Search Results (36,626)

Hyperspectral–multispectral (HSI–MSI) image fusion aims to reconstruct high-spatial-resolution hyperspectral images (HR-HSIs) by combining the spectral fidelity of low-resolution HSIs (LR-HSIs) with the spatial details of high-resolution MSIs (HR-MSIs). A key challenge is preserving spectral–spatial consistency under cross-modal resolution mismatch, where inadequate long-range dependency modeling and unstable inter-modality interaction may induce spectral distortion and structural discontinuities. This paper proposes DSIR-Net (DSIR), a dual-stream state-space fusion architecture equipped with an implicit neural representation (INR) module. DSIR decouples spectral and spatial representation learning into two coordinated streams and leverages state-space modeling to aggregate global context efficiently during progressive fusion. Moreover, INR-based coordinate-conditioned refinement provides continuous sub-pixel compensation, enhancing high-frequency detail recovery while suppressing fusion-induced artifacts. Across four commonly used benchmark datasets, DSIR shows consistent advantages over the competing methods in both numerical metrics and visual reconstruction quality. In addition to sharper structural details, DSIR preserves spectral information more faithfully. Using the best result among the baselines on each dataset as reference, the PSNR improvements are 0.040 dB (Houston), 0.204 dB (PaviaU), 0.093 dB (Botswana), and 0.163 dB (Chikusei). Full article

Thick oil shale roofs in the Zichang mining area frequently suffer from delamination and sudden brittle fracture, compromising support stability. Using the 50117 return-air roadway as a case study, this paper integrates microstructural characterization (SEM-EDS/XRD), mechanical testing, theoretical interpretation, and FLAC3D simulation to elucidate the instability mechanism. Results indicate that the preferred orientation of clay minerals along bedding yields a “weak friction” signature, facilitating delamination. Simultaneously, the rigid quartz framework enables rapid energy storage, yet constrained bending dissipation triggers instantaneous fracture. This “weak friction-strong cementation” property drives the “delamination-brittle fracture” mechanism. Notably, the roof exhibits low principal stress concentration but extreme sensitivity to deviatoric stress, typifying a “low-stress environment and weak structural damage” behavior. Accordingly, a synergistic control technology featuring “high-prestress normal clamping and dowel shear resistance” was proposed. Field application confirmed its effectiveness in suppressing delamination and reducing rib convergence, thereby ensuring long-term roadway stability. Full article

This study examined the role of e-modules and learning applications in enhancing scientific literacy among Grade 11 Life Sciences learners in a South African secondary school. Grounded in constructivist and connectivist learning theories, the research responded to persistent challenges in learners’ conceptual understanding, scientific reasoning, and application of scientific knowledge. A mixed-methods case study design was employed, combining quantitative pre- and post-test data with qualitative classroom observations and semi-structured learner interviews. Thirty learners participated in a technology-enhanced instructional intervention using curriculum-aligned e-modules delivered through Binogi and Google Classroom. Quantitative findings revealed a statistically significant improvement in scientific literacy following the intervention. Learners’ mean scores increased from 39.20% (pre-test) to 63.07% (post-test), representing a gain of 23.87 percentage points. A paired-samples t-test confirmed that this improvement was extremely significant (t (29) = 11.58, p < 0.0001), with a very large effect size (Cohen’s d = 2.11). Qualitative findings indicated that learners experienced enhanced engagement, improved conceptual clarity, and greater motivation when using digital learning tools, particularly through visualisations, animations, and self-paced learning. However, persistent difficulties with graph interpretation were also identified. The study concludes that the intentional integration of e-modules and learning applications can substantially enhance scientific literacy in Life Sciences by supporting conceptual understanding, reasoning, and learner engagement. These findings highlight the importance of pedagogically guided digital integration and teacher professional development to strengthen science learning outcomes. Full article

Large deformations in deep soft rock roadways primarily stem from low rock strength under high in situ stress and intense mining disturbance. This renders stability control a critical challenge in tunneling support engineering. Utilizing Xinhe Coal Mine’s deep soft rock tunnel as a representative case, this study integrates field monitoring, laboratory experimentation, and numerical simulation to investigate how excavation and grouted rock bolting influence surrounding rock stability. Building upon field-observed deformation mechanisms and support failure patterns, constitutive models for FLAC^3D’s embedded cable and beam elements were modified to achieve high-fidelity simulation of grouted support systems. Numerical models simulating diverse support schemes were established to analyze roadway displacement fields, plastic failure development, and structural behavior of support components, ultimately identifying the optimal rehabilitation solution. The research results indicate that the numerical simulation outcomes of the original support scheme exhibit good agreement with field observations in terms of roadway deformation patterns, deformation magnitudes, and occurrences of bolt/cable fractures. This demonstrates that the adopted refined numerical simulation methodology and parameters are reasonable and exhibit high reliability. Considering both surrounding rock stability and cost control, Roadway Rehabilitation Scheme S1 was identified as the optimal support solution. Its specific parameters are pre-grouting + full-section rock bolts (diameter 22 mm, length 2.4 m, spacing 0.8 m, row spacing 1.6 m) + full-section grouted cables (diameter 22 mm, length 6.2 m, spacing 1.0 m, row spacing 1.6 m). Full article

Lead-free perovskite solar cells have become attractive as they are more environmentally friendly than their lead-based counterparts. Among these lead-free perovskite materials is MASnI₂Br, which has attracted considerable attention due to its environmentally friendly advantages and beneficial optoelectronic properties. However, further enhancement is required in order to improve the power conversion efficiencies. In this study, an MASnI₂Br-based perovsdkite solar cell is designed and optimized using SCAPS-1D simulations. An extensive iterative simulation approach is carried out to optimize critical parameters such as electron affinity, energy bandgap, layer thickness and doping concentration for both transport layers. In addition, the thickness of the MASnI₂Br absorbing layer is optimized. With the improved device setup, the maximum achievable power conversion efficiency is 24%. Furthermore, by matching the optimized electronic structure with realistic transport materials, CBTS and TiO₂ are identified as suitable hole and electron transport layers, respectively. The proposed TiO₂/MASnI₂Br/CBTS perovskite solar cell has a power conversion efficiency of about 23.6%. Full article

Restoring the ecological function of degraded wetlands from the perspective of hydrological connectivity is of great significance for maintaining the stability of wetland ecosystem and biodiversity. Taking Zoige Wetland as the study area, this paper quantitatively analyzed the changing law of hydrological connectivity of wetland from 2000 to 2020 in terms of structural connectivity and functional connectivity by using the landscape index and the landscape connectivity index, and identified the important habitat patches, as well as the main influencing factors of hydrological connectivity. The results showed that functional connectivity increased slightly overall, with Probability of Connectivity (PC) and Integral Index of Connectivity (IIC) showing synchronized interannual fluctuations and higher mean levels in 2010–2020 than in 2000–2009. Patch-importance analysis (dPC) identified connectivity “backbone” areas along the Yellow River main channel and Central Zoige County. Pearson correlations (n = 21) indicated that PC was positively associated with precipitation (r = 0.77) and runoff (r = 0.68), and negatively associated with temperature (r = −0.41), vegetation cover (FVC; r = −0.68), and human disturbance proxy (PAFRAC; r = −0.66). These results help elucidate degradation processes and drivers in the Zoige Wetland and inform protection and restoration. Future studies should combine denser time series with field surveys to reduce uncertainties in remote-sensing water mapping. Full article

Man-made hazards pose serious threats to the safety and preservation of heritage structures. With armed conflict becoming increasingly prominent, it is urgent to enhance our understanding of how these structures respond under extreme conditions to drive conservation strategies. The Citadel of Aleppo in Syria, placed on the List of World Heritage in Danger in 2013 due to the civil war, tragically exemplifies the vulnerability of cultural heritage in times of conflict. In such a framework, this study focuses on the Minaret of the Ayyubid Great Mosque of the Citadel of Aleppo as a representative masonry tower to investigate the effects of man-made threats. Based on a 3D finite element model built in the Abaqus/Explicit environment, blast scenarios associated with aviation bombs and human-borne improvised explosive devices (IEDs) were simulated. The Conventional Weapons Effects (CONWEP) model was used to assess the structural response to blast pressures, also as a function of charge size, standoff distance, and modelling parameters (mesh size, strain rate). This study’s outcomes provide insights into the potential damage caused by aviation bombs and IED attacks, advancing the understanding of the vulnerability of tower-like masonry structures to such hazards while also informing future conservation strategies. Full article

With the rise of telecommunication systems in recent decades, the implications for human health have prompted a search for ways to reduce the impact of electromagnetic waves in buildings when necessary. A viable and promising solution to realize electromagnetic shielding could be the use of drywall panels coated with a biochar paste, as proposed in this study. Biochar (bio-charcoal), a low-cost and carbon-based material, can be obtained by the thermochemical conversion of different biomass sources. A commercial wood-based biochar thermally treated at 750 °C is considered in this work. Transmission coefficients of several gypsum board elements with a biochar coating are measured in the frequency K-band (18–27 GHz). In addition, the SE of a double panel configuration, obtained by joining two coated boards to form a multilayer structure, is evaluated. The results show that the biochar coating significantly enhances the SE compared to uncoated drywall. At the highest biochar loading investigated (0.20 g/cm²), the shielding effectiveness consistently exceeds 27 dB for single panels and 46 dB for double panels across the entire frequency band. These findings indicate that biochar-coated drywall systems offer a practical and sustainable solution for integrating electromagnetic shielding into building envelopes, paving the way for innovative applications in indoor exposure control. Full article

The grinding of Tremella fuciformis is a critical step for its value-added processing and the efficient utilization of its functional components, significantly impacting product quality and process adaptability. This study investigated ultrafine grinding (UFG) as a mechano-physical strategy to improve product quality, systematically analyzing its impact on physical properties (particle size, powder characteristics, color), extraction efficiency, chemical composition, and rheological behavior compared to conventional grinding (CG). The results revealed that UFG treatment induced an extensive disruption of the matrix, reducing particle size by 91.8% (D90 = 18.18 μm) and significantly increasing specific surface area. Notably, this physical modification directly translated into enhanced processing performance. UFG powder exhibited reduced powder flowability, superior solubility and improved color brightness. This structural degradation proved beneficial for extraction, unlocking a substantially higher yield (60.98–66.48%). Concurrently, the aqueous extracts of UFG powder exhibited more fluid-like rheological characteristics. This study confirms the potential of UFG as an effective pretreatment for the intensive processing of T. fuciformis and indicates its promising application in functional food development and the extraction of bioactive components. Full article

This paper presents a high-sensitivity two-dimensional fiber-optic hydrophone designed for the detection and localization of underwater acoustic sources. The device comprises two sensing heads, each incorporating a fiber Bragg grating (FBG) embedded within a customized 3D-printed encapsulation. To enhance acoustic sensitivity, the design utilizes a silicone thin-film coupled with a pyramidal channel that spatially concentrates acoustic energy from the base to the apex, where the FBG is positioned. Incident acoustic pressure induces vibrations in the film, which are amplified by the channel structure, imparting strain on the FBG and resulting in a shift in the Bragg wavelength. The acoustic frequency response is demodulated by converting the overlapping optical power between the sensing and reference gratings into an electrical signal via a photodetector. By arranging the two sensing heads orthogonally, the system effectively determines the direction and angle of the acoustic source. Experimental results show a peak sensitivity of −210.59 dB re 1 V/μPa, with a FWHM of 57.92–66.27 Hz and a figure of merit (FOM) up to 3.64 dB/Hz. In addition, the acoustic-field SNR is approximately 26 dB in the dominant band, and the LOD is 64.19 dB re 1 μPa (10–400 Hz). Experimental validation confirms the hydrophone’s high sensitivity and localization accuracy, demonstrating its significant potential for underwater acoustic sensing applications. Full article

Most existing research in human pose estimation focuses on predicting joint positions, paying limited attention to recovering the full 6D human pose, which comprises both 3D joint positions and bone orientations. Position-only methods treat joints as independent points, often resulting in structurally implausible poses and increased sensitivity to depth ambiguities—cases where poses share nearly identical joint positions but differ significantly in limb orientations. Incorporating bone orientation information helps enforce geometric consistency, yielding more anatomically plausible skeletal structures. Additionally, many state-of-the-art methods rely on large, computationally expensive models, which limit their applicability in real-time scenarios, such as human–robot collaboration. In this work, we propose STAG-Net, a novel 2D-to-6D lifting network that integrates Graph Convolutional Networks (GCNs), attention mechanisms, and Temporal Convolutional Networks (TCNs). By simultaneously learning joint positions and bone orientations, STAG-Net promotes geometrically consistent skeletal structures while remaining lightweight and computationally efficient. On the Human3.6M benchmark, STAG-Net achieves an MPJPE of 41.8 mm using 243 input frames. In addition, we introduce a lightweight single-frame variant, STG-Net, which achieves 50.8 mm MPJPE while operating in real time at 60 FPS using a single RGB camera. Extensive experiments on multiple large-scale datasets demonstrate the effectiveness and efficiency of the proposed approach. Full article

Multi-plane computer-generated holography is a key technology for enabling volumetric and near-eye displays. However, its widespread adoption remains constrained by the high computational cost of phase optimization and the persistent issue of axial crosstalk between depth planes. In this work, we propose a physics-informed deep learning framework that directly generates holograms for 3D multi-plane displays. Our approach implements a learnable mapping from spatial distributions to depth-dependent reconstructions and incorporates a trainable Fourier transform layer, enabling end-to-end optimization entirely in the physical domain (i.e., from the hologram plane to the multi-plane reconstruction). As a result, hologram generation time is decreased significantly, while effectively suppressing crosstalk across axial planes. Experimental validation demonstrates that the obtained phase hologram successfully reconstructs sparse multi-plane structured patterns with low visible crosstalk. These results highlight the potential of deep learning to advance practical applications in dynamic 3D display and holographic optical tweezer technologies. Full article

Autism classification is challenging due to the subtle, heterogeneous, and overlapping neural activation profiles that occur in individuals with autism. Novel deep learning approaches, such as Convolutional Neural Networks (CNNs) and their variants, as well as Transformers, have shown moderate performance in discriminating between autism and normal cohorts; yet, they often struggle to jointly capture the spatial–structural and temporal–functional variations present in autistic brains. To overcome these shortcomings, we propose a novel hierarchical deep learning framework that extracts the inherent spatial dependencies from the dual-modal MRI scans. For sMRI, we develop a 3D Hierarchical Convolutional Neural Network to capture both fine and coarse anatomical structures via multi-view projections along the axial, sagittal, and coronal planes. For the fMRI case, we introduced a bidirectional LSTM-based temporal encoder to examine regional brain dynamics and functional connectivity. The sequential embeddings and correlations are combined into a unified spatiotemporal representation of functional imaging, which is then classified using a multilayer perceptron to ensure continuity in diagnostic predictions across the examined modalities. Finally, a cross-modality fusion scheme was employed to integrate feature representations of both modalities. Extensive evaluations on the ABIDE I dataset (NYU repository) demonstrate that our proposed framework outperforms existing baselines, including Vision/Swin Transformers and various newly developed CNN variants. For the sMRI branch, we achieved 90.19 ± 0.12% accuracy (precision: 90.85 ± 0.16%, recall: 89.27 ± 0.19%, F1-score: 90.05 ± 0.14%, and focal loss: 0.3982). For the fMRI branch, we achieved an accuracy of 88.93 ± 0.15% (precision: 89.78 ± 0.18%, recall: 88.29 ± 0.20%, F1-score: 89.03 ± 0.17%, and focal loss of 0.4437). These outcomes affirm the superior generalization and robustness of the proposed framework for integrating structural and functional brain representations to achieve accurate autism classification. Full article

The onshore southern Lake Albert Rift Basin in Uganda represents a geologically complex and hydrocarbon-prone segment of the western branch of the East African Rift System. This study integrates seismic, well and geochemical data, and 2D Basin and Petroleum Systems modeling to reconstruct the petroleum system of the basin. Results highlight spatial variations in source rock maturity and indicate a predominantly oil-prone character. Migration modeling reveals hydrocarbon expulsion and vertical migration into both the overlying Middle—late Miocene Kakara and underlying early Miocene Kisegi sandstone reservoirs, facilitated by fault-controlled pathways. The late Miocene—early Pliocene Oluka Formation proves to be an effective regional seal, supported by its low modeled porosity, while overpressure zones enhance migration and accumulation efficiency. Present-day thermal maturity profiles and porosity–depth relationships indicate favorable conditions for hydrocarbon generation, migration, and preservation. These findings redefine our understanding of petroleum system dynamics in the Albert Rift and underscore the exploration potential of underexplored structural and stratigraphic traps in the southern sector of this rift and analogous rift settings. Full article

Type 2 diabetes mellitus and prediabetes often develop silently and may remain undiagnosed for years. This is particularly relevant in regions where laboratory-based screening is not always readily accessible. Against this background, the present work explores whether multilead electrocardiography can provide physiologically meaningful markers potentially associated with disturbances in glucose metabolism. We developed and tested an upgraded wearable 12-lead ECG system capable of synchronized multichannel recording under controlled conditions. ECG signals were acquired in sitting and standing positions, with a sampling frequency of 500 Hz and a recording duration of one minute per posture. The hardware architecture included a high resolution analog front-end and wireless data transmission; the accompanying software provided acquisition control, preprocessing, visualization, and data storage within a unified framework. Signal processing focused on the extraction of rhythm-related and morphological parameters, with particular attention to ventricular repolarization indices. QT interval, heart rate–corrected QT (QTc), and QT dispersion (QTd) were calculated across leads, as these parameters are known to reflect heterogeneity of repolarization and autonomic influences on myocardial electrophysiology. The analysis was structured to ensure reproducible boundary detection and systematic feature formation rather than isolated parameter measurement. The study had a pilot character and included a limited and unbalanced sample (healthy n = 10; prediabetes n = 1; T2DM n = 1). For this reason, the results are presented descriptively and should be regarded as preliminary observations. In representative cases, differences in QT-related indices were noted between categories of glycemic status; however, the potential influence of age, sex, and other confounders cannot be excluded. A pilot expert comparison of T-wave end detection demonstrated close agreement between the automated algorithm and cardiologist assessment (mean Δ$T_{end}$ approximately −1 to −2 ms; MAE 10–24 ms). Diagnostic performance metrics such as ROC/AUC, sensitivity, and specificity were not calculated at this stage, as validation in a larger cohort with biochemical confirmation (HbA1c, OGTT) is required. The study demonstrates the technical feasibility of combining synchronized 12-lead wearable acquisition with structured multilead repolarization analysis. The proposed system should therefore be considered a research platform intended to support further clinical validation and methodological development rather than a finished screening solution. Full article