Search Results (2,211)

Comprehensive mechanized solid backfilling technology exhibits significant advantages in solid waste disposal, “three-under” coal mining, and dynamic disaster control. However, its large-scale application is constrained by low production efficiency, high unit production cost, and high labor intensity. Therefore, industrial upgrading through intelligent technologies is urgently required. In this study, methods including literature review, theoretical analysis, and field measurements are employed to propose three backfilling modes. The configurations of the six core subsystems under each mode are systematically summarized, and the core definition of an intelligent backfilling mine is established. Furthermore, a key technology framework for intelligent backfill mining is developed, based on PLC control and PID algorithms, with a closed-loop architecture centered on “perception–decision–execution.” Engineering applications demonstrate that the surface gangue intelligent pretreatment system achieves functions including automatic vehicle washing, intelligent dust suppression spraying at discharge points, dynamic metering during conveying, and adaptive adjustment of feeding systems. The intelligent surface-to-underground coal gangue vertical feeding system enables full silo alarm and level regulation. The underground jigging intelligent separation system realizes intelligent jigging ratio adjustment, intelligent bed layer measurement and control, and intelligent air volume regulation, with the coal content in gangue discharge maintained below 4%. At the working face, the intelligent solid backfilling system doubles monthly coal output, boosts backfilling efficiency by 50%, and cuts the workforce by 8–10 workers. The intelligent backfilling effectiveness monitoring system operates stably, with a working face weighting factor of 1.12 and precise ground deformation control within Grade I limits. Full article

Against the backdrop of environmental governance systems transitioning from command-and-control to multi-stakeholder collaboration, elucidating the mechanisms and pathways through which voluntary environmental regulations influence green technological innovation in heavily polluting enterprises holds significant implications for advancing green innovation and high-quality development. This paper systematically examines the synergistic mechanisms of command-and-control versus voluntary environmental regulations on green technological innovation in heavily polluting enterprises, utilising data from listed companies in China’s high-pollution industries between 2008 and 2024. Unlike previous studies predominantly focused on the impact of a single regulatory type, this study reveals an interactive effect between the two: moderate command-and-control regulation provides essential institutional support for voluntary environmental regulation, such as ISO 14001 certification, thereby generating a complementary enhancement effect. However, overly stringent command-and-control regulation diverts innovation resources from enterprises, thereby suppressing the incentive effect of voluntary regulation. This conclusion transcends the traditional analytical paradigm within environmental regulation theory that treats command-and-control and voluntary regulations as mutually exclusive opposites, revealing instead a dynamic relationship where both synergistic and constraining effects coexist. This discovery provides crucial theoretical underpinnings and empirical evidence for constructing an environmental governance system that combines command-and-control constraints with flexible incentives, ensuring compatibility between policy objectives and corporate behaviour. Full article

In slab continuous casting, the internal hydrodynamics of the submerged entry nozzle (SEN) play a determining role in mold flow stability and product quality, particularly when external electromagnetic flow-control technologies are not employed. This study analyzes a novel bifurcated SEN design intended to promote stable, highly symmetric outlet jets under asymmetric inlet flow conditions produced by typical flow-control devices. The proposed configuration combines three geometric modifications: a square-section bore, a flow-divider bottom wall derived from a rotated mountain-type geometry, and two bell-shaped protrusions that act as flow modulators positioned immediately above the outlet ports. The hydrodynamic behavior inside the nozzle was investigated using complementary experimental and numerical approaches. Physical modeling was conducted in a scaled water model using particle image velocimetry (PIV) to characterize time-averaged velocity fields and flow fluctuations. In parallel, three-dimensional large-eddy simulations (LESs) were performed to resolve transient flow structures and quantify jet characteristics at the nozzle exits. Both approaches show consistent results. The combined action of the flow modulators and the flow-divider bottom wall robustly induces the formation of two nearly identical counter-rotating vortices in the lower region of the SEN. This flow structure suppresses stagnation and recirculation zones near the outlet ports, mitigates inlet-induced asymmetries, and enhances flow evacuation efficiency. Quantitative analysis of the outlet jets indicates a significant reduction in angular dispersion and a flow-rate imbalance below 0.2%, markedly lower than that observed in conventional SEN configurations. The results demonstrate that appropriate internal geometric design can effectively stabilize SEN hydrodynamics without active control systems, offering a feasible and scalable strategy for improving mold flow stability in industrial continuous casting operations. Full article

Carbon nanotube field-effect transistors (CNT FETs) hold great promise for extending Moore’s Law, yet their performance is critically limited by excessive off-state leakage, caused by band-to-band tunneling (BTBT) in narrow bandgap CNT channels. In this work, we overcome this long-standing bottleneck by introducing a co-design strategy that integrates a small-diameter HiPco CNT channel with a novel asymmetric gate architecture. This approach strategically reshapes the channel electrostatics to simultaneously suppress the gate-induced drain leakage (GIDL) effect and preserve excellent carrier transport. The efficacy of this strategy is rigorously validated through calibrated technology computer-aided design (TCAD) simulations for both NMOS and PMOS operation, demonstrating an ultralow off-current of 10 fA/µm, an on-current of 1.08 mA/µm, and a record on–off ratio of 1.1 × 10¹¹ for back-gated CNTFETs at the 90 nm node. The design exhibits outstanding scalability: at the scaled 28 nm node with a supply voltage of 0.7 V, the PMOS device achieves 3 mA/µm on-current and 6 pA/µm off-current, maintaining an on–off ratio of 5 × 10⁸. This work establishes a scalable pathway toward femtoampere-level CNT CMOS, addressing the static power challenge in future nano-electronics. Full article

To enhance the aerodynamic performance of Ti6Al4V functional components, this paper systematically investigated the femtosecond laser processing technology for surface drag-reduction microstructures, aiming to fabricate high-performance microstructures. (1) V-shaped, U-shaped, and rectangular micro-grooves were designed based on the boundary layer theory, and their drag-reduction mechanisms were elucidated through CFD numerical simulations. The results indicate that the V-shaped groove achieves a peak drag-reduction rate of 13.1% at a dimensionless depth of h⁺ = 15 and an aspect ratio of 1, primarily due to the formation of a low-velocity zone and the suppression of turbulent bursts by secondary vortices. (2) Through single-factor experiments, the influence laws of femtosecond laser process parameters on the V-shaped groove were explored. (3) Regression prediction models for groove dimensions were established using the Response Surface Methodology (RSM) to optimize the processing parameters. Under the optimized conditions, high-quality V-shaped groove arrays with a width of 55.9 μm and a depth of 55.5 μm were successfully fabricated on the Ti6Al4V surface, characterized by high consistency and a minimal heat-affected zone. This research provides an effective technical solution for the precision manufacturing of high-performance drag-reduction structures on titanium alloy surfaces. Full article

Infrared imaging technology has been widely adopted for industrial gas leak detection due to its capability for large field-of-view, long-range, and dynamic monitoring. However, in practical applications, natural object interference within the scene, together with the blurred contours and low contrast of infrared images, severely degrades the performance of gas detection and leakage region segmentation. To address these challenges, this paper proposes a gas leak detection method that integrates gas characteristics with spatiotemporal information. Specifically, the non-solid characteristics of gas are incorporated to constrain the foreground extraction process of the Gaussian Mixture Model (GMM), thereby suppressing interfering moving objects. Furthermore, by exploiting the spatiotemporal information in infrared image sequences, a multi-scale cross-attention fusion model is designed to fuse multi-scale and global feature representations, improving the accuracy of foreground detection. Finally, density-based clustering is employed to achieve complete segmentation of gas regions with irregular shapes. Experimental results demonstrate that the proposed method effectively suppresses interference from solid objects, accurately detects gas leakage, and successfully segments the diffusion regions. Compared with existing approaches, the proposed method shows significant advantages and provides a valuable reference for research on infrared imaging-based gas leak detection. Full article

Low-refresh-rate driving is an effective way to reduce the power consumption of active-matrix organic light-emitting diode (AMOLED) displays. However, in conventional low-temperature polycrystalline silicon (LTPS) thin-film transistor (TFT) pixel circuits, leakage current through switching TFTs can disturb the stored gate voltage of the driving TFT during the long emission period. This causes the time-dependent variation in driving current and visible flicker. In this study, a novel pixel circuit for leakage suppression in low-refresh-rate driving is presented. Bias aging was first applied to reduce the leakage current of the LTPS TFT, and a device model was then built from the characteristics measured at 60 °C. Based on this model, the leakage-induced instability of a conventional 7T1C pixel circuit was analyzed. To suppress this effect, a new 8T1C pixel circuit was proposed. The key idea is to reduce the source–drain voltage of the leakage-sensitive switching TFT during the emission period by raising the initial line potential to a level close to the storage node potential. Simulation results show that the proposed circuit greatly reduces the time-dependent variation in both the driving TFT gate voltage and the driving current compared with the conventional 7T1C circuit. Perceptual evaluation based on human visual sensitivity also confirms stable low-refresh-rate operation down to 20 Hz over the practical gray range. These results show that the proposed circuit is an effective solution for moderate low-refresh-rate operation without relying on low-temperature polycrystalline silicon and oxide (LTPO) technology. Full article

Plant-derived bioactive metabolites have emerged as promising modulators of oxidative stress and inflammation, two interconnected processes involved in the pathogenesis of numerous chronic diseases. Arid ecosystems, particularly the Sonoran Desert, constitute an underexplored source of structurally diverse phytochemicals with significant pharmacological potential. This review provides a comprehensive overview of major classes of plant-derived bioactives, including polyphenols, flavonoids, terpenoids, and alkaloids, with emphasis on their molecular mechanisms of antioxidant and anti-inflammatory action. These compounds exert cytoprotective effects through direct reactive oxygen species (ROS) scavenging and indirect regulation of endogenous defense systems, primarily via activation of the Nrf2/Keap1 pathway and suppression of NF-κB signaling. Additional pathways, including MAPK, PI3K/Akt, AMPK, and mitochondrial regulatory networks, are discussed as critical mediators of redox balance and inflammatory control. Particular attention is given to Sonoran Desert plant species such as Bucida buceras, Phoradendron californicum, Larrea tridentata, Opuntia spp., and Agave deserti, all of which demonstrate promising biological activities associated with enhanced adaptation to environmental stress. Experimental approaches used to evaluate phytochemical bioactivity, including chemical assays, cellular models, omics technologies, and translational strategies, are also examined. Furthermore, this review discusses current limitations related to bioavailability, phytochemical variability, and clinical validation, highlighting emerging nanodelivery systems and precision medicine approaches as potential solutions. Collectively, the evidence supports the therapeutic relevance of Sonoran Desert plant bioactives as multi-target agents for modulating oxidative stress, inflammation, and chronic disease progression. Full article

Surface rock movement can lead to geological or environmental problems such as surface subsidence, ground fissure development, and deformation of engineering structures, and its evolution process exhibits significant spatiotemporal heterogeneity. Therefore, conducting high-precision, spatiotemporally continuous monitoring of surface deformation is of great significance for revealing subsidence mechanisms, assessing potential risks, and guiding disaster reduction decisions. GNSS and InSAR have become mainstream methods for monitoring surface deformation, but they still have limitations in terms of spatial sparsity, 3D deformation inversion capability, and data gaps in areas of strong deformation. To address these issues, this paper takes the Jinchuan copper-nickel mine’s No. 2 mining area as the research object and comprehensively utilizes multi-source monitoring data from GNSS and InSAR to construct a joint inversion model of the surface 3D deformation field based on posterior variance component estimation, achieving adaptive optimization of weight allocation and collaborative solution of 3D deformation. To address the issue of InSAR decorrelation in areas of strong deformation, which leads to missing deformation information, a fitting and estimation approach was applied to supplement six decorrelated points that spatially coincide with GNSS stations. These points are located in key deformation areas, and their reconstruction effectively improves the completeness and reliability of the deformation field in critical regions. Based on this, an automated solution process for the fusion model is implemented using MATLAB R2022b, and the joint inversion yields spatiotemporally continuous 3D deformation fields in the northward, eastward, and vertical directions. The results show that compared with traditional monitoring methods, the proposed fusion model exhibits higher inversion accuracy and stability under different InSAR technology conditions, effectively suppressing the impact of single data source errors on the overall solution results. Among them, SBAS-InSAR shows slightly higher accuracy in the vertical direction, while PS-InSAR achieves higher accuracy in the planar direction, as indicated by lower RMSE and MAE values. The research results improve the accuracy and reliability of surface deformation monitoring in mining areas, providing important technical support for safe mining and refined management. Full article

Cosmic-Ray Neutron Sensing (CRNS) has become a standard method for non-invasive soil moisture monitoring at the field scale. With most CRNS sensors being derivatives from scientific nuclear equipment, the development of instruments based on alternative neutron detection technologies is a major development goal for CRNS. We present a modular instrument family based on boron-10-lined proportional counters, specifically designed for long-term autonomous field operation. The system is controlled by a data logger supporting various telemetry options and external SDI-12 environmental sensors, while the frontend electronics use pulse-height and pulse-length information to suppress non-neutron background and electronic noise. Our results show high energy efficiency, with the latest generation close to 50 mW, allowing solar-powered operation even in challenging environments. The performance of the instruments is validated within long-term field deployments in different settings, showing that boron-10-based systems provide a scalable, low-power and cost-efficient alternative for the next generation of CRNS monitoring networks. Full article

This paper examines the influence of Aldous Huxley’s dystopian vision—particularly Brave New World—on Ali Smith’s Seasonal Quartet, arguing that Smith’s post-Brexit novels can be read as contemporary, politically embedded responses to the dystopian tradition Huxley helped establish. While Smith’s fiction is rarely labelled dystopian in genre, the Quartet is deeply informed by a dystopic sense of cultural, ecological, and political decay in 21st-century Britain. I propose that Smith adopts and adapts key dystopian motifs from Huxley but repurposes them through a radical humanist lens that privileges relationality, art, and memory as sources of resistance and repair. The paper will be structured in three sections. The first outlines Huxley’s dystopian framework, with a focus on Brave New World’s criticism of technological control, emotional appeasement, and the suppression of dissent through pleasure. The second analyzes Smith’s Seasonal Quartet as a world not governed by totalitarian regimes but by apathy, misinformation, and ideological fragmentation. The final section traces Smith’s divergence from Huxley: where Huxley’s world often excludes hope in favor of bleak satire, Smith inserts gestures of resistance, particularly through intergenerational friendships, the presence of art and literature, and the recurrence of seasonal cycles as metaphors for renewal. Although Autumn explicitly references Huxley’s Brave New World, sustained critical comparisons between the two authors remain relatively rare. Most scholarship approaches Huxley through the tradition of twentieth-century dystopian fiction, while Smith’s Quartet is typically discussed within the context of Brexit literature and contemporary narrative experimentation. Reading the Quartet alongside Huxley, therefore, reveals an unexpected dialogue between early twentieth-century dystopian critique and twenty-first-century literary responses to political crisis. Full article

This paper presents a current-reused vertically stacked (CRVS) topology for a high-dynamic-range amplifier (HDRA) implemented in a 0.1 μm GaAs pHEMT process, targeting wideband millimeter-wave (mm-wave) receiver front-ends. The proposed design breaks the inherent trade-off between noise figure (NF), linearity, and bandwidth, achieving simultaneous enhancement of transconductance efficiency, Miller effect suppression, and wideband matching. The fabricated prototype operates over a continuous 20–43 GHz bandwidth (covering K- and Ka-bands), demonstrating state-of-the-art performance: a flat gain of 24 ± 0.6 dB, a minimum NF of 2.2 dB, a maximum output 1 dB compression point (OP1dB) of 15.8 dBm and a low power consumption of 5 V/65 mA, with both input and output return losses better than −10 dB across the entire band. The results validate the effectiveness of the CRVS topology and highlight the competitiveness of GaAs pHEMT technology for high-performance wideband mm-wave front-ends, making the design suitable for applications including 5G/6G communication, satellite systems, and mm-wave test equipment. Full article

Heat pump technology can efficiently recover waste heat from oil and gas gathering, processing, and transportation. However, the energy transfer mechanism of high-speed rotating internal flow in the scroll compressor remains unclear under unbalanced load conditions, leading to low equipment energy efficiency and high operation and maintenance costs. This study adopted dynamic grid technology, finite element analysis and one-way thermal–fluid–solid coupling method to quantitatively study the flow field characteristics and mechanical response of four characteristic phases. The results showed that the internal pressure and temperature fields of the compressor presented a non-uniform distribution. The deformation of the scroll wraps was mainly concentrated in the compression chamber, and the maximum stress was concentrated at the wraps’ root. Further analysis revealed that temperature loading played a dominant role in the structural responses. At a spindle rotation angle of 0°, under temperature loading alone, the maximum deformation and maximum stress were 28.605 μm and 521.81 MPa, respectively, while the corresponding values under pressure loading alone were small. In addition, the deformation and stress under coupled loading were not a linear superposition of the individual loading effects, with a deformation deviation of 0.938 μm and a stress deviation of 7.18 MPa at a spindle rotation angle of 0°. In this study, a numerical model of the scroll compressor was established and experimentally verified, which provided a theoretical basis for optimizing scroll profile design, suppressing wrap tip wear and improving the energy efficiency of heat pump systems. Full article

Radiotherapy remains one of the main pillars of cancer treatment and is used in more than half of all oncological patients. Despite continuous technological improvements, ionizing radiation inevitably causes damage to surrounding healthy tissues, leading to acute and chronic complications affecting multiple organs, including the skin, mucosa, heart, lungs, bones and gastrointestinal tract. Radiation-induced injuries significantly impair patients’ quality of life, limit therapeutic doses, and represent a major unmet clinical challenge. Hydrogels have emerged as promising biomaterials for managing radiation-induced damage due to their high content of water, tunable mechanics, and ability to mimic the extracellular matrix. Recent innovations have introduced functional systems, including stimuli-responsive, injectable, and bioactive hydrogels, capable of delivering antioxidants, growth factors, or living cells. Unlike traditional material-based reviews, this work proposes a novel classification framework based on the hydrogel’s mechanism of action within the pathophysiology of radiation injury. We evaluate how specific designs, such as ROS-scavenging matrices, barrier-forming injectable shields, and bioactive delivery vehicles, address distinct phases of inflammation and fibrosis. By providing a comprehensive overview of radiation-induced injuries across different organs, this review summarizes current hydrogel-based strategies for both prevention and therapy. We highlight the potential of these mechanistically aligned systems to protect healthy tissues, suppress chronic inflammation, and promote effective tissue regeneration. Full article

In recent years, channel state information (CSI)-based sensing technology has gradually attracted widespread attention as a contactless and low-cost approach for robotic arm motion understanding. Despite continuous progress in CSI-based human sensing, existing methods of robotic motion sensing still face two key challenges when directly applied to robotic motion sensing: (1) CSI perturbations induced by robotic arm motion are weak and locally distributed, making fine-grained feature extraction difficult. (2) Discriminative information in long robotic arm motion sequences is sparsely concentrated in a few key intervals, and its adaptive temporal selection and enhancement remain challenging. To address the above challenges, this paper proposes an efficient multi-stage robotic arm motion recognition method (named MSPoolNet). The proposed method consists of three key modules: an adaptive temporal downsampling module, a temporal gating module, and a Transformer-based feature encoding module. Specifically, the adaptive temporal downsampling module processes the raw CSI signal at the input stage to achieve local pattern extraction. The temporal gating module adaptively reweights temporal features, dynamically highlighting key temporal segments while suppressing irrelevant information. The proposed Transformer-based feature encoding module replaces conventional self-attention with pooling operations, enabling global information interaction and fine-grained feature representation in a computationally efficient manner. Extensive experimental results demonstrate that the proposed method achieves state-of-the-art performance on two representative public datasets, maintaining a compact model size with an accuracy exceeding 99%. Full article