Search Results (1,633)

In tunnel blasting, an analytical solution for dynamic stress in the surrounding rock of adjacent tunnels is critical for dynamic response analysis, mechanical evaluations, and crack propagation control. Previous studies on stress field analytical solutions primarily modeled rock as a linear elastic material, focusing mainly on the P-wave effects from instantaneous detonation. Based on Heelan’s short cylindrical cavity model, this paper derives an analytical solution for blast-induced dynamic stresses in adjacent tunnel rock, incorporating both induced SV-waves and a rock mass damage factor through rigorous theoretical analysis. Numerical case studies and field measurements were used to analyze stress propagation during tunnel blasting, and theoretical results were compared with measured data. The key findings were as follows: Radial stress > axial stress > hoop stress. All three stresses decay with increasing distance and damage factor, following an inversely proportional relationship with distance. Radial stress decays faster than axial and hoop stresses. Stress also decays exponentially over time, with the peak occurring after the transverse wave arrival. The theoretical results show approximately 10% deviation from the existing empirical formulas, while field measurements closely match the theoretical model, showing consistent stress trends and an average error of 7.02% (radial), 7.56% (axial) and 7.05% (hoop), confirming the reliability of the proposed analytical solution. Full article

Background/Objectives: Perceptions of obesity critically influence people’s eating behaviors and responses to food stimuli. However, few studies have investigated the impact of negative body perception on behavioral and neural responses to food stimuli. This study investigates how elevated body dissatisfaction modulates food-related inhibitory control. Methods: Fifty-one participants comprising three cohorts—overweight/obese individuals (OO), normal-weight participants exhibiting high negative body image (HNN), and healthy controls—performed a food-specific inhibitory control task under EEG recording. Results: The results showed that the HNN cohort achieved superior no-go accuracy and enhanced inhibitory control compared to controls. An event-related potentials (ERPs) analysis revealed increased conflict detection (P200) for high-calorie foods and reduced conflict resolution (LPP) in the HNN group, similar to the overweight/obese group. A multivariate pattern analysis (MVPA) identified earlier neural discrimination in the HNN group, suggesting more efficient inhibitory processing. Conclusions: These findings underscore negative body perception as a critical modulator of food-related cognitive control mechanisms. Full article

Ujimqin sheep, known for its distinctive multi-vertebrae phenotypes (T13L7, T14L6, and T14L7) and economic value, has garnered significant attention. However, conventional phenotypic detection methods suffer from low efficiency and high costs. In this study, based on a key SNP locus (ABCD4 gene, Chr7:89393414, C > T) identified through a genome-wide association study (GWAS), a TaqMan-MGB (minor groove binder) genotyping system was developed. the objective was to establish a high-throughput and efficient molecular marker-assisted selection (MAS) tool. Specific primers and dual fluorescent probes were designed to optimize the reaction system. Standard plasmids were adopted to validate genotyping accuracy. A total of 152 Ujimqin sheep were subjected to TaqMan-MGB genotyping, digital radiography (DR) imaging, and Sanger sequencing. the results showed complete concordance between TaqMan-MGB and Sanger sequencing, with an overall agreement rate of 83.6% with DR imaging. For individuals with T/T genotypes (127/139), the detection accuracy reached 91.4%. This method demonstrated high specificity, simplicity, and cost-efficiency, significantly reducing the time and financial burden associated with traditional imaging-based approaches. the findings indicate that the TaqMan-MGB technique can accurately identify the T/T genotype at the SNP site and its strong association with the multi-vertebrae phenotypes, offering an effective and reliable tool for molecular breeding of Ujimqin sheep. Full article

Background/Objectives: Prior research suggest that poor working memory significantly contributes to the growth of overweight and obesity. This study investigated the behavioral and neural aspects of general and food-specific working memory in females with overweight or obesity (OW/OB). Method: A total of 54 female participants, with 26 in the OW/OB group and 28 in the normal-weight (NW) group, completed a general and a food-related two-back task while an EEG was recorded. Results: In the general task, the OW/OB group showed significantly poorer performance (higher IES) than the NW group (p = 0.018, η² = 0.10), with reduced theta power during non-target trials (p = 0.040, η² = 0.08). No group differences were found for P2, N2, or P3 amplitudes. In the food-related task, significant group × stimulus interactions were observed. The OW/OB group showed significantly higher P2 amplitudes in high-calorie (HC) versus low-calorie (LC) food conditions (p = 0.005, η² = 0.15). LPC amplitudes were greater in the OW/OB group for HC targets (p = 0.036, η² = 0.09). Alpha power was significantly lower in OW/OB compared to NW in HC non-targets (p = 0.030, η² = 0.09), suggesting a greater cognitive effort. Conclusions: These findings indicate that individuals with OW/OB exhibit deficits in general working memory and heightened neural responses to high-calorie food cues, particularly during non-target inhibition. The results suggest an interaction between reward salience and cognitive control mechanisms in obesity. Full article

The spatial variability in rock mass mechanical parameters critically affects slope stability assessments. This study investigated the southern slope of the Bayan Obo open-pit mine. A representative elementary volume (REV) with a side length of 14 m was determined through discrete fracture network (DFN) simulations. Based on the rock quality designation (RQD) data from 40 boreholes, a three-dimensional spatial distribution model of the RQD was constructed using Ordinary Kriging interpolation. The RQD values were converted into geological strength index (GSI) values through an empirical correlation, and the generalized Hoek–Brown criterion was applied to develop a spatially heterogeneous equivalent mechanical parameter field. Numerical simulations were performed using FLAC3D, with the slope stability evaluated using the point safety factor (PSF) method. For comparison, three homogeneous benchmark models based on the 5th, 25th, and 50th percentiles produced profile-scale safety factors of 0.96–1.92 and failed to replicate the observed failure geometry. By contrast, the heterogeneous model yielded safety factors of approximately 1.03–1.08 and accurately reproduced the mapped sliding surface. These findings demonstrate that incorporating spatial heterogeneity significantly improves the accuracy of slope stability assessments, providing a robust theoretical basis for targeted monitoring and reinforcement design. Full article

Adipose tissue inflammation contributes to obesity-induced insulin resistance. However, increasing evidence shows that high BMI (obesity) is not an accurate predictor of poor metabolic health in individuals. The molecular mechanisms regulating the metabolically activated M1 macrophage phenotype in the adipose tissues leading to insulin resistance remain largely unknown. Although the Janus Kinase (Jak)/signal transducer and activator of transcription 3 (Stat3) signaling in myeloid cells are known to promote the M2 phenotype in tumors, we demonstrate here that the Jak2/Stat3 pathway amplifies M1-mediated adipose tissue inflammation and insulin resistance under metabolic challenges. Ablating Jak2 in the myeloid compartment reduces insulin resistance in obese mice, which is associated with a decrease in infiltration of adipose tissue macrophages (ATMs). We show that the adoptive transfer of Jak2-deficient myeloid cells improves insulin sensitivity in obese mice. Furthermore, the protection of obese mice with myeloid-specific Stat3 deficiency against insulin resistance is also associated with reduced tissue infiltration by macrophages. Jak2/Stat3 in the macrophage is required for the production of pro-inflammatory cytokines that promote M1 macrophage polarization in the adipose tissues of obese mice. Moreover, free fatty acids (FFAs) activate Stat3 in macrophages, leading to the induction of M1 cytokines. Silencing the myeloid cell Stat3 with an in vivo siRNA targeted delivery approach reduces metabolically activated pro-inflammatory ATMs, thereby alleviating obesity-induced insulin resistance. These results demonstrate Jak2/Stat3 in myeloid cells is required for obesity-induced insulin resistance and inflammation. Moreover, targeting Stat3 in myeloid cells may be a novel approach to ameliorate obesity-induced insulin resistance. Full article

Background/Objectives: Food-related memory influences appetite regulation, with memory inhibition potentially reducing cravings. While obesity is linked to inhibitory deficits, how restrained eating affects memory suppression in healthy-weight individuals remains unclear. This study examined the cognitive and neural mechanisms of food-memory suppression in young women. Methods: Forty-two female participants completed a think/no-think task with high-/low-calorie food cues while an EEG was recorded. Event-related potentials (ERPs) were assessed and time–frequency analyses (theta/beta oscillations) were performed. Results: Restrained eaters showed reduced memory control for both food types. The ERP analysis revealed significant N200 amplitude differences between think/no-think conditions (p = 0.03) and a significant interaction between food calories and think/no-think conditions (p = 0.032). Theta oscillations differed by group, food calories, and conditions (p = 0.038), while beta oscillations reflected food-cue processing variations. Conclusions: In conclusion, restrained eaters exhibit distinct neural processing and attenuated food-memory suppression. These results elucidate the neurocognitive mechanisms underlying dietary behavior, suggesting that targeted interventions for maladaptive eating could strengthen memory inhibition. Full article

Circular RNAs (circRNAs) have emerged as a transformative class of RNA therapeutics, distinguished by their closed-loop structure conferring nuclease resistance, reduced immunogenicity, and sustained translational activity. While challenges in pharmacokinetic control and manufacturing standardization require resolution, emerging synergies between computational design tools and modular delivery platforms are accelerating clinical translation. In this review, we synthesize recent advances in circRNA therapeutics, with a focused analysis of their stability and immunogenic properties in vaccine and drug development. Notably, key synthesis strategies, delivery platforms, and AI-driven optimization methods enabling scalable production are discussed. Moreover, we summarize preclinical and emerging clinical studies that underscore the potential of circRNA in vaccine development and protein replacement therapies. As both a promising expression vehicle and programmable regulatory molecule, circRNA represents a versatile platform poised to advance next-generation biologics and precision medicine. Full article

The prevention and control of mine inrush water has always been a major challenge for safety. By identifying the type of water source and analyzing the real-time changes in water composition, sudden water inrush accidents can be monitored in a timely manner to avoid major accidents. This paper proposes a novel explainable machine learning model for source type identification of mine inrush water. The paper expands the original monitoring system into the XinJi No.2 Mine in Huainan Mining Area. Based on the online water composition data, using the Spearman coefficient formula, it analyzes the water chemical characteristics of different aquifers to extract key discriminant factors. Then, the Conv1D-GRU model was built to deeply connect factors for precise water source identification. The experimental results show an accuracy rate of 85.37%. In addition, focused on the interpretability, the experiment quantified the impact of different features on the model using SHAP (Shapley Additive Explanations). It provides new reference for the source type identification of mine inrush water in mine disaster prevention and control. Full article

Modeling and simulation of aneurysm formation, growth, and rupture plays an essential role in a wide spectrum of application scenarios, ranging from risk stratification to stability prediction, and from clinical decision-making to treatment innovation. Unfortunately, it remains a non-trivial task due to the difficulties imposed by the complex and under-researched pathophysiological mechanisms behind the different development stages of various aneurysms. In this paper, we present a novel computational method for aneurysm simulation using smoothed particle hydrodynamics (SPH). Firstly, we consider blood in a vessel as a kind of incompressible fluid and model its flow dynamics using the SPH method; and then, to simulate aneurysm growth and rupture, the relationship between the aneurysm development and the properties of fluid particles is established by solving the motion control equation. In view of the prevalence of aneurysms in bifurcation vessels, we further enhance the capability of the model by introducing a solution for bifurcation aneurysms simulation according to Murray’s law. In addition, a CUDA parallel computing scheme is also designed to speed up the simulation process. To evaluate the performance of the proposed method, we conduct extensive experiments with different physical parameters associated with morphological characteristics of an aneurysm. The experimental results demonstrate the effectiveness and efficiency of proposed method in modeling and simulating aneurysm formation, growth, and rupture. Full article

Crohn’s disease is a chronic inflammation affecting the gastrointestinal tract. To date, patients are commonly treated with corticosteroids or more aggressive biologics for high-risk subjects. Stem Cell Educator therapy has been successfully utilized to treat patients with type 1 diabetes and other autoimmune conditions. A 78-year-old patient with long-standing Crohn’s disease received one treatment with the Stem Cell Educator therapy, followed by clinical, radiographic, pathological examinations and immune marker testing by flow cytometry. After the treatment with Stem Cell Educator therapy, the patient’s clinical symptoms were quickly improved with normal bowel movements, without abdominal pain or rectal bleeding. Flow cytometry analysis revealed a marked decline in inflammatory markers, such as the percentage of monocyte/macrophage-associated cytokine interleukin-1 beta (IL-1β)⁺ cells, which reduced from 94.98% at the baseline to 18.21%, and down-regulation of the percentage of chemokine CXCL16⁺ cells from 91.92% at baseline to 42.58% at 2-month follow-up. Pathologic examination of the biopsy specimens from colonoscopy five weeks and six months post-treatment showed ileal mucosa with no specific abnormality and no significant inflammation or villous atrophy; no granulomas were identified. A follow-up CT scan four and one-half months post-treatment showed no evidence of the previously seen stenosis of the ilio-colonic anastomosis with proximal dilatation. Stem Cell Educator therapy markedly reduced inflammation in the subject with Crohn’s disease, leading to durable clinical, immunological, radiographic, and pathological improvements. Full article

To enable accurate evaluation of satellite laser communication terminals under solar outage interference, this paper presents the design and implementation of a solar radiation simulation system targeting the 1540–1560 nm communication band. The system reconstructs co-propagating interference conditions through standardized and continuously tunable output, based on high irradiance and spectral uniformity. A compound beam homogenization structure—combining a multimode fiber and an apodizator—achieves 85.8% far-field uniformity over a 200 mm aperture. A power–spectrum co-optimization strategy is introduced for filter design, achieving a spectral matching degree of 78%. The system supports a tunable output from 2.5 to 130 mW with a 50× dynamic range and maintains power control accuracy within ±0.9%. To suppress internal background interference, a BRDF-based optical scattering model is established to trace primary and secondary stray light paths. Simulation results show that by maintaining the surface roughness of key mirrors below 2 nm and incorporating a U-shaped reflective light trap, stray light levels can be reduced to 5.13 × 10⁻¹² W, ensuring stable detection of a 10⁻¹⁰ W signal at a 10:1 signal-to-background ratio. Experimental validation confirms that the system can faithfully reproduce solar outage conditions within a ±3° field of view, achieving consistent performance in spectrum shaping, irradiance uniformity, and background suppression. The proposed platform provides a standardized and practical testbed for ground-based anti-interference assessment of optical communication terminals. Full article

We propose a single-phase chiral elastic metamaterial capable of simultaneously exhibiting negative effective mass density and negative bulk modulus in the ultrasonic frequency range. The unit cell consists of a regular hexagonal frame connected to a central circular mass through six obliquely oriented, slender aluminum beams. The design avoids the manufacturing complexity of multi-phase systems by relying solely on geometric topology and chirality to induce dipolar and rotational resonances. Dispersion analysis and effective parameter retrieval confirm a double-negative frequency region from 30.9 kHz to 34 kHz. Finite element simulations further demonstrate negative refraction behavior when the metamaterial is immersed in water and subjected to 32 kHz and 32.7 kHz incident plane wave. Equifrequency curves (EFCs) analysis shows excellent agreement with simulated refraction angles, validating the material’s double-negative performance. This study provides a robust, manufacturable platform for elastic wave manipulation using a single-phase metallic metamaterial design. Full article

Aquaculture is vital for global food security but faces challenges like disease, water quality control, and resource optimization. Digital twin technology, a real-time virtual replica of physical aquaculture systems, emerges as a transformative solution. By integrating sensors and data analytics, it enables monitoring and optimization of water quality, feed efficiency, fish health, and operations. This review explores the current adoption status of digital twins in aquaculture, highlighting applications in real-time monitoring and system optimization. It addresses key implementation challenges, including data integration and scalability, and identifies emerging opportunities for advancing sustainable, intelligent aquaculture practices. Full article

Artificial reservoirs in arid regions provide unique ecological environments for studying the spatial and functional dynamics of plankton communities under the combined stressors of climate change and anthropogenic activities. This study conducted a systematic investigation of the phytoplankton community structure and its environmental drivers in 17 artificial reservoirs in the Ili region of Xinjiang in August and October 2024. The Ili region is located in the temperate continental arid zone of northwestern China. A total of 209 phytoplankton species were identified, with Bacillariophyta, Chlorophyta, and Cyanobacteria comprising over 92% of the community, indicating an oligarchic dominance pattern. The decoupling between numerical dominance (diatoms) and biomass dominance (cyanobacteria) revealed functional differentiation and ecological complementarity among major taxa. Through multivariate analyses, including Mantel tests, principal component analysis (PCA), and redundancy analysis (RDA), we found that phytoplankton community structures at different ecological levels responded distinctly to environmental gradients. Oxidation-reduction potential (ORP), dissolved oxygen (DO), and mineralization parameters (EC, TDS) were key drivers of morphological operational taxonomic unit (MOTU). In contrast, dominant species (SP) were more responsive to salinity and pH. A seasonal analysis demonstrated significant shifts in correlation structures between summer and autumn, reflecting the regulatory influence of the climate on redox conditions and nutrient solubility. Machine learning using the random forest model effectively identified core taxa (e.g., MOTU1 and SP1) with strong discriminatory power, confirming their potential as bioindicators for water quality assessments and the early warning of ecological shifts. These core taxa exhibited wide spatial distribution and stable dominance, while localized dominant species showed high sensitivity to site-specific environmental conditions. Our findings underscore the need to integrate taxonomic resolution with functional and spatial analyses to reveal ecological response mechanisms in arid-zone reservoirs. This study provides a scientific foundation for environmental monitoring, water resource management, and resilience assessments in climate-sensitive freshwater ecosystems. Full article