Search Results (18,782)

Tactile Internet (TI) is an innovative paradigm for emerging generations of communication systems that support ultra-low latency and highly robust transmission of haptics, actuation, and immersive communication in real time. It is considered a critical facilitator for remote surgery, industrial automation, and extended reality (XR). Originally intended as a flagship application for the fifth-generation (5G) networks, their strict constraints, especially the one-millisecond end-to-end latency, ultra-high reliability, and seamless adaptation, present formidable challenges. These challenges are the bottleneck for evolution to sixth-generation (6G) networks; thus, new architects and technologies are urgently required. This survey systematically discusses the most important underlying technologies for TI and immersive communications. It especially highlights using software-defined networking (SDN) and edge intelligence (EI) as enabling technologies. SDN improves the programmability, adaptability, and dynamic control of network infrastructures. In contrast, EI exploits intelligence-based artificial intelligence (AI)-driven decision-making at the network edge for latency optimization, resource usage, and service offering. Moreover, this work describes other enabling technologies, including network function virtualization (NFV), digital twin, quantum computing, and blockchain. Furthermore, the work investigates the recent achievements and studies in which SDN and EI are combined in TI and presents their effect on latency reduction, optimum network utilization, and service stability. A comparison of several State-of-the-Art methods is performed to determine present limitations and gaps. Finally, the work provides open research problems and future trends, focusing on the importance of intelligent, autonomous, and scalable network topologies for defining the paradigm of TI and immersive communication systems. Full article

Background: Despite percutaneous coronary intervention (PCI) for revascularization, patients with acute coronary syndrome (ACS) still face residual risks of adverse outcomes. Insulin resistance (IR) and renal impairment are independent predictors of poor prognosis in these patients, yet their interaction and underlying mechanisms linked to post-PCI outcomes remain incompletely elucidated. Methods: A retrospective cohort study was conducted involving patients with ACS who underwent PCI at the Third People’s Hospital of Chengdu from July 2018 to December 2020. Insulin resistance (IR) was quantified using the triglyceride–glucose (TyG) index, and renal function was evaluated via the estimated glomerular filtration rate (eGFR). The primary endpoint was major adverse cardiovascular events (MACEs), a composite of all-cause death, non-fatal myocardial infarction, non-fatal stroke, and unplanned revascularization. Multivariable Cox proportional hazards regression and mediation analyses were applied to explore the associations of TyG index and eGFR with patient prognosis, and to quantify the mediating effect of eGFR on the relationship between TyG index and prognosis. Results: A total of 1340 patients with ACS were included in the final analysis. Over a median follow-up duration of 31.02 (interquartile range [IQR]: 27.34–35.03) months, 124 patients (9.25%) experienced MACEs. After adjusting for potential confounders, both the TyG index and eGFR were identified as significant independent predictors of MACEs in the overall population and across predefined subgroups. Specifically, each one-unit increase in the TyG index was associated with a 73.8% higher risk of MACEs (HR 1.738; 95% CI 1.273–2.372), whereas each ten-unit decrease in eGFR was linked to a 12.7% increased MACEs risk (HR 1.127; 95% CI 1.032–1.232). Importantly, after further adjustment for confounders, eGFR significantly mediated 9.63% of the total effect of the TyG index on MACEs risk. Conclusions: Renal impairment partially mediates the association between IR and adverse cardiovascular outcomes in ACS patients undergoing PCI. This finding underscores the clinical importance of the metabolic–cardiorenal axis in this population, suggesting that a comprehensive assessment targeting both IR and renal function-related pathways may enhance risk-stratification accuracy and optimize therapeutic strategies for ACS patients. Full article

Background: Obesity is a multifactorial metabolic disorder influenced not only by excessive caloric intake but also by micronutrient imbalances such as zinc deficiency. Emerging evidence suggests that zinc regulates microRNA (miRNA) biogenesis and expression, linking nutritional status to metabolic regulation. Objective: This review delineates the molecular interplay between zinc and miRNAs in obesity, emphasizing the mechanistic, clinical, and translational relevance of zinc-sensitive miRNAs in adipogenesis, insulin resistance, inflammation, and oxidative stress. Results: Zinc deficiency alters miRNA expression profiles associated with metabolic dysregulation. Key miRNAs—miR-21, miR-34a, miR-122, and miR-144-3p—are consistently modulated by zinc status, influencing inflammation, lipid metabolism, and insulin signaling. Zinc repletion restores several miRNAs (e.g., miR-10b, miR-155, miR-145), suggesting reversibility, while excessive zinc may upregulate miR-144-3p and exacerbate oxidative stress. Circulating and exosomal miRNAs show promise as dynamic biomarkers for zinc intervention efficacy. Methods: A literature search was performed in 4 databases up to August 2025 using keywords related to zinc, miRNAs, and obesity. Eligible studies included both preclinical and human research evaluating zinc status or supplementation and miRNA expression in metabolic contexts. Conclusion: Maintaining optimal zinc levels may normalize miRNA expression and improve insulin sensitivity. The “zinc–miRNA axis” represents a novel frontier for precision nutrition in obesity management. Full article

Industrial Internet of Things (IIoT) systems face severe security and trust challenges, particularly under cross-domain data sharing and federated orchestration. We present QuantumTrust-FedChain, a cyber-resilient federated learning framework integrating quantum variational trust modeling, blockchain-backed provenance, and Byzantine-robust aggregation for secure IIoT collaboration in 6G networks. The architecture includes a Quantum Graph Attention Network (Q-GAT) for modeling device trust evolution using encrypted device logs. This consensus-aware federated optimizer penalizes adversarial gradients using stochastic contract enforcement, and a shard-based blockchain for real-time forensic traceability. Using datasets from SWaT and TON IoT, experiments show 98.3% accuracy in anomaly detection, 35% improvement in defense against model poisoning, and full ledger traceability with under 8.5% blockchain overhead. This framework offers a robust and explainable solution for secure AI deployment in safety-critical IIoT environments. Full article

Japanese quail production can be optimized by selecting appropriate dietary lipid sources, yet comparative effects on performance and egg quality during the laying phase are not fully established. This study evaluated the impact of five lipid sources, namely soybean oil, corn oil, canola oil, sunflower oil, and poultry fat, on performance, egg quality, nutrient metabolism, serum metabolites, and organ traits of 350 Japanese quail aged 60 days with an average weight of 170 ± 10 g. Birds were assigned to diets containing 2800 kcal/kg in a completely randomized design with 10 replicates of seven birds each. Performance was recorded over three 28-day periods and egg quality assessed at the end of each period; at 84 days, one bird per replicate was sampled for nutrient metabolism, serum metabolites, and organ characteristics, and a metabolism trial estimated metabolizability coefficients and metabolizable energy. Data were analyzed by Tukey’s test at the 5% level. Egg production (p = 0.010) and marketable egg production (p = 0.008) were highest with soybean, corn, and sunflower oils, while feed conversion per dozen eggs was less efficient with canola oil (p = 0.048). Egg quality differed in specific gravity (p = 0.027), yolk color (p = 0.008), Haugh unit (p = 0.011), and air cell size (p = 0.001), with poultry fat improving yolk color and Haugh unit. Canola oil increased dry matter (p = 0.027) and ether extract digestibility (p = 0.026), while serum metabolites, organ weights, and reproductive traits were not affected (p > 0.05). All diets supported physiological health, and lipid sources can be chosen according to cost and availability to optimize quail production without compromising performance or health. Full article

As the environmental burden of traditional plastics continues to grow, bioplastics (BPs) have emerged as a promising alternative due to their renewable origins and potential for biodegradability. However, the most popular anaerobic systems (ASs)—anaerobic digestion (AD), acidogenic fermentation (AF), and enzyme hydrolysis (EH)—for BPs degradation still face many challenges, e.g., low degradation efficiency, process instability, etc. As a sustainable clean energy technology, bioelectrochemical systems (BESs) have demonstrated strong potential in the treatment of complex organic waste when integrated with ASs. Nevertheless, research on the synergistic degradation of BPs using BES-ASs remains relatively limited. This review systematically summarizes commonly used anaerobic degradation methods for BPs, along with their advantages and limitations, and highlights the BES-AS as an innovative strategy to enhance BPs degradation efficiency. BESs can accelerate the decomposition of complex polymer structures through the activity of electroactive microorganisms, while also offering benefits such as energy recovery and real-time process monitoring. When coupled with anaerobic digestion, the BES-AS demonstrates significant synergistic effects, improving degradation efficiency and promoting the production of high-value-added products such as volatile fatty acids (VFAs) and biogas, thereby showing great application potential. This review outlines current research progress, identifies key knowledge gaps in mechanism elucidation, system design, source recovery, etc., and proposes future research directions. These include system optimization, microbial community engineering, development of advanced electrode materials, and omics-based mechanistic studies. Advancing multidisciplinary integration is expected to accelerate the practical application of BES-ASs in BP waste management and contribute to achieving the goals of sustainability, efficiency, and circular utilization. Full article

This paper tackles a core challenge in reverse engineering: high-fidelity reconstruction of continuous B-spline surfaces from discrete point clouds, where optimal knot placement remains pivotal yet not fully resolved. We propose a new fitting method based on the Hungry Predation Algorithm (HPA) to improve efficiency, accuracy, and robustness. This method introduces a hybrid knot-guidance strategy that combines geometry-aware preselection with a complexity-driven probabilistic distribution to address knot placement. On the optimization side, HPA simulates starvation-driven predator–prey dynamics to enhance global search capability, maintain population diversity, and accelerate convergence. We also develop an adaptive parameter adjustment framework that automatically tunes key settings according to surface complexity and accuracy thresholds. Comparative experiments against classical approaches, six state-of-the-art optimizers, and the commercial CAD system CATIA demonstrate HPA’s superiority in control-point reduction, fitting accuracy, and computational efficiency. This method shows high applicability to engineering-scale tasks (e.g., ship hull design), where the point-to-surface RMSE (e.g., <10⁻³ L_max) achieved satisfies stringent requirements for downstream hydrodynamic performance analysis and manufacturing. Full article

Glaucoma is a major ocular neurodegenerative disease and a leading cause of irreversible blindness worldwide, with prevalence projected to exceed 110 million by 2040. Although lowering intraocular pressure (IOP) remains the only proven treatment, glaucoma arises from a complex interplay of genetic, local, and systemic factors—including oxidative stress, vascular dysregulation, mitochondrial dysfunction, and neuroinflammation. Emerging evidence suggests that modifiable lifestyle factors may influence these pathogenic pathways. In this review, higher dietary nitrate from leafy greens is consistently associated with lower primary open-angle glaucoma risk, aligning with nitric-oxide-mediated endothelial support and more stable ocular perfusion pressure. Flavonoids (anthocyanins and flavanols), carotenoids (lutein/zeaxanthin), and B vitamins have strong biological rationale for glaucoma prevention but have limited support from long-term, large population-based studies. The effect of polyunsaturated fats on glaucoma remains inconsistent and warrants source-(plant vs. animal) and substitution-based analyses. Consistent protective effects of aerobic exercise and high-quality sleep may be associated with favorable metabolic profiles and ocular perfusion, potentially mitigating retinal ganglion cell loss. Conversely, smoking and alcohol use are frequently coupled with poorer diet quality (e.g., lower vegetable intake) and heightened oxidative stress, which may exacerbate glaucomatous neurodegeneration. However, much of the current literature is constrained by cross-sectional designs, reliance on self-reported food frequency questionnaires, and insufficient use of structural endpoints such as retinal nerve fiber layer imaging. This review focuses on the potential of lifestyle modification and future directions in prevention and treatment strategies for glaucoma, highlighting the need for large-scale, multi-ethnic, genotype-stratified longitudinal studies and randomized controlled trials to establish causality and define optimal intervention strategies. Full article

The high-efficiency and clean utilization of coal resources is a key strategy for new energy development, and converting coal into carbon materials offers a promising route to valorize bituminous coal. However, fabricating high-performance bituminous coal-derived carbon for sodium ion (Na⁺) insertion/extraction remains a major challenge, as it is difficult to regulate the carbon’s microstructural properties to match Na⁺ storage demands. Herein, we propose a molten salt-assisted carbonization strategy to prepare bituminous coal-derived hard carbon (HC) for use as a sodium-ion battery (SIB) anode material, and we focus on regulating the structure of carbon. The results show that as-prepared HC exhibits significantly enhanced electrochemical performance for Na⁺ storage when the molar ratio of NaCl to KCl is 1:1. The optimized material achieves a reversible capacity of 366.7 mAh g⁻¹ at the current density of 100 mA g⁻¹ after 60 cycles and retains 99% of its initial capacity after 500 cycles at a current density of 1 A g⁻¹. The main finding is that the lattice spacing can be regulated by tuning the composition of the molten salt, and anode performance is enhanced remarkably by changes in the HC structure. This work provides a feasible strategy for designing and preparing a bituminous coal-derived carbon anode material for use in the energy storage field. Full article

This paper proposes two improved algorithms, the DE-PSO algorithm, which combines differential evolution and phased strategy, and the hybrid particle swarm optimization algorithm integrating whale algorithm (WOAPSO), which combines the whale optimization mechanism. Compared to traditional calibration methods (such as the Newmark three- and two-parameter methods), which rely on empirical simplified models, adapting them to the complex seismic nonstationarity and multipeak characteristics is difficult. However, although intelligent optimization algorithms, such as particle swarm optimization (PSO) and differential evolution (DE) have improved calibration accuracy in recent years, insufficient convergence stability and low computational efficiency, among other problems, persist. Therefore, based on experiments, the performances of these algorithms were compared with those of standard PSO, traditional DE, and other algorithms. The results demonstrate the significant superiority of DE-PSO and WOAPSO. In 50 repeated experiments, the fitness standard deviation (STD) was significantly reduced, and the algorithms achieved rapid convergence by the mid-iteration stage, which effectively resolves the issues of premature convergence and local oscillation tendencies inherent in the standard Particle Swarm Optimization algorithm. Regarding the key parameters ($T_g$, ${\beta }_{max}$, $\gamma$) of the standard, the STD of the improved algorithm approached zero, verifying its strong adaptability to multimodal optimization problems. Furthermore, the DE-PSO algorithm had the best performance in balancing computational efficiency and stability, with a convergence speed that is three times faster than that of standard DE algorithm while maintaining the lowest parameter volatility. This study provides an efficient algorithmic tool for the rapid analysis of strong motion records and the efficient calibration of design response spectra, which has implications for the seismic optimization design of complex structures and can be guided by regulations, contributing to engineering seismic practice. Full article

Optimizing nutrient formulations is essential to improving the biomass yield and C-phycocyanin (C-PC) productivity of Spirulina sp., a cyanobacterium with wide-ranging applications in food, pharmaceutical, and biotechnological industries. This study evaluated the effects of macronutrient modifications on growth and pigment biosynthesis using a two-level full factorial design across eight Zarrouk-based formulations compared to the standard medium. Cultivation experiments were conducted in triplicate, and growth was evaluated using linear growth rate, maximum optical density (OD₆₈₀), and dry biomass, while C-PC was quantified in crude extracts (PCL), dried biomass (PCD), and the purity index (PI). Among the tested formulations, F2 (16 g/L NaHCO₃, 5 g/L NaNO₃, 0.25 g/L K₂HPO₄) achieved the highest biomass productivity, yielding a 37.6% increase in dry weight and a 38.1% improvement in daily productivity compared to the control. In contrast, F3 (16 g/L NaHCO₃, 5 g/L NaNO₃, 1 g/L K₂HPO₄) yielded the highest C-PC content, nearly doubling both PCL and PCD values and enhancing pigment purity by 40.2%. ANOVA and interaction analyses confirmed that carbon and nitrogen synergistically promoted biomass formation, while phosphorus had a strong effect on pigment biosynthesis through C:N:P interactions. These findings demonstrate that Spirulina sp. requires distinct nutrient balances for optimal growth and pigment formation. Formulation F2 is ideal for maximizing biomass productivity, whereas F3 is optimal for high-value C-PC production. The results provide a rational framework for designing nutrient-efficient cultivation systems to advance sustainable Spirulina-based biomanufacturing. Full article

To address the limitation that single-index evaluation fails to fully reflect the development performance of reservoirs of different types and at various development stages, a multi-index comprehensive evaluation system featuring the workflow of “index screening–weight determination–model evaluation–strategy guidance” was established. Firstly, the grey correlation analysis method (with a correlation degree threshold set at 0.65) was employed to screen 12 key evaluation indicators, including reservoir physical properties (porosity, permeability) and development dynamics (recovery factor, water cut, well activation rate). Subsequently, the fuzzy analytic hierarchy process (FAHP, for subjective weighting, with the consistency ratio (CR) of expert judgments < 0.1) was coupled with the attribute measurement method (for objective weighting, with information entropy redundancy < 5%) to determine the indicator weights, thereby balancing the influences of subjective experience and objective data. Finally, two evaluation models, namely the fuzzy comprehensive decision-making method and the unascertained measurement method, were constructed to conduct evaluations on 308 reservoirs in the Liaohe Oilfield (covering five major categories: integral medium–high-permeability reservoirs, complex fault-block reservoirs, low-permeability reservoirs, special lithology reservoirs, and thermal recovery heavy oil reservoirs). The results indicate that there are 147 high-efficiency reservoirs categorized as Class I and Class II in total. Although these reservoirs account for 47.7% of the total number, they control 71% of the geological reserves (154,548 × 10⁴ t) and 78% of the annual oil production (738.2 × 10⁴ t) in the oilfield, with an average well activation rate of 65.4% and an average recovery factor of 28.9. Significant quantitative differences are observed in the development characteristics of different reservoir types: Integral medium–high-permeability reservoirs achieve an average recovery factor of 37.6% and an average well activation rate of 74.1% by virtue of their excellent physical properties (permeability mostly > 100 mD), with Block Jin 16 (recovery factor: 56.9%, well activation rate: 86.1%) serving as a typical example. Complex fault-block reservoirs exhibit optimal performance at the stage of “recovery degree > 70%, water cut ≥ 90%”, where 65.6% of the blocks are classified as Class I, and the recovery factor of blocks with a “good” rating (42.3%) is 1.8 times that of blocks with a “poor” rating (23.5%). For low-permeability reservoirs, blocks with a rating below medium grade account for 68% of the geological reserves (8403.2 × 10⁴ t), with an average well activation rate of 64.9%. Specifically, Block Le 208 (permeability < 10 mD) has an annual oil production of only 0.83 × 10⁴ t. Special lithology reservoirs show polarized development performance, as Block Shugu 1 (recovery factor: 32.0%) and Biantai Buried Hill (recovery factor: 20.4%) exhibit significantly different development effects due to variations in fracture–vug development. Among thermal recovery heavy oil reservoirs, ultra-heavy oil reservoirs (e.g., Block Du 84 Guantao, with a recovery factor of 63.1% and a well activation rate of 92%) are developed efficiently via steam flooding, while extra-heavy oil reservoirs (e.g., Block Leng 42, with a recovery factor of 19.6% and a well activation rate of 30%) are constrained by reservoir heterogeneity. This system refines the quantitative classification boundaries for four development levels of water-flooded reservoirs (e.g., for Class I reservoirs in the high water cut stage, the recovery factor is ≥35% and the water cut is ≥90%), as well as the evaluation criteria for different stages (steam huff and puff, steam flooding) of thermal recovery heavy oil reservoirs. It realizes the transition from traditional single-index qualitative evaluation to multi-index quantitative evaluation, and the consistency between the evaluation results and the on-site development adjustment plans reaches 88%, which provides a scientific basis for formulating development strategies for the Liaohe Oilfield and other similar oilfields. Full article

The development of porous carbon materials that meet the demands of commercial supercapacitors is challenging, primarily due to the requirements for high energy and power density, as well as large-scale manufacturing capabilities. Herein, we present a sustainable and cost-effective method for synthesizing N–O–S co-doped hierarchical porous carbons (designated as ALK_x) from ammonium lignosulfonate (AL), an industrial by–product. This process employs a low KOH/AL mass ratio (x ≤ 0.75) and a carbonization temperature of 900 °C. The resulting materials, ALK₀.₅₀ and ALK_0.75, exhibit an exceptionally high specific surface area (>2000 m² g⁻¹), a well-balanced micro-mesoporous structure, and tunable heteroatom content, which collectively enhance their electrochemical performance in both aqueous and ionic liquid electrolytes. Notably, ALK_0.75 features a heteroatom content of 13.2 at.% and a specific surface area of 2406 m² g⁻¹, owing to its abundant small mesopores. When tested as an electrode in a two–electrode supercapacitor utilizing a 6 M KOH electrolyte, it achieves a high specific capacitance of 250 F g⁻¹ at a current density of 0.25 A g⁻¹ and retains 197 F g⁻¹ even at 50 A g⁻¹, demonstrating remarkable rate capability. In contrast, ALK_0.50, characterized by a lower heteroatom content and an optimized pore structure, exhibits superior compatibility with the ionic liquid electrolyte EMIMBF₄. A symmetric supercapacitor constructed with ALK_0.50 electrodes attains a high energy density of 90.2 Wh kg⁻¹ at a power density of 885.5 W kg⁻¹ (discharge time of 60 s). These findings provide valuable insights into heteroatom doping and the targeted regulation of pore structures in carbon materials, while also highlighting new opportunities for the high-value utilization of AL. Full article

The accuracy of Precise Orbit Determination (POD) for Global Navigation Satellite Systems (GNSS) critically depends on optimal tracking station selection. This study proposed and validates a novel framework that integrates a hybrid-weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model with spherical k-means clustering, effectively resolving the challenge of balancing station data quality with uniform spatial distribution. The framework generates by first a comprehensive quality score for each station based on 40 indicators and then selects the top-scoring station from distinct geographical clusters to construct a well-distributed, high-quality network. To validate the methodology, we performed multi-GNSS POD using networks of 30, 60, and 90 stations selected by the proposed framework. The accuracy was assessed via two independent methods: orbit comparisons (Root Mean Square, RMS) against final Analysis Center (AC) orbits and Satellite Laser Ranging (SLR) validation. The results demonstrate that the optimized 60-station network (e.g., RMS of ~2.5, 5.3, 2.1, and 5.4 cm for GPS, GLONASS, Galileo, and BDS, respectively) achieves an accuracy comparable to that of a 90-station network. Moreover, a 30-station globally uniform network outperforms a 90-station network of high-quality but spatially clustered stations. This study provides an objective and quantitative solution for establishing efficient and reliable GNSS tracking networks, directly benefiting ACs and other high-precision applications. Full article

Sesame seed oil is a bioactive-rich lipid source, notable for lignans, tocopherols, and unsaturated fatty acids that underpin its antioxidant and cardioprotective properties. This study optimized two innovative, non-thermal extraction techniques—pulsed electric field (PEF) and ultrasound bath-assisted extraction (UBAE)—to maximize yield and preserve oil quality for functional food applications. A blocked definitive screening design combined with response surface methodology modeled the effects of energy power (X₁, 60–100%), liquid-to-solid ratio (X₂, 10–20 mL/g), and extraction time (X₃, 10–30 min) on fat content, DPPH antiradical activity, and oxidative stability indices (Conjugated Dienes, CDs/Conjugated Trienes, CTs). UBAE achieved the highest fat yield—59.0% at low energy (60%), high X₂ (20 mL/g), and short X₃ (10 min)—while PEF maximized DPPH to 36.0 μmol TEAC/kg oil at high energy (100%), moderate X₂ (17 mL/g), and short X₃ (10 min). CDs were minimized to 19.78 mmol/kg (UBAE, 60%, 10 mL/g, 10 min) and CTs to 3.34 mmol/kg (UBAE, 60%, 12 mL/g, 10 min). Partial least squares analysis identified X₂ and X₃ as the most influential variables (VIP > 0.8), with energy–time interplay (X₁ × X₃) being critical for antioxidant capacity. Compared to cold-pressing and Soxhlet extraction, PEF and cold-pressing retained higher antioxidant activity (~19 μmol TEAC/kg) and oxidative stability (TBARS ≤ 0.30 mmol MDAE/kg), while Soxhlet—though yielding 55.65% fat—showed the poorest quality profile (Totox value > 560). Both non-thermal techniques can deliver bioactive-rich sesame oil with lower oxidative degradation, supporting their application in functional foods aimed at improving dietary antioxidant intake and mitigating lipid oxidation burden. PEF at high energy/short time and UBAE at low energy/short time present complementary, scalable options for producing high-value edible oils aligned with human health priorities. As a limitation, we did not directly quantify lignans or tocopherols in this study, and future work will address their measurement and bioaccessibility. Full article