Search Results (3,385)

This study investigates the relationship between the compressive strength of two-course masonry specimens and three-course masonry specimens extracted from previously constructed walls, to correlate the execution control specimens with the retest specimens. Compressive strength tests were performed on clay masonry units, laboratory-built two-course masonry specimens, and three-course masonry specimens extracted from constructed walls, following the prescriptions of NBR 15270 and NBR 16868-3. The results demonstrate that three-course masonry specimens exhibit lower compressive strength (characteristic and average, 44.83% and 40.29%, respectively) compared to two-course masonry specimens. Additionally, it was found that the dispersion of results is greater in three-course masonry specimens. Given that three-course specimens are typically used when it becomes necessary to verify the structural compliance of executed masonry—usually following unsatisfactory results from execution control using two-course specimens—more data are needed to compare such results. Factors such as increased height-to-thickness ratio, the presence of head joints, and the influence of execution conditions at the construction site seem to influence the difference between two and three-course specimens, as well as the dispersion of the results. Therefore, it is essential that technical standards provide supporting criteria to enable a reliable comparison between two-course specimens used for execution control and three-course specimens used as retest elements. Full article

The abandoned goaf resulting from coal resource integration in China poses a significant threat to coal mine safety. The transient electromagnetic method (TEM) has emerged as a crucial technology for detecting goafs in coal mines due to its adaptable equipment and efficient implementation. In recent years, small-loop TEM has demonstrated high resolution and adaptability in challenging terrains with vegetation, such as coal mine ponding areas, karst regions, and reservoir seepage scenarios. By considering the sedimentary characteristics of coal seams and addressing the resistivity changes encountered in single-point inversion, a joint optimization inversion process incorporating lateral weighting factors and vertical roughness constraints has been developed to enhance the connectivity between adjacent survey points and improve the continuity of inversion outcomes. Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. Using the Xiaolong Coal Mine as a geological context, the impact of lateral and vertical weighting factors on the inversion outcomes of high- and low-resistivity structural models is examined through a control variable method. The analysis reveals that optimal inversion results are achieved with a combination of a lateral weighting factor of 0.5 and a vertical weighting factor of 0.1, ensuring both result continuity and accurate depiction of vertical and lateral electrical interfaces. The practical application of this approach validates its effectiveness, offering theoretical support and technical assurance for old goaf detection in coal mines, thereby holding significant engineering value. Full article

Haemophilic arthropathy is caused by repeated joint bleeding episodes, primarily affecting knees, ankles and elbows. Conservative options should be considered prior to surgery, as well as postural evaluation, since any functional overload promotes the development of new bleeding. The aim of this study is to verify the use of foot orthoses in combination with postural rehabilitation, assessing the incidence of spontaneous haemarthroses and haematomas. In total, 15 patients were enrolled and randomly divided into two groups: 8 in group A, composed of patients who were prescribed foot orthoses and a 20-session rehabilitation program, and 7 in group B, composed of patients who were instructed to use foot orthoses only. All patients were evaluated at baseline (T0), at 3 months (T1—end of the rehabilitation program), and at 12 months (T2), using the following scales: Functional Independence Score in Haemophilia (FISH), Haemophilia Joint Health Score (HJHS) and Numerical Rating Scale (NRS). During the 12 months between the first and the last assessment, no patient in group A developed hemarthroses or hematomas, while one case of hemarthrosis was recorded in group B. The HJHS improved significantly (≤0.05) in group A at both T1 and T2, while in group B it improved significantly only in T2. As for FISH, it showed significant improvements in both groups at T1 and T2. NRS showed a significant reduction only at T2 in both groups (p-value T0–T1 0.3 in group A e 0.8 in group B). No patient reported any adverse effects from the use of orthotic insoles. The combination of postural rehabilitation, the use of foot orthoses and pharmacological prophylaxis could improve functioning and joint status in patients affected by haemophilic arthopathy, delaying or preventing new hemarthroses by improving the distribution of joint loads and the modification of musculoskeletal system’s characteristics. Full article

Τhe Greek Seas are one of the most favorable locations for offshore wind energy development in the Mediterranean basin. In 2023, the Hellenic Hydrocarbons & Energy Resources Management Company SA published the draft National Offshore Wind Farm Development Programme (NDP-OWF), including the main pillars for the design, development, siting, installation, and exploitation of offshore wind farms, along with the Strategic Environmental Impact Assessment. The NDP-OWF is under assessment by the relevant authorities and is expected to be finally approved through a Joint Ministerial Decision. In this work, the preliminary offshore wind energy assessment of the Greek Seas is performed using the CERRA wind reanalysis data and in situ measurements from six offshore locations of the Greek Seas. The in situ measurements are used in order to assess the performance of the reanalysis datasets. The results reveal that CERRA is a reliable source for preliminary offshore wind energy assessment studies. Taking into consideration the potential offshore wind farm organized development areas (OWFODA) according to the NDP-OWF, the study of the local wind characteristics is performed. The local wind speed and wind power density are assessed, and the wind energy produced from each OWFODA is estimated based on three different capacity density settings. According to the balanced setting (capacity density of 5.0 MW/km²), the annual energy production will be 17.5 TWh, which is equivalent to 1509.1 ktoe. An analysis of the wind energy correlation, synergy, and complementarity between the OWFODA is also performed, and a high degree of wind energy synergy is identified, with a very low degree of complementarity. Full article

Facial expression recognition (FER) is a critical research direction in artificial intelligence, which is widely used in intelligent interaction, medical diagnosis, security monitoring, and other domains. These applications highlight its considerable practical value and social significance. Face expression recognition models often need to run efficiently on mobile devices or edge devices, so the research on lightweight face expression recognition is particularly important. However, feature extraction and classification methods of lightweight convolutional neural network expression recognition algorithms mostly used at present are not specifically and fully optimized for the characteristics of facial expression images, yet fail to make full use of the feature information in face expression images. To address the lack of facial expression recognition models that are both lightweight and effectively optimized for expression-specific feature extraction, this study proposes a novel network design tailored to the characteristics of facial expressions. In this paper, we refer to the backbone architecture of MobileNet V2 network, and redesign LightExNet, a lightweight convolutional neural network based on the fusion of deep and shallow layers, attention mechanism, and joint loss function, according to the characteristics of the facial expression features. In the network architecture of LightExNet, firstly, deep and shallow features are fused in order to fully extract the shallow features in the original image, reduce the loss of information, alleviate the problem of gradient disappearance when the number of convolutional layers increases, and achieve the effect of multi-scale feature fusion. The MobileNet V2 architecture has also been streamlined to seamlessly integrate deep and shallow networks. Secondly, by combining the own characteristics of face expression features, a new channel and spatial attention mechanism is proposed to obtain the feature information of different expression regions as much as possible for encoding. Thus improve the accuracy of expression recognition effectively. Finally, the improved center loss function is superimposed to further improve the accuracy of face expression classification results, and corresponding measures are taken to significantly reduce the computational volume of the joint loss function. In this paper, LightExNet is tested on the three mainstream face expression datasets: Fer2013, CK+ and RAF-DB, respectively, and the experimental results show that LightExNet has 3.27 M Parameters and 298.27 M Flops, and the accuracy on the three datasets is 69.17%, 97.37%, and 85.97%, respectively. The comprehensive performance of LightExNet is better than the current mainstream lightweight expression recognition algorithms such as MobileNet V2, IE-DBN, Self-Cure Net, Improved MobileViT, MFN, Ada-CM, Parallel CNN(Convolutional Neural Network), etc. Experimental results confirm that LightExNet effectively improves recognition accuracy and computational efficiency while reducing energy consumption and enhancing deployment flexibility. These advantages underscore its strong potential for real-world applications in lightweight facial expression recognition. Full article

Three-dimensional (3D) radar imaging is essential for target detection and measurement of scattering characteristics. Cylindrical scanning, a prevalent spatial sampling technique, provides benefits in engineering applications and has been extensively utilized for assessing the radar stealth capabilities of large aircraft. Traditional cylindrical scanning generally utilizes highly sampled full-coverage techniques, leading to an excessive quantity of sampling points and diminished image efficiency, constraining its use for quick detection applications. This work presents an efficient 3D sampling strategy that integrates vertical linear scanning with horizontal rotating motion to overcome these restrictions. A joint angle–space sampling model is developed, and geometric constraints are implemented to enhance the scanning trajectory. The experimental results demonstrate that, compared to conventional techniques, the proposed method achieves a 94% reduction in the scanning duration while maintaining a peak sidelobe level ratio (PSLR) of 12 dB. Furthermore, this study demonstrates that 3D imaging may be accomplished solely by a “V”-shaped trajectory, efficiently determining the minimal possible sampling aperture. This approach offers novel insights and theoretical backing for the advancement of high-efficiency, low-redundancy 3D radar imaging systems. Full article

Background and objective. Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) affects small- to medium-sized vessels and is characterized by the production of ANCAs. The ANCA-negative term is used if the patient otherwise fulfills the definition for AAV but has negative results on serologic testing for ANCAs. The objective of this study was to compare ANCA-positive and -negative vasculitis patients and to evaluate the main differences possibly related to the presence of ANCAs. Material and methods. A cross-sectional study of 73 patients treated at the tertiary Rheumatology Centre of University Hospital from the 1 January, 2001, to the 31August, 2023, with diagnoses of AAV was carried out. Clinical characteristics and laboratory data were collected at the onset or at the first year of the disease. Results. Forty-eight (65.8%) patients were ANCA-positive, while twenty-five (34.3%) were ANCA-negative. Distribution by gender was similar in both groups, with a female–male ratio of 2:1. C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were elevated for all AAV patients, but values were higher in the ANCA-positive patients’ group. The median hemoglobin was 106 g/L in the seropositive group and 127 g/L in the seronegative group. A higher prevalence of kidney involvement (60.4%) with elevated serum creatinine level (93.5 µmol/L) was observed in the ANCA-positive group compared with 24% and 70 µmol/l in the ANCA-negative group (p < 0.05). Neurological involvement was more frequently found in the ANCA-positive patient group, too: 29.2% compared to 20%. Among patients with ANCA-negative vasculitis, 88% had pulmonary; 92% ear, nose, throat (ENT); 48% joint; and 28% skin presentation. In comparison, involvement of these organs was less common in the ANCA-positive patients’ group, at 79.2%, 60.4%, 31.3%, and 25 %, respectively. Conclusions. ANCA-positive patients appear to be in a more difficult clinical situation in terms of organ involvement and laboratory changes. Full article

Dual three-phase PMSMs (DTP-PMSMs) have attracted increasing attention in the field of robotics industry for their higher power density and enhanced fault-tolerant ability. The non-phase-shifted DTP-PMSM (NPSDTP-PMSM), which shows naturally prevailed performance on zero-sequence current (ZSC) suppression, necessitates the investigation on the control method with improved fault-tolerant performance. In this paper, a novel fault-tolerant control (FTC) method for NPSDTP-PMSM is proposed, which concurrently simultaneously reduces copper loss and suppresses torque ripple under single and dual open phase fault. Firstly, the mathematical model of NPSDTP-PMSM is established, where the ZSC self-suppressing mechanism is revealed. Based on which, investigations on open phase fault and the copper loss characteristics for NPSDTP-PMSM are conducted. Subsequently, a novel fault-tolerant control method is proposed for NPSDTP-PMSM, where the torque ripple is reduced by mutual cancellation of harmonic torques from two winding sets and minimized copper loss is achieved based on the convex characteristic of copper loss. Experimental validation on an integrated robotic joint motor platform confirms the effectiveness of the proposed method. Full article

Microelectromechanical system (MEMS) devices are specialized electronic devices that integrate the benefits of both mechanical and electrical structures. However, the contact behavior between the interfaces of these structures can significantly impact the performance of MEMS devices, particularly when the surface roughness approaches the characteristic size of the devices. In such cases, the contact between the interfaces is not a perfect face-to-face interaction but occurs through point-to-point contact. As a result, the contact area changes with varying contact pressures and surface roughness, influencing the thermal and electrical performance. By integrating the CMY model with finite element simulations, we systematically explored the thermal conductance regulation mechanism of MEMS contact switches. We analyzed the effects of the contact pressure, micro-hardness, surface roughness, and other parameters on thermal conductance, providing essential theoretical support for enhancing reliability and optimizing thermal management in MEMS contact switches. We examined the thermal contact, gap, and joint conductance of an MEMS switch under different contact pressures, micro-hardness values, and surface roughness levels using the CMY model. Our findings show that both the thermal contact and gap conductance increase with higher contact pressure. For a fixed contact pressure, the thermal contact conductance decreases with rising micro-hardness and root mean square (RMS) surface roughness but increases with a higher mean asperity slope. Notably, the thermal gap conductance is considerably lower than the thermal contact conductance. Full article

This article investigates the revolutionary potential of AI-powered virtual assistants in augmented reality (AR) and virtual reality (VR) environments, concentrating primarily on their impact on special needs schooling. We investigate the complex characteristics of these virtual assistants, the influential elements affecting their development and implementation, and the joint efforts of educational institutions and technology developers, using a rigorous quantitative approach. Our research also looks at strategic initiatives aimed at effectively integrating AI into educational practices, addressing critical issues including infrastructure, teacher preparedness, equitable access, and ethical considerations. Our findings highlight the promise of AI technology, emphasizing the ability of AI-powered virtual assistants to provide individualized, immersive learning experiences adapted to the different needs of students with special needs. Furthermore, we find strong relationships between these virtual assistants’ features and deployment tactics and their subsequent impact on educational achievements. This study contributes to the increasing conversation on harnessing cutting-edge technology to improve educational results for all learners by synthesizing current research and employing a strong methodological framework. Our analysis not only highlights the promise of AI in increasing student engagement and comprehension but also emphasizes the importance of tackling ethical and infrastructure concerns to enable responsible and fair adoption. Full article

The varying characteristics of grid-connected energy resources necessitate a clear and effective approach for managing and scheduling generation units. Without proper control, high levels of renewable integration can pose challenges to optimal dispatch, especially as more generation sources, like wind and solar PV, are introduced. As a result, conventional power sources require an advanced management system, for instance, a virtual power plant (VPP), capable of accurately monitoring power supply and demand. This study thoroughly explores the dispatch of battery energy storage systems (BESSs) and diesel generators (DGs) through a distributionally robust joint chance-constrained optimization (DR-JCCO) framework utilizing the conditional value at risk (CVaR) and heuristic-X (H-X) algorithm, structured as a bilevel optimization problem. Furthermore, Binomial expansion (BE) is employed to linearize the model, enabling the assessment of BESS dispatch through a mathematical program with equilibrium constraints (MPECs). The findings confirm the effectiveness of the DRO-CVaR and H-X methods in dispatching grid network resources and BE under the MPEC framework. Full article

To improve the mobility of mobile robots in complex terrain environments, a novel 2-UPS&PRPU parallel mechanism is proposed, for which the parallel mechanism branched-chain decomposition and synthesis method is adopted. Based on the structural characteristics of the Hooke joint kinematic substructure, an inverse solution calculation for the mechanism is carried out, and the parameters of the simulation model are formulated to determine the workspace of the parallel mechanism. The linear velocity dexterity and minimum output carrying capacity of the parallel mechanism are analyzed, allowing the optimal parameters of the mechanism to be selected through dimension optimization, thus greatly improving the mechanism’s linear velocity dexterity and carrying capacity. The results show that the proposed parallel mechanism can satisfy the mobility requirements of mobile robots. Full article

A steel modular building is a highly prefabricated form of steel construction. It offers rapid assembly, a high degree of industrialization, and an environmentally friendly construction site. To promote the application of multi-story steel modular buildings in earthquake fortification zones, it is imperative to conduct in-depth research on their seismic behavior. In this study, a seven-story modular steel building is investigated using shaking table tests. Three seismic waves (artificial ground motion, Tohoku wave, and Tianjin wave) are selected and scaled to four intensity levels (PGA = 0.035 g, 0.1 g, 0.22 g, 0.31 g). It is found that no residual deformation of the structure is observed after tests, and its stiffness degradation ratio is 7.65%. The largest strains observed during the tests are 540 × 10⁻⁶ in beams, 1538 × 10⁻⁶ in columns, and 669 × 10⁻⁶ in joint regions, all remaining below a threshold value of 1690 × 10⁻⁶. Amplitudes and frequency characteristics of the acceleration responses are significantly affected by the characteristics of the seismic waves. However, the acceleration responses at higher floors are predominantly governed by the structure’s low-order modes (first-mode and second-mode), with the corresponding spectra containing only a single peak. When the predominant frequency of the input ground motion is close to the fundamental natural frequency of the modular steel structure, the acceleration responses will be significantly amplified. Overall, the structure demonstrates favorable seismic resistance. Full article

This paper proposes a novel Global Navigation Satellite System (GNSS)-based remote sensing method for simulating Radar Doppler Map (RDM) features through joint electromagnetic scattering modeling and signal processing, enabling characteristic parameter extraction for both point and ship targets in multi-satellite scenarios. Simulations demonstrate that the B3I signal achieves a significantly enhanced range resolution (tens of meters) compared to the B1I signal (hundreds of meters), attributable to its wider bandwidth. Furthermore, we introduce an Unscented Particle Filter (UPF) algorithm for dynamic target tracking and state estimation. Experimental results show that four-satellite configurations outperform three-satellite setups, achieving <10 m position error for uniform motion and <18 m for maneuvering targets, with velocity errors within ±2 m/s using four satellites. The joint detection framework for multi-satellite, multi-target scenarios demonstrates an improved detection accuracy and robust localization performance. Full article

High-density polyethylene (HDPE) pipes are widely used in urban natural gas pipeline systems due to their excellent mechanical and chemical properties. However, welding joints are critical weak points in these pipelines, and defects, such as cold welding—caused by reduced temperature or/and insufficient pressure—pose significant safety risks. Traditional non-destructive testing (NDT) methods face challenges in detecting cold welding defects due to the polymer’s complex structure and characteristics. This study presents a microwave-based NDT system for detecting cold welding defects in thermal fusion welds of HDPE pipes. The system uses a focusing antenna with a resonant cavity, connected to a vector network analyzer (VNA), to measure changes in microwave parameters caused by cold welding defects in thermal fusion welds. Experiments conducted on HDPE pipes welded at different temperatures demonstrated the system’s effectiveness in identifying areas with a lack of fusion. Mechanical and microstructural analyses, including tensile tests and scanning electron microscopy (SEM), confirmed that cold welding defects lead to reduced mechanical properties and lower material density. The proposed microwave NDT method offers a sensitive, efficient approach for detecting cold welds in HDPE pipelines, enhancing pipeline integrity and safety. Full article