Search Results (2,577)

Coal fly ash contains valuable rare earth elements (REEs), making its comprehensive utilization highly significant. In this study, REEs were recovered from two typical types of coal fly ash by Acidithiobacillus ferrooxidans, and the influencing factors and leaching mechanisms were explored. The results showed that favorable pulp density for bioleaching was 2% and the bacterial inoculum size was 5%. Among the three tested energy substances, the leaching system with sulfur as the energy source achieved the highest REE leaching efficiency. The Zhunneng coal fly ash bioleaching system had a REE leaching efficiency of 40.41%, which was significantly higher than that of Faer coal fly ash (12.93%). Generated from a pulverized coal furnace, Faer coal fly ash had a spherical shape and smooth surface, differing markedly from the Zhunneng samples from a circulating fluidized bed. Compared with the Zhunneng sample, there are more quartz and mullite in Faer coal fly ash which are refractory to bacterial decomposition. Also, Faer coal fly ash contains more REEs associated with aluminosilicate, while Zhunneng coal fly ash contains more organic/sulfide-bound and acid-soluble REEs. Furthermore, bioleaching demonstrated high selectivity for REEs. This study provides new insights for the green and economic management of coal fly ash. Full article

Regular endurance exercise is consistently associated with lower cardiovascular mortality, a favorable cardiometabolic profile, and superior cardiorespiratory fitness. However, coronary imaging studies in master endurance athletes have raised a clinically relevant paradox: despite a low burden of conventional risk factors, some athletes—particularly older men with high lifetime exercise exposure—show a greater prevalence of coronary artery calcium and subclinical coronary plaque than sedentary or less active controls. This observation has challenged the long-standing assumption that high-volume endurance exercise is uniformly protective against coronary artery disease. A binary interpretation of this literature is inadequate. Coronary flow reserve and ischemic threshold may remain adequate in some athletes, although this concept is supported by limited functional and outcome data. Based on experimental vascular biology and indirect human evidence, repetitive high-flow states during endurance exercise generate sustained laminar shear stress, cyclic wall strain, and marked increases in coronary blood flow, thereby activating endothelial mechanotransduction pathways and influencing vascular smooth muscle cell behavior, extracellular matrix remodeling, and calcification biology. These adaptations may culminate in positive arterial remodeling, luminal enlargement, and, in some individuals, a predominantly calcified plaque phenotype. Importantly, structural remodeling does not necessarily equate to functional impairment. In selected athletes, when outward remodeling and endothelial responsiveness are preserved, coronary flow reserve and ischemic threshold may remain adequate, although this concept remains supported by limited functional and outcome data. This narrative review integrates the clinical imaging literature with current concepts in vascular mechanobiology to propose that coronary remodeling in endurance athletes exists along an adaptive–maladaptive continuum shaped by cumulative exercise load, aging, sex, conventional risk factors, and biological susceptibility. This framework may help clinicians interpret CAC/CCTA findings in athletes more appropriately and avoid equating plaque burden with equivalent functional or prognostic significance. Full article

Rate of penetration (ROP) is a key indicator of drilling efficiency, governed by nonlinear coupling among mechanical, hydraulic, drilling fluid, and formation factors. This study develops an ExtraTrees model optimized by an improved Harris hawks optimization algorithm (IHHO-ET) using field while drilling data from Well Z in the Tarim Oilfield. A preprocessing workflow involving drilling section identification, abnormal condition filtering, 3 × IQR outlier removal, Savitzky–Golay smoothing, and standardization is combined with correlation and gray relational analysis under engineering mechanism constraints to select 14 input features. Logistic chaotic initialization, adaptive Gaussian mutation, and dynamic weighting are introduced into HHO, with validation set RMSE as the fitness function. To reduce the influence of random splitting and initialization, all comparison models are evaluated with repeated seeds and validation set tuning. Using R² and RMSE as primary criteria, IHHO-ET achieves R² = 0.910 ± 0.004 and RMSE = 0.871 ± 0.019 on the same-well test set. Its improvement over HHO-ET is small and not significant (p = 0.109), indicating that the IHHO strategies mainly refine search stability. Same-region leave-one-well-out validation gives an average R² = 0.696, suggesting that the model suits same-region trend prediction rather than direct closed-loop control. The proposed workflow provides a practical reference for ROP prediction. Full article

Background/Objectives: Atherosclerotic plaque instability is driven by complex interactions among inflammatory, structural, and cellular remodeling programs. While bulk RNA sequencing provides insight into tissue-level transcriptional states and single-cell RNA sequencing (scRNA-seq) defines cellular heterogeneity, integration across these transcriptomic layers remains limited. We aimed to identify coordinated transcriptional programs associated with stable and unstable plaque phenotypes and map these programs to specific cellular compartments and regulatory networks. Methods: Paired bulk RNA-seq data from stable and unstable human carotid plaques (GSE120521) and scRNA-seq data from human coronary atherosclerotic lesions (GSE131778) were analyzed. Differential expression and Hallmark gene set enrichment analyses were performed using limma and clusterProfiler. Bulk-derived inflammatory and structural signatures were projected onto single-cell data using Seurat module scoring. Compartment-level transcriptional scores, an inflammatory–structural endotype index, and transcription factor activity inference using decoupleR and DoRothEA were used to characterize plaque-associated transcriptional states. Results: Unstable plaques demonstrated enrichment of inflammatory pathways, including interferon gamma response, inflammatory response, TNFα/NF-κB signaling, IL6/JAK/STAT3 signaling, complement activation, and reactive oxygen species pathways. In contrast, stable plaques demonstrated relative enrichment of myogenesis and structural remodeling programs. Projection of bulk-derived signatures onto single-cell data localized inflammatory programs predominantly to TREM2hi and inflammatory macrophage populations, whereas structural programs localized to smooth muscle cell and fibromyocyte-like compartments. Compartment-level analyses showed increased myeloid and adaptive immune signatures in unstable plaques and increased smooth muscle cell/fibro-remodeling signatures in stable plaques. Transcription factor activity analysis identified increased SPI1, NFKB1, RELA, and STAT1 activity in unstable plaques and higher SRF and TEAD1 activity in stable plaques. Conclusions: Integrative analysis of bulk and single-cell transcriptomic data identified distinct inflammatory and structural plaque transcriptional states associated with unstable and stable plaque phenotypes, respectively. These findings support a systems-level framework linking tissue-level plaque behavior to specific cellular and regulatory programs and provide evidence for inflammatory and structural plaque endotypes in human atherosclerosis. Full article

To address localization error accumulation in autonomous underwater vehicle (AUV) swarms due to underwater acoustic communication interruptions, this paper proposes a cooperative localization method that integrates Long Short-Term Memory (LSTM) prediction and factor graph optimization. During the real-time stage, each AUV uses a trained LSTM to predict observations, ensuring the Unscented Kalman filter (UKF) maintains continuous state estimation during interruptions and mitigates error accumulation. During the post-processing stage, a factor graph comprising motion model factors, cooperative observation factors, and LSTM prediction factors is constructed on the AUV swarm master node. By adaptively switching factor types based on communication status, global nonlinear optimization is performed on the AUV states. Simulation results show that compared with UKF + LSTM, the proposed method reduces the Average Localization Error (ALE) by 55% and the Root Mean Square Error (RMSE) by 60%; compared with the Rauch–Tung–Striebel (RTS) smoothing algorithm, it reduces the ALE by 36% and the RMSE by 44%. This fully verifies that the strategy combining real-time state maintenance and post-processing global optimization can more effectively correct AUV localization errors in communication-interrupted regions. Experiments under different communication interruption durations further confirm the robustness of the proposed algorithm, with the maximum error-to-range ratio remaining below 0.2% of the range. Full article

As a key component of space telescopes, the rational structure of the mirror is a crucial factor affecting the telescope’s environmental adaptability and imaging performance. To address the technical challenges of simultaneously achieving lightweight, environmental adaptability, and surface accuracy in large-aperture ultrathin mirrors, this paper proposes a mirror optimization method based on multiphysics coupling. Based on the finite element method and thermoelasticity theory, the interaction relationship between the temperature physical field and the force physical field was established. The P-norm was used to solve the problems of non-smoothness and inability to solve the sensitivity of the $\max (·)$ function. An optimized model for the mirror was determined using a combination of topology optimization and parameter optimization. Compared to a solid mirror, the optimized mirror achieved a mass reduction rate of 82.04%. Under temperature and gravity conditions, the surface accuracy of the optimized mirror met the requirements. In terms of response dynamics, the optimized mirror performs better, with a maximum response amplification factor of 4.39, below the threshold of 4.5 required to maintain structural stability, which is crucial for maintaining the structural integrity of the mirror. This method will provide a feasible approach for the optimized design of lightweight mirrors with strong environmental adaptability. Full article

Accurate network simulation is essential for evaluating wireless communication systems; however, the fidelity of simulation results strongly depends on the underlying modeling assumptions, particularly at the physical (PHY) layer. In this paper, we present a comparative analysis of OMNeT++ and Riverbed Modeler with respect to feature support and throughput prediction accuracy, validated against measurements obtained from a controlled wireless testbed. In this paper, we investigate simulator performance across representative scenarios, including line-of-sight (LOS), non-line-of-sight (NLOS), interference, and congestion conditions. To identify the sources of performance deviation, the analysis further examines the relationship among the signal-to-interference-plus-noise ratio (SINR), packet error rate (PER), and throughput. The results obtained show that both simulators achieve high accuracy under ideal conditions, particularly for LOS and congestion scenarios, where higher layer effects dominate or channel impairments are minimal. However, significant discrepancies arise under NLOS and interference conditions, where accurate modeling of channel dynamics and error behavior is critical. The results show that Riverbed consistently demonstrates closer agreement with testbed, owing to its continuous SINR tracking and probabilistic PER modeling. This enables smooth adaptation of throughput to varying channel conditions. In contrast, OMNeT++ exhibits step-like SINR–throughput and SINR–PER relationships caused by threshold-based abstractions, leading to noticeable inaccuracies in transitional SINR regimes (5–15 dB). Overall, this study highlights that PHY-layer abstraction fidelity is the dominant factor influencing throughput accuracy in network simulation. While OMNeT++ offers flexibility and extensibility suitable for research and prototyping, Riverbed Modeler provides more reliable performance prediction in scenarios requiring high modeling precision. Finally, we provide guidelines for best practice checklists in network simulation and model validation. Full article

Perennial alfalfa roots form a composite with the soil, contributing to intensified grassland degradation and reduced yields. Soil-loosening and root-cutting tools are effective in disrupting root–soil composites and reducing soil compaction. However, loosening and root-cutting operations commonly face challenges, such as high tillage resistance and disturbance. This study developed a simulation model of the alfalfa root–soil composite based on the coupled Finite Element Method (FEM) and Smoothed Particle Hydrodynamics (SPH) method when considering the biomechanical properties of roots. The validity of the model was verified using direct shear and cutting tests. The errors in both simulation and test results were less than 8%. Additionally, a vibration root-cutting shovel was designed. The factors of tillage speed, vibration frequency, amplitude, and direction were analyzed for their impact on tillage resistance and root shear displacement. Results indicated that the incorporation of vibration enhanced soil breaking and reduced root-cutting displacement. The optimal combination of parameters determined using the Response Surface Method (RSM) for minimizing tillage resistance and shear displacement were a tillage speed of 0.86 m·s⁻¹, vibration amplitude of 3.79 mm, vibration frequency of 45.05 Hz, and vibration parallel to the tillage direction. Field tests confirmed the effectiveness of the vibratory root-cutting shovel. The addition of vibration parallel to the tillage direction can reduce tillage resistance by 16.68% and penetration resistance by 26.80%. This study provides a methodology for modeling root–soil composite and improving the root-cutting shovel for grassland degradation restoration. Full article

Aortic dissection (AD) is a life-threatening vascular disease characterized by progressive vascular remodeling, oxidative stress, and inflammation. Among them, severe oxidative stress and systemic inflammation are important driving factors causing vascular integrity damage. Cistanche deserticola polysaccharides (CTPs) have definite deserticola anti-inflammatory and antioxidant properties. However, their influence on the progression of AD remains to be studied. In this study, we investigated the protective effects of CTP in a BAPN-induced mouse model of aortic dissection and explored the underlying mechanisms. CTP administration significantly attenuated aortic dilation and reduced the incidence of aortic dissection, accompanied by suppression of oxidative stress and inflammatory responses, preservation of extracellular matrix integrity, and maintenance of the contractile phenotype of vascular smooth muscle cells. Most importantly, CTP inhibits oxidative stress responses, as evidenced by the recovery of endogenous antioxidant enzyme activity and the reduction in lipid peroxidation. At the same time, CTP also suppresses systemic inflammatory responses. In addition, CTP markedly reshaped gut microbiota composition, characterized by enrichment of Akkermansia and Lachnospiraceae and reduction in Desulfovibrio and Escherichia–Shigella. Correlation analyses revealed close associations between gut microbial alterations and antioxidant, vascular remodeling, and smooth muscle cell phenotypic modulation. Collectively, these findings suggest that CTP confers vascular protection against aortic dissection through coordinated regulation of oxidative stress, inflammation, and vascular remodeling. The observed changes in gut microbiota composition may represent an additional mechanism associated with the beneficial effects of CTP and warrant further investigation. Full article

Heritable thoracic aortic diseases (HTADs) comprise a genetically heterogeneous group of disorders predisposing patients to thoracic aortic aneurysm and dissection, yet current medical therapies remain limited to slowing disease progression rather than preventing aortic wall failure. Although pathogenic variants affect diverse genes encoding extracellular matrix (ECM) components, smooth muscle contractile proteins, and signaling molecules, these defects converge on disruption of the mechanobiological systems that maintain aortic wall integrity. The thoracic aorta functions as a mechanically integrated tissue in which endothelial cells, vascular smooth muscle cells, fibroblasts, immune cells and ECM continuously sense and respond to pulsatile biomechanical forces. Genetic perturbations affecting ECM architecture, contractile force generation, or growth factor signaling alter force transmission across this multicellular network, leading to maladaptive mechanotransduction, cellular phenotypic modulation, and progressive aneurysm formation. Using Marfan syndrome as a paradigmatic ECM-driven aortic disease, this review synthesizes current understanding of how altered biomechanics, biochemical signaling and immune responses reshape intercellular communication and activate disease-associated signaling pathways, including dysregulated TGF-β, nitric oxide, angiotensin receptor, calcium-dependent, and metabolic signaling. We highlight how single-cell transcriptomic analyses have elaborated changes in different cell-level functions including, ECM degradation, iron homeostasis, circadian/stress responses. Changes in iron metabolism in different cell types in the aorta suggest possible coordinated metabolic changes in aneurysm progression. These mechanistic insights enable the identification of cell-type–specific pathogenic programs and therapeutic discovery through systems-level approaches. We highlight the translational opportunities and challenges emerging from mouse models and human studies, emphasizing that therapeutic efficacy depends not only on pathway selection but also on disease stage, cellular context, and timing of intervention. Together, these findings support a model in which HTAD progression reflects dynamic, multicellular failure of mechanobiological homeostasis and provide a framework for the development of more precise, mechanism-based therapies. Full article

To address the labor intensity and potential vegetative damage associated with mechanical picking of Osmanthus fragrans at full bloom, this study proposed a selective separation mechanism using a flexible roller-brush. Biomechanical measurements established a quasi-static operational window, with floral detachment requiring up to 1.2 N and petiole–branch retention remaining above 5.0 N during the observed period. Rigid–flexible coupled transient simulations provided mechanistic support for a flexible unloading effect, predicting approximately 1.3 N at the floral junction and approximately 2.5 N at the petiole–branch junction under the simplified model assumptions. A CZD-01 picker with a three-degree-of-freedom contour-following arm was developed, and a mixed I-Optimal response-surface design was used to identify a candidate-set optimum within the tested three-level factor domain. Bristle configuration was the strongest tested factor affecting immediate leaf detachment (p < 0.0001). Under the selected configuration of 161 r/min roller-brush speed, 8 r/min circumferential speed, and smooth PU bristles, ten validation trials in a flat standardized plantation yielded a flower-picking rate of 84.0 ± 1.38% and an immediate leaf detachment rate of 6.5 ± 0.61%. These results demonstrate promising selective-picking performance under the tested conditions; transferability to other cultivars, seasons, terrains, and long-term tree responses remains to be established. Full article

Deforestation promotes environmental changes capable of altering regional microclimatic dynamics, intensifying wildfires, and increasing population exposure to cardiovascular risk factors. This study investigated the spatiotemporal association between deforestation and acute myocardial infarction mortality across health regions of the Brazilian Amazon between 2000 and 2023. An ecological study design was adopted using data aggregated by health region and year. Generalized additive models with a negative binomial distribution were fitted to evaluate nonlinear associations between deforestation and acute myocardial infarction mortality, including temporal lag analyses of one, two, and three years. Spatial dynamics were further investigated through Bayesian spatiotemporal modeling incorporating structured spatial effects and a smoothed temporal trend. A significant nonlinear association was identified between deforestation and acute myocardial infarction mortality, with progressive risk intensification observed in areas subjected to greater environmental degradation. Lagged models demonstrated persistence of the association over time, suggesting cumulative effects of environmental exposure. Spatial analysis revealed an expansion of areas with elevated relative risk, particularly within the Arc of Deforestation of the Amazon region. Overall, the findings indicate that deforestation may act as an important socioenvironmental determinant of cardiovascular health in the Brazilian Amazon. Full article

To address the issues of slow response to preceding vehicles and poor string stability in distributed platoon control of connected and autonomous vehicles (CAVs) under mixed traffic flow, this paper proposes a sliding mode control method based on LSTM trajectory prediction, denoted as LSTM-SMC, within a multi-agent framework. The LSTM model is trained using the HighD naturalistic driving dataset to achieve high-precision prediction of the leader vehicle’s trajectory over a horizon of 3 s, with root mean square errors (RMSE) of 8.52 m in the X-direction and 0.896 m in the Y-direction. The predicted trajectory information is converted into a preview error and embedded directly into the design of the sliding surface, enabling each following vehicle to anticipate disturbances before they propagate. A diminishing preview gain strategy (${\gamma }_1=0.4$, ${\gamma }_2=0.2$, ${\gamma }_3=0.1$) is employed to suppress error propagation along the platoon, while a saturation function is introduced to eliminate chattering and ensure smooth control inputs. Three simulation scenarios—prescribed leading, HDV (human-driven vehicle) leading, and curved road scenario—are constructed to validate the proposed method against traditional constant time headway (CTH) control, pure sliding mode control (SMC), and LSTM-MPC. Results demonstrate that under extreme conditions, the proposed method reduces the speed RMSE of the 3rd following vehicle by 18.3% compared to CTH and by 39.7% compared to SMC. Under HDV leading conditions, all string stability amplification factors are less than 1, and the position RMSE of the 3rd vehicle is only 5.03 m in the curved road scenario. Compared with LSTM-MPC, the proposed LSTM-SMC achieves comparable tracking accuracy while reducing computational cost by 1.43–3.51×. The proposed method achieves a native integration of prediction and robust control, significantly improving tracking accuracy, string stability, and computational efficiency across diverse operating conditions in mixed traffic flow. Full article

Pressure fluctuations in the articulated steering system of wheel loaders can degrade steering smoothness, operational stability, and energy utilization efficiency. To address this issue, this study starts from the stroke difference and force-arm difference of steering cylinders induced by articulation motion, systematically reveals the structural mechanism responsible for pressure fluctuations in the steering mechanism, and proposes a suppression method based on hinge-point optimization. Specifically, a mathematical model of the articulated steering mechanism is established according to the analytical relationships between the stroke difference, force-arm difference, and articulation angle. The Dung Beetle Optimizer (DBO) is introduced to optimize and compare the hinge-point coordinates of the steering cylinders under different single-objective and multi-objective functions, thereby clarifying that the force-arm difference is the dominant factor affecting pressure fluctuations. Prototype modification and full-vehicle experiments are then conducted for validation. The results demonstrate that the hinge-point coordinates optimized with the force-arm difference as the objective function can significantly suppress steering pressure fluctuations. This study provides a theoretical basis and engineering reference for structural design, hinge-point layout optimization, and pressure-fluctuation suppression in articulated steering systems of wheel loaders. Full article

Background/Objectives: Hypocalcemia is a major transition-cow disorder in dairy cattle, with clinical and subclinical forms differing in detectability, severity, timing, and herd-level consequences. This systematic review integrates evidence on calcium (Ca) homeostasis, classification of clinical hypocalcemia (CHC) and subclinical hypocalcemia (SCH), diagnostic interpretation, risk factors, systemic effects, and preventive and therapeutic strategies in dairy cows. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement, PubMed, ScienceDirect, SpringerLink, and CAB Abstracts were searched in February 2026 for 1994–2025 publications, and 23 reports were included in a qualitative synthesis; meta-analysis was not performed because of methodological and outcome heterogeneity. Results: The evidence indicates that hypocalcemia should be interpreted as a failure of homeorhetic adaptation to abrupt mammary Ca export rather than as a simple mineral deficiency. The parathyroid hormone–vitamin D axis, skeletal Ca mobilization, renal Ca conservation, intestinal Ca absorption, magnesium (Mg) status, dietary cation–anion difference (DCAD), dry matter intake, parity, and acid–base balance jointly determine whether blood Ca is maintained during early lactation. Total calcium (tCa) thresholds are useful decision aids for herd-level monitoring, but their interpretation depends on sampling time, parity, persistence pattern, clinical signs, and the relationship between tCa and ionized calcium (iCa). Subclinical hypocalcemia is most relevant when it is delayed, persistent, or occurs in high-risk cows because reduced Ca availability can impair smooth muscle function, feed intake, immune competence, uterine health, and metabolic resilience. Management should therefore combine prepartum ration control, Mg adequacy, DCAD and urine pH monitoring, selective Ca testing in high-risk cows, targeted oral Ca supplementation for standing cows, and intravenous Ca treatment for recumbent CHC cases. Conclusions: The evidence supports a risk-based, context-aware strategy rather than universal threshold-driven treatment. Full article