Search Results (13,926)

Noisy permutation channels are applied in modeling biological storage systems and communication networks. For noisy permutation channels with strictly positive and full-rank square matrices, new achievability bounds are given in this paper, which are tighter than existing bounds. To derive this bound, we use the $ϵ$-packing with Kullback–Leibler divergence as a distance and introduce a novel way to illustrate the overlapping relationship of error events. This new bound shows analytically that for such a matrix W, the logarithm of the achievable code size with a given block n and error probability $ϵ$ is closely approximated by $\ell log\left({\displaystyle \frac{\sqrt{n}}{-{\Phi }^{-1}(ϵ/G)}}\right)+logV\left(W\right)$, where $\ell =\mathsf{rank}\left(W\right)-1$, $G=2\left({\displaystyle \genfrac{}{}{0pt}{}{\ell +1}{2}}\right)$, and $V\left(W\right)$ is a characteristic of the channel referred to as channel volume ratio. Our numerical results show that the new achievability bound significantly improves the lower bound of channel coding. Additionally, the Gaussian approximation can replace the complex computations of the new achievability bound over a wide range of relevant parameters. Full article

RISC-V has emerged as a compelling alternative to proprietary instruction set architectures, distinguished by its openness, extensibility, and modularity. As the ecosystem matures, attention has turned to building confidential computing foundations, notably Trusted Execution Environments (TEEs) and secure enclaves, to support sensitive workloads. These efforts explore a variety of design directions, yet reveal important trade-offs. Some approaches achieve strong isolation guarantees, but fall short in scalability or broad adoption. Others introduce defenses, such as memory protection or side-channel resistance, although often with significant performance costs that limit deployment in constrained systems. Lightweight enclaves address embedded contexts, but lack the advanced security features demanded by complex applications. In addition, early-stage development, complex programming models, and limited real-world validation hinder their usability. This survey reviews the current landscape of RISC-V TEEs and secure enclaves, analyzing their architectural principles, strengths, and weaknesses. To the best of our knowledge, this is the first work to present such a consolidated view. Finally, we highlight open challenges and research opportunities, aiming toward establishing a cohesive and trustworthy RISC-V trusted computing ecosystem. Full article

The effective design and operation of hydraulic structures, particularly open channel spillways, are crucial for water resource management and flood risk reduction in dams. A clear understanding of flow properties, such as velocity fluctuations and discharge, across various depths is essential for optimizing performance. In this study, experimental analysis and numerical simulation using FLOW-3D were combined to investigate the hydraulic parameters of a scaled model of the Romaine IV spillway located in Quebec, Canada. Measurements focused on flow properties, including velocity fluctuations at various discharge rates in specific flow depths, at selected points along the spillway. The numerical model was assessed by reproducing experimental geometry, initial water levels, and boundary conditions, and through sensitivity analyses to ensure accurate flow representation. Comparisons of flow rates of 180, 240, and 340 L/s showed that while simulations with the renormalized group (RNG) turbulence model reliably predicted average velocities, they underestimated maximum values and overestimated minimum values, especially at higher discharges. The results highlight the difficulty of accurately capturing velocity extremes in turbulent flows and the need for further model refinement. This was evident from the 60% discrepancy in minimum velocities observed at the channel center. Despite these discrepancies, the study advances our understanding of spillway performance and identifies avenues to improve the accuracy of numerical modeling in hydraulic engineering. Full article

This study proposes a comprehensive and computationally efficient system for the recognition of heart valve diseases (HVDs) in phonocardiogram (PCG) signals, emphasizing an end-to-end workflow suitable for real-world deployment. The core of the system is a lightweight weighted convolutional neural network (WCNN) featuring a key weighting calculation (KWC) layer, which enhances noise robustness by adaptively weighting feature map channels based on global average pooling. The proposed system incorporates optimized feature extraction using Mel-frequency cepstral coefficients (MFCCs) guided by GradCAM, and a band energy ratio (BER) metric to assess signal quality, showing that lower BER values are associated with higher misclassification rates due to noise. Experimental results demonstrated classification accuracies of 99.6% and 90.74% on the GitHub PCG and PhysioNet/CinC Challenge 2016 databases, respectively, where the models were trained and tested independently. The proposed model achieved superior accuracy using significantly fewer parameters (312,357) and lower computational cost (4.5 M FLOPs) compared with previously published research. Compared with the model proposed by Karhade et al., the proposed model use 74.9% fewer parameters and 99.3% fewer FLOPs. Furthermore, the proposed model was implemented on a Raspberry Pi, achieving real-time HVDs detection with a detection time of only 1.87 ms for a 1.4 s signal. Full article

We present an analytical and numerical study of nonlinear wave localization in a one-dimensional rhombic (diamond) waveguide array that combines forward- and backward-propagating channels. This mixed-index configuration, realizable through Bragg-type couplers or corrugated waveguides, produces a tunable spectral gap and supports nonlinear self-localized states in both transmission and forbidden-band regimes. Starting from the full set of coupled-mode equations, we derive the effective evolution model, identify the role of coupling asymmetry and nonlinear coefficients, and obtain explicit soliton solutions using the method of multiple scales. The resulting envelopes satisfy a nonlinear Schrödinger equation with an effective nonlinear parameter $\theta$, which determines the conditions for soliton existence ($\theta >0$) for various combinations of focusing and defocusing nonlinearities. We distinguish solitons formed outside and inside the bandgap and analyze their dependence on the dispersion curvature and nonlinear response. Direct numerical simulations confirm the analytical predictions and reveal robust propagation and interactions of counter-propagating soliton modes. Order-of-magnitude estimates show that the predicted effects are accessible in realistic integrated photonic platforms. These results provide a unified theoretical framework for soliton formation in mixed-index lattices and suggest feasible routes for realizing controllable nonlinear localization in Bragg-type photonic structures. Full article

This study proposes a composite acoustic porous duct metamaterial muffler composed of a perforated tortuous channel and an externally wrapped porous layer, integrating both structural resonance and material damping effects. Theoretical models for the perforated plate, tortuous channel, and porous material were established, and analytical formulas for the total acoustic impedance and transmission loss of the composite structure were derived. Finite element simulations verified the accuracy of the models. A systematic parametric study was then performed on the effects of porous material type, thickness, and width on acoustic performance, showing that polyester fiber achieves the best results at a thickness of 30 mm and a width of 5 mm. Further analysis of periodic distribution modes revealed that axial periodic arrangement significantly enhances the peak noise attenuation, radial periodic arrangement broadens the effective bandwidth, and multi-frequency parallel configurations further expand the operating range. Considering practical duct conditions, a single-layer multi-cell array was constructed, and its modal excitation mechanism was clarified. By employing the Particle Swarm Optimization (PSO) algorithm for multi-parameter optimization, the average transmission loss was improved from 26.493 dB to 29.686 dB, corresponding to an increase of approximately 12.05%. Finally, physical samples were fabricated via 3D printing, and four-sensor impedance tube experiments confirmed good agreement among theoretical, numerical, and experimental results. The composite structure exhibited an average experimental transmission loss of 24.599 dB, outperforming the configuration without porous material. Overall, this work highlights substantial scientific and practical advances in sound energy dissipation mechanisms, structural optimization design, and engineering applicability, providing an effective approach for broadband and high-efficiency duct noise reduction. Full article

As oilfield development enters the mid-to-late stages, conventional water flooding techniques face increasing challenges such as high water cut and limited improvement in recovery efficiency. Gas flooding has gradually become a critical method for enhancing oil recovery (EOR). However, significant heterogeneity in pore structures within complex reservoirs severely affects flow capacity and development performance during gas flooding processes. To elucidate the microscale flow mechanisms influenced by heterogeneity, this study constructs a series of two-dimensional pore network models with varying degrees of heterogeneity based on an improved Quartet Structure Generation Set algorithm. Gas-oil two-phase flow simulations were conducted using the multiphase flow module of COMSOL Multiphysics® 6.2. By adjusting the bimodal pore size ratio and pore distribution parameters, the heterogeneity level of the reservoir was systematically controlled, and relative permeability curves were extracted to inform macro-scale development strategy design. Simulation results indicate that (1) strong heterogeneity reduces the stability of the displacement front, leading to pronounced gas channeling; (2) in strongly heterogeneous pore structures, residual oil saturation significantly increases, with small pore regions forming residual oil-enriched zones that are difficult to mobilize; (3) relative permeability curves vary markedly under different heterogeneity conditions—oil-phase permeability declines rapidly during displacement, while gas-phase permeability rises sharply at high gas saturation levels. This study systematically investigates, for the first time, the microscale impact of pore structure heterogeneity on gas flooding behavior and applies pore-scale simulation outcomes to optimize macro-scale development strategies. The findings offer theoretical support and a technical pathway for gas injection design in complex heterogeneous reservoirs. While two-dimensional pore-network models enable controlled mechanistic and sensitivity analyses of heterogeneity, they do not fully capture three-dimensional connectivity and tortuosity. Accordingly, our results are positioned as mechanistic priors that are calibrated to field data during upscaling. Full article

Three-dimensional holographic imaging technology is increasingly applied in biomedical detection, materials science, and industrial non-destructive testing. Achieving high-resolution, large-field-of-view, and high-speed three-dimensional imaging has become a significant challenge. This paper proposes and implements a three-dimensional holographic imaging method based on trillion-frame-frequency all-optical multiplexing. This approach combines spatial and temporal multiplexing to achieve multi-channel partitioned acquisition of the light field via a two-dimensional diffraction grating, significantly enhancing the system’s imaging efficiency and dynamic range. The paper systematically derives the theoretical foundation of holographic imaging, establishes a numerical reconstruction model based on angular spectrum propagation, and introduces iterative phase recovery and image post-processing strategies to optimize reproduction quality. Experiments using standard resolution plates and static particle fields validate the proposed method’s imaging performance under static conditions. Results demonstrate high-fidelity reconstruction approaching diffraction limits, with post-processing further enhancing image sharpness and signal-to-noise ratio. This research establishes theoretical and experimental foundations for subsequent dynamic holographic imaging and observation of large-scale complex targets. Full article

Image restoration tasks such as deraining, deblurring, and dehazing are crucial for enhancing the environmental perception of autonomous vehicles and traffic systems, particularly for tasks like vehicle detection, pedestrian detection and lane line identification. While transformer-based models excel in these tasks, their prohibitive computational complexity hinders real-world deployment on resource-constrained platforms. To bridge this gap, this paper introduces a novel Soft Knowledge Distillation (SKD) framework, designed specifically for creating highly efficient yet powerful image restoration models. Our core innovation is twofold: first, we propose a Multi-dimensional Cross-Net Attention(MCA) mechanism that allows a compact student model to learn comprehensive attention relationships from a large teacher model across both spatial and channel dimensions, capturing fine-grained details essential for high-quality restoration. Second, we pioneer the use of a contrastive learning loss at the reconstruction level, treating the teacher’s outputs as positives and the degraded inputs as negatives, which significantly elevates the student’s reconstruction quality. Extensive experiments demonstrate that our method achieves a superior trade-off between performance and efficiency, notably enhancing downstream tasks like object detection. The primary contributions of this work lie in delivering a practical and compelling solution for real-time perceptual enhancement in autonomous systems, pushing the boundaries of efficient model design. Full article

The E reservoir in Daqing Oilfield exhibits strong heterogeneity, resulting in inconsistent performance of conventional development methods. Polymer flooding is currently implemented using 106 m and 150 m well patterns. To characterize the influence of well spacing variations on polymer flooding effectiveness and enhance oil recovery, we conducted experiments to evaluate the apparent viscosity, solution concentration, viscoelasticity, plugging resistance, and profile modification performance of polymer solutions at different relative migration distances. Subsequent experiments employing differently scaled intra-layer heterogeneous models investigated polymer flooding’s oil recovery enhancement at various migration distances. Results indicate the following: (1) At identical relative migration distances, polymer systems in shorter sand-packed tubes demonstrate a higher effective migration distance proportion and superior viscoelasticity compared to 30 cm models, enabling more effective remaining oil mobilization and improved microscopic displacement efficiency. (2) The 20 cm sand-packed tube model exhibits enhanced plugging resistance and profile modification capabilities with higher maintained viscosity and concentration retention. Polymer solutions at 20%, 40%, 60%, and 80% migration distances in longer tubes established resistance factors of 30, 15, 7.8, and 3.6, and residual resistance factors of 9.6, 5.6, 2.2, and 1.5, respectively. These solutions effectively migrate to reservoir depths, forming efficient plugs and demonstrating superior deep profile control compared to their longer tube counterparts. (3) Polymer flooding response occurred at 0.194 PV injection in the 40 cm model with a maximum water cut reduction of 36.04%, whereas the 60 cm model required 0.31 PV injection to achieve a response, yielding only a 26.7% maximum water cut reduction. This comparative result demonstrates that smaller well spacing enables faster establishment of effective displacement pressure systems, suppresses high-permeability layer channeling, and significantly improves medium- and low-permeability layer utilization efficiency. (4) Crude oil mobilization in medium- and low-permeability layers is substantially reduced in larger well-spacing models. Collectively, reduced well spacing accelerates polymer flooding response, mitigates reservoir heterogeneity impacts, and extends the operational range of polymer plugging resistance and profile modification capabilities, thereby increasing recovery in heterogeneous reservoirs. Full article

Tight gas reservoirs are characterized by low porosity, low permeability, and strong heterogeneity. CO₂ flooding, as an important approach for enhancing gas recovery while achieving carbon sequestration, is often restricted by gas channeling. Based on the sandstone reservoir parameters of the Shihezi Formation in the Ordos Basin, a two-dimensional fracture–matrix coupled numerical model was developed to systematically investigate the effects of fracture number, fracture inclination, fracture width, injection pressure, and permeability contrast on gas breakthrough time and sweep efficiency. A second-order regression model was further established using response surface methodology (RSM). The results show that a moderate fracture density can extend breakthrough time and improve sweep efficiency, while permeability contrast is the fundamental factor controlling gas channeling risk. When the contrast increases from 0.7 to 9.9, the breakthrough efficiency decreases from 88.5% to 68.9%. The response surface analysis reveals significant nonlinear interactions, including the coupled effects of fracture number with fracture width, injection pressure, and inclination angle. Under the optimized conditions, the breakthrough time can be extended to 46,984 h, with a corresponding sweep efficiency of 87.7%. These findings provide a quantitative evaluation method and engineering optimization guidance for controlling CO₂ channeling in tight gas reservoirs. Full article

There has been a growing demand for clean energy in recent years, with the advancement of the carbon neutrality vision. Wind power has occupied a significant percentage of clean energy sources. Usually deployed in open fields, on mountaintops, and in offshore areas, wind turbines are particularly vulnerable to lightning strikes due to their unique operational characteristics. Therefore, accurately evaluating the lightning strike risk of wind turbines is an important issue that should be addressed. Current IEC standards lack a physically grounded approach for calculating the equivalent collection area, leading to an overestimation of this value. This paper employs an upward leader initiation model to develop a novel calculation method for the equivalent collection area of wind turbines. By considering the impact of upward leader channel initiation and development, the model demonstrates accuracy through comparison with observational data (0.7761 strikes/year), showing only a −7.1% discrepancy. This study also examines the impact of various blade rotation angles, stepped leader speeds, and peak current of the return stroke on the equivalent collection area. Results indicate that the lightning strike distance specified in IEC standards underestimates the equivalent collection area due to neglecting the upward leader channel, resulting in significant differences compared to our approach, with a maximum deviation of up to 313.12%. Full article

Photovoltaic/Thermal (PV/T) technology efficiently harnesses solar energy by co-generating electricity and hot water. Unlike conventional PV systems, PV/T systems improve thermal utilization, cool PV modules, and prevent performance degradation caused by high temperatures. Among the various PV/T configurations, micro-channel heat pipe (MCHP) systems are prominent due to their ability to enhance heat transfer through the use of vacuum-filled, refrigerant-sealed MCHPs. This study explores how factors such as working fluid type, evaporation section heat flux, fill ratio, and condensation section length impact system performance. A 3D steady-state CFD model simulating phase-change heat transfer was developed to analyze thermal and electrical efficiencies. The results reveal that R134a outperforms acetone in heat transfer, with thermal resistance showing a significant decrease (from 0.5 °C·W⁻¹ at a 30% fill rate to 0.3 °C·W⁻¹ at a 70% fill rate) under varying heat source powers. The optimal fill ratio depends on the heat flux; for powers up to 70 W, the fill ratio ranges from 30% to 50%, while above 70 W, it shifts to 60–80%. Additionally, a longer condensation section reduces thermal resistance by up to 30% and enhances heat transfer efficiency, improving the overall system performance by 10%. These findings offer valuable insights into optimizing MCHP PV/T systems for increased efficiency. Full article

High-quality corporate innovation serves as a critical driver for achieving corporate sustainable development. This study bridges the gap between macroeconomic fiscal sustainability and microeconomic innovation quality. Specifically, this paper investigates the influence of local fiscal sustainability on high-quality corporate innovation, examining the underlying mechanisms and heterogeneous effects. Methodologically, data were collected using Python-based retrieval and web-scraping techniques. A multi-dimensional index of local fiscal sustainability was constructed, comprising five key dimensions to quantitatively map provincial fiscal sustainability across China. Corporate innovation quality was measured using patent citation metrics. Employing panel data from A-share listed companies over the 2015–2023 period, we implemented a two-way fixed-effects model for rigorous empirical econometric analysis. The findings indicate a significant positive relationship between local fiscal sustainability and high-quality corporate innovation. This result remains robust after a battery of robustness tests, including the use of instrumental variable (IV) methods. Mechanism analysis reveals that the resource compensation effect is the primary channel. Furthermore, our analysis identifies heterogeneity across varying innovation environments, economic regions, and industry characteristics. The positive influence is particularly pronounced in provinces with stronger intellectual property protection, firms located in the eastern regions, and High-Tech Enterprises. Collectively, the conclusions drawn from this research offer valuable policy implications for strengthening local fiscal sustainability and enhancing high-quality corporate innovation. Full article

Understanding visitor sentiment is essential for developing effective tourism strategies, particularly as Google Maps reviews have become a key channel for public feedback on tourist attractions. Yet, the unstructured format and dialectal diversity of Arabic reviews pose significant challenges for extracting actionable insights at scale. This study evaluates the performance of traditional machine learning and transformer-based models for aspect-based sentiment analysis (ABSA) on Arabic Google Maps reviews of tourist sites across Saudi Arabia. A manually annotated dataset of more than 3500 reviews was constructed to assess model effectiveness across six tourism-related aspects: price, cleanliness, facilities, service, environment, and overall experience. Experimental results demonstrate that multi-head BERT architectures, particularly AraBERT, consistently outperform traditional classifiers in identifying aspect-level sentiment. Ara-BERT achieved an F1-score of 0.97 for the cleanliness aspect, compared with 0.91 for the best-performing classical model (LinearSVC), indicating a substantial improvement. The proposed ABSA framework facilitates automated, fine-grained analysis of visitor perceptions, enabling data-driven decision-making for tourism authorities and contributing to the strategic objectives of Saudi Vision 20300. Full article