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13 pages, 2180 KB

Open AccessReview

Atrioventricular Junction Ablation with High-Definition Recording of Atrioventricular Node Potential

by Andrea Matteucci, Enrico Maggio, Domenico Dardani, Maurizio Russo, Marco Galeazzi, Federico Nardi, Silvio Fedele, Claudio Pandozi and Furio Colivicchi

J. Cardiovasc. Dev. Dis. 2025, 12(12), 479; https://doi.org/10.3390/jcdd12120479 (registering DOI) - 4 Dec 2025

Abstract

Atrioventricular (AV) node ablation represents an established therapeutic option in the management of atrial fibrillation (AF) and other atrial tachyarrhythmias, particularly in patients with symptomatic tachycardia who remain unresponsive or intolerant to pharmacological therapy. The procedure is often considered in cases of refractory [...] Read more.

Atrioventricular (AV) node ablation represents an established therapeutic option in the management of atrial fibrillation (AF) and other atrial tachyarrhythmias, particularly in patients with symptomatic tachycardia who remain unresponsive or intolerant to pharmacological therapy. The procedure is often considered in cases of refractory arrhythmias, antiarrhythmic drugs intolerance, or tachycardiomyopathy, and plays a key role in optimizing outcomes in patients undergoing cardiac resynchronization therapy, where achieving adequate biventricular pacing is otherwise compromised by rapid ventricular responses. Traditionally, AV node ablation is performed using radiofrequency energy delivered at the region of the His bundle, guided by the earliest His potential recordings. However, the anatomical complexity of the AV node and Koch’s triangle poses important challenges, including the risk of incomplete ablation, persistence of conduction, lack of reliable junctional escape rhythms, and increased risk of proarrhythmia. Recent advances in high-resolution mapping and electroanatomical guidance have enabled a more precise anatomical approach, selectively targeting the compact AV node while reducing collateral injury. These developments offer the potential for improved procedural safety, long-term efficacy, and a more standardized strategy for patient management. This review summarizes current evidence, techniques, and clinical implications of AV node ablation, highlighting its role in the evolving landscape of arrhythmia treatment. Full article

(This article belongs to the Special Issue Updates on Atrio-Ventricular Node Anatomy and Physiology and on AVNRTs Circuit)

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16 pages, 2075 KB

Open AccessArticle

Comparative Transcriptomics Reveals the Molecular Basis for Inducer-Dependent Efficiency in Gastrodin Propionylation by Aspergillus oryzae Whole-Cell Biocatalyst

by Desheng Wu, Maohua Ma, Xiaohan Liu, Xiaofeng Li and Guanglei Zhao

Biomolecules 2025, 15(12), 1695; https://doi.org/10.3390/biom15121695 (registering DOI) - 4 Dec 2025

Abstract

Propionylated derivatives of gastrodin are valuable due to their enhanced lipophilicity and bioavailability. This study investigated the molecular basis for the differential catalytic efficiency of Aspergillus oryzae whole cells in gastrodin propionylation. A high conversion rate of 96.84% was achieved with soybean oil [...] Read more.

Propionylated derivatives of gastrodin are valuable due to their enhanced lipophilicity and bioavailability. This study investigated the molecular basis for the differential catalytic efficiency of Aspergillus oryzae whole cells in gastrodin propionylation. A high conversion rate of 96.84% was achieved with soybean oil induction, compared to only 8.23% under glucose induction. Comparative transcriptomic analysis identified 20,342 differentially expressed genes (DEGs), which were significantly enriched in lipid metabolism and signal transduction pathways. From 26 upregulated lipase-related DEGs, a candidate triacylglycerol lipase gene (CL24.Contig40_All) was prioritized. Homology modeling and molecular docking supported its potential role by demonstrating that the encoded enzyme possesses a typical α/β hydrolase fold with a catalytic triad and favorable binding with both gastrodin and vinyl propionate. These findings indicate that soybean oil may enhance lipase expression by activating lipid metabolic and phosphatidylinositol signaling pathways, providing crucial transcriptional-level insights and genetic targets for the rational design of efficient whole-cell biocatalysts. Full article

(This article belongs to the Special Issue Industrial Microorganisms and Enzyme Technologies)

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23 pages, 2621 KB

Open AccessArticle

Water Resource Allocation Considering the Effects of Emergency Supply Augmentation Costs and Water Use Compression Losses Under Extreme Drought Conditions

by Chentao He, Xi Guo and Zening Wu

Hydrology 2025, 12(12), 319; https://doi.org/10.3390/hydrology12120319 (registering DOI) - 4 Dec 2025

Abstract

Extreme drought intensifies the complexity of the water resource allocation system, and unreasonable water distribution exacerbates drought losses. Drought mitigation measures such as emergency water supply augmentation and water use compression incur additional costs or losses, thereby compromising the accuracy of water allocation [...] Read more.

Extreme drought intensifies the complexity of the water resource allocation system, and unreasonable water distribution exacerbates drought losses. Drought mitigation measures such as emergency water supply augmentation and water use compression incur additional costs or losses, thereby compromising the accuracy of water allocation outcomes. To address the insufficient consideration of the impacts of emergency water supply augmentation and water use compression measures under extreme drought conditions in current research, this study employs emergy theory to systematically identify and quantify the emergency water supply augmentation costs and water use compression losses. A dual-objective water resource allocation model was constructed under extreme drought conditions by taking the minimization of the sum of the emergency water supply augmentation costs and water use compression losses as the comprehensive loss objective, and the minimization of the total water scarcity as the water use guarantee objective. The model was subsequently transformed into a single-objective optimization problem for solution. The allocation model was applied to the typical severe drought scenario in Chuxiong Prefecture of Yunnan Province in 2011. The results demonstrate that the scheme implementing both measures reduced comprehensive losses by 4.97 × 10¹⁹ sej and total water shortage by 7.02 × 10⁶ m³ compared to the scheme excluding these measures. The water resource allocation model considering emergency water supply augmentation costs and water use compression losses can effectively mitigate the drought impact in the study area. Full article

(This article belongs to the Special Issue Sustainable Water Management in the Face of Drastic Climate Change)

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18 pages, 665 KB

Open AccessReview

The Hidden Face of Danon Disease: Unique Challenges for Female Patients

by Laura Torlai Triglia, Federico Barocelli, Enrico Ambrosini, Alberto Bettella, Filippo Luca Gurgoglione, Michele Bianconcini, Angela Guidorossi, Francesca Russo, Antonio Percesepe and Giampaolo Niccoli

Cardiogenetics 2025, 15(4), 32; https://doi.org/10.3390/cardiogenetics15040032 (registering DOI) - 4 Dec 2025

Abstract

Danon Disease (DD) is a rare X-linked autophagic vacuolar myopathy caused by pathogenic variants in the lysosome-associated membrane protein 2 (LAMP-2) gene. Alternative splicing of the terminal exon 9 leads to the creation of three different isoforms, each with essential roles in regulating [...] Read more.

Danon Disease (DD) is a rare X-linked autophagic vacuolar myopathy caused by pathogenic variants in the lysosome-associated membrane protein 2 (LAMP-2) gene. Alternative splicing of the terminal exon 9 leads to the creation of three different isoforms, each with essential roles in regulating autophagy. DD is characterized by cardiomyopathy, skeletal myopathy, cognitive impairment, and retinal disorders, with cardiac involvement being the primary cause of morbidity and mortality. Muscle biopsy may reveal signs of vacuolar myopathy, but the diagnosis is typically confirmed through sequencing and deletion/duplication analysis of the LAMP-2 gene using peripheral blood. Although few genotype–phenotype correlations have been described, with most being limited to isoform 2B of exon 9, the most significant prognostic indicator remains sex. The disease manifests earlier and with a more severe systemic presentation in males due to their hemizygous status, whereas in females, the typical presentation is late-onset hypertrophic or dilated cardiomyopathy, generally without extracardiac involvement. Cases of severely affected women have been described, potentially due to non-random or defective X-inactivation. The less typical and delayed clinical presentation in females can result in incorrect or missed diagnoses. The aim of this narrative review is to summarize the natural history, diagnostic criteria, management strategies, and recent advancements in the understanding of DD in women. Full article

(This article belongs to the Section Rare Disease-Genetic Syndromes)

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39 pages, 2450 KB

Open AccessArticle

Design and Implementation of an Integrated Framework for Smart City Land Administration and Heritage Protection

by Dan Alexandru Mitrea, Constantin Viorel Marian, Mihaela Iacob, Andrei Vasilateanu, Umit Cali and Cristian Alexandru Cazan

Heritage 2025, 8(12), 510; https://doi.org/10.3390/heritage8120510 (registering DOI) - 4 Dec 2025

Abstract

Smart cities rely on digital infrastructures and utilize data-driven frameworks to enhance quality of life, optimizing public services by promoting transparency in urban and heritage management. Based on the ArchTerr project for archeological heritage protection, this study introduces an integrated framework uniting two [...] Read more.

Smart cities rely on digital infrastructures and utilize data-driven frameworks to enhance quality of life, optimizing public services by promoting transparency in urban and heritage management. Based on the ArchTerr project for archeological heritage protection, this study introduces an integrated framework uniting two components: GIS-based land mapping and blockchain-enabled document management. The system supports urban planning, land administration, and governance by combining spatial intelligence with secure data handling. The GIS module enables precise land mapping using geographic coordinates, facilitating spatial analysis, land use monitoring, and infrastructure planning. The document management system employs blockchain storage functionalities to ensure the immutability, transparency, and traceability of records such as land ownership documents, permits, and regulatory filings. Developed using the Design Science Research methodology, the framework translates abstract principles of data immutability and interoperability into a functional architecture that addresses persistent issues of fragmented datasets, insecure records, and limited institutional accountability and improves scalability, efficiency, and transparency in a variety of urban situations. We explored its implications for policy and governance, illustrating how interdisciplinary technology serves as a basis for transparent, accountable, and resilient urban management. This study advances theoretical understanding of how the convergence of spatial and trust-based technologies can foster geo-trusted governance and contribute to more transparent and resilient heritage management. Full article

21 pages, 29027 KB

Open AccessArticle

Research on Deep Learning-Based Identification Methods for Geological Interface Types and Their Application in Mineral Exploration Prediction—A Case Study of the Gouli Region in Qinghai, China

by Yawen Zong, Linfu Xue, Jianbang Wang, Peng Wang and Xiangjin Ran

Minerals 2025, 15(12), 1281; https://doi.org/10.3390/min15121281 (registering DOI) - 4 Dec 2025

Abstract

Geological interfaces are crucial elements governing deposit formation, such as silica–calcium surfaces, intrusive contact interfaces, and unconformities can serve as key symbols for mineral exploration prediction. Geological maps provide relatively detailed representations of primary geological interfaces and their interrelationships. However, in previous mineral [...] Read more.

Geological interfaces are crucial elements governing deposit formation, such as silica–calcium surfaces, intrusive contact interfaces, and unconformities can serve as key symbols for mineral exploration prediction. Geological maps provide relatively detailed representations of primary geological interfaces and their interrelationships. However, in previous mineral resource predictions, the type differences in different geological interfaces were ignored, and the types of different geological interfaces vary greatly, thus affecting the validity of the mineral prediction results. Manual interpretation and analysis of geological interfaces involve substantial workloads and make it difficult to effectively apply the rich geological information depicted on geological maps to mineral exploration prediction processes. Therefore, this study proposes a model for intelligent identification of geological interface types based on deep learning. The model extracts the attribute information, such as the age and lithology of the geological bodies on both sides of the geological boundary arc, based on the digital geological map of the Gouli gold mining area in Dulan County, Qinghai Province, China. The learning dataset comprising 5900 sets of geological interface types was constructed through manual annotation of geological interfaces. The arc segment is taken as the basic element; the model adopts natural language processing technology to conduct word vector embedding processing on the text attribute information of geological bodies on both sides of the geological interface. The processed embedding vectors are fed into the convolutional neural network (CNN) for training to generate the geological interface type recognition model. This method can effectively identify the type of geological interface, and the identification accuracy can reach 96.52%. Through quantitative analysis of the spatial relationship between different types of geological interfaces and ore points, it is known that they have a good correlation in spatial distribution. Experimental results show that the proposed method can effectively improve the accuracy and efficiency of geological interface recognition, and the accuracy of mineral prediction can be improved to some extent by adding geological interface type information in the process of mineral prediction. Full article

(This article belongs to the Section Mineral Exploration Methods and Applications)

24 pages, 5466 KB

Open AccessArticle

Magnesium Dross and Ground Granulated Blast Furnace Slag Utilisation for Phosphate Elimination from Water

by Reham Alwash, Manolia Andredaki, Iacopo Carnacina, Monower Sadique and Joseph Amoako-Attah

Appl. Sci. 2025, 15(23), 12844; https://doi.org/10.3390/app152312844 (registering DOI) - 4 Dec 2025

Abstract

It is well known that elevated phosphate concentrations in water bodies trigger the eutrophication process, posing adverse environmental, health, and economic consequences that necessitate effective removal solutions. Phosphate removal has therefore been widely studied using various methods, including chemical precipitation, membrane filtration, and [...] Read more.

It is well known that elevated phosphate concentrations in water bodies trigger the eutrophication process, posing adverse environmental, health, and economic consequences that necessitate effective removal solutions. Phosphate removal has therefore been widely studied using various methods, including chemical precipitation, membrane filtration, and crystallisation. However, most of these methods are often expensive or inefficient for low phosphate concentrations. Therefore, in this study, an eco-friendly, sustainable and biodegradable adsorbent was manufactured by extracting calcium ions from an industrial by-product, ground granulated blast furnace slag (GGBS) and magnesium ions from magnesium dross (MgD), then immobilising them on sodium alginate to form Ca-Mg-SA beads. The new adsorbent was applied to remove phosphate from water under different flow patterns (batch and continuous flow), initial pH levels, contact times, agitation speeds and adsorbent doses. Additionally, the degradation time of the new adsorbent, recycling potential, its morphology, formation of functional groups and chemical composition were investigated. The results obtained from batch experiments demonstrated that the new adsorbent achieved 90.2% phosphate removal efficiency from a 10 mg/L initial concentration, with a maximum adsorption capacity of 1.75 mg P/g at an initial pH of 7, a contact time of 120 min, an agitation speed of 200 rpm and an adsorbent dose of 1.25 g/50 mL. The column experiments demonstrated a 0.82 mg P/g removal capacity under the same optimal conditions as the batch experiments. The findings also showed that the adsorption process fitted well to the Freundlich and Langmuir isotherm models and followed a pseudo-second-order kinetic model. Characterisation of Ca-Mg-SA beads using EDX, SEM and FTIR confirmed successful ion immobilisation and phosphate adsorption. Furthermore, the beads fully biodegraded in soil within 75 days and demonstrated potential recycling as a fertiliser. Full article

(This article belongs to the Special Issue New Technologies for Water Quality: Treatment and Monitoring)

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18 pages, 2017 KB

Open AccessArticle

Magnetic Field Amplification and Reconstruction in Rotating Astrophysical Plasmas: Verifying the Roles of α and β in Dynamo Action

by Kiwan Park

Particles 2025, 8(4), 98; https://doi.org/10.3390/particles8040098 (registering DOI) - 4 Dec 2025

Abstract

We investigate the

α

and

β

effects in a rotating spherical plasma system relevant to astrophysical contexts. In particular, we focus on how kinetic and magnetic (current) helicities influence the magnetic diffusivity

β

. These coefficients were modeled using three complementary theoretical approaches. [...] Read more.

We investigate the

α

and

β

effects in a rotating spherical plasma system relevant to astrophysical contexts. In particular, we focus on how kinetic and magnetic (current) helicities influence the magnetic diffusivity

β

. These coefficients were modeled using three complementary theoretical approaches. Direct numerical simulation (DNS) data (large-scale magnetic field

\bar{B}

, turbulent velocity

u

, and turbulent magnetic field

b

) were then used to obtain the actual values of

α_{EM - HM}

,

β_{EM - HM}

,

β_{vv - vw}

, and

β_{bb + jb}

. Using these coefficients, we reconstructed

\bar{B}

and compared it with the DNS results. In the kinematic regime, where

\bar{B}

remains weak, all models agree well with DNS. In the nonlinear regime, however, the field reconstructed with

β_{vv - vw}

alone deviates from DNS and grows without bound. Incorporating the turbulent magnetic diffusion term

β_{bb + jb}

suppresses this unphysical growth and restores consistency. Specifically,

{\bar{B}}_{D N S}

saturates at approximately 0.23 in the nonlinear regime. The reconstructed

\bar{B}

using

β_{E M - H M}

saturates at

\bar{B}

∼0.3. When

β_{v v - v w + b b + j b}

(= β_{v v - v w} + β_{b b + j b})

is used,

\bar{B}

varies from about 0.3 to 0.23. These results indicate that kinetic helicity reduces

β

(or provides a negative contribution), thereby amplifying

\bar{B}

, whereas turbulent current helicity, together with turbulent magnetic and kinetic energies, enhances

β

, thus suppressing

\bar{B}

in the nonlinear regime. In this respect, the new form of

β

differs from the conventional one, which acts solely to diffuse the magnetic field. Full article

(This article belongs to the Special Issue Particles and Plasmas in Strong Fields)

17 pages, 593 KB

Open AccessArticle

Defining and Predicting HIV Immunological Non-Response: A Multi-Definition Analysis from an Indonesian Cohort

by Brian Eka Rachman, Yehuda Tri Nugroho Supranoto, Soraya Isfandiary Iskandar, Tri Pudy Asmarawati, Siti Qamariyah Khairunisa, Muhammad Vitanata Arfijanto, Usman Hadi, Muhammad Miftahussurur, Nasronudin Nasronudin, Masanori Kameoka, Retno Pudji Rahayu and Afif Nurul Hidayati

Viruses 2025, 17(12), 1581; https://doi.org/10.3390/v17121581 (registering DOI) - 4 Dec 2025

Abstract

Immunological non-response (INR) to antiretroviral therapy (ART) is a critical concern for PLHIV, characterized by inadequate CD4⁺ T-cell recovery despite virological suppression. This retrospective study analyzed medical records of virologically suppressed adult PLHIV on ART (2004–2024) at two hospitals in Surabaya, Indonesia, [...] Read more.

Immunological non-response (INR) to antiretroviral therapy (ART) is a critical concern for PLHIV, characterized by inadequate CD4⁺ T-cell recovery despite virological suppression. This retrospective study analyzed medical records of virologically suppressed adult PLHIV on ART (2004–2024) at two hospitals in Surabaya, Indonesia, using four operational categories to identify clinical and demographic determinants of INR. Patients were classified as immunological responders (IRs) or non-responders (INRs) based on four definitions: INR1 (CD4⁺ gain < 100 cells/mm³), INR2 (CD4⁺ < 350 cells/mm³), INR3 (meeting of either criterion), and INR4 (meeting of both criteria). Of 464 patients, 382 were analyzed. Baseline CD4⁺ < 200 cells/mm³ strongly predicted INR2 (aOR = 5.60, 95% CI: 2.95–10.62) and INR3 (aOR = 4.46, 95% CI: 2.39–8.29), while anal sexual transmission was protective against INR2 (aOR = 0.42, 95% CI: 0.19–0.92) and INR3 (aOR = 0.41, 95% CI: 0.19–0.89). By month 12, IR groups had over 350 CD4⁺ cells/mm³, with faster recovery slopes in months 0–6 (IR: >20 vs. INR: <10 cells/mm³/month). INR1 and INR4 had flat or negative slopes at 12–24 months, while IR groups had positive slopes. Baseline CD4⁺ was the strongest INR predictor, suggesting the value of early ART and individualized care for Indonesian PLHIV. Full article

(This article belongs to the Special Issue Cascade of Care for HIV, Hepatitis and Sexually Transmitted Infections)

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28 pages, 3763 KB

Open AccessArticle

Diagnosing Multistage Fracture Treatments of Horizontal Tight Oil Wells with Distributed Acoustic Sensing

by Hanbin Zhu, Wenqiang Liu, Zhengguang Zhao, Bobo Li, Jizhou Tang and Lei Li

Processes 2025, 13(12), 3925; https://doi.org/10.3390/pr13123925 (registering DOI) - 4 Dec 2025

Abstract

Distributed acoustic sensing (DAS) technology is gaining popularity for real-time monitoring during the hydraulic fracturing of unconventional reservoirs. By transforming a standard optical fiber into a dense array of acoustic sensors, DAS provides continuous spatiotemporal measurements along the entire wellbore. Although accurate DAS-based [...] Read more.

Distributed acoustic sensing (DAS) technology is gaining popularity for real-time monitoring during the hydraulic fracturing of unconventional reservoirs. By transforming a standard optical fiber into a dense array of acoustic sensors, DAS provides continuous spatiotemporal measurements along the entire wellbore. Although accurate DAS-based real-time diagnosis of multistage hydraulic fracturing is critical for optimizing the efficiency of stimulation operations and mitigating operational risks in horizontal tight oil wells, existing methods often fail to provide integrated qualitative and quantitative insights. To address this gap, we present an original diagnostic workflow that synergistically combines frequency band energy (FBE), low-frequency DAS (LF-DAS), and surface injection data for simultaneous fluid/proppant allocation and key downhole anomaly identification. Field application of the proposed framework in a 47-stage well demonstrates that FBE (50–200 Hz) enables robust cluster-level volume estimation, while LF-DAS (<0.5 Hz) reveals fiber strain signatures indicative of mechanical integrity threats. The workflow can successfully diagnose sand screenout, diversion, out-of-zone flow, and early fiber failure—events often missed by conventional monitoring. By linking distinct acoustic fingerprints to specific physical processes, our approach transforms raw DAS data into actionable operational intelligence. This study provides a reproducible, field-validated framework that enhances understanding in the context of fracture treatment, supports real-time decision making, and paves the way for automated DAS interpretation in complex completions. Full article

(This article belongs to the Special Issue Hydraulic Fracturing Process, Simulation and Modeling in Petroleum Engineering)

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18 pages, 1537 KB

Open AccessArticle

Adaptive Visual Servo Control for GIS Partial Discharge Detection Robots: A Model Predictive Control Approach

by Yongchao Luo, Zifan Zhang and Yingxi Xie

Energies 2025, 18(23), 6365; https://doi.org/10.3390/en18236365 (registering DOI) - 4 Dec 2025

Abstract

Gas-insulated switchgear (GIS) serves as the core equipment in substations. Its partial discharge detection requires ultrasonic sensors to be precisely aligned with millimeter-level measurement points. However, existing technologies face three major bottlenecks: the lack of surface texture on GIS makes visual feature extraction [...] Read more.

Gas-insulated switchgear (GIS) serves as the core equipment in substations. Its partial discharge detection requires ultrasonic sensors to be precisely aligned with millimeter-level measurement points. However, existing technologies face three major bottlenecks: the lack of surface texture on GIS makes visual feature extraction difficult; strong electromagnetic interference in substations causes image noise and loss of feature point tracking; and fixed gain control easily leads to end-effector jitter, reducing positioning accuracy. To address these challenges, this paper first employs AprilTag visual markers to define GIS measurement point features, establishing an image-based visual servo model that integrates GIS surface curvature constraints. Second, it proposes an adaptive gain algorithm based on model predictive control, dynamically adjusting gain in real-time according to visual error, electromagnetic interference intensity, and contact force feedback, balancing convergence speed and motion stability. Finally, experiments conducted on a GIS inspection platform built using a Franka Panda robotic arm demonstrate that the proposed algorithm reduces positioning errors, increases positioning speed, and improves positioning accuracy compared to fixed-gain algorithms, providing technical support for the engineering application of GIS partial discharge detection robots. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Electrical Power Systems)

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18 pages, 12425 KB

Open AccessArticle

Preparation of Ni-Based Composite Coatings on the Inner Surfaces of Tubes via Cylindrical Electro-Spark Powder Deposition

by Hang Zhao, Gaowei Yu, Xinwen Guo, Fei Luo, Fengbo Zhu and Yaohu Lei

Coatings 2025, 15(12), 1426; https://doi.org/10.3390/coatings15121426 (registering DOI) - 4 Dec 2025

Abstract

To address the challenge of fabricating metal-based composite coatings on the inner surfaces of tubular and internal hole components, a novel cylindrical electro-spark powder deposition (CEPD) technique is introduced. Utilizing the CEPD process, Ni-based composite coatings are successfully prepared on the inner surface [...] Read more.

To address the challenge of fabricating metal-based composite coatings on the inner surfaces of tubular and internal hole components, a novel cylindrical electro-spark powder deposition (CEPD) technique is introduced. Utilizing the CEPD process, Ni-based composite coatings are successfully prepared on the inner surface of 316L stainless-steel tubes. The resultant Ni-based composite coatings completely covered the inner surface, exhibiting a splattered morphology and forming a robust metallurgical bond. Microstructural analysis revealed that the composite coatings primarily consisted of submicron-sized fine dendrites, with the main phases identified as Ni, FeNi₃, and Fe₃Ni₂, in addition to Ag particles. These fine grains and reinforcing phases contributed to a substantial increase in coating hardness, with an average value of 673.33 HV, representing approximately 2.82 times the hardness of the substrate. Tribological testing indicated that the high-hardness Ni-based composite coatings nearly doubled the surface wear resistance of the substrate and exhibited a significantly lower friction coefficient. Compared to other existing inner surface coating techniques, the CEPD process offers simplicity, low cost, and the ability to produce functional composite coatings with complex compositions. The prepared coatings exhibit considerable development potential and may offer a novel approach for the advancement of coating techniques for non-line-of-sight surfaces. Full article

(This article belongs to the Section Surface Characterization, Deposition and Modification)

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20 pages, 1330 KB

Open AccessArticle

Development of a Test Rig for Detecting Fatigue Cracks in a Plastic Component of a Medical Device via Acoustic Signal Acquisitions

by Luigi Leopardi, Valerio Mangeruga, Matteo Giacopini, Marco Di Settimi and Roberto Rosi

Machines 2025, 13(12), 1118; https://doi.org/10.3390/machines13121118 (registering DOI) - 4 Dec 2025

Abstract

This work presents the design and implementation of a mechanical test bench developed for the comparative evaluation of three configurations of a mechanical biomedical device: the reference version and two optimized alternatives aimed at improving long-term reliability and functional performance. The test bench [...] Read more.

This work presents the design and implementation of a mechanical test bench developed for the comparative evaluation of three configurations of a mechanical biomedical device: the reference version and two optimized alternatives aimed at improving long-term reliability and functional performance. The test bench performs mechanical fatigue testing under controlled and repeatable conditions, simulating the cyclic loads typical of real-world operation. A key innovation of this system is the integration of a non-invasive acoustic acquisition module, which continuously monitors the dynamic behavior of the device during testing. The analysis of acoustic signals allows for the early detection of wear, looseness, deformation, and the onset of structural defects, providing valuable insight into the device’s mechanical health without altering its configuration. This study also details the engineering design of the control system, emphasizing both hardware integration and software architecture supporting real-time signal processing. Experimental results demonstrate that acoustic analysis represents an effective non-destructive approach for evaluating the endurance and reliability of compact plastic biomedical devices. The proposed methodology contributes to more accurate service life estimation, supports product validation, and promotes continuous improvements in the safety and quality of mechanical systems used in biomedical applications. Full article

(This article belongs to the Special Issue Design and Experimental Activity of Testing Machines and Mechanical Test Rigs)

20 pages, 1413 KB

Open AccessArticle

Therapeutic Potential of Gynostemma pentaphyllum (Thunb.) Makino Against COVID-19 Identified Through Network Pharmacology

by Min Ho Kim, Jin Ah Won, Jun Sang Yu, Su Min Kim, Dong Keun Lee, Xiang-Lan Piao and Hye Hyun Yoo

Pharmaceuticals 2025, 18(12), 1851; https://doi.org/10.3390/ph18121851 (registering DOI) - 4 Dec 2025

Abstract

Background/Objectives: The ongoing challenges posed by COVID-19 have highlighted the need for multi-target therapeutic strategies addressing both acute immune responses and systemic complications. Gynostemma pentaphyllum (Thunb.) Makino, a traditional herbal medicine rich in flavonoids and saponins, exhibits diverse pharmacological activities, including immunomodulatory and [...] Read more.

Background/Objectives: The ongoing challenges posed by COVID-19 have highlighted the need for multi-target therapeutic strategies addressing both acute immune responses and systemic complications. Gynostemma pentaphyllum (Thunb.) Makino, a traditional herbal medicine rich in flavonoids and saponins, exhibits diverse pharmacological activities, including immunomodulatory and cardiovascular effects. In this study, we investigated the potential of G. pentaphyllum as a complementary treatment for COVID-19 using a network pharmacology approach combined with molecular docking analysis. Methods: To delve into the therapeutic mechanisms of G. pentaphyllum, we identified 59 active compounds and predicted 408 protein targets, of which 19 overlapped with COVID-19-associated genes, including IL1B, IL6, TNF, ACE, and REN. GO and KEGG enrichment analyses were conducted to determine relevant biological processes and pathways, focusing on cytokine signaling, inflammatory responses, and the renin–angiotensin system. Network analyses evaluated interactions of flavonoids and triterpenoid saponins with immunological, inflammatory, renin–angiotensin system, and host entry pathways. Molecular docking was performed to validate the binding affinities of key compounds to their predicted targets. Results: The compound–target–pathway network revealed class-specific patterns: flavonoids primarily mapped to immuno-inflammatory nodes, whereas triterpenoid saponins were enriched for renin–angiotensin system/host-entry–related targets. Docking energies spanned −6.1 to −11.9 kcal/mol, with six compound–target pairs ≤ −10.0 kcal/mol. Notably, NOS2–rutin (−11.9 kcal/mol), NOS2–gypenoside LI (−11.6 kcal/mol), and ACE–gypenoside LI (−11.3 kcal/mol) showed the strongest affinities. Conclusions: These findings provide evidence that G. pentaphyllum exerts therapeutic effects through the complementary actions of flavonoid and saponin components, each modulating distinct molecular pathways. This dual mechanistic potential underscores the value of G. pentaphyllum as a versatile therapeutic for COVID-19 therapy. Full article

(This article belongs to the Special Issue Network Pharmacology of Natural Products, 2nd Edition)

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11 pages, 1058 KB

Open AccessArticle

Challenges in Young Siberian Forest Height Estimation from Winter TerraSAR-X/TanDEM-X PolInSAR Observations

by Tumen Chimitdorzhiev, Irina Kirbizhekova and Aleksey Dmitriev

Forests 2025, 16(12), 1815; https://doi.org/10.3390/f16121815 (registering DOI) - 4 Dec 2025

Abstract

Accurate estimation of young forest height is essential for assessing the carbon sequestration potential of vast Siberian boreal forests recovering from wildfires. Satellite radar interferometry, particularly PolInSAR, is a promising tool for this task. However, its application in winter conditions and over sparse [...] Read more.

Accurate estimation of young forest height is essential for assessing the carbon sequestration potential of vast Siberian boreal forests recovering from wildfires. Satellite radar interferometry, particularly PolInSAR, is a promising tool for this task. However, its application in winter conditions and over sparse young forests remains underexplored. This study proposes a novel method for estimating the height of sparse young pine (Pinus sylvestris) stands using fully polarimetric bistatic TerraSAR-X/TanDEM-X data acquired in winter. The method is based on an analysis of the multimodal distribution of the unwrapped interferometric phase of the surface scattering component, which was isolated via PolInSAR decomposition. We hypothesize that the phase centers correspond to the snow-covered ground (located between tree groups) and the rough surface formed by the upper layer of branches and needles (of the tree groups). The results demonstrate that the difference between the dominant modes of the surface scattering phase distribution correlates with the height of young trees. However, the measurable height difference is limited by the interferometric height of ambiguity. Furthermore, a temporal analysis of the phase and meteorological data revealed a strong correlation between sudden phase shifts and daytime temperature rises around 0 °C. This is interpreted as the formation of a layered snowpack structure with a dense ice crust. This study confirms the potential of X-band PolInSAR for monitoring the structure of young Siberian forests in winter but also highlights a significant limitation: the critical impact of snowpack metamorphism, particularly melt-freeze cycles, on the interferometric phase. The proposed method is only applicable to certain forest regeneration stages where tree height does not exceed the ambiguity limit and snow conditions are stable. Full article

(This article belongs to the Special Issue Post-Fire Recovery and Monitoring of Forest Ecosystems)

46 pages, 13429 KB

Open AccessArticle

Artificial Intelligence-Based Anomaly Detection Technology for Equipment Condition Monitoring in Smart Farms

by Hyeon-O Choe and Meong-Hun Lee

Appl. Sci. 2025, 15(23), 12843; https://doi.org/10.3390/app152312843 (registering DOI) - 4 Dec 2025

Abstract

In Korea, agricultural policy increasingly promotes high-efficiency digital agriculture; however, insufficient sensor reliability and data accuracy continue to limit the practical adoption of smart farm technologies. To address these limitations, this study aims to develop and field-validate an AI-based Prognostics and Health Management [...] Read more.

In Korea, agricultural policy increasingly promotes high-efficiency digital agriculture; however, insufficient sensor reliability and data accuracy continue to limit the practical adoption of smart farm technologies. To address these limitations, this study aims to develop and field-validate an AI-based Prognostics and Health Management (PHM) framework for anomaly detection and remaining useful life (RUL) estimation of sensors and actuators in commercial smart farms. To collect smart farm data, we developed a switch voltage and current data acquisition system and selected problematic switches and environmental sensors in operating greenhouses as PHM targets. Using PHM techniques, we implemented mathematical and artificial intelligence (AI)-based anomaly detection and failure prediction algorithms. In experiments, sensor behavior was predicted with mathematical and AI models, achieving over 90% predictive accuracy compared with observations. Based on these predictions, thresholds were estimated and the remaining useful life (RUL) of sensors was predicted up to 80 h in advance. For switches, vibration, noise, and voltage data were collected to detect anomalies. Actuator anomaly detection employed thresholds derived from statistical indicators and machine learning; a hybrid approach combining interquartile range, Z-score, and Isolation Forest leveraged the strengths of both paradigms to provide robust and adaptive detection. Deviation features were then combined with environmental factors to construct an RUL model, and the remaining life of devices in operation was estimated using a k-nearest neighbors approach. In field validation, the lifetime of four switches was predicted, yielding a mean RUL of 1655 d. Finally, we implemented a web-based platform that enables farms to monitor and manage equipment health. Compared with prior studies, the key novelty of this work lies in integrating sensor-and-actuator PHM, providing real-field validation in operating greenhouses, and delivering an operational web platform that supports practical smart farm maintenance. By integrating these methods, the study aims to improve system efficiency, reduce energy consumption, and extend the operating life of smart farm components. We anticipate substantial benefits as the proposed approach is applied to smart farm equipment, enabling more reliable data acquisition and stable maintenance in practice. Full article

(This article belongs to the Special Issue AI-Based Machinery Health Monitoring)

32 pages, 1563 KB

Open AccessReview

Low pH, High Stakes: A Narrative Review Exploring the Acid-Sensing GPR65 Pathway as a Novel Approach in Renal Cell Carcinoma

by Michael Grant, Barbara Cipriani, Alastair Corbin, David Miller, Alan Naylor, Stuart Hughes, Tom McCarthy, Sumeet Ambarkhane, Danish Memon, Michael Millward, Sumanta Pal and Ignacio Melero

Cancers 2025, 17(23), 3883; https://doi.org/10.3390/cancers17233883 (registering DOI) - 4 Dec 2025

Abstract

Renal cell carcinoma (RCC) is a biologically heterogeneous malignancy accounting for 3% of adult cancers globally. Despite advances in immune checkpoint inhibitors (ICIs) and vascular endothelial growth factor (VEGF)-targeted therapies, durable disease control remains elusive for many patients. Increasing evidence implicates the acidic [...] Read more.

Renal cell carcinoma (RCC) is a biologically heterogeneous malignancy accounting for 3% of adult cancers globally. Despite advances in immune checkpoint inhibitors (ICIs) and vascular endothelial growth factor (VEGF)-targeted therapies, durable disease control remains elusive for many patients. Increasing evidence implicates the acidic tumour microenvironment (TME) as a critical mediator of RCC progression, immune evasion, and therapeutic resistance. Solid tumours, including RCC, exhibit reversed pH gradients, characterised by acidic extracellular (pH 6.2–6.9) and alkaline intracellular conditions. This dysregulation arises from enhanced glycolysis, hypoxia-driven lactate accumulation, and the overexpression of pH-regulating enzymes such as carbonic anhydrase (CA9). Acidic TMEs impair cytotoxic T-cell and NK-cell activity, promote tumour-associated macrophage (TAM) polarisation towards an immunosuppressive phenotype, and upregulate alternative immune checkpoints. These mechanisms collectively undermine ICI efficacy and contribute to primary and secondary treatment resistance. Proton-sensing G-protein-coupled receptors (GPCRs), notably GPR65, have emerged as pivotal mediators linking extracellular acidosis to immune dysfunction. Preclinical studies demonstrate that GPR65 antagonists restore anti-tumour immune activity by reversing acidosis-driven immunosuppression and enhancing antigen processing. In RCC models, selective GPR65 inhibitors have shown the ability to reduce immunosuppressive cytokine IL-10 production, induce immunoproteasome activation, and synergise with anti-PD-1 therapy. The first-in-class GPR65 inhibitor, PTT-4256, is now under evaluation in the Phase I/II RAISIC-1 trial (NCT06634849) in solid tumours, including RCC. Targeting acid-sensing pathways represents a novel and promising therapeutic strategy in RCC, aiming to remodel the TME and overcome ICI resistance. Integrating GPR65 inhibition with existing immunotherapies may define the next era of RCC management, warranting continued translational and clinical investigation. Full article

(This article belongs to the Special Issue Understanding the Molecular Basis and Immunobiology of Renal Cell Carcinoma and Exploring Novel Therapeutic Strategies)

10 pages, 244 KB

Open AccessArticle

Trends in Anthropometric and Cardiometabolic Risk Factor Changes Among Health Professionals: A 3-Year Follow-Up Study in Taiwan

by Yi-Ru Chen, Nain-Feng Chu, Der-Min Wu and Wen-Chuan Shen

Obesities 2025, 5(4), 89; https://doi.org/10.3390/obesities5040089 (registering DOI) - 4 Dec 2025

Abstract

Objectives: The purpose of this study is to evaluate the trend of anthropometric and cardiometabolic risk (CMRs) changes among health professionals over a three-year period at a medical center in Taiwan. Study Design: A 3-year follow-up cohort study design. Methods: This cohort study [...] Read more.

Objectives: The purpose of this study is to evaluate the trend of anthropometric and cardiometabolic risk (CMRs) changes among health professionals over a three-year period at a medical center in Taiwan. Study Design: A 3-year follow-up cohort study design. Methods: This cohort study was conducted from 2019 to 2022 in a single healthcare center. The participants underwent annual physical check-ups for three consecutive years. CMRs were measured using standard methods and weight status change was measured using BMI. We used McNemar test and Wilcoxon Sign Rank test to evaluate the differences within and between subgroups. We used logistic regression to examine the risk of increased CMRs among subgroups of different weight status changes. Results: A total of 2217 participants (1641 females and 576 males) were included in this study, with a mean age of 40.2 ± 10.2 years. During this period, 72 (4.4%) female participants’ weight status changed from normal weight to overweight or obese and 530 (32.3%) remained overweight or obese. Among males, the proportion was 6.8% and 61.1%, respectively (p < 0.01). Participants who remained overweight or obese have more adverse CMRs. Compared to remained normal weight male subjects, the mean systolic blood pressure (131.0 ± 18.1 mmHg) and fasting blood glucose (94.4 ± 13.5 mg/dL) were higher in remained overweight or obese subjects (p < 0.001). Among females, those who remained overweight or obese have 4.01 (95% CI 2.92–5.51) times higher risk for abnormal diastolic blood pressure and 2.98 (95% CI 2.05–4.32) times higher risk for abnormal blood glucose compared to those with remained normal weight. Conclusions: Participants who remained overweight or became obese had more adverse CMRs such as high blood pressure, hyperglycemia, and dyslipidemia during the 3-year follow-up period. Full article

21 pages, 4146 KB

Open AccessArticle

Network Pharmacology Analysis and Experimental Study of Yinchen Against Neuroinflammation in Ischemic Stroke

by Minmin Guo, Yijie Ma, Linlin Wang, Ruipeng Ge, You Wang, Gefei Ma, Guanhua Du and Li Li

Pharmaceuticals 2025, 18(12), 1852; https://doi.org/10.3390/ph18121852 (registering DOI) - 4 Dec 2025

Abstract

Objective: Ischemic stroke (IS) is an acute neurologic injury in which inflammatory responses play a key role. Yinchen, a common medicinal plant used in Traditional Chinese Medicine (TCM), has been proven to possess strong anti-inflammatory effects. However, its efficacy in treating IS remains [...] Read more.

Objective: Ischemic stroke (IS) is an acute neurologic injury in which inflammatory responses play a key role. Yinchen, a common medicinal plant used in Traditional Chinese Medicine (TCM), has been proven to possess strong anti-inflammatory effects. However, its efficacy in treating IS remains unclear. In this study, we aimed to investigate the therapeutic potential of Yinchen for IS and the material basis of this potential. Methods: The main active components in Artemisia scoparia extract (ASE, the extract of Yinchen), were identified by HPLC and MS. The targets of Yinchen and IS were obtained from public databases. Network pharmacology, molecular docking, and experimental investigation were further applied to acquire the core constituents in Yinchen that work against the neuroinflammation that occurs during IS. The neurological outcomes were evaluated in a transient Middle Cerebral Artery Occlusion (tMCAO) rat model. Additionally, the changes in the inflammatory responses in both the ischemic brain and in lipopolysaccharide (LPS)-treated microglial cells were examined using real-time qPCR. Results: Four active compounds of ASE, including isochlorogenic acid C (ICGA-C), isochlorogenic acid B (ICGA-B), isochlorogenic acid A (ICGA-A), and chlorogenic acid (CGA), were identified by HPLC and MS. Network pharmacology predicted that 103 compounds of Yinchen had 198 intersection targets with IS. The top five of these targets were TNF, STAT3, IL1B, AKT1, and SRC. Molecular docking results demonstrated that the abovementioned four compounds detected in ASE showed good interaction with all of the above five core targets. Moreover, both the four compounds and ASE were observed to attenuate NO release and suppress the release of various inflammatory factors (TNF-α, IL-1β, IL-6, and MCP-1) in a dose-dependent manner in LPS-induced BV2 microglial cells. ASE was further found to exert neuroprotective effects against ischemia–reperfusion (I/R) injury and inhibit the production of inflammatory factors in tMCAO rats. Conclusions: Yinchen exerts an anti-neuroinflammatory effect on IS and constituents, with high scores in its ability to bind to five core targets, thus contributing to this effect. This supports its potential as an anti-inflammatory agent for the treatment of IS. Full article

(This article belongs to the Special Issue Network Pharmacology of Natural Products, 2nd Edition)

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12 pages, 4335 KB

Open AccessArticle

ZnS Nanomaterials with Hexagon and Pentagon Structures: Effect of Surfactants on Surface Morphology and Biosensing Application

by Antony Ananth, Ihn Han, Eun Ha Choi and Jin-Hyo Boo

Chemosensors 2025, 13(12), 419; https://doi.org/10.3390/chemosensors13120419 (registering DOI) - 4 Dec 2025

Abstract

Zinc sulfide nanomaterials (ZnS NMs) are widely used in many important technological applications, and the performance efficiency is determined by the nanostructure, size, and shape. This indicates that achieving a desirable surface architecture is pivotal for any application. One of the efficient and [...] Read more.

Zinc sulfide nanomaterials (ZnS NMs) are widely used in many important technological applications, and the performance efficiency is determined by the nanostructure, size, and shape. This indicates that achieving a desirable surface architecture is pivotal for any application. One of the efficient and cost-effective techniques, the hydrothermal method, offers uniform size, specific shape, and bulk synthesis capability. This research deals with the preparation of ZnS NMs exhibiting unique surface structures such as spherical, nano-pentagon, and nano-hexagon shapes through employing different zinc precursors and surfactants. The obtained material’s crystal structure was classified as cubic sphalerite and exhibited high purity, as analyzed by XRD, SEM-EDX, TEM, and XPS. Furthermore, the synthesized ZnS NMs were tested for their shape-dependent biosensing application, such as specific antibacterial tests against routine human pathogens such as E. coli, K. pneumoniae, and S. aureus. Several antibacterial methods, such as bacterial colony plate count, growth inhibition analysis, and minimum inhibition concentration (MIC) measurements were carried out. The results confirmed that the antibacterial action in the method employed was dependent on three factors: the NM shape, concentration, and type/nature of bacteria. Especially, the prepared ZnS NMs exhibited excellent antibacterial sensing characteristics, as observed from the lower MIC values in the range of 15.6~250 µg/mL. Full article

(This article belongs to the Special Issue Nanomaterials in Chemosensors and Biosensors: Development and Application (2nd Edition))

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13 pages, 3264 KB

Open AccessArticle

CFD-Based Evaluation of Stirred Tank Designs for High-Viscosity Copolymer Aramid Dope Mixing

by Dong-Hyun Yeo, Hyun-Sung Yoon, Seong-Hun Yu and Jee-Hyun Sim

Polymers 2025, 17(23), 3233; https://doi.org/10.3390/polym17233233 (registering DOI) - 4 Dec 2025

Abstract

High-viscosity aramid copolymer solutions are widely used in fiber manufacturing and advanced composite applications, but their elevated viscosity poses significant challenges for mixing and agitation processes. This study employs computational fluid dynamics (CFD) simulations to enhance the mixing performance of such systems. Flow [...] Read more.

High-viscosity aramid copolymer solutions are widely used in fiber manufacturing and advanced composite applications, but their elevated viscosity poses significant challenges for mixing and agitation processes. This study employs computational fluid dynamics (CFD) simulations to enhance the mixing performance of such systems. Flow behavior around the impeller was analyzed within a cylindrical stirred tank while varying the number of baffles (0, 2, 4, and 6) and comparing two different impeller designs (A and B). Simulation results showed that installing a sufficient number of baffles—particularly four—effectively suppressed swirling flows commonly observed in high-viscosity fluids, thereby significantly improving mixing efficiency. Additionally, impeller geometry played a critical role in performance: the axial-flow impeller promoted faster homogenization and broader circulation compared with the radial-flow design. Through this CFD-based analysis, this study elucidates the key mechanisms governing mixing in high-viscosity fluids and provides practical design and operational guidelines for industrial stirred tank systems. These findings complement existing empirical guidelines focused on low-viscosity fluids and contribute to improving the efficiency and reliability of high-viscosity polymer processing. Full article

(This article belongs to the Special Issue High-Performance Polymer Materials and Fiber-Reinforced Composites for Engineering Applications)

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20 pages, 4077 KB

Open AccessArticle

Influence of Cooling Strategies on Surface Integrity After Milling of NiTi Alloy

by Małgorzata Kowalczyk

Materials 2025, 18(23), 5472; https://doi.org/10.3390/ma18235472 (registering DOI) - 4 Dec 2025

Abstract

Nickel–titanium (NiTi) alloys are extensively utilised in aerospace, biomedical, and precision engineering applications due to their distinctive functional properties, including superelasticity and the shape memory effect. However, their poor machinability and strong sensitivity to cutting conditions render it challenging to obtain surfaces with [...] Read more.

Nickel–titanium (NiTi) alloys are extensively utilised in aerospace, biomedical, and precision engineering applications due to their distinctive functional properties, including superelasticity and the shape memory effect. However, their poor machinability and strong sensitivity to cutting conditions render it challenging to obtain surfaces with stable functional integrity. The present study investigates the impact of diverse cooling methodologies—namely dry machining, minimum quantity lubrication (MQL) and cryogenic cooling employing liquid nitrogen (LN2)—on the three-dimensional (3D) surface topography of NiTi alloy following milling. A comprehensive set of three-dimensional surface roughness parameters was employed to quantify the surface geometry and evaluate its potential functional performance. The findings indicated that both dry milling and MQL yielded significantly divergent surface parameters, suggesting unstable surface formation, which may potentially compromise component durability. MQL frequently resulted in topographies that were functionally detrimental and characterised by high parameter dispersion. In contrast, cryogenic cooling (LN2) resulted in the most homogeneous surface topography, as evidenced by the lowest dispersion of 3D roughness indicators. To strengthen the analysis, a Taguchi–TOPSIS multi-criteria optimisation was also performed on ten 3D surface parameters, enabling an integrated ranking of all machining trials. The optimisation process confirmed the superior performance of cryogenic machining, with LN2 conditions achieving the highest overall surface quality index. Full article

(This article belongs to the Section Manufacturing Processes and Systems)

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23 pages, 1037 KB

Open AccessArticle

Oral Supplementation with Prunus domestica L. Extract Restores Recognition Memory Impairment Caused by D-Galactose in Rats

by Anusara Aranarochana, Puncharatsm Pannin, Papatchaya Sintow, Apiwat Sirichoat, Nataya Sritawan, Wanassanan Pannangrong, Rawiwan Charoensup, Wuttichai Jaidee, Piti Ungarreevittaya, Peter Wigmore and Jariya Umka Welbat

Nutrients 2025, 17(23), 3804; https://doi.org/10.3390/nu17233804 (registering DOI) - 4 Dec 2025

Abstract

Background/Objectives: Aging-related cognitive decline, linked to oxidative stress and impaired hippocampal neurogenesis, is a major contributor to neurodegenerative disorders. In rodents, this condition can be modeled by D-galactose (D-gal) administration, which induces oxidative stress and recognition memory deficits. Prunus domestica L. (PD), rich [...] Read more.

Background/Objectives: Aging-related cognitive decline, linked to oxidative stress and impaired hippocampal neurogenesis, is a major contributor to neurodegenerative disorders. In rodents, this condition can be modeled by D-galactose (D-gal) administration, which induces oxidative stress and recognition memory deficits. Prunus domestica L. (PD), rich in phenolic and flavonoid compounds with antioxidant properties, may counteract such impairments. This study evaluated the effects of PD extract on D-gal-induced memory decline by analyzing its phytochemical content, antioxidant activity, and neuroprotective potential. Methods: Phytochemicals were quantified by colorimetric and pH differential methods, and antioxidant capacity was determined using DPPH and FRAP assays. Male Sprague Dawley rats (12 weeks; n = 12/group) were assigned to 8 groups: vehicle, D-gal, PD (75, 100, or 150 mg/kg), and D-gal + PD (same respective doses). D-gal (50 mg/kg, i.p.) and/or PD were administered by oral gavage daily for 8 weeks. Recognition memory was assessed by the novel object recognition (NOR) test. Hippocampal tissues were processed for immunofluorescence staining of the proliferation marker Ki-67 and superoxide dismutase (SOD) activity using the cytochrome C reduction method. Results: PD extract contained abundant phenolics, tannins, flavonoids, and anthocyanins, and exhibited notable antioxidant activity. D-gal impaired recognition memory, reduced hippocampal cell proliferation, and decreased SOD activity. Co-treatment with PD improved memory performance, enhanced hippocampal neurogenesis, and restored antioxidant enzyme activity. Conclusions: PD extract may protect against D-gal-induced age-related cognitive decline through antioxidant effects and support of hippocampal neurogenesis. Full article

(This article belongs to the Section Nutrition and Neuro Sciences)

27 pages, 1244 KB

Open AccessArticle

Modeling Health-Supportive Urban Environments: The Role of Mixed Land Use, Socioeconomic Factors, and Walkability in U.S. ZIP Codes

by Maged Zagow, Ahmed Mahmoud Darwish and Sherif Shokry

Sustainability 2025, 17(23), 10873; https://doi.org/10.3390/su172310873 (registering DOI) - 4 Dec 2025

Abstract

Over recent decades, planners in the U.S. have increasingly adopted mixed-use projects to reduce automobile dependency and strengthen local community identity, although results remain inconsistent across cities. Urban health and fitness outcomes are shaped by complex interactions between the built environment, socioeconomic factors, [...] Read more.

Over recent decades, planners in the U.S. have increasingly adopted mixed-use projects to reduce automobile dependency and strengthen local community identity, although results remain inconsistent across cities. Urban health and fitness outcomes are shaped by complex interactions between the built environment, socioeconomic factors, and demographic characteristics. This study introduces a Health and Fitness Index (HFI) for 28,758 U.S. ZIP codes, derived from normalized measures of walkability, healthcare facility density, and carbon emissions, to assess spatial disparities in health-supportive environments. Using four modeling approaches—lasso regression, multiple linear regression, decision trees, and k-nearest neighbor classifiers—we evaluated the predictive importance of 15 urban and socioeconomic variables. Multiple linear regression produced the strongest generalization performance (R² = 0.60, RMSE = 0.04). Key positive predictors included occupied housing units, business density, land-use mix, household income, and racial diversity, while income inequality and population density were negatively associated with health outcomes. This study evaluates five statistical formulations (Metropolis Hybrid Models) that incorporate different combinations of walkability, land-use mix, environmental variables, and socioeconomic indicators to test whether relationships between urban form and socioeconomic conditions remain consistent under different variable combinations. In cross-sectional multivariate regression, although mixed-use development in high-density areas is strongly associated with healthcare facilities, these areas tend to serve younger and more racially diverse populations. Decision tree feature importance rankings and clustering profiles highlight structural inequalities across regions, suggesting that enhancing business diversity, land-use integration, and income equity could significantly improve health-supportive urban design. This research provides a data-driven framework for urban planners to identify underserved neighborhoods and develop targeted interventions that promote walkability, accessibility to health infrastructure, and sustainability. It contributes to the growing literature on urban health analytics, integrating machine learning, spatial clustering, and multidimensional urban indicators to advance equitable and resilient city planning. Full article

(This article belongs to the Section Sustainable Urban and Rural Development)

18 pages, 1115 KB

Open AccessArticle

An Enhanced, Lightweight Large Language Model-Driven Time Series Forecasting Approach for Air Conditioning System Cooling Load Forecasting

by Cong Zhu, Yongkuan Yang, Haiping Chen and Miao Zeng

Mathematics 2025, 13(23), 3887; https://doi.org/10.3390/math13233887 (registering DOI) - 4 Dec 2025

Abstract

Accurate cooling load forecasting in high-efficiency chiller plants with ice storage systems is essential for intelligent control, energy conservation, and maintaining indoor comfort. However, conventional forecasting methods often struggle to model the complex nonlinear dependencies among influencing variables, limiting their predictive performance. To [...] Read more.

Accurate cooling load forecasting in high-efficiency chiller plants with ice storage systems is essential for intelligent control, energy conservation, and maintaining indoor comfort. However, conventional forecasting methods often struggle to model the complex nonlinear dependencies among influencing variables, limiting their predictive performance. To address this, this paper introduces Time-LLM, a novel time series forecasting framework that leverages a frozen large language model (LLM) to improve the accuracy and generalization of cooling load forecasting. Time-LLM extracts features from historical data, reformulates them as natural language prompts, and uses the LLM for temporal sequence modeling; a linear projection layer then maps the LLM output to final predictions. To enable lightweight deployment and improve temporal feature prompting, we propose ETime-LLM, an enhanced variant of Time-LLM. ETime-LLM significantly reduces deployment costs and mitigates the original model’s response lag during trend transitions by focusing on possible turning points. Extensive experiments demonstrate that ETime-LLM consistently outperforms or matches state-of-the-art baselines across short-term, long-term, and few-shot forecasting tasks. Specifically, in the commonly used 24 h forecasting horizon, compared with the original model, ETime-LLM achieves an approximately 17.3% reduction in MAE and a 19.3% reduction in RMSE. It achieves high-quality predictions without relying on costly external data, offering a robust and scalable solution for green and energy-efficient HVAC system management. Full article

25 pages, 2763 KB

Open AccessArticle

Implementation of Vital Signs Detection Algorithm for Supervising the Evacuation of Individuals with Special Needs

by Krzysztof Konopko, Dariusz Janczak and Wojciech Walendziuk

Sensors 2025, 25(23), 7391; https://doi.org/10.3390/s25237391 (registering DOI) - 4 Dec 2025

Abstract

The article describes a system for monitoring the vital parameters of evacuated individuals, integrating three key functionalities: pulse detection, verification of wristband contact with the skin, and motion recognition. For pulse detection, the system employs the MAX30102 optical sensor and a signal processing [...] Read more.

The article describes a system for monitoring the vital parameters of evacuated individuals, integrating three key functionalities: pulse detection, verification of wristband contact with the skin, and motion recognition. For pulse detection, the system employs the MAX30102 optical sensor and a signal processing algorithm presented in the study. The algorithm is based on spectral analysis using the Fast Fourier Transform (FFT) and incorporates a nonparametric estimator of the probability density function (PDF) in the form of Kernel Density Estimation (KDE). This developed real-time algorithm enables reliable assessment of vital parameters of evacuated individuals. The wristband contact with the skin is verified by measuring the brightness of backscattered light and the temperature of the wrist. Motion detection is achieved using the MPU-9250 inertial module, which analyzes acceleration across three axes. This allows the system to distinguish between states of rest and physical activity, which is crucial for accurately interpreting vital parameters during evacuation. The experimental studies, which were performed on a representative group of individuals, confirmed the correctness of the developed algorithm. The system ensures reliable monitoring of vital parameters by combining precise pulse detection, skin contact verification, and motion analysis. The classifier achieves nearly 95% accuracy and an F₁-score of 0.9465, which indicates its high quality. This level of effectiveness can be considered fully satisfactory for evacuation monitoring systems. Full article

(This article belongs to the Special Issue Sensing Signals for Biomedical Monitoring—2nd Edition)

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