Search Results (1,570)

Cross-media vehicles, which combine the advantages of airplanes and submarines, are capable of performing complex tasks in different media and have attracted significant interest in recent years. In practice, however, cross-media rotorcrafts face numerous challenges during the cross-media transition, one of which is the complex mixed air–water flows induced by their rotors operating in close proximity to the water surface. These flows can result in aerodynamic penalties and structural damage to the rotors. The interactions between a water surface and a rotor wake bring about potential risks of cross-media locomotion, which is known as the near-water effect of rotors. Given that the distinctions between the near-water effect and the ground effect of rotors are not yet widely understood, this study details the discovery of the near-water effect and provides a comprehensive review of the evolutionary development of the near-water effect, tracing its understanding from the ground effect to the influence of droplets through aerodynamic modeling, numerical simulations, and near-water experimental studies. Furthermore, open problems and challenges associated with the near-water effect are discussed, including flow field measurements and numerical simulation approaches. Additionally, potential applications of the near-water effect for the development of cross-media rotorcraft are also described, which are valuable for aerodynamic design and cross-media control. Full article

This study evaluates the energy consumption of a light electric flying-wing unmanned aerial system (UAS) during low-altitude holding maneuvers. Two flight patterns were investigated: circular holding at a specified altitude and a figure-eight trajectory. Test flights were conducted under varying meteorological and wind conditions, including scenarios where wind aligned and crossed the flight path. Key flight parameters such as pitch, yaw, heading deviation, flight altitude, ground speed, and airspeed were monitored. Concurrently, current and battery voltage were measured to compute the instantaneous power consumption of the propulsion system. This approach allowed for the determination and comparison of energy consumption across the two holding patterns. The outcomes contribute to a better understanding of power efficiency during prolonged flight maneuvers, supporting advancements in autonomous low-altitude UAS operations. Full article

High-resolution visible remote sensing imagery, as a fundamental contributor to Earth observation, has found extensive application in land use classification. However, the heterogeneous array of optical sensors, distinguished by their unique design architectures, exhibit disparate spectral responses and spatial distributions when observing ground objects. These discrepancies between multi-sensor data present a significant obstacle to the widespread application of intelligent methods. In this paper, we propose a method tailored to accommodate these disparities, with the aim of achieving a smooth transfer for the model across diverse sets of images captured by different sensors. Specifically, to address the discrepancies in spatial resolution, a novel positional encoding has been incorporated to capture the correlation between the spatial resolution details and the characteristics of ground objects. To tackle spectral disparities, random amplitude mixup augmentation is introduced to mitigate the impact of feature anisotropy resulting from discrepancies in low-level features between multi-sensor images. Additionally, we integrate convolutional neural networks and Transformers to enhance the model’s feature extraction capabilities, and employ a fine-tuning strategy with dynamic pseudo-labels to reduce the reliance on annotated data from the target domain. In the experimental section, the Gaofen-2 images (4 m) and the Sentinel-2 images (10 m) were selected as training and test datasets to simulate cross-sensor model transfer scenarios. Also, Google Earth images of Suzhou City, Jiangsu Province, were utilized for further validation. The results indicate that our approach effectively mitigates the degradation in model performance attributed to image source inconsistencies. Full article

The Clean Propulsion Technologies (CPT) project, established in 2021, brought together 15 research partners and original equipment manufacturers. The goal was to create a common vision and sustainable business solutions so that the worldwide technological leadership of the Finnish powertrain industry is secured. With a EUR 15.5 M budget, CPT brought early-stage innovative concepts towards technology readiness level (TRL) 6. The project’s particular significance was its unique cross-coupling of marine and off-road sectors, which have similar emission reduction targets but which do not compete for similar customers. The project yielded 21 innovative solutions, from accelerated model-based design methodologies and progress in combustion and aftertreatment control to hybrid energy management solutions. These were encapsulated in four ground-breaking demonstrations, including a next-generation marine engine working in low-temperature, reactivity-controlled compression ignition (RCCI) mode and a hydrogen off-road engine. An advanced close-coupled selective catalyst reduction (SCR) system and a hybrid wheel-platform with digital hydraulics were also demonstrated. The University of Vaasa led the consortium and was responsible for coordinated model-based rapid prototyping. This report examines University of Vaasa’s achievements during the CPT in terms of 26 milestones, 13 deliverables, and 32 research papers. It focuses also on other aspects, including lessons learned from managing large-scale academic–industry research. Full article

This article introduces a high-precision vertical pendulum tiltmeter with rapid deployment capability to improve the observation efficiency, practicality, and reliability of geophysical site tilt observation instruments. The system consists of a pendulum body, a triangular platform, a locking pendulum motor, a sealed cover, a ratio measurement bridge, a high-precision ADC, and an embedded data acquisition unit. The sensing unit adopts a vertical pendulum system suspended by a cross spring and a differential capacitance bridge measurement circuit, which can simultaneously measure two orthogonal directions of ground tilt. The pendulum is installed on a short baseline triangular platform, sealed as a whole with the platform, and equipped with a locking pendulum motor. When the pendulum is locked and packaged, it can withstand a 2 m free fall impact, with high reliability and easy use. It can be quickly deployed without the need for professional technicians. This article analyzes its various performance and technical indicators based on its application in the rapid deployment of the Zeketai seismic station in Xinjiang. It is of great significance for emergency response, mobile observation, base detection, anomaly verification, and other applications of ground tilt. Full article

To address the challenge of accurately detecting hidden water inrush hazards ahead of working faces, a cross-hole transient electromagnetic (TEM) method utilizing a grounded-wire source is proposed. The technique positions a step-current-driven grounded-wire source within a working-face borehole, while electrode arrays in adjacent boreholes measure secondary electric field responses. This configuration minimizes interference from metal supports or machines, thereby enhancing the signal-to-noise ratio of the TEM signals. A theoretical analysis based on the unstructured finite-element (FE) method is used to investigate the configuration. The collected data are processed using differential techniques, and the results confirm the method’s effectiveness in detecting anomalies. This paper investigates the response of our cross-hole method to anomalies in terms of size, resistivity contrasts, and spatial location, with anomaly boundaries quantitatively delineated via first-order differential analysis. This significantly enhances the capability of TEM detection in identifying anomalies. A comparison between our cross-hole method and the traditional roadway–borehole TEM method, using the trapped column model, demonstrates that the proposed cross-hole device more effectively locates anomalies and improves accuracy. Furthermore, this technique enables the formation of a 3D observation framework by utilizing existing boreholes, presenting promising prospects for future applications. Full article

Using the method of moments, we analyze three array antennas for low cross-polarized radiation. Each antenna comprises two dual-loop elements connected to a feedline horizontal to the ground plane. First, a feedline end is excited with an unbalanced source as a reference antenna. Next, the feedline center is excited with a balanced source, after the transformation of a decoupling array configuration. It is found that the antenna exhibits a cross-polarized radiation lower by 12 dB than the reference antenna. Last, the decoupling antenna is modified to have an unbalanced source without a complicated balun circuit design. It is pointed out that the modified antenna is an array of four loop elements, sequentially rotated by 90º. Full article

Small and medium-sized enterprises (SMEs) play a crucial role in fostering economic growth and sustainability, requiring a deliberate emphasis on innovation and applying knowledge to navigate ever-changing markets. This study, grounded in resource-based view (RBV) theory, explores the synergy of entrepreneurial leadership and team diversity, exploring pathways to entrepreneurial success in Pakistan’s SMEs. This study employed a cross-sectional design, utilizing a non-probability convenience sampling approach to survey 350 owners, supervisors, managers, and employees of SMEs in Khyber Pakhtunkhwa, Pakistan. Data were gathered through a survey questionnaire and subsequently analyzed using SPSS and SMART-PLS to validate the measurement model and examine the hypotheses for moderated analysis. The results indicated a significant moderating influence. Entrepreneurial leadership accounted for 15.8% of the variation in entrepreneurial success, while team diversity contributed 8.5%. Moreover, the moderating influence of team diversity substantially affected ES (59.7%), underscoring the pivotal role of team diversity in the interplay between EL and ES. Drawing from RBV theory, this study advances the framework by acknowledging that team diversity is a crucial element that strengthens the connections between EL and ES. This study enhances the existing literature by clarifying the mechanisms by which leadership and diversity collaboratively promote entrepreneurial outcomes. This highlights the necessity for SME leaders and policymakers to utilize team diversity as a strategic asset to improve competitive advantage and ensure sustainable success. Full article

Accurate retrieval of column-averaged dry-air mole fraction of methane (XCH₄) in the atmosphere is important for greenhouse gas emission management. Traditional XCH₄ retrieval methods are complex, while machine learning can be used to model nonlinear relationships by analyzing large datasets, providing an efficient alternative. This study proposes an XGBoost algorithm-based retrieval method to improve the efficiency of atmospheric XCH₄ retrieval. First, the key wavelengths affecting XCH₄ retrieval were determined using a radiative transfer model. The TROPOspheric Monitoring Instrument (TROPOMI) L1B satellite data, L2 XCH₄ products, and auxiliary data were matched to construct the dataset. The dataset constructed was used to train the XGBoost model and obtain the TRO_XGB_XCH₄ model. Finally, the accuracy of the proposed model was evaluated using various parameter values and validated against XCH₄ products and Total Carbon Column Observing Network (TCCON) ground-based observations. The results showed that the proposed TRO_XGB_XCH₄ model had a tenfold cross-validation accuracy R of 0.978, a ground-based validation R of 0.749, and a temporal extension accuracy R of 0.863. Therefore, the accuracy of the TRO_XGB_XCH₄ retrieval model is comparable to that of the official TROPOMI L2 product. Full article

The growing demand for electricity, integration of renewable energy sources, and recent advances in power electronics have driven the development of HVDC systems. Multi-terminal HVDC (MTDC) grids, enabled by Voltage Source Converters (VSCs), provide increased operational flexibility, including the ability to reverse power flow and independently control both active and reactive power. However, fault propagation in DC grids occurs more rapidly, potentially leading to significant damage within milliseconds. Unlike AC systems, HVDC systems lack natural zero-crossing points, making fault isolation more complex. This paper presents the implementation of a wavelet-based protection algorithm to detect faults in a four-terminal VSC-HVDC grid, modelled in MATLAB and SIMULINK. The study considers several fault scenarios, including two internal DC pole-to-ground faults, an external DC fault in the load branch, and an external AC fault outside the protected area. The discrete wavelet transform, using Symlet decomposition, is applied to classify faults based on the wavelet entropy and sharp voltage and current signal variations. The algorithm processes the decomposition coefficients to differentiate between internal and external faults, triggering appropriate relay actions. Key factors influencing the algorithm’s performance include system complexity, fault location, and threshold settings. The suggested algorithm’s reliability and suitability are demonstrated by the real-time implementation. The results confirmed the precise fault detection, with fault currents aligning with the values in offline models. The internal faults exhibit more entropy than external faults. Results demonstrate the algorithm’s effectiveness in detecting faults rapidly and accurately. These outcomes confirm the algorithm’s suitability for a real-time environment. Full article

Background/Objectives: Eccentric loading during landing is considered a key factor in the development of patellar tendinopathy and is associated with stiff landings and patellar tendinopathy. This study aims to investigate the relationship between tendon structure, presence of pain, and sex differences in landing kinematics and kinetics during countermovement jumps (CMJ) and tuck jump tests (TJT) in professional volleyball players. Methods: Professional volleyball players aged 18 to 30 years old (14 females and 25 males) participated in a cross-sectional study. Data included the Victorian Institute of Sport Assessment Patellar Tendon (VISA-P) questionnaire; patellar tendon ultrasound characterization tissue (UTC) scans, in order to identify groups with misaligned tendon fibers (MTF) or aligned tendon fibers (ATF); and biomechanical assessments for CMJ and TJT. The joint angle (JA) at the lower limb was measured at peak ground reaction force (peak_vGRF) and maximal knee flexion (max_KF). A general linear model was used to evaluate joint JA differences between tendon alignment, pain, and sex variables. Sample t-tests compared peak_vGRF, load time, load rate, and area based on tendon alignment, pain presence, sex, and jump. The statistical significance of p-value is >0.05, and the effect size (ES) was also calculated. Results: The MTF group revealed decreased knee JA during TJT at peak_vGRF (p = 0.01; ES = −0.66) and max_KF (p = 0.02; ES = −0.23). The presence of pain was associated with increased JA during the CMJ, particularly at peak_vGRF and max_KF for trunk, hip, and ankle joints. Females showed decreased peak_vGRF than males. Landing with misaligned tendon fibers showed longer load times compared to aligned tendon fibers (p = 0.021; ES = −0.80). The TJT exhibited a greater load rate than the CMJ (p = 0.00; ES = −0.62). Conclusions: Pain is a critical factor influencing greater JA during landing, particularly at the trunk, hip, and ankle joints in CMJ. Misaligned tendon fibers compromise landing dynamics by increasing trunk JA during TJT. Kinetics varied significantly by sex and jump type, while pain and tendon structure revealed limited differences. Full article

Arecaceae (palms) are an important resource for indigenous communities as well as fauna populations across Amazonia. Understanding the spatial patterns and the environmental factors that determine the habitats of palms is of considerable interest to rainforest ecologists. Here, we utilize remotely sensed imagery in conjunction with topography and soil attribute data and employ a generalized cluster identification algorithm, Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), to study the underlying patterns of palms in two areas of Guyana, South America. The results of the HDBSCAN assessment were cross-validated with several point pattern analysis methods commonly used by ecologists (the quadrat test for complete spatial randomness, Morista Index, Ripley’s L-function, and the pair correlation function). A spatial logistic regression model was generated to understand the multivariate environmental influences driving the placement of cluster and outlier palms. Our results showed that palms are strongly clustered in the areas of interest and that the HDBSCAN’s clustering output correlates well with traditional analytical methods. The environmental factors influencing palm clusters or outliers, as determined by logistic regression, exhibit qualitative similarities to those identified in conventional ground-based palm surveys. These findings are promising for prospective research aiming to integrate remote flora identification techniques with traditional data collection studies. Full article

Due to the difficulty in obtaining label information in practical applications, semi-supervised cross-modal retrieval has emerged. However, the existing semi-supervised cross-modal hashing retrieval methods mainly focus on exploring the structural relationships between data and generating high-quality discrete pseudo-labels while neglecting the relationships between data and categories, as well as the structural relationships between data and categories inherent in continuous pseudo-labels. Based on this, Proxy-based Semi-Supervised Cross-Modal Hashing (PSSCH) is proposed. Specifically, we propose a category proxy network to generate category center points in both feature and hash spaces. Additionally, we design an Adaptive Dual-Label Loss function, which applies different learning strategies to discrete ground truth labels and continuous pseudo-labels and adaptively increases the training weights of unlabeled data with more epochs. Experiments on the MIRFLICKR-25K, NUS-WIDE, and MS COCO datasets show that PSSCH achieves the highest mAP improvements of 3%, 1%, and 4%, respectively, demonstrating better results than the latest baseline methods. Full article

Introduction: Glioma Grade 4 (GG4) tumors, which include both IDH-mutated and IDH wild-type astrocytomas, are the most prevalent and aggressive form of primary brain tumor. Radiomics is gaining ground in neuro-oncology. The integration of this data into machine learning models has the potential to improve the accuracy of prognostic models for GG4 patients. Karnofsky Performance Status (KPS), an established preoperative prognostic factor for survival, is commonly used in these patients. In this study, we developed a nomogram to identify patients with improved functional performance as indicated by an increase in KPS after surgery by analyzing radiomic features from preoperative 3D MRI scans. Methods: Quantitative imaging features were extracted from the -3D T1 GRE sequence of 157 patients from a single center and were used to develop the machine learning (ML) model. To improve applicability and create a nomogram, multivariable logistic regression analysis was performed to build a model incorporating clinical characteristics and radiomics features. Results: We labeled 55 cases in which KPS was improved after surgery (35%, KPS-flag = 1). The resulting model was evaluated according to test series results. The best model was obtained by XGBoost using the features extracted by pyradiomics, with a Matthew coefficient score (MCC) of 0.339 (95% CI: 0.330–0.3483) in cross-validation. The out-of-sample evaluation on the test set yielded an MCC of 0.302. A nomogram evaluating the improvement of KPS post-surgery was built based on statistically significant variables from multivariate logistic regression including clinical and radiomics data (c-index = 0.760, test set). Conclusions: MRI radiomic analysis represents a powerful tool to predict postoperative functional outcomes, as evaluated by KPS. Full article

This cross-sectional laboratory-based study investigates the stress characteristics of the anterior cruciate ligament (ACL) during side-cutting using a knee finite element (FE) model and identifies biomechanical factors influencing ACL stress. Kinematics and ground reaction forces (GRF) were collected from eight participants (age: 30.3 ± 5.3 years; BMI: 25.6 ± 2.4 kg/m²; time since surgery: 12.8 ± 1.2 months) one year post–ACL reconstruction during side-cutting tasks. A knee FE model incorporating time-varying knee angles, knee forces, and femoral translation was developed to simulate the knee biomechanics. The relationships between ACL stress and lower limb biomechanics were analyzed. The results indicated the highest stress concentrations at the femoral attachment during the early landing phase. Posterior femoral displacement relative to the tibia was significantly correlated with peak ACL equivalent stress (r = 0.89, p = 0.003) and peak ACL shear stress (r = 0.82, p = 0.023). Peak ACL equivalent stress also showed positive correlations with posterior GRF (r = 0.77, p = 0.025) and knee extension moments (r = 0.71, p = 0.049). In contrast, peak ACL shear stress exhibited a significant negative correlation with hip extension moment (r = −0.80, p = 0.032). This study identified key biomechanical factors affecting ACL stress, highlighting the roles of femoral displacement, knee extension moments, and ground reaction forces, while demonstrating a negative relationship with hip extension moments. Full article