquots taken from the canals were plated on blood agar broth and the plates were incubated for 36 h. Results: In this study, significant differences were observed between the antimicrobial activity of Endoxal, Octenisolv, Endosal, 2% NaOCl, and sterile saline solution. Conclusions: The compound irrigants Endosal, Endoxal, and a novel irrigant containing disodium edetate and octenidine, which were evaluated in this study, exhibited relatively good antimicrobial properties against Enterococcus faecalis. The use of Endosal, Octenisolv or Endoxal appears promising, yet their clinical efficacy remains to be confirmed through further studies. Full article

(This article belongs to the Special Issue Current Advances in Endodontics and Dental Traumatology)

15 pages, 453 KB

Open AccessArticle

Adaptive Observer Design with Fixed-Time Convergence, Online Disturbance Learning, and Low-Conservatism Linear Matrix Inequalities for Time-Varying Perturbed Systems

by Essia Ben Alaia, Slim Dhahri and Omar Naifar

Math. Comput. Appl. 2025, 30(5), 112; https://doi.org/10.3390/mca30050112 (registering DOI) - 8 Oct 2025

Abstract

This paper proposes a finite-time adaptive observer with online disturbance learning for time-varying disturbed systems. By integrating parameter-dependent Lyapunov functions and slack matrix techniques, the method eliminates conservative static disturbance bounds required in prior work while guaranteeing fixed-time convergence. The proposed approach features [...] Read more.

This paper proposes a finite-time adaptive observer with online disturbance learning for time-varying disturbed systems. By integrating parameter-dependent Lyapunov functions and slack matrix techniques, the method eliminates conservative static disturbance bounds required in prior work while guaranteeing fixed-time convergence. The proposed approach features a non-diagonal gain structure that provides superior noise rejection capabilities, demonstrating 41% better performance under measurement noise compared to conventional methods. A power systems case study demonstrates significantly improved performance, including 62% faster convergence and 63% lower steady-state error. These results are validated through LMI-based synthesis and adaptive disturbance estimation. Implementation analysis confirms the method’s feasibility for real-time systems with practical computational requirements. Full article

(This article belongs to the Special Issue Applied Optimization in Automatic Control and Systems Engineering)

16 pages, 7024 KB

Open AccessArticle

Preexisting Genetic Background Primes the Responses of Human Neurons to Amyloid β

by Adedamola Saidi Soladogun and Li Zhang

Int. J. Mol. Sci. 2025, 26(19), 9804; https://doi.org/10.3390/ijms26199804 (registering DOI) - 8 Oct 2025

Abstract

The deposition of amyloid beta (Aβ) in the human brain is a hallmark of Alzheimer’s disease (AD). Aβ has been shown to exert a wide range of effects on neurons in cell and animal models. Here, we take advantage of differentiated neurons from [...] Read more.

The deposition of amyloid beta (Aβ) in the human brain is a hallmark of Alzheimer’s disease (AD). Aβ has been shown to exert a wide range of effects on neurons in cell and animal models. Here, we take advantage of differentiated neurons from iPSC-derived neural stem cells of human donors to examine its effects on human neurons. Specifically, we employed two types of neurons from genetically distinct donors: one male carrying APO E2/E2 (M E2/E2) and one female carrying APO E3/E3 (F E3/E3). Genome-wide RNA-sequencing analysis identified 64 and 44 genes that were induced by Aβ in M E2/E2 and F E3/E3 neurons, respectively. GO and pathway analyses showed that Aβ-induced genes in F E3/E3 neurons do not constitute any statistically significant pathways whereas Aβ-induced genes in M E2/E2 neurons constitute a complex network of activated pathways. These pathways include those promoting inflammatory responses, such as IL1β, IL4, and TNF, and those promoting cell migration and movement, such as chemotaxis, migration of cells, and cell movement. These results strongly suggest that the effects of Aβ on neurons are highly dependent on their genetic background and that Aβ can promote strong responses in inflammation and cell migration in some, but not all, neurons. Full article

(This article belongs to the Special Issue New Trends in Alzheimer’s Disease Research: From Molecular Mechanisms to Therapeutics: 3rd Edition)

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38 pages, 1176 KB

Open AccessReview

Gepirone for Major Depressive Disorder: From Pharmacokinetics to Clinical Evidence: A Narrative Review

by Natalia Gałka, Emilia Tomaka, Julia Tomaszewska, Patrycja Pańczyszyn-Trzewik and Magdalena Sowa-Kućma

Int. J. Mol. Sci. 2025, 26(19), 9805; https://doi.org/10.3390/ijms26199805 (registering DOI) - 8 Oct 2025

Abstract

Gepirone, a selective 5-hydroxytryptamine (serotonin) 1A (5-HT_1A) receptor agonist, offers a promising strategy for treating mood and anxiety disorders. The therapeutic importance of 5-HT_1A modulation is well established, as these receptors regulate serotonergic neurotransmission both presynaptically, in the somatodendritic regions [...] Read more.

Gepirone, a selective 5-hydroxytryptamine (serotonin) 1A (5-HT_1A) receptor agonist, offers a promising strategy for treating mood and anxiety disorders. The therapeutic importance of 5-HT_1A modulation is well established, as these receptors regulate serotonergic neurotransmission both presynaptically, in the somatodendritic regions of raphe neurons, and postsynaptically, in structures including the hippocampus, neocortex, septum, amygdala, and hypothalamus. Gepirone exhibits a distinctive pharmacological profile, acting as a full agonist at presynaptic autoreceptors and a partial agonist at postsynaptic receptors, with high affinity for 5-HT_1A and much lower affinity for 5-HT_2A receptors. Its effects on serotonergic signaling are time-dependent. Acute administration suppresses serotonergic firing through autoreceptor activation, while chronic treatment induces autoreceptor desensitization, leading to enhanced 5-HT release in projection areas. This process is complemented by partial agonism at postsynaptic 5-HT_1A receptors, which further supports long-term neuromodulation. This article provides an integrated overview of gepirone’s mechanism of action, bridging receptor pharmacology, neurophysiological adaptations, and therapeutic implications. Particular emphasis is placed on the compound’s unique dual role in regulating serotonergic tone over time, a feature that differentiates it from other 5-HT_1A-targeting agents. By linking molecular mechanisms to clinical outcomes, we highlight gepirone’s potential advantages in efficacy, safety, and tolerability compared with conventional antidepressants. This comprehensive perspective underscores gepirone as a paradigmatic example of selective 5-HT_1A modulation and offers novel insights into the development of targeted treatments for depression and anxiety. Full article

(This article belongs to the Special Issue Molecular Research on Depression—2nd Edition)

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