Search Results (2,019)

Low-rank ultrafine flotation clean coal typically yields filter cake moisture above 20% due to abundant oxygen-containing functional groups and strong surface hydrophilicity. Conventional polyacrylamide (PAM) flocculants are hydrophilic and improve dewatering only by altering cake porosity, not by reducing particle surface hydrophilicity, so they remove little adsorbed water. In this study, hydrophobically modified anionic polyacrylamides (HMAPAM) were synthesized by grafting lauryl acrylate onto APAM. FTIR, ¹H NMR, XPS, and SEM confirmed the grafting and progressive enrichment of hydrophobic alkyl chains on the surface. Moderate hydrophobic modification markedly improved solid–liquid separation. HMAPAM-D (APAM/LA = 4.5:0.5) achieved a settling velocity of 0.817 cm/s at 9 mg/L, 50.2% higher than APAM, and reduced filter cake moisture to 16.64% at 1 mg/L under 0.6 MPa versus 19.39% for unmodified APAM. Excessive modification (HMAPAM-E, 4:1) promoted intramolecular self-association, producing heterogeneous flocs and higher filtration resistance that degraded dewatering efficiency. The performance gain stems from hydrophobic association combined with adsorption bridging. These results clarify how hydrophobic group content controls flocculation and dewatering, informing the design of better flocculants for this type of coal slurry. Full article

Urban traffic congestion remains a persistent global challenge, contributing to significant economic inefficiencies, elevated greenhouse gas emissions, and diminished quality of life. This paper presents a real-world video-based traffic monitoring study combined with a proposed adaptive signal control framework. In the monitoring component, YOLOv11 object detection was applied directly to footage recorded from an overhead bridge position on a 40 km/h road. The model successfully detected and tracked multiple road-user categories, including cars, trucks, buses, motorcycles, cyclists, and pedestrians, yielding 1041 vehicle detections across 25 unique tracked objects. Vehicle speeds were estimated from inter-frame centroid displacement, and a Region of Interest (ROI) occupancy model was used to classify congestion states as High, Medium, or Free Flow using thresholds grounded in Highway Capacity Manual (HCM) level-of-service criteria. The system detected 11 high-congestion frames (3.8%), 184 medium-congestion frames (63.9%), and 93 free-flow frames (32.3%), consistent with moderate congestion observed during the recording period. In the proposed control component, a Proximal Policy Optimisation (PPO)-based reinforcement learning signal controller is designed around the YOLOv11 detection outputs as its state representation. Based on comparable adaptive traffic signal control studies in the literature, the proposed framework is projected to achieve approximately 25% higher peak-hour throughput, 35% shorter queue lengths, and 32% lower average waiting times relative to a fixed-time signal baseline. The detection accuracy (mAP@0.5 = 93.2%) and inference speed (32 FPS) cited are published YOLOv11 benchmarks used as indicative performance references. This work bridges real-world perception and proposed intelligent control, providing a transparent and reproducible methodology for next-generation smart city traffic management. Full article

Bulk RNA-sequencing (bulk RNA-seq) averages gene expression across cell mixtures, obscuring single-cell heterogeneity and spatial architectures essential for understanding pathological processes. We developed HistoMap, a deep learning-based framework for single-cell spatial deconvolution. The model employs a two-stage pipeline: first, reconstructing high-fidelity single-cell profiles from bulk data using a β-variational autoencoder, and second, utilizing a Histological Vision Transformer (H-ViT) to map these cells to tissue coordinates via dual guidance from transcriptomic references and H&E-stained morphological constraints. HistoMap demonstrated superior performance across diverse human tissues, achieving a Pearson Correlation Coefficient (PCC) of 0.800 on external validation. Application to 14 colorectal cancer cases revealed a Macro_SPP1-mediated desmoplastic barrier. SPP1+ macrophages act as spatial hubs at the invasive front, forming a physical “sequestration belt” that functionally excludes cytotoxic T cells from the tumor core. HistoMap successfully bridges bulk RNA-seq and spatial single-cell architectures. Our findings provide a molecular rationale for immune checkpoint blockade resistance and identify the SPP1-fibroblast axis as a pivotal target for therapeutic sensitization. Full article

The global expansion of highly pathogenic avian influenza A (H5N1), particularly the clade 2.3.4.4b lineage, has renewed urgent concerns about its pandemic potential in the context of its ongoing panzootic expansion and increasing cross-species transmission. Despite decades of preparedness initiatives, critical technological and structural gaps persist, especially in low- and middle-income countries (LMICs), where both vaccine access and sustainable manufacturing capacity remain limited. In this perspective, we examine key lessons from past influenza pandemics and global preparedness strategies, including the Global Action Plan for Influenza Vaccines, highlighting persistent challenges related to sustainable manufacturing capacity and equitable vaccine access. Additionally, we examine the potential of messenger RNA (mRNA) vaccine platforms to address these limitations, given their rapid design, scalable manufacturing, and adaptability to emerging pathogens. Moreover, we examine the role of neuraminidase (NA) as a complementary antigen capable of broadening immune protection and reducing viral transmission. Finally, we describe recent advances in Latin America, focusing on Argentina’s participation in the mRNA Technology Transfer Programme co-led by the World Health Organization (WHO) and the Medicines Patent Pool (MPP), as a model for strengthening regional manufacturing capacity and contributing to global pandemic preparedness. Together, these elements indicate that effective H5N1 pandemic preparedness will require the integration of improved antigen design, flexible mRNA platforms, and sustainable regional manufacturing systems aligned with global procurement strategies. Full article

The connection of a dianionic 2,2’-biimidazolate (biim²⁻) bridging unit to cis-[Cr(N^∩N)₂]³⁺ (N^∩N is a chelating didentate ligand) or cis-[Cr(N^∩N^∩N^∩N)]³⁺ building blocks (N^∩N^∩N^∩N is a chelating tetradentate ligand) produces heteroleptic pseudo-octahedral [CrN₆]⁺ chromophores. Their reduced cationic charge is compatible with the subsequent complexation of trivalent lanthanides (Ln³⁺) to give d-f {[(N^∩N)₂Cr(biim)]_nLn}⁽³⁺ⁿ⁾⁺ (n = 1–4), {[(N^∩N)₂Cr(biim)]Ln(Tp)₂}²⁺ and {[(N^∩N^∩N^∩N)Cr(biim)]Ln(Tp)₂}²⁺ adducts (Tp is tri(1H-pyrazol-1-yl)-λ⁴-borate). Moving from polyaromatic N^∩N (1,10 phenanthroline) to saturated N^∩N^∩N^∩N polyamine (cyclam) receptors controls the photophysical properties and leads to tunable light conversion in the target heterometallic complexes when Eu(III) is exploited as the activator for downshifting and Er(III) as the activator for upconversion. Full article

With the integrated development of high-speed railways and urban underground rail transit, large high-speed railway station buildings are often seamlessly connected or even co-constructed with subway structures, forming a complex structural system that integrates high-speed rail, subway, and station buildings. To investigate the dynamic performance of such “ integrated station-bridge” station buildings constructed with subways, this paper takes Yichang North Station as an engineering case study and examines its vertical dynamic characteristics under multi-source train-induced loads. The station adopts a structural configuration where the station tracks are fully integrated with the station building, while the main lines are separated from it. To accurately simulate the entire process of train operation, this study established a refined “train-track-station” spatially coupled dynamics model that incorporates high-speed and subway trains, tracks, and the station structure. Based on this model, various operational scenarios were systematically analyzed, including high-speed trains passing at different speeds, parallel operation of multiple train lines, and combined operation of high-speed and subway trains. The results demonstrate that, when single or multiple high-speed train lines pass through the station at the design entry speed of 80 km/h, the vertical vibration acceleration of the elevated waiting level meets human comfort standards. The train-induced vibration response is transmitted and superimposed along the “column–beam–slab” path, resulting in localized acceleration peaks at the mid-span regions of beams and slabs directly above the tracks. Second, the impact of subway train operation alone on the vibration of the elevated level is significantly weaker than that of high-speed trains. Furthermore, under combined high-speed and subway train operations, the additional vibration contribution from subway trains shows a decreasing trend as the number of simultaneously operating high-speed train lines increases. The findings of this study validate the effectiveness of the structural design of Yichang North Station in terms of train operational safety and passenger waiting comfort. The revealed patterns of multi-source vibration transmission and superposition can provide important theoretical and numerical references for the dynamic optimization design and vibration control of similar integrated transportation hub structures. Full article

With the increasing penetration of renewable energy systems, multilevel inverters have been widely adopted to meet the growing demand for high-power and high-quality energy conversion. Among various multilevel topologies, cascaded H-bridge multilevel inverters (CHMIs) are particularly attractive due to their modular structure and improved output voltage quality. However, the increased number of power semiconductor devices and switching states significantly complicates fault diagnosis under practical operating conditions. Currently, most existing neural networks for fault diagnosis are manually designed based on domain expertise. This may limit their adaptability to task-specific fault patterns as well as edge-side inference performance. To reduce the dependence on manually designed diagnostic networks, an edge-oriented fault diagnosis framework based on differentiable architecture search (DARTS) is proposed to automatically design task-specific diagnostic networks. A simplified special cell search strategy is adopted to improve search efficiency and facilitate practical deployment. The searched architectures are lightweight and suitable for deployment on edge platforms. The experiments show that the proposed method achieves an average diagnostic accuracy of 99.44% on the test set under the RL load of $(7\mathrm{\Omega },6\mathrm{mH})$. Furthermore, the searched model contains only 0.2417 M trainable parameters, and edge deployment experiments on the Jetson Orin Nano platform show low-latency inference capability. Full article

Silica dispersion in rubber matrices remains a critical issue due to the polarity mismatch between silica and the rubber phase. This study aimed to synthesize functionalized liquid polyisoprene rubber (F-LIR) and evaluate its role in improving the interfacial interaction between silica and solution styrene–butadiene rubber (SSBR). F-LIR was synthesized by introducing an alkoxysilane-containing functionalizing agent at the termination stage of anionic polymerization. Fourier transform infrared spectroscopy (FT-IR) and proton nuclear magnetic resonance spectroscopy (¹H-NMR) were used to confirm the successful introduction of silyl groups at the chain ends of liquid polyisoprene. The optimal loading of F-LIR in SSBR was evaluated through bound rubber content, dynamic mechanical analysis, and mechanical performance testing. The results demonstrated that F-LIR improved the tensile strength, modulus at 300% elongation, and bound rubber content of SSBR composites. These enhancements are attributed to the reaction between the silyl groups of F-LIR and surface hydroxyl groups of silica, together with the co-crosslinking interaction between F-LIR and SSBR. The composites containing 4 phr F-LIR exhibited the best overall balance of properties. This study provides a novel method for synthesizing F-LIR, which bridges silica and the rubber matrix by enhanced filler–rubber interactions at the filler–rubber interface. Full article

Zero-shot learning (ZSL) enables the recognition of unseen categories by leveraging models trained only on labeled seen-class samples in the source domain. Traditional ZSL methods typically assume identical data distributions across source and target domains—an assumption that rarely holds in real-world scenarios and causes dramatic performance degradation under domain shift. While existing generative ZSL methods have achieved promising results, they overlook the fundamental challenge of distribution shift. This paper bridges this gap by proposing GM-CDZSL, a generative framework that unifies semantic-conditioned feature synthesis and multi-source domain alignment for cross-distribution zero-shot learning. Unlike conventional approaches that only align semantic and visual features while ignoring latent domain discrepancies, our method imposes explicit distribution consistency constraints in the embedding space. Specifically, we design a set of one-vs-all domain discriminators and construct a distribution-aware loss based on empirical H-divergence to mitigate domain gaps and learn domain-invariant representations. Extensive experiments on multiple public benchmarks demonstrate that our method achieves consistent performance improvements over representative ZSL and domain generalization baselines, offering a practical solution to realistic cross-distribution zero-shot recognition tasks. Full article

We propose an interactive approach to teaching Coulomb’s law and electrostatics in general, rooted in two complementary pedagogical methodologies: hyper-constructivism (H-C) and neo-realism. Unlike standard constructivism, our hyper-constructivist approach treats students’ prior ideas—even if incomplete or inconsistent—as essential “submerged logs” that teachers may use to guide students across the cognitive lake, toward the correct understanding. We implement a triadic model of cognitive didactics, balancing amusement (the ludic “hook”), formal teaching, and deepening scientific inquiry. Here, we present a hyper-constructivist path on electrostatics—Coulomb’s and Gauss’s laws. Through a sequential path of experiments involving plastic rods, “trained” aluminum cans, Volta’s electrophorus, and “Christmas” ornaments, we demonstrate how students can spontaneously formulate problems and bridge the gap between intuitive observations and complex effects of electrical polarization, going beyond the scholastic Coulomb’s law, via numerical modeling. The proposed interactive approach is rooted in phenomena-based learning and leverages discrepant events—surprising physical phenomena that challenge prior intuitions—as “ludic hooks” to trigger spontaneous inquiry and conceptual reconstruction. The main goal of our strategies is to trigger and develop young students’ interest in physics, which in many European countries is low. This method not only facilitates the acquisition of physical laws but also fosters “intellectual inquisitiveness” and social competencies, proving that well-rooted knowledge emerges from a synthesis of tangible experience and advanced scientific modeling. Our contribution constitutes a complex pedagogical proposal, iteratively developed and implemented in diverse didactical environments over several years. This paper presents a pedagogical proposal developed and refined through more than twenty years of educational practice. For teachers interested in implementing hyper-constructivist instruction, we provide a detailed teaching pathway on electrostatics, with didactical explanations and pedagogical notes. Full article

Gradient amplifiers are a critical subsystem in Magnetic Resonance Imaging (MRI), as their performance directly impacts image fidelity, scan time, and overall system cost. This article surveys gradient amplifier topologies and design techniques reported in the literature, with particular emphasis on the practical trade-offs between high-performance solutions and cost-driven implementations. The review covers a broad range of architectures, from stacked H-bridge configurations that can provide high slew rate with low steady-state ripple, to modified audio-amplifier-derived approaches targeting low-cost platforms. Reported experimental results are synthesized to enable a comparative discussion in terms of key figures of merit, including linearity, efficiency, current ripple, dynamic response, and power density. The paper also discusses requirements and constraints arising from emerging MRI platforms, where compactness and energy efficiency are increasingly important. Finally, persistent challenges and open research directions are outlined, highlighting the need for architectures that improve efficiency without compromising linearity under high slew-rate operation, across both high-end clinical scanners and specialized low-cost systems. Full article

Turpan Black (TBL) and Altay (ALT) sheep are indigenous breeds adapted to extreme heat and severe cold in their respective native environments. However, the mechanisms underlying their divergent meat quality remain unclear. Using longissimus dorsi muscle from 15 TBL and 15 ALT sheep, we integrated phenotypic evaluation with non-targeted metabolomics and proteomics to elucidate the impact of environmental adaptation on ovine meat quality. Compared to the cold-adapted ALT sheep, the heat-tolerant TBL sheep exhibited lower post-mortem pH, reduced cooking loss, smaller muscle fiber cross-sectional area, and elevated selenium and magnesium levels. Multi-omics identified 99 differentially expressed proteins and 364 differentially expressed metabolites. Core divergence was enriched in lipid and amino acid metabolism and stress response networks, particularly the Apelin signaling, glycerophospholipid metabolism, and ferroptosis pathways. Lipid remodeling driven by glycerophospholipid metabolism emerged as a critical bridge linking adaptation to meat quality. Notably, glycero-3-phosphocholine, regulated by GPCPD1 and related enzymes, maintained cell membrane homeostasis and osmotic pressure, thereby enhancing water-holding capacity and tenderness. These findings reveal the multi-omics basis of climate-driven divergence in ovine meat quality, offering theoretical support for breeding stress-resilient, high-quality indigenous sheep breeds in extreme environments. Full article

Red mud (RM) and fly ash (FA) were used as a 30% replacement of cement in a sodium silicate-activated system. Composite mortar specimens with RM/FA ratios of 0:30, 1:5, 1:2, 1:1, and 2:1 were prepared with polypropylene fibers (PPF) for toughness enhancement. The mechanical properties and microstructure of the fiber-reinforced mortar were systematically investigated. The results showed that RM20F10 (RM/FA = 2:1) exhibited the best overall mechanical performance among all tested proportions. At this ratio, the 28-day compressive, flexural, and splitting tensile strengths reached 32.4 MPa, 7.3 MPa, and 4.2 MPa, exceeding the control mortar by 12.5%, 15.9%, and 23.5%, respectively. The RM/FA ratio of 1:1 achieved the highest 7-day flexural-to-compressive strength ratio. At 28 days, autogenous shrinkage increased from 910 με to 1100 με as the RM/FA ratio rose from 0:30 to 2:1, and all RM-containing specimens exhibited higher water absorption than the control mortar. Microstructural analysis by SEM, XRD, and FTIR revealed a denser matrix with reduced porosity, attributed to the synergistic formation of C–S–H, C–A–S–H, and N–A–S–H gels. RM reduced early-age porosity by promoting C–A–S–H gel formation, while FA facilitated late-age densification through delayed activation. PPF effectively bridged microcracks via fiber pull-out, leading to a ductile failure mode. Full article

Cascaded H-bridge (CHB) multilevel inverters are pivotal in high-power applications, such as renewable energy subsystems and motor drives, due to their superior modularity and harmonic performance. However, selecting the optimal number of levels remains a complex engineering trade-off between power quality, switching losses, and system complexity. This study presents a systematic investigation into CHB inverters ranging from three to twenty-one levels under carrier-phase-shifted sinusoidal pulse width modulation (CPS-SPWM) control. A detailed MATLAB/Simulink framework in version R2023a was established, incorporating a zero-order hold (ZOH) data synchronization protocol and parameterized macro-model MOSFETs to accurately quantify total harmonic distortion (THD) and individual switching energy dissipation. To evaluate the efficiency–quality equilibrium, a novel comprehensive evaluation index, the performance-to-loss ratio (PLR), is proposed. Simulation results indicate that while THD improves significantly with higher level counts, the marginal gains diminish beyond the 13-level configuration. Utilizing the PLR framework, the nine-level configuration is identified as a local optimum for cost-sensitive modularity, whereas the twenty-one-level setup provides the global optimum for high-performance scenarios where spectral purity is paramount. Accordingly, this proof-of-concept study provides a quantitative roadmap for designers and experimentalists to navigate the complex design space of multilevel inverters, enabling optimal allocation of hardware resources toward the net-zero vision while guiding future experimental efforts away from costly, exhaustive hardware characterization. Full article

Accurate regional lymph node staging is essential for guiding treatment and predicting outcomes in non-small cell lung cancer. While the 9th edition of the TNM classification introduced prognostic subdivisions for N2 disease, the N1 category remains a single, unified descriptor. However, N1 disease is highly heterogeneous. Evidence shows significant survival differences between single-station (N1a) and multi-station (N1b) involvement, as well as between peripheral (N1p) and hilar (N1h) metastases. Standard medical imaging evaluation and conventional bronchoscopy often fail to detect “occult N1 disease,” leading to postoperative stage migration and suboptimal treatment sequencing. This diagnostic gap affects critical clinical decisions, including the selection of patients for sublobar resection, the administration of neoadjuvant chemoimmunotherapy, and the precision of radiation target volumes. The main obstacle to refining N1 staging has been the limited ability of existing clinical staging modalities to access and accurately assess N1p nodes. However, recent technological advances, particularly in thin convex probe endobronchial ultrasound examination, have renewed interest in bronchoscopic evaluation of N1p and in improving preoperative clinical N1 staging. The purpose of this review is to summarize the biological and immunological basis for N1 subclassification and evaluate how emerging technologies can bridge the gap between clinical and pathological staging. Refining the N1 compartment is vital for a personalized staging system that reflects the true biological spectrum of lung cancer. Full article