Search Results (3,072)

Background: Growing evidence highlights the beneficial effects of flavonoids, including anthocyanins, as key components in reducing cardiovascular risk, and emphasizes that incorporating anthocyanin-rich fruits into the daily diet significantly impacts public health. Methods: The effect of bioactive polyphenols from raspberry fruit (RBF) on molecular pathways in inflammation was studied in activated RAW 264.7 macrophages and their protective potential against endothelial dysfunction was analyzed using TNF-α-induced human umbilical vein endothelial cells (HUVECs). Results: The results have shown that RBF extract, along with its anthocyanin and polyphenol fractions, has a significant anti-inflammatory effect in macrophage cell culture by inhibiting the LPS-induced expression of pro-inflammatory genes, including IL-6, IL-1β, TNF-α, and NF-κB. Moreover, RBF and both fractions have demonstrated a protective effect on endothelial function by decreasing the expression of several inflammation-related genes and adhesion molecules, such as IL-6, IL-1β, VCAM-1, ICAM-1, and SELE, in TNF-α-induced HUVECs. Conclusions: The consumption of RBF and/or polyphenol-rich extracts may help prevent the onset of early atherosclerosis. This is attributed to their ability to improve inflammation status and enhance vascular endothelial function. Given the strong anti-inflammatory properties of RBF, incorporating them into a daily diet could significantly reduce the risk of non-communicable diseases related to inflammation. Full article

Background: Artificial sweeteners, widely used as non-nutritive sugar substitutes, are increasingly prevalent in ultra-processed products. Although promoted for weight management due to their minimal caloric content, their impact on systemic inflammation remains uncertain. This systematic review of animal studies aims to evaluate the association between artificial sweetener consumption and inflammatory biomarkers. Methods: A systematic literature search was conducted up to May 2025 across PubMed, Web of Science, and Scopus, following PRISMA guidelines and registered in PROSPERO (CRD420251084004). Risk of bias was assessed using the ARRIVE guidelines and SCYRCLE’s risk of bias tool. Results: Thirty-seven animal studies were included: aspartame (n = 17), sucralose (n = 16), acesulfame potassium (n = 5), and saccharin (n = 4). Protocols varied in terms of dosage, exposure duration, animal models, and assessment of inflammatory outcomes, including C-reactive protein, interleukins (IL-6 and IL-1β), and tumor necrosis factor alpha. Aspartame and sucralose could elevate inflammatory markers, with sucralose also disrupting gut integrity and microbiota. Acesulfame K and saccharin showed variable, dose-dependent effects. Conclusions: This systematic review of animal studies suggests a possible mechanistic association between the consumption of certain artificial sweeteners and systemic inflammation. However, this relationship remains to be clarified and warrants exploration through well-designed, large-scale randomized controlled trials. Full article

The rapid expansion of electric vehicles in high-altitude Andean cities, such as the Metropolitan District of Quito, Ecuador’s capital, presents unique challenges for electrical infrastructure planning, necessitating advanced methodologies that capture behavioral heterogeneity and mass synchronization effects in high-penetration scenarios. This study introduces a hybrid approach that combines agent-based modelling with Monte Carlo simulation and a TimescaleDB architecture project charging demand with quarter-hour resolution through 2040. The model calibration deployed real-world data from 764 charging points collected over 30 months, which generated 2.1 million charging sessions. A dynamic coincidence factor ($F_C=0.222+0.036\ast e^{(-0.0003n)}$) was incorporated, resulting in a 52% reduction in demand overestimation compared to traditional models. The results for the 2040 project show a peak demand of 255 MW (95% CI: 240–270 MW) and an annual consumption of 800 GWh. These findings reveal that non-optimized time-of-use tariffs can generate a critical “cliff effect,” increasing peak demand by 32%, whereas smart charging management with randomization reduces it by 18 ± 2.5%. Model validation yields a MAPE of 4.2 ± 0.8% and an RMSE of 12.3 MW. The TimescaleDB architecture demonstrated processing speeds of 2398.7 records/second and achieved 91% data compression. This methodology offers robust tools for urban energy planning and demand-side management policy optimization in high-altitude contexts, with the source code available to ensure reproducibility. Full article

Energy consumption and environmental pollution pose significant challenges to sustainable development. This study develops a comprehensive coupled framework model that advances the quantitative integration of carbon (C), nitrogen (N), and phosphorus (P) cycles driven by multiple anthropogenic pollution sources. This paper used Panjin city as a case study to analyze the dynamic changes and interconnections among C, N, and P. Results indicated that net anthropogenic carbon inputs (NAI_C) increased by 33% from 2016–2020, while net anthropogenic nitrogen inputs (NAI_N) and net anthropogenic phosphorus inputs (NAI_P) decreased by 14% and 28%, respectively. The primary driver of NAI_C was energy consumption, while wetlands were the dominant carbon sequestration sink. Agricultural production was identified as the primary source of NAI_N and NAI_P, and approximately 4.5% of NAI_N and 2.9% of NAI_P were discharged into receiving water bodies. We demonstrate that human activities and natural processes exhibit dual attributes, producing positive and negative environmental effects. The increase in carbon emissions drives economic growth and industrial restructuring; however, the enhanced economic capacity also strengthens the ability to mitigate pollution through environmental protection measures. Similarly, natural ecosystems, including forests and grasslands, contribute to carbon sequestration and the release of non-point source pollution. The comprehensive environmental impact assessment of C, N, and P revealed that the comprehensive environmental index for Panjin city exhibited an improved trend. The factors of energy structure, energy efficiency, and economic scale promoted NAI_C growth, with the economic scale factor alone accounting for 93% of the total increment. Environmental efficiency factor and population size factor were the primary drivers in reducing NAI_N and NAI_P discharges into the receiving water bodies. We propose a novel management model, ecological restoration, clean energy utilization, resource recycling, and pollution source reduction to achieve systemic governance of C, N, and P inputs. Full article

Based on the Cost Theory and Porter’s Hypothesis, this study focuses on high-carbon-emission enterprises and systematically explores how carbon risk affects their value creation. The sample comprises listed firms in high-carbon-emission industries listed on China’s Shanghai and Shenzhen A-shares during 2012–2022. A carbon risk measurement index is constructed using industrial energy consumption data, and a two-way fixed-effects model is employed to empirically test the relationship between carbon risk and value creation of these enterprises. Further, the internal mechanisms by which debt financing costs and innovation R&D expenditures influence the impact of carbon risk on enterprise value creation are analyzed separately. Finally, differences in the inhibitory effect of carbon risk on value creation across heterogeneous enterprises are examined. The results show that carbon risk significantly reduces value creation. It raises debt financing costs and diverts resources away from innovation, weakening firms’ capacity to create value. The negative effect is stronger for small firms, non-state-owned firms, and younger firms. The findings provide evidence for policymakers to improve carbon pricing mechanisms, for financial institutions to better assess climate risk, and for firms to develop effective carbon risk management strategies. Overall, the study offers practical implications for promoting a green and low-carbon transition in the real economy. Full article

In this study, the effects of batch and continuous grinding on the ceramic floor tile body were investigated in terms of cost, capacity, and technical aspects. In batch milling, a changing speed during grinding was more efficient than a constant speed. Capacity and energy consumption increased as the mill rotation speed increased in continuous grinding. Specific energy consumptions were measured as 36 kW/ton and 43.1 kW/ton, with 1.6 ton/h and 8.375 t/h capacities. Additionally, d₁₀, d₅₀, and d₉₀ values for ground ceramic floor tile bodies were determined to be 2.5, 9.5, and 47.2 µm and 2.5, 9.4, and 48.1 µm for batch and continuous grinding, respectively. No significant difference was observed in the color and shrinkage values, while water absorptions were calculated to be 1.1% and 0.3% as sintering properties for batch and continuous methods, respectively. In the phase analysis of a sintered body prepared using the continuous method, mullite and quartz were observed, while microcline was also analyzed differently from such minerals for the batch one. Structural changes, surface morphology, and roughness were also interpreted by DTA/TG, SEM, and AFM analysis. The presence of plastic clay minerals during the grinding process in batch milling caused non-plastic raw materials not to be ground sufficiently, and sintering characteristics changed. Full article

Background: The hemoglobin-to-red-cell distribution width ratio has emerged as a novel prognostic marker in various clinical settings. However, its association with total bone mineral density in adolescents remains inadequately explored. Methods: This cross-sectional study was based on data from the 2011–2018 National Health and Nutrition Examination Survey, including adolescents aged 12–19 years with complete data on hemoglobin, red cell distribution width, and total bone mineral density. Weighted multivariable linear regression models and generalized additive models were used to evaluate the association between hemoglobin-to-red-cell distribution width and total bone mineral density. A two-piecewise linear regression model was applied to assess potential threshold effects, with log-likelihood ratio tests used to determine the significance of inflection points. Subgroup and interaction analyses were further conducted to examine whether age, sex, race, and milk product consumption modified this association. Results: A total of 3789 adolescents were included. Participants in the highest hemoglobin-to-red-blood-cell distribution width ratio quartile had significantly higher hemoglobin levels, lower red blood cell distribution width, greater total bone mineral density, higher total calcium and blood urea nitrogen levels, and lower body mass index, high-density lipoprotein cholesterol, and serum 25OHD levels compared to lower quartiles. The hemoglobin-to-red-blood-cell distribution width ratio was positively associated with total bone mineral density (fully adjusted β = 0.078, 95% CI: 0.053, 0.104, p < 0.0001). A two-piecewise linear regression model identified an inflection point at the hemoglobin-to-red-cell distribution width ratio = 1.055; the positive association became stronger above this threshold (β = 0.143 vs. β = 0.039 below the threshold, p = 0.003 for nonlinearity). Subgroup analysis revealed significant gender interactions (p < 0.0001). A higher HRR was significantly associated with greater total BMD in males (β = 0.130, 95% CI: 0.089–0.171, p < 0.0001), whereas no significant association was observed in females (β = −0.009, 95% CI: −0.043–0.025, p = 0.604). Positive associations were also observed among participants aged 12–15 years, non-Hispanic Whites, non-Hispanic Blacks, other Hispanics, Mexican Americans, and frequent milk consumers. Conclusions: Our results indicate that the hemoglobin-to-red-cell distribution width ratio shows a potential association with bone mineral density in male adolescents, which may offer supportive value for bone health assessment but requires further validation. Full article

Corbicula fluminea protein (CFP) and cyanidin-3-O-glucoside (C3G) are natural nutrient fortifiers. During consumption or processing, they may interact with each other, inducing alternations in their structural and functional properties. However, nothing was known about the mechanism of their interaction and their synergistic antioxidant effect. In this research, C3G was physically mixed with CFP to simulate practical scenarios. The impact of the presence of C3G on the multispectral characteristics, antioxidant activity, and particle properties of CFP was examined and compared to chemically fabricated C3G-CFP covalent conjugates. The results indicate that C3G tended to spontaneously bind to CFP and formed compact non-covalent complex, with hydrophobic forces predominantly governing the interaction. This binding resulted in the statically quenched intrinsic fluorescence of CFP, accompanied by a dynamic model. Moreover, C3G preferentially induced Trp residue in CFP exposed to a more polar microenvironment, yet it exerted nearly no effects on CFP when analyzed using ultraviolet–visible (UV-Vis) spectroscopy and synchronous fluorescence spectroscopy (SFS). Additionally, although the formed non-covalent complex demonstrated strengthened antioxidant capacity, C3G displayed an antagonistic effect with CFP, whereas lower C3G concentrations led to synergistic effects in covalent conjugates. These findings provide new insights into the effective application of C3G and CFP as nutritional antioxidants. Full article

Conventional separation methods often prove ineffective for complex, refractory high-phosphorus iron ores. Recent advances propose a coal-based direct reduction dephosphorization-magnetic separation process, achieving significant dephosphorization efficiency. This review systematically analyzes phosphorus occurrence states in high-phosphorus oolitic iron ores across global deposits, particularly within iron minerals. We categorize contemporary research and elucidate dephosphorization mechanisms during coal-based direct reduction. Key factors influencing iron mineral phase transformation, iron enrichment, and phosphorus removal are comprehensively evaluated. Phosphorus primarily exists as apatite and collophane gangue m horization agents function by: (1) inhibiting phosphorus-bearing mineral reactions or binding phosphorus into soluble salts to prevent incorporation into metallic iron; (2) enhancing iron oxide reduction and coal gasification; (3) disrupting oolitic structures, promoting metallic iron particle growth, and improving the intergrowth relationship between metallic iron and gangue. Iron mineral phase transformations follow the sequence: Fe₂O₃ → Fe₃O₄ → FeO (FeAl₂O₄, Fe₂SiO₄) → Fe. Critical parameters for effective dephosphorization under non-reductive phosphorus conditions include reduction temperature, duration, reductant/dephosphorization agent types/dosages. Future research should focus on: (1) investigating phosphorus forms in iron minerals for targeted ore utilization; (2) reducing dephosphorization agent consumption and developing sustainable alternatives; (3) refining models for metallic iron growth and improving energy efficiency; (4) optimizing reduction atmosphere control; (5) implementing low-carbon emission strategies. Full article

High energy consumption in Chinese rural residential buildings, caused by rudimentary construction methods and the poor thermal performance of building envelopes, poses a significant challenge to national sustainability and “dual carbon” goals. To address this, this study proposes a comprehensive modeling and analysis framework integrating an improved Bio-inspired Black-winged Kite Optimization Algorithm (IBKA) with Support Vector Regression (SVR). Firstly, to address the limitations of the original B-inspired BKA, such as premature convergence and low efficiency, the proposed IBKA incorporates diversification strategies, global information exchange, stochastic behavior selection, and an NGO-based random operator to enhance exploration and convergence. The improved algorithm is benchmarked against BKA and six other optimization methods. An orthogonal experimental design was employed to generate a dataset by systematically sampling combinations of influencing factors. Subsequently, the IBKA-SVR model was developed for energy consumption prediction and analysis. The model’s predictive accuracy and stability were validated by benchmarking it against six competing models, including GA-SVR, PSO-SVR, and the baseline SVR and so forth. Finally, to elucidate the model’s internal decision-making mechanism, the SHAP (SHapley Additive exPlanations) interpretability framework was employed to quantify the independent and interactive effects of each influencing factor on energy consumption. The results indicate that: (1) The IBKA demonstrates superior convergence accuracy and global search performance compared with BKA and other algorithms. (2) The proposed IBKA-SVR model exhibits exceptional predictive accuracy. Relative to the baseline SVR, the model reduces key error metrics by 37–40% and improves the R² to 0.9792. Furthermore, in a comparative analysis against models tuned by other metaheuristic algorithms such as GA and PSO, the IBKA-SVR consistently maintained optimal performance. (3) The SHAP analysis reveals a clear hierarchy in the impact of the design features. The Insulation Thickness in Outer Wall and Insulation Thickness in Roof Covering are the dominant factors, followed by the Window-wall Ratios of various orientations and the Sun space Depth. Key features predominantly exhibit a negative impact, and a significant non-linear relationship exists between the dominant factors (e.g., insulation layers) and the predicted values. (4) Interaction analysis reveals a distinct hierarchy of interaction strengths among the building design variables. Strong synergistic effects are observed among the Sun space Depth, Insulation Thickness in Roof Covering, and the Window-wall Ratios in the East, West, and North. In contrast, the interaction effects between the Window-wall Ratio in the South and other variables are generally weak, indicating that its influence is approximately independent and linear. Therefore, the proposed bio-inspired framework, integrating the improved IBKA with SVR, effectively predicts and analyzes residential building energy consumption, thereby providing a robust decision-support tool for the data-driven optimization of building design and retrofitting strategies to advance energy efficiency and sustainability in rural housing. Full article

As the world is technologically advancing, the integration of FSO communication in non-terrestrial platforms is transforming the landscape of global connectivity. By enabling high-data-rate inter-satellite links, secure UAV–ground channels, and efficient HAPS backhaul, FSO technology is paving the way for sustainable 6G non-terrestrial networks. However, the stringent requirement for precise line-of-sight (LoS) alignment between the optical transmitter and receivers poses a hindrance in practical deployment. As non-terrestrial missions require continuous movement across the mission area, the platform is subject to vibrations, dynamic motion, and environmental disturbances. This makes maintaining the LoS between the transceivers difficult. While fine-pointing mechanisms such as fast steering mirrors and adaptive optics are effective for microradian angular corrections, they rely heavily on an initial coarse alignment to maintain the LoS. Coarse pointing modules or gimbals serve as the primary mechanical interface for steering and stabilizing the optical beam over wide angular ranges. This survey presents a comprehensive analysis of coarse pointing and gimbal modules that are being used in FSO communication systems for non-terrestrial platforms. The paper classifies gimbal architectures based on actuation type, degrees of freedom, and stabilization strategies. Key design trade-offs are examined, including angular precision, mechanical inertia, bandwidth, and power consumption, which directly impact system responsiveness and tracking accuracy. This paper also highlights emerging trends such as AI-driven pointing prediction and lightweight gimbal design for SWap-constrained platforms. The final part of the paper discusses open challenges and research directions in developing scalable and resilient coarse pointing systems for aerial FSO networks. Full article

The wind–solar–storage–thermal combined power generation system is one of the key measures for China’s energy structure transition, and rational capacity planning of each generation entity within the system is of critical importance. First, this paper addresses the uncertainty of wind and photovoltaic (PV) power outputs through scenario-based analysis. Considering the diversity of generation entities and their complex interest demands, a bi-level capacity optimization framework based on game theory is proposed. In the upper-level framework, a game-theoretic method is designed to analyze the multi-agent decision-making process, and the objective function of capacity allocation for multiple entities is established. In the lower-level framework, multi-objective optimization is performed on utility functions and node voltage deviations. The Nash equilibrium of the non-cooperative game and the Shapley value of the cooperative game are solved to study the differences in the capacity allocation, economic benefits, and power supply stability of the combined power generation system under different game modes. The case study results indicate that under the cooperative game mode, when the four generation entities form a coalition, the overall system achieves the highest supply stability, the lowest carbon emissions at 30,195.29 tons, and the highest renewable energy consumption rate at 53.93%. Moreover, both overall and individual economic and environmental performance are superior to those under the non-cooperative game mode. By investigating the capacity configuration and joint operation strategies of the combined generation system, this study effectively enhances the enthusiasm of each generation entity to participate in the energy market; reduces carbon emissions; and promotes the development of a more efficient, environmentally friendly, and economical power generation model. Full article

Consumption of meat singed with non-standard fuels is a common practice in many low- and middle-income settings, yet it may introduce combustion-derived toxicants with serious health consequences. While the toxicological effects of pollutants such as polycyclic aromatic hydrocarbons and heavy metals are well documented, the specific impact of singed meat consumption on endocrine regulation remains poorly understood. Of particular concern is the reproductive hormonal network, which not only serves as a sensitive biomarker of systemic disruption but also represents an evolutionary safeguard of fertility and generational continuity. Our study addresses this knowledge gap using male Wistar rats fed for 90 days (week 0 to week 12) on diets containing increasing proportions (25%, 50%, 75%) of meat singed with firewood, liquefied petroleum gas (LPG), or tyres. Firewood- and tyre-singed meat induced dose- and source-dependent toxicity, including hepatocellular injury, impaired protein metabolism, elevated blood urea nitrogen and creatinine, organ hypertrophy, and pronounced oxidative stress. Hormonal analysis revealed reduced testosterone alongside increased FSH, LH, and prolactin, indicating hypothalamic–pituitary–gonadal axis disruption and reproductive risk. In contrast, LPG-singed meat caused only minor alterations. These findings highlight reproductive hormones as sensitive biomarkers, underscoring the health risks of singeing practices and their evolutionary implications for fertility and population fitness. Full article

Climate change mitigation for the built environment has become a subject of greatest urgency, as buildings account for nearly 40% of total energy consumption and nearly one-third of total CO₂ emissions. While environmental, social, and governance (ESG) indicators are increasingly used to monitor sustainability performance, their collective role in impacting building-related emissions is yet largely under-investigated. The current research closes that gap through an examination of the ESG dimension–CO₂ emissions intersection of 180 nations from 2000 to 2022, in the hope of illuminating how environmental, social, and governance elements interact to facilitate decarbonization. The research is guided by a multi-method design, including econometric examination, cluster modeling, and machine learning techniques, which provide causal evidence and predictive analysis, respectively. The findings reveal that the deployment of renewable energy significantly reduces emissions, while per capita energy use and PM_2.5 air pollution exacerbate this effect. The social indicators show mixed results: learning, women’s parliamentary representation, and women’s workforce representation reduce emissions, while food production and growth among the lowest-income individuals demonstrate higher emissions. Governance demonstrates mixed results as well, with good regulation reducing emissions under specific conditions yet primarily supporting high-income countries with superior infrastructure. The examination of clusters reveals that ESG-balanced performance is retained by countries in the low-emission clusters, whereas decentralized ESG pillars are associated with higher emissions. Machine learning confirms the existence of non-linear effects and identifies PM_2.5 exposure and renewable energy deployment as the strongest predictors of the relationship. In summary, the findings suggest that successful policies for decarbonizing the built environment are constructed upon the consistency of environmental, social, and governance plans, rather than single steps. Full article

Waste management poses escalating threats to environmental sustainability, particularly with municipal solid waste (MSW) growth. Incineration, a widely adopted method for reducing waste volume, produces millions of tons of municipal solid waste incineration fly ash (MSWIFA) each year. Despite its high toxicity and classification as a hazardous solid waste, its ultrafine particle size and pozzolanic activity offer potential for its use in construction materials. In this study, MSWIFA was used to replace 6%, 12%, 18% and 24% of cementitious materials, and the effect of MSWIFA substitution rate on the workability, mechanical properties, microstructure, and durability of UHPC was studied. Furthermore, the study assessed the solidification capacity of the UHPC for heavy metal ions and quantitatively analyzed its eco-economic benefits. The results show that, under standard curing conditions, substituting 12% of cementitious materials with MSWIFA significantly modified UHPC hydration, shortened setting time, reduced fluidity, and increased wet packing density. The 28-day compressive strength reached 134.63 MPa, comparable to the control group. Concurrently, fluidity, durability, and heavy metal leaching all met the required standards, with energy consumption reduced by 14.86%, carbon emissions lowered by 12.76%, and economic costs decreased by 6.41%. This study provides a feasible solution for recycling MSWIFA into non-hazardous concrete, facilitating sustainable hazardous waste management and mitigating heavy metal-related environmental pollution. Full article