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Article

08 August 2025

Rolling Bearing Health Indicator: From Design to Modeling and Evaluation

As a key component of industrial machinery, accurate prediction of the degradation trend of rolling bearings is crucial for equipment safety. However, traditional health indicator (HI) extraction methods often suffer from feature redundancy, and prediction models lack the ability to capture spatial dimension features, leading to significant prediction errors. To address these issues, 16 time-frequency domain features were first extracted, and a new HI was constructed by combining the Gaussian Process latent variable model (GPLVM) for non-linear feature fusion and exponentially weighted moving average (EWMA) for smoothing. Additionally, a spatial-temporal convolutional long short-term memory network (ST-CNet) was proposed, which integrates a 3-layer CLSTM, fully connected layers, and batch normalization to effectively capture local and long-term spatiotemporal dependencies. Case studies on IMS bearing datasets show that the constructed HI accurately describes the degradation process, and ST-CNet achieves superior performance with lower MAE and RMSE compared to existing methods.

Keywords: Prediction of degradation trend; Multi-feature fusion; ST-CNet; Rolling bearing; Health indicator
Intell. Sustain. Manuf.
2025,
2
(2), 10025; 
Open Access

Article

07 August 2025

Daoism, Confucianism, and the Rights of Nature: Transformative Relations in Ecological Governance

Confronting a global ecological crisis, this paper argues that conventional anthropocentric governance models, rooted in instrumental rationality, are inadequate. Drawing on Edoardo Ongaro’s concept of an integrative approach to an ontological and political philosophical understanding of public governance and administration, it proposes a relational framework for ecological governance by integrating the Rights of Nature (RoN) movement with classical Chinese philosophical traditions. The study emphasizes the complementary foundations offered by Daoism, specifically its concepts of ziran (natural spontaneity) and wuwei (non-coercive action) which support decentralized governance aligned with ecological self-organization, and Confucianism, particularly tian ren he yi (unity of heaven and humanity), which embeds ecological stewardship within moral self-cultivation (ren) and social duty (li). Comparative case studies highlight cultural complexities in implementing such relational governance. This paper outlines a tripartite pathway for building transformative capacities within this relational framework and discusses policy implications.

Keywords: Rights of nature; Relational governance; Ecological governance; Daoism; Confucianism
Ecol. Civiliz.
2025,
2
(4), 10013; 
Open Access

Article

07 August 2025

Examining Interactions among Challenges of Green Financing in India

This study examines the challenges of green financing in India using Interpretive Structural Modeling (ISM) to identify hierarchical relationships among key factors. The research identifies regulatory deficiencies as the foundational barrier, cascading into secondary challenges such as data gaps, low investor awareness, high costs, and limited access to financial products. These issues, compounded by greenwashing, hinder transparency and the accurate measurement of environmental returns. The structural modeling approach provides a novel contribution by revealing how these interconnected challenges stem from weak regulatory frameworks—an insight not previously mapped in Indian green finance literature. The study underscores the importance of strong legal systems, standardized metrics, technological advancement, and policy harmonization to build investor trust and improve accessibility. For scalable and effective solutions, future research should explore the integration of emerging technologies and conduct cross-regional comparative analysis.

Keywords: Green financing; Nominal Group Technique (NGT); Interpretive Structural Modeling (ISM)
Ecol. Civiliz.
2025,
2
(4), 10012; 
Open Access

Review

07 August 2025

Progress in the Study of Transition Metal-Based Carbon Nanotube Composites for Electrochemical Hydrogen Evolution

Hydrogen is an efficient, clean, and economical energy source, primarily due to its remarkably high energy density. Electrolytic water is considered an attractive and feasible method for hydrogen production. The high cost and scarcity of traditional Pt-based catalysts limit their large-scale application. Transition metals (TMs)-based composites, particularly those integrated with carbon nanotubes (CNTs), have emerged as promising alternatives due to their high conductivity, surface area, and ability to enhance the catalytic properties of TMs. Currently, there is no systematic summary of TMs-based CNTs composites for electrochemical hydrogen evolution reaction (HER). In this review, the main synthesis methods, including the wet chemical method, chemical vapor deposition, and electrochemical techniques, were first summarized. Then, the latest advancements of TMs/CNTs composites, focusing on their structure, electronic properties and superior HER catalytic performance, were systematically discussed. The catalytic mechanisms are meticulously examined, with particular emphasis on the pivotal role of CNTs in enhancing charge transfer and stabilizing metal nanoparticles. Finally, this review addresses the current challenges and future development directions for HER catalysts.

Keywords: Carbon nanotubes; Transition metals; Composites; Hydrogen evolution reaction
Green Chem. Technol.
2025,
2
(3), 10012; 
Open Access

Communication

05 August 2025

Autoimmune Adverse Events Following Immunization

Adverse events (AEs) following immunization can include autoimmune AEs for some vaccines and combinations. This study retrospectively examines autoimmune AEs to detect safety signals for vaccines and concomitantly administered vaccines in the Vaccine Adverse Event Reporting System (VAERS) database. This study focuses on which vaccines were administered or coadministered for retrospective analysis of analyzed autoimmune AEs. Observed results include multiple autoimmune AE safety signals: human papillomavirus (HPV) Cervarix, HPV Gardasil, hepatitis (Hep) A + Hep B (Twinrix), Lyme disease (LYMErix), coadministered COVID-19 Moderna + Pfizer-BioNTech, Hep B (Engerix-B), and others. Identified arthritis AE safety signals include Lyme disease (LYMErix), rubella (Meruvax II), HPV (Cervarix), Anthrax (Biothrax) + Smallpox (Dryvax), and more. Coadministered DTaP + HepB + IPV (Pediarix) + Hib (Pedvaxhib) + Pneumococcal (Prevnar13) + Rotavirus (Rotarix) may be exhibiting synergy AE rate for eczema AEs. Thirty five influenza vaccines were observed with Guillain–Barré syndrome (GBS) AE safety signals, plus additional safety signals for multiple other vaccines. influenza (H1N1 monovalent) (GSK) exhibits a very high rate for narcolepsy AEs.

Keywords: Autoimmune; Adverse events; Arthritis; Complex regional pain syndrome; Guillain-Barré syndrome; Henoch Schonlein purpura; Postural orthostatic tachycardia syndrome; Systemic lupus erythematosus
Immune Discov.
2025,
1
(3), 10010; 
Open Access

Article

01 August 2025

Eastern Lubber Grasshopper Extract-Inspired Silver Nanoparticles Selectively Inhibit Methicillin-Resistant Staphylococcus aureus

Silver nanoparticles (AgNPs) were synthesized using a protein/polypeptide-rich aqueous extract from the Eastern lubber grasshopper (Romalea microptera), as a natural reducing and capping agent. The resulting AgNPs exhibited relatively uniform sizes (10–60 nm) and were characterized by Fourier Transform Infrared Spectroscopy (FTIR), Ultraviolet-visible (UV-Vis) spectroscopy, Transmission electron microscopy (TEM), and Scanning Electron Microscopy (SEM). Disk diffusion tests against five bacterial strains (Methicillin-resistant Staphylococcus aureus (MRSA), Burkholderia cenocepacia, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Escherichia coli) demonstrated that the insect-extract-induced AgNPs selectively and significantly inhibited MRSA growth, with an average value of zone of inhibition of 9.16 ± 1.11 mm (n = 4). Statistical analysis confirmed the superior antibacterial activity of the Eastern lubber grasshopper-derived AgNPs against MRSA compared to citrate-capped AgNPs and free silver ions. These findings reveal the potential of insect-derived AgNPs as selective, green-synthesized antibacterial agents with enhanced efficacy and reduced side effects, particularly against antibiotic-resistant pathogens.

Keywords: Silver nanoparticle assembly; Eastern lubber grasshopper; Bio-inspired synthesis; Nano-biomaterials; Selective antibacterial activity
Open Access

Article

31 July 2025

Reversal of Remimazolam-Mediated Inhibition of Jurkat T Cell Activation by TGFBI Depletion

GABAA receptors are well-recognized targets for intravenous anesthetics and have been identified in T lymphocytes. Remimazolam, a GABAA receptor-binding agent, enhances the inhibitory effects of γ-aminobutyric acid (GABA) and provides a rapid onset and offset of sedation, making it suitable for procedural sedation and anesthesia. However, the impact of remimazolam on T cell function remains poorly understood. In this study, we used mass spectrometry analysis to confirm that Jurkat T cells produce and secrete GABA de novo. Consequently, treatment with remimazolam inhibited Jurkat T cell activation, even in the absence of exogenous GABA. Transcriptomic profiling of remimazolam-treated Jurkat T cells exhibited a significant upregulation of TGFBI expression. Furthermore, CRISPR/Cas9-mediated knockout of TGFBI reversed the inhibitory effects of remimazolam on Jurkat T cell activation. These findings highlight the profound influence of anesthetics on T cell activation and could be crucial for optimizing their clinical application.

Keywords: GABAA receptor; GABA; Remimazolam; T cell activation; TGFBI
Immune Discov.
2025,
1
(3), 10009; 
Open Access

Article

31 July 2025

Experimental Study on the Strength Distribution and Pore Distribution of Industrial Pellet and DRI

Against the backdrop of the “dual-carbon” goals driving the steel industry's transition toward hydrogen metallurgy, the hydrogen-based shaft furnace process has emerged as a focal point due to its low-carbon emissions. This study employs compression testing, mercury intrusion porosimeter, and industrial computed tomography  characterization to compare the mechanical properties and pore structures of industrial pellets and direct reduced iron (DRI). The results show that the compressive strength and mass specific breakage energy of DRI are lower than those of pellets, and the breakage characteristic parameters at the same particle size are lower, making it more prone to breakage; the compressive strength of both increases with the increase of particle size, the mass specific breakage energy decreases with the increase of particle size, and the strength growth rate of pellets is faster. In terms of pore structure, pellets are mainly composed of uniform macropores of 3428 nm with a porosity of 22.3%; DRI has a porosity of 48.8%, mainly composed of 3431 nm macropores and 831 nm micropores, with a low tortuosity index, which is conducive to gas diffusion. This study provides parameters and theoretical basis for modeling of burden movement and crushing in shaft furnace.

Keywords: Ironmaking; Pellet; DRI; Compressive strength; Breakage energy; Porosity
High-Temp. Mat.
2025,
2
(3), 10018; 
Open Access

Article

31 July 2025

Single Shift Segmentation Improves Moderate Flood Estimates under Nonstationary Conditions across the United States

Precipitation, particularly at high quantiles, has been reported to increase in various regions across the globe, raising pluvial flood risk. One of the main challenges in reliable flood frequency analysis is handling nonstationarity arising from climate variability or anthropogenic disturbances such as land use/cover change or river regulation. To separate these nonstationary footprints, we analyzed annual maximum peak flow records from 18 reference (minimally disturbed) and 66 non-reference stream gages, each with more than 100 years of flood records across the United States. Next, we used a nonparametric Pettitt test to identify statistically significant change points. When present, the flood record was split into pre- and post-change segments with a Log-Pearson III distribution fitted to each. Depending on the region and site type, using a segmented record improved the quantile estimate. At the majority of reference sites, post-change data produced the highest flood quantiles, reflecting recent climate-driven nonstationarity. Conversely, at several non-reference sites, pre-change data returned larger estimates, indicating that long-standing anthropogenic disturbances can attenuate the signal of climatic variations. Our study confirms that fitting a flood frequency model to the segment that minimizes nonstationarity, rather than the entire record, returns more reliable estimates for moderate flood magnitudes of up to a 25-year return interval. The approach highlights the need to understand the population from which flood records are extracted, to separate those populations where appropriate, and then fit a statistical distribution. This practical approach offers a simple thought process for updating moderate flood forecasts to guide infrastructure design or rehabilitation in the current dynamic environment, an era of constant change that needs flexibility in everything we design.

Keywords: Flood frequency analysis; Nonstationary; Petit change point detection; Log Pearson Type III (LP3); Reference versus non-reference basins; Anthropogenic disturbance; Climate variability; United States
Hydroecol. Eng.
2025,
2
(3), 10009; 
Open Access

Article

30 July 2025

Effects of Virtual Reality (VR) Rehabilitation on Mental Health in SCI Patients: A Randomized Controlled Trial

This randomized controlled trial investigates the effects of virtual reality (VR) rehabilitation on mental health in spinal cord injury (SCI) patients. Seventy-four participants were randomized to 12 weeks of VR-based or traditional rehabilitation, with mental health assessed via the Hospital Anxiety and Depression Scale (HADS) and World Health Organization Quality of Life-BREF (WHOQOL-BREF). The VR group showed significantly greater reductions in HADS scores at 6 weeks (mean change: −4.2 vs. −2.4, p < 0.001) and 12 weeks (mean change: −6.4 vs. −3.9, p < 0.001), with a large effect size (Cohen’s d = 1.21). VR also improved WHOQOL-BREF psychological health scores (+13.5 vs. +6.4, p < 0.001), self-esteem (+7.2 vs. +3.2, p < 0.001), and sleep quality (−5.1 vs. −2.8, p < 0.001). Subgroup analysis indicated greater benefits for younger patients and those with incomplete SCI. VR rehabilitation outperforms traditional methods in enhancing mental health, supporting its integration into comprehensive SCI care.

Keywords: Spinal cord injury; Virtual reality; Rehabilitation; Mental health; Randomized controlled trial
Lifespan Dev. Ment. Health
2025,
1
(3), 10012; 
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