Search Results (2,346)

This study proposes the SMR Smart Net-Zero City (SSNC) framework—a scalable model for achieving carbon neutrality by integrating Small Modular Reactors (SMRs), renewable energy sources, and sector coupling within a microgrid architecture. As deploying renewables alone would require economically and technically impractical energy storage systems, SMRs provide a reliable and flexible baseload power source. Sector coupling systems—such as hydrogen production and heat generation—enhance grid stability by absorbing surplus energy and supporting the decarbonization of non-electric sectors. The core contribution of this study lies in its real-time data emulation framework, which overcomes a critical limitation in the current energy landscape: the absence of operational data for future technologies such as SMRs and their coupled hydrogen production systems. As these technologies are still in the pre-commercial stage, direct physical integration and validation are not yet feasible. To address this, the researchers leveraged real-time data from an existing commercial microgrid, specifically focusing on the import of grid electricity during energy shortfalls and export during solar surpluses. These patterns were repurposed to simulate the real-time operational behavior of future SMRs (ProxySMR) and sector coupling loads. This physically grounded simulation approach enables high-fidelity approximation of unavailable technologies and introduces a novel methodology to characterize their dynamic response within operational contexts. A key element of the SSNC control logic is a day–night strategy: maximum SMR output and minimal hydrogen production at night, and minimal SMR output with maximum hydrogen production during the day—balancing supply and demand while maintaining high SMR utilization for economic efficiency. The SSNC testbed was validated through a seven-day continuous operation in Busan, demonstrating stable performance and approximately 75% SMR utilization, thereby supporting the feasibility of this proxy-based method. Importantly, to the best of our knowledge, this study represents the first publicly reported attempt to emulate the real-time dynamics of a net-zero city concept based on not-yet-commercial SMRs and sector coupling systems using live operational data. This simulation-based framework offers a forward-looking, data-driven pathway to inform the development and control of next-generation carbon-neutral energy systems. Full article

Background/Objectives: Cannabinoid use is rising among patients undergoing spinal fusion, yet its influence on bone healing is poorly defined. The endocannabinoid system (ECS)—through cannabinoid receptors 1 (CB1) and 2 (CB2)—modulates skeletal metabolism. We reviewed preclinical, mechanistic and clinical evidence to clarify how individual cannabinoids affect fracture repair and spinal arthrodesis. Methods: PubMed, Web of Science and Scopus were searched from inception to 31 May 2025 with the terms “cannabinoid”, “CB1”, “CB2”, “spinal fusion”, “fracture”, “osteoblast” and “osteoclast”. Animal studies, in vitro experiments and clinical reports that reported bone outcomes were eligible. Results: CB2 signaling was uniformly osteogenic. CB2-knockout mice developed high-turnover osteoporosis, whereas CB2 agonists (HU-308, JWH-133, HU-433, JWH-015) restored trabecular volume, enhanced osteoblast activity and strengthened fracture callus. Cannabidiol (CBD), a non-psychoactive phytocannabinoid with CB2 bias, accelerated early posterolateral fusion in rats and reduced the RANKL/OPG ratio without compromising final union. In contrast, sustained or high-dose Δ⁹-tetrahydrocannabinol (THC) activation of CB1 slowed chondrocyte hypertrophy, decreased mesenchymal-stromal-cell mineralization and correlated clinically with 6–10% lower bone-mineral density and a 1.8–3.6-fold higher pseudarthrosis or revision risk. Short-course or low-dose THC appeared skeletal neutral. Responses varied with sex, age and genetic background; no prospective trials defined safe perioperative dosing thresholds. Conclusions: CB2 activation and CBD consistently favor bone repair, whereas chronic high-THC exposure poses a modifiable risk for nonunion in spine surgery. Prospective, receptor-specific trials stratified by THC/CBD ratio, patient sex and ECS genotype are needed to establish evidence-based cannabinoid use in spinal fusion. Full article

The textile industry’s reliance on synthetic dyes contributes significantly to pollution, highlighting the need for sustainable alternatives like biopigments. This study investigates the production and application of the biopigment prodigiosin, which was produced by Pseudomonas putida with a yield of 1.85 g/L. Prodigiosin was prepared under acidic, neutral, and alkaline conditions, resulting in varying protonation states that influenced its affinity for cotton and polyester fibers. Three surfactants (anionic, cationic, non-ionic) were tested, with non-ionic Tween 80 yielding a promising color strength (above 4) and fastness results with neutral prodigiosin at 1.3 g/L. Cotton and polyester demonstrated good washing (color difference up to 14 for cotton, 5 for polyester) and light fastness (up to 15 for cotton, 16 for polyester). Cellulose acetate, used in the conventional printing process as a thickener, produced superior color properties compared to commercial thickeners. Neutral prodigiosin achieved higher color strength, and cotton fabrics displayed halochromic properties, distinguishing them from polyester, which showed excellent fastness. Prodigiosin-printed samples also exhibited strong antimicrobial activity against Pseudomonas aeruginosa and retained halochromic properties over 10 pH cycles. These findings suggest prodigiosin as a sustainable dye alternative and pH sensor, with potential applications in biomedical materials, such as antimicrobial and pH-responsive wound dressings. Full article

Cystic echinococcosis is a zoonosis caused by the cestode Echinococcus granulosus sensu stricto. Population genetic studies and phylogeographic patterns are essential to understanding the transmission dynamics of this parasite under varying environmental conditions. In this study, the genetic diversity of E. granulosus s.s. was evaluated using 46 hydatid cyst samples obtained from sheep, goats, cattle, and humans across three regions of Chile: Coquimbo, La Araucanía, and Magallanes. Mitochondrial cox1 gene sequences were analyzed and compared with reference sequences reported from South America, Europe, Africa, Asia, and Oceania. In Chile, the EG01 haplotype was the predominant haplotype. A total of four haplotypes were identified, with low haplotype diversity (Hd = 0.461 ± 0.00637) and low nucleotide diversity (π = 0.00181 ± 0.00036). The haplotype network displayed a star-like configuration, with the EG01 genotype at the center, suggesting a potentially ancestral or widely distributed lineage. In Coquimbo (Tajima’s D = −0.93302, p = 0.061; Fu’s Fs = −0.003, p = 0.502) and Magallanes (Tajima’s D = −0.17406, p = 0.386; Fu’s Fs = −0.121, p = 0.414), both neutrality tests were non-significant, indicating no strong evidence for recent population expansion or selection. Star-like haplotype network patterns were also observed in populations from Europe, the Middle East, Asia, Africa, and Oceania, with the EG01 genotype occupying the central position. The population genetic structure of Echinococcus granulosus s.s. in Chile demonstrates considerable complexity, with EG01 as the predominant haplotype. Further comprehensive studies are required to assess the intraspecific genetic variability of E. granulosus s.s. throughout Chile and to determine whether this variability influences the key biological traits of the parasite. This structure may prove even more complex when longer fragments are analyzed, which could allow for the detection of finer-scale microdiversity among isolates from different hosts. We recommended that future cystic echinococcosis control programs take into account the genetic variability of E. granulosus s.s. strains circulating in each endemic region, to better understand their epidemiological, immunological, and possibly pathological differences. Full article

Steel is an important product in many engineering sectors; however, steelmaking remains one of the largest ${\mathrm{CO}}_2$ emitters. Therefore, new governmental policies drive the steelmaking industry toward a cleaner and more sustainable operation such as the gas-based direct reduction–electric arc furnace process. To become carbon neutral, utilizing more scrap is one of the feasible solutions to achieve this goal. Addressing knowledge gaps regarding scrap heterogeneity (size, shape, and composition) is essential to evaluate the effects of increased scrap ratios in basic oxygen furnace (BOF) operations. This review systematically examines heat and mass transfer correlations relevant to scrap melting in BOF steelmaking, with a focus on low Prandtl number fluids (thick thermal boundary layer) and dense particulate systems. Notably, a majority of these correlations are designed for fluids with high Prandtl numbers. Even for the ones tailored for low Prandtl, they lack the introduction of the porosity effect which alters the melting behavior in such high temperature systems. The review is divided into two parts. First, it surveys heat transfer correlations for single elements (rods, spheres, and prisms) under natural and forced convection, emphasizing their role in predicting melting rates and estimating maximum shell size. Second, it introduces three numerical modeling approaches, highlighting that the computational fluid dynamics–discrete element method (CFD–DEM) offers flexibility in modeling diverse scrap geometries and contact interactions while being computationally less demanding than particle-resolved direct numerical simulation (PR-DNS). Nevertheless, the review identifies a critical gap: no current CFD–DEM framework simultaneously captures shell formation (particle growth) and non-isotropic scrap melting (particle shrinkage), underscoring the need for improved multiphase models to enhance BOF operation. Full article

Cystic fibrosis produces viscous mucus in the lung that increases bacterial invasion, causing persistent infections and subsequent inflammation. Pseudomonas aeruginosa and Staphylococcus aureus are two of the most common infections in cystic fibrosis patients that are resistant to antibiotics. One antibiotic approved to treat these infections is levofloxacin (LVX), which functions to inhibit bacterial replication but can be further developed into tailorable particles. Nanoparticles are an emerging inhaled therapy due to enhanced targeting and delivery. The extracellular matrix (ECM) has been shown to possess pro-regenerative and non-toxic properties in vitro, making it a promising delivery agent. The combination of LVX and ECM formed into nanoparticles may overcome barriers to lung delivery to effectively treat cystic fibrosis bacterial infections. Our goal is to advance CF care by providing a combined treatment option that has the potential to address both bacterial infections and lung damage. Two hybrid formulations of a 10:1 and 1:1 ratio of LVX to ECM have shown neutral surface charges and an average size of ~525 nm and ~300 nm, respectively. The neutral charge and size of the particles may suggest their ability to attract toward and penetrate through the mucus barrier in order to target the bacteria. The NPs have also been shown to slow the drug dissolution, are non-toxic to human airway epithelial cells, and are effective in inhibiting Pseudomonas aeruginosa and Staphylococcus aureus. LVX-ECM NPs may be an effective treatment for pulmonary CF bacterial treatments. Full article

Work-related musculoskeletal disorders (WMSDs) are a leading concern in industrial ergonomics, often stemming from sustained non-neutral postures and repetitive tasks. This paper presents a vision-based framework for real-time, frame-level ergonomic risk classification using a lightweight Vision Transformer (ViT). The proposed system operates directly on raw RGB images without requiring skeleton reconstruction, joint angle estimation, or image segmentation. A single ViT model simultaneously classifies eight anatomical regions, enabling efficient multi-label posture assessment. Training is supervised using a multimodal dataset acquired from synchronized RGB video and full-body inertial motion capture, with ergonomic risk labels derived from RULA scores computed on joint kinematics. The system is validated on realistic, simulated industrial tasks that include common challenges such as occlusion and posture variability. Experimental results show that the ViT model achieves state-of-the-art performance, with F1-scores exceeding 0.99 and AUC values above 0.996 across all regions. Compared to previous CNN-based system, the proposed model improves classification accuracy and generalizability while reducing complexity and enabling real-time inference on edge devices. These findings demonstrate the model’s potential for unobtrusive, scalable ergonomic risk monitoring in real-world manufacturing environments. Full article

Background and Objectives: The management of type 2 diabetes (T2D) extends beyond glycemic control, requiring a more global strategy that includes optimization of body composition, even more so in the context of sarcopenia and visceral adiposity, as they contribute to poor outcomes. Past reviews have typically been focused on weight reduction or glycemic effectiveness, with limited inclusion of new therapies’ effects on muscle and fat distribution. In addition, the emergence of incretin-based therapies and dual agonists such as tirzepatide requires an updated synthesis of their impacts on body composition. This review attempts to bridge the gap by taking a systematic approach to how current blood-glucose lowering therapies affect lean body mass, fat mass, and the risk of sarcopenia in T2D patients. Materials and Methods: Between January 2015 and March 2025, we conducted a narrative review by searching the PubMed, Scopus, and Web of Science databases for English-language articles. The keywords were combinations of the following: “type 2 diabetes,” “lean body mass,” “fat mass,” “body composition,” “sarcopenia,” “GLP-1 receptor agonists,” “SGLT2 inhibitors,” “tirzepatide,” and “antidiabetic pharmacotherapy.” Reference lists were searched manually as well. The highest precedence was assigned to studies that aimed at adult type 2 diabetic subjects and reported body composition results. Inclusion criteria for studies were: (1) type 2 diabetic mellitus adult patients and (2) reporting measures of body composition (e.g., lean body mass, fat mass, or muscle function). We prioritized randomized controlled trials and large observational studies and excluded mixed diabetic populations, non-pharmacological interventions only, and poor reporting of body composition. Results: Metformin was widely found to be weight-neutral with minimal effects on muscle mass. Insulin therapy, being an anabolic hormone, often leads to fat mass accumulation and increases the risk of sarcopenic obesity. Incretin-based therapies induced substantial weight loss, mostly from fat mass. Notable results were observed in studies with tirzepatide, demonstrating superior reduction not only in fat mass, but also in visceral fat. Sodium-glucose cotransporter 2 inhibitors (SGLT2 inhibitors) promote fat loss but are associated with a small yet significant decrease in lean muscle mass. Conclusions: Blood-glucose lowering therapies demonstrated clinically relevant effects on body composition. Treatment should be personalized, balancing glycemic control, cardiovascular, and renal benefits, together with optimal impact on muscle mass along with glycemic, cardiovascular, and renal benefits. Full article

Rough sets and fuzzy sets are two complementary approaches for modeling uncertainty and imprecision. Their integration enables a more comprehensive representation of complex, uncertain systems. However, existing rough fuzzy sets models lack the expressive power to fully capture the interactions among structural uncertainty, cognitive hesitation, and multi-level granular information. To address these limitations, we achieve the following: (1) We propose intuitionistic fuzzy covering rough membership and non-membership degrees based on maximal description and construct a new single-granulation model that more effectively captures both the structural relationships among elements and the semantics of fuzzy information. (2) We further extend the model to a multi-granulation framework by defining optimistic and pessimistic approximation operators and analyzing their properties. Additionally, we propose a neutral multi-granulation covering rough intuitionistic fuzzy sets based on aggregated membership and non-membership degrees. Compared with single-granulation models, the multi-granulation models integrate multiple levels of information, allowing for more fine-grained and robust representations of uncertainty. Finally, a case study on real estate investment was conducted to validate the effectiveness of the proposed models. The results show that our models can more precisely represent uncertainty and granularity in complex data, providing a flexible tool for knowledge representation in decision-making scenarios. Full article

Under the dual challenges of global energy crisis and climate change, the building sector, as a major carbon emitter consuming 33% of global primary energy, has seen its energy efficiency optimization become a critical pathway towards achieving carbon neutrality goals. The Window-to-Wall Ratio (WWR), serving as a core parameter in building envelope design, directly influences building energy consumption, with its optimized design playing a decisive role in balancing natural daylighting, ventilation efficiency, and thermal comfort. This study focuses on the traditional One-Seal dwellings (Yikeyin) in Kunming, China, establishing a dynamic wind field-thermal environment coupled analysis framework to investigate the impact mechanism of window dimensions (WWR and aspect ratio) on indoor thermal comfort under natural wind conditions in transitional climate zones. Utilizing the Grasshopper platform integrated with Ladybug, Honeybee, and Butterfly plugins, we developed parametric models incorporating Kunming’s Energy Plus Weather meteorological data. EnergyPlus and OpenFOAM were employed, respectively, for building heat-moisture balance calculations and Computational Fluid Dynamic (CFD) simulations, with particular emphasis on analyzing the effects of varying WWR (0.05–0.20) on temperature-humidity, air velocity, and ventilation efficiency during typical winter and summer weeks. Key findings include, (1) in summer, the baseline scenario with WWR = 0.1 achieves a dynamic thermal-humidity balance (20.89–24.27 °C, 65.35–74.22%) through a “air-permeable but non-ventilative” strategy, though wing rooms show humidity-heat accumulation risks; increasing WWR to 0.15–0.2 enhances ventilation efficiency (2–3 times higher air changes) but causes a 4.5% humidity surge; (2) winter conditions with WWR ≥ 0.15 reduce wing room temperatures to 17.32 °C, approaching cold thresholds, while WWR = 0.05 mitigates heat loss but exacerbates humidity accumulation; (3) a symmetrical layout structurally constrains central ventilation, maintaining main halls air changes below one Air Change per Hour (ACH). The study proposes an optimized WWR range of 0.1–0.15 combined with asymmetric window opening strategies, providing quantitative guidance for validating the scientific value of vernacular architectural wisdom in low-energy design. Full article

Background/Objectives: Mucosal vaccines, delivered intranasally or via inhalation, are being studied for respiratory infectious diseases like COVID-19 and influenza. These vaccines aim to provide non-invasive administration and strong immune responses at infection sites, making them a promising area of research. This systematic review and meta-analysis assessed their immunogenicity, safety, and protective efficacy. Methods: The study design was a systematic review and meta-analysis, searching PubMed and Cochrane databases up to 30 May 2025. Inclusion criteria followed the PICOS framework, focusing on mucosal vaccines for COVID-19, influenza, RSV, pertussis, and tuberculosis. Results: A total of 65 studies with 229,614 participants were included in the final analysis. Mucosal COVID-19 vaccines elicited higher neutralizing antibodies compared to intramuscular vaccines (SMD = 2.48, 95% CI: 2.17–2.78 for wild-type; SMD = 1.95, 95% CI: 1.32–2.58 for Omicron), with varying efficacy by route (inhaled VE = 47%, 95% CI: 22–74%; intranasal vaccine VE = 17%, 95% CI: 0–31%). Mucosal influenza vaccines protected children well (VE = 62%, 95% CI: 30–46%, I² = 17.1%), but seroconversion rates were lower than those of intramuscular vaccines. RSV and pertussis vaccines had high seroconversion rates (73% and 52%, respectively). Tuberculosis vaccines were reviewed systemically, exhibiting robust cellular immunogenicity. Safety was comparable to intramuscular vaccines or placebo, with no publication bias detected. Conclusions: Current evidence suggests mucosal vaccines are immunogenic, safe, and protective, particularly for respiratory diseases. This review provides insights for future research and vaccination strategies, though limitations include varying efficacy by route and study heterogeneity. Full article

The tufted deer (Elaphodus cephalophus), a Near-Threatened (NT) species endemic to China and Myanmar, requires robust genetic data for effective conservation. However, the genetic landscape of key populations, such as those in Chongqing, remains poorly understood. This study aimed to comprehensively evaluate the genetic diversity, population structure, gene flow, and demographic history of tufted deer across this critical region. We analyzed mitochondrial DNA (mtDNA) from 46 non-invasively collected fecal samples from three distinct populations: Jinfo Mountain (JF, n = 13), Simian Mountain (SM, n = 21), and the Northeastern Mountainous region (NEM, n = 12). Genetic variation was assessed using the cytochrome b (Cyt b) and D-loop regions, with analyses including F_st, gene flow (N_m), neutrality tests, and Bayesian Skyline Plots (BSP). Our results revealed the highest genetic diversity in the SM population, establishing it as a genetic hub. In contrast, the JF population exhibited the lowest diversity and significant genetic differentiation (>0.23) from the SM and NEM populations, indicating profound isolation. Gene flow was substantial between SM and NEM but severely restricted for the JF population. Demographic analyses, including BSP, indicated a long history of demographic stability followed by a significant expansion beginning in the Middle to Late Pleistocene. We conclude that the SM/NEM metapopulation serves as the genetic core for the species in this region, while the highly isolated JF population constitutes a distinct and vulnerable Management Unit (MU). This historical demographic expansion is likely linked to climatic and environmental changes during the Pleistocene, rather than recent anthropogenic factors. These findings underscore the urgent need for a dual conservation strategy: targeted management for the isolated JF population and the establishment of ecological corridors to connect the Jinfo Mountain and Simian Mountain populations, ensuring the long-term persistence of this unique species. Full article

Background: Clinical diagnostics, food industries, and biotechnological processes typically use an enzyme called alpha-amylase to metabolize carbohydrates. Objective: The aim of this study is to investigate how low-level laser irradiation (LLLI) affects alpha-amylase activity towards determining the usability of LLLI in non-invasive enzymatic modulation. Methods: Enzyme solutions were irradiated at 10, 20, 30, and 40 J/cm² utilizing 589 nm and 532 nm diode-pumped solid-state lasers. The iodine–starch colorimetric method was used to quantify post-irradiation enzymatic activity, with inverse correlations found between absorbance and activity levels. Modulation was determined by the wavelength and dosage. Results: Enzymatic activity significantly improved when utilizing 589 nm irradiation at lower doses, maximizing at 120% at 20 J/cm² (p < 0.01). Neutral or inhibitory effects were revealed when higher doses were applied. Enzymatic activity showed progressive inhibition when 532 nm irradiation was applied, declining to 75% at 40 J/cm² (p < 0.01). Conclusions: These outcomes indicate that conformational flexibility and catalytic efficiency occur when applying lower-energy photons at 589 nm, whilst oxidative stress and impaired enzymatic function are induced by higher-energy photons at 532 nm. This is consistent with the biphasic dose–response characteristic of photobiomodulation. Full article

Recent outbreaks of highly pathogenic human RNA viruses from probable zoonotic origin have highlighted the relevance of epidemic preparedness as a society. However, research in vaccinology and virology, as well as epidemiologic surveillance, is often constrained by the biological risk that live virus experimentation entails. These also involve expensive costs, time-consuming procedures, and advanced personnel expertise, hampering market access for many drugs. Most of these drawbacks can be circumvented with the use of pseudotyped viruses, which are surrogate, non-pathogenic recombinant viral particles bearing the surface envelope protein of a virus of interest. Pseudotyped viruses significantly expand the research potential in virology, enabling the study of non-culturable or highly infectious pathogens in a safer environment. Most are derived from lentiviral vectors, which confer a series of advantages due to their superior efficiency. During the past decade, many studies employing pseudotyped viruses have evaluated the efficacy of vaccines or monoclonal antibodies for relevant pathogens such as HIV-1, Ebolavirus, Influenza virus, or SARS-CoV-2. In this review, we aim to provide an overview of the applications of pseudotyped viruses when evaluating the neutralization capacity of exposed individuals, or candidate vaccines and antivirals in both preclinical models and clinical trials, to further help develop effective countermeasures against emerging neutralization-escape phenotypes. Full article

As a crucial reactive oxygen species, hydrogen peroxide (H₂O₂) serves as both a physiological regulator and a pathological indicator in human systems. Its urinary concentration has emerged as a valuable biomarker for assessing metabolic disorders and renal function. While conventional colorimetric determination methods predominantly employ enzymatic or nanozyme catalysts, we present an innovative non-catalytic approach utilizing the redox-responsive properties of organic neutral radicals. Specifically, we designed and synthesized a novel radical TTM-DMODPA based on the tris (2,4,6-trichlorophenyl) methyl (TTM) scaffold, which exhibits remarkable optical tunability and oxidative sensitivity. This system enables dual-mode H₂O₂ quantification: (1) UV-vis spectrophotometry (linear range: 2.5–250 μmol/L, LOD: 1.275 μmol/L) and (2) smartphone-based visual analysis (linear range: 2.5–250 μmol/L, LOD: 3.633 μmol/L), the latter being particularly suitable for point-of-care testing. Validation studies using urine samples demonstrated excellent recovery rates (96–104%), confirming the method’s reliability for real-sample applications. Our work establishes a portable, instrument-free platform for urinary H₂O₂ determination, with significant potential in clinical diagnostics and environmental monitoring. Full article