Search Results (1,565)

With the development of wave energy, a promising renewable resource, oscillating water column (OWC) devices, has been extensively studied for its potential in harnessing this energy. However, traditional OWC devices face challenges such as corrosion and damage from prolonged exposure to harsh marine environments, limiting their long-term viability and efficiency. To address these limitations, this paper proposes a novel U-tube type dual chamber OWC wave energy conversion device integrated within a marine vehicle. The research involves the design of a U-tube dual-chamber OWC device, which utilizes the pitch motion of a marine vehicle to drive the oscillation of water columns within the U-tube, generating reciprocating airflow that drives an air turbine. Numerical simulations using computational fluid dynamics (CFD) were conducted to analyze the effects of various structural dimensions, including device length, width, air chamber height, U-tube channel width, and bottom channel height, on the aerodynamic power output. The simulations considered real sea conditions, focusing on low-frequency waves prevalent in China’s sea areas. Simulation results reveal that increasing the device’s length and width substantially boosts aerodynamic power, while air chamber height and U-tube channel width have minor effects. These findings provide valuable insights into the optimal design of U-tube dual-chamber OWC devices for efficient wave energy conversion, laying the foundation for future physical prototype development and experimental validation. Full article

The compound effects of extreme climate change and intensive urban development have led to more frequent urban inundation, highlighting the urgent need for the fine-scale evaluation of stormwater drainage system performance in high-density urban built-up areas. A typical basin, located in Shenzhen, was selected, and a pipe–river coupled SWMM was developed and calibrated via a genetic algorithm to simulate the storm drainage system. Design storm scenario analyses revealed that regional inundation occurred in the central area of the basin and the enclosed culvert sections of the midstream river, even under a 0.5-year recurrence period, while the downstream open river channels maintained a substantial drainage capacity under a 200-year rainfall event. To systematically identify bottleneck zones, two novel metrics, namely, the node cumulative inundation volume and the conduit cumulative inundation length, were proposed to quantify the local inundation severity and spatial interactions across the drainage network. Two critical bottleneck zones were selected, and strategic improvement via the cross-sectional expansion of pipes and river culverts significantly enhanced the drainage efficiency. This study provides a practical case study and transferable technical framework for integrating hydraulic modeling, spatial analytics, and targeted infrastructure upgrades to enhance the resilience of drainage systems in high-density urban environments, offering an actionable framework for sustainable urban stormwater drainage system management. Full article

In the attention-driven environment of online video platforms, understanding the factors that influence content selection and channel subscriptions is crucial for creators, marketers, and platform managers. This study investigates how thumbnails, view counts, video length, genre, and the number of advertisements affect user decision-making on YouTube. Grounded in random utility theory and reference-dependent preference theory, this study conducted a choice experiment with 525 respondents and employed a combined model of rank-ordered and binary logit methods to analyze viewing and subscription behaviors. The results indicate a significant preference for thumbnails with subtitles and shorter videos. Notably, we found evidence of reference-dependent effects, whereby a higher-than-expected number of ads decreased viewing probability, while a lower-than-expected number significantly increased subscription probability. This study advances our understanding of the factors that influence user behavior on social media, specifically in terms of viewing and subscribing, and empirically supports prospect theory in the online advertising market. Our findings offer both theoretical and practical insights into optimizing video content and monetization strategies in competitive social media markets. Full article

Addressing the challenges of bulky, low-efficiency sound-insulation materials at low frequencies, this work proposes an acoustic metamaterial based on curve fractal channels. Each unit cell comprises a concentric circular-ring channel recursively iterated: as the fractal order increases, the channel path length grows exponentially, enabling outstanding sound-insulation performance within a deep-subwavelength thickness. Finite-element and transfer-matrix analyses show that increasing the fractal order from one to three raises the number of bandgaps from three to five and expands total stop-band coverage from 17% to over 40% within a deep-subwavelength thickness. Four-microphone impedance-tube measurements on the third-order sample validate a peak transmission loss of 75 dB at 495 Hz, in excellent agreement with simulations. Compared to conventional zigzag and Hilbert-maze designs, this curve fractal architecture delivers enhanced low-frequency broadband insulation, structural lightweighting, and ease of fabrication, making it a promising solution for noise control in machine rooms, ducting systems, and traffic environments. The method proposed in this paper can be applied to noise reduction of transmission parts for ceramic automation production. Full article

Channels with three standard symmetrical sections and one asymmetric section are mounted as cantilever beams with the web oriented vertically. A classical solution to the analysis of stress in each thin-walled cantilever channel is provided using the principle of wall shear flow superposition. The latter is coupled with a further superposition between axial stress arising from bending and from the constraint placed on free warping imposed at the fixed end. Closed solutions for design are tabulated for the net shear stress and the net axial stress at points around any section within the length. Stress distributions thus derived serve as a benchmark structure for alternative numerical solutions and for experimental investigations. The conversion of the transverse free end-loading applied to a thin-walled cantilever channel into the shear and axial stress that it must bear is outlined. It is shown that the point at which this loading is applied within the cross-section is crucial to this stress conversion. When a single force is applied to an arbitrary point at the free-end section, three loading effects arise generally: bending, flexural shear and torsion. The analysis of each effect requires that this force’s components are resolved to align with the section’s principal axes. These forces are then considered in reference to its centroid and to its shear centre. This shows that axial stress arises directly from bending and from the constraint imposed on free warping at the fixed end. Shear stress arises from flexural shear and also from torsion with a load offset from the shear centre. When the three actions are combined, the net stresses of each action are considered within the ability of the structure to resist collapse from plasticity and buckling. The novelty herein refers to the presentation of the shear flow calculations within a thin wall as they arise from an end load offset from the shear centre. It is shown how the principle of superposition can be applied to individual shear flow and axial stress distributions arising from flexural bending, shear and torsion. Therein, the new concept of a ‘trans-moment’ appears from the transfer in moments from their axes through centroid G to parallel axes through shear centre E. The trans-moment complements the static equilibrium condition, in which a shift in transverse force components from G to E is accompanied by torsion and bending about the flexural axis through E. Full article

This paper investigates point-to-point multimodal digital semantic communications in a task-oriented setup, where messages are classified at the receiver. We employ a pre-trained transformer model to extract semantic information and propose three methods for generating semantic codewords. First, we propose semantic quantization that uses quantized embeddings of source realizations as a codebook. We investigate the fixed-length coding, considering the source semantic structure and end-to-end semantic distortion. We propose a neural network-based codeword assignment mechanism incorporating codeword transition probabilities to minimize the expected semantic distortion. Second, we present semantic compression that clusters embeddings, exploiting the inherent semantic redundancies to reduce the codebook size, i.e., further compression. Third, we introduce a semantic vector-quantized autoencoder (VQ-AE) that learns a codebook through training. In all cases, we follow this semantic source code with a standard channel code to transmit over the wireless channel. In addition to classification accuracy, we assess pre-communication overhead via a novel metric we term system time efficiency. Extensive experiments demonstrate that our proposed semantic source-coding approaches provide comparable accuracy and better system time efficiency compared to their learning-based counterparts. Full article

Secure autonomous secret key distillation (SKD) systems traditionally depend on external common randomness (CR) sources, which often suffer from instability and limited reliability over long-term operation. In this work, we propose a novel SKD architecture that synthesizes CR by combining a keystream of a shared-key keystream generator $KSG\left(K_G\right)$ with locally generated binary Bernoulli noise. This construction emulates the statistical properties of the classical Maurer satellite scenario while enabling deterministic control over key parameters such as bit error rate, entropy, and leakage rate (LR). We derive a closed-form lower bound on the equivocation of the shared-secret key $K_G$ from the viewpoint of an adversary with access to public reconciliation data. This allows us to define an admissible operational region in which the system guarantees long-term secrecy through periodic key refreshes, without relying on advantage distillation. We integrate the Winnow protocol as the information reconciliation mechanism, optimized for short block lengths ($N=8$), and analyze its performance in terms of efficiency, LR, and final key disagreement rate (KDR). The proposed system operates in two modes: ideal secrecy, achieving secret key rates up to 22% under stringent constraints (KDR < 10⁻⁵, LR < 10⁻¹⁰), and perfect secrecy mode, which approximately halves the key rate. Notably, these security guarantees are achieved autonomously, without reliance on advantage distillation or external CR sources. Theoretical findings are further supported by experimental verification demonstrating the practical viability of the proposed system under realistic conditions. This study introduces, for the first time, an autonomous CR-based SKD system with provable security performance independent of communication channels or external randomness, thus enhancing the practical viability of secure key distribution schemes. Full article

The development of an integrated circuit faces the challenge of the physical limit of Moore’s Law. One of the most important “Beyond Moore” challenges is the scaling down of Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) versus their increasing static power consumption. This is because, at room temperature, the thermal emission transportation mechanism will cause a physical limitation on subthreshold swing (SS), which is fundamentally limited to a minimum value of 60 mV/decade for MOSFETs, and accompanied by an increase in off-state leakage current with the process of scaling down. Moreover, the impacts of short-channel effects on device performance also become an increasingly severe problem with channel length scaling down. Due to the band-to-band tunneling mechanism, Tunnel Field-Effect Transistors (TFETs) can reach a far lower SS than MOSFETs. Recent research works indicated that TFETs are already becoming some of the promising candidates of conventional MOSFETs for ultra-low-power applications. This paper provides a review of some advances in materials and structures along the evolutionary process of TFETs. An in-depth discussion of both experimental works and simulation works is conducted. Furthermore, the performance of TFETs with different structures and materials is explored in detail as well, covering Si, Ge, III-V compounds and 2D materials, alongside different innovative device structures. Additionally, this work provides an outlook on the prospects of TFETs in future ultra-low-power electronics and biosensor applications. Full article

Radio frequency (RF)-based wireless systems are broadly used in communication systems such as mobile networks, satellite links, and monitoring applications. These systems offer outstanding advantages over wired systems, particularly in terms of ease of installation. However, researchers are looking for safer alternatives as a result of worries about possible health problems connected to high-frequency radiofrequency transmission. Using the visible light spectrum is one promising approach; three cutting-edge technologies are emerging in this regard: Optical Camera Communication (OCC), Light Fidelity (Li-Fi), and Visible Light Communication (VLC). In this paper, we propose a Multiple-Input Multiple-Output (MIMO) modulation technology for Internet of Things (IoT) applications, utilizing an LED array and time-domain on-off keying (OOK). The proposed system is compatible with both rolling shutter and global shutter cameras, including commercially available models such as CCTV, webcams, and smart cameras, commonly deployed in buildings and industrial environments. Despite the compact size of the LED array, we demonstrate that, by optimizing parameters such as exposure time, camera focal length, and channel coding, our system can achieve up to 20 communication links over a 20 m distance with low bit error rate. Full article

Carbon nanotube field-effect transistors (CNTFETs) are becoming a strong competitor for the next generation of high-performance, energy-efficient integrated circuits due to their near-ballistic carrier transport characteristics and excellent suppression of short-channel effects. However, CNT FETs with large diameters and small band gaps exhibit obvious bipolarity, and gate-induced drain leakage (GIDL) contributes significantly to the off-state leakage current. Although the asymmetric gate strategy and feedback gate (FBG) structures proposed so far have shown the potential to suppress CNT FET leakage currents, the devices still lack scalability. Based on the analysis of the conduction mechanism of existing self-aligned gate structures, this study innovatively proposed a design strategy to extend the length of the source–drain epitaxial region (L_ext) under a vertically stacked architecture. While maintaining a high drive current, this structure effectively suppresses the quantum tunneling effect on the drain side, thereby reducing the off-state leakage current (I_off = 10⁻¹⁰ A), and has good scaling characteristics and leakage current suppression characteristics between gate lengths of 200 nm and 25 nm. For the sidewall gate architecture, this work also uses single-walled carbon nanotubes (SWCNTs) as the channel material and uses metal source and drain electrodes with good work function matching to achieve low-resistance ohmic contact. This solution has significant advantages in structural adjustability and contact quality and can significantly reduce the off-state current (I_off = 10⁻¹⁴ A). At the same time, it can solve the problem of off-state current suppression failure when the gate length of the vertical stacking structure is 10 nm (the total channel length is 30 nm) and has good scalability. Full article

This paper presents a UAV-based building crack real-time detection system that integrates an improved YOLOv8 algorithm with Linear Active Disturbance Rejection Control (LADRC). The system is equipped with a high-resolution camera and sensors to capture high-definition images and height information. First, a trajectory tracking controller based on LADRC was designed for the UAV, which uses a linear extended state observer to estimate and compensate for unknown disturbances such as wind interference, significantly enhancing the flight stability of the UAV in complex environments and ensuring stable crack image acquisition. Secondly, we integrated Convolutional Block Attention Module (CBAM) into the YOLOv8 model, dynamically enhancing crack feature extraction through both channel and spatial attention mechanisms, thereby improving recognition robustness in complex backgrounds. Lastly, a skeleton extraction algorithm was applied for the secondary processing of the segmented cracks, enabling precise calculations of crack length and average width and outputting the results to a user interface for visualization. The experimental results demonstrate that the system successfully identifies and extracts crack regions, accurately calculates crack dimensions, and enables real-time monitoring through high-speed data transmission to the ground station. Compared to traditional manual inspection methods, the system significantly improves detection efficiency while maintaining high accuracy and reliability. Full article

Background: Despite being one of the most performed bariatric procedures, there is no consensus regarding optimal limb lengths for Roux-en-Y gastric bypass (RYGB), which may impact weight loss and obesity-related comorbidity resolution. We hypothesize that a ratio-adjusted small bowel to Roux and BP limb lengths in RYGB results in superior outcomes. Objectives: This study aims to define total intestinal length (TIL) and the feasibility of its intraoperative measurement during RYGB. The findings will serve as a foundation for a subsequent randomized trial evaluating different limb length ratios and their effect on postoperative outcomes. Setting: This was a single-center prospective cohort study conducted at Cleveland Clinic Foundation-Main Campus, a tertiary referral center in the United States. Methods: Between January and June 2023, 25 patients with BMI > 40 undergoing RYGB were enrolled. Total small bowel length was measured intraoperatively, and feasibility of measurement was assessed. Patient outcomes, including total weight loss, 30-day complications, and comorbidities at 1 year were captured. Results: Mean preoperative BMI was 47.6 ± 8.0 kg/m². Mean total small bowel length was 592 ± 93.3 cm, with a mean biliopancreatic (BP) limb length of 109 ± 29 cm (18.86% ± 5.84 of total length) and Roux limb length of 103 ± 15 cm (17.71% ± 3.06 of total length). Measurement added an average of 11.5 min to operative time. Measurement feasibility was rated as “moderate” or easier in 80% of cases. One-year postoperative outcomes included a mean total weight loss of 31% and significant reductions in antihypertensive and anti-diabetic medication use. Conclusions: Total small bowel length measurement during RYGB is safe and feasible. High variability in bowel length was observed, with no significant correlation to demographic factors. Establishing individualized limb length ratios may improve weight loss outcomes and comorbidity resolution. Further studies are warranted to evaluate the impact of tailored limb length strategies. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

This research investigates enhancing the performance of an Archimedes screw-type hydrokinetic turbine (ASHT). A 3D transient computational model employing the six degrees of freedom (6-DOF) methodology within the ANSYS Fluent software 2022 R1, was selected for this purpose. A central composite design (CCD) methodology was applied within the response surface methodology (RSM) to enhance the turbine’s power coefficient ($C_p$). Key independent factors, including blade length (L), blade inclination angle ($\gamma$), and external diameter ($D_e$), were systematically varied to determine their optimal values. The optimization process yielded a maximum $C_p$ of 0.337 for L, $\gamma$, and $D_e$ values of 168.921 mm, 51.341°, and 245.645 mm, respectively. Experimental validation was conducted in a hydraulic channel, yielding results that demonstrated a strong correlation with the numerical predictions. This research underscores the importance of geometric design optimization in improving the energy capture efficiency of the ASHT, contributing to its potential viability as a competitive renewable energy solution in the pre-commercial phase of development. Full article

In this study, we propose a method for systematic nanowire length control through the precise control of the polyvinylpyrrolidone (PVP) concentration during the synthesis of tellurium nanowires. Furthermore, we report the changes in the electrical properties of thin-film transistor (TFT) devices with different lengths of synthesized tellurium nanowires used as channels. Through the use of scanning electron microscopy (SEM) and atomic force microscopy (AFM), it was determined that the length of the wires increased in relation to the amount of PVP incorporated, while the diameter remained consistent. The synthesized long wires formed a well-connected percolation network with a junction density of 4.6 junctions/µm², which enabled the fabrication of devices with excellent electrical properties, the highest on/off ratio of 10³, and charge mobility of 1.1 cm²/V·s. In contrast, wires with comparatively reduced PVP content demonstrated a junction density of 2.1 junctions/µm², exhibiting a lower on/off ratio and reduced charge mobility. These results provide guidance on how the amount of PVP added during wire growth affects the length of the synthesized wires and how it affects the connectivity between the wires when they form a network, which may help optimize the performance of high-performance nanoelectronic devices. Full article