Miracle-dz/UniFAR-FTUs huggingface dataset:
Pediatric Orthopaedic Venous Thromboembolism

Background: There is growing evidence of increased venous thromboembolism (VTE) incidence in children with trauma or infection. The purpose of this study was to conduct a systematic review of existing literature related to VTE in the pediatric orthopaedic population, to estimate the overall incidence of VTE and identify risk factors associated with this condition. Methods: A systematic review of the available literature was performed to identify articles that described VTE in pediatric orthopaedic surgery or admission. Literature queries were performed to identify articles published from 1980 to 2021 that included patients ≤21 years of age. A stepwise search strategy of 5 electronic databases yielded 1,426 articles, which were filtered by 2 reviewers to identify 30 articles for full-text review. The primary aim was to determine the rate of VTE, and the secondary aim was to identify risk factors for VTE. The pooled incidence of VTE was estimated and reported in cases per 10,000. Studies were stratified by study size, by trauma versus elective surgery, and by orthopaedic subspecialty. Results: The 30 articles reported 3,113 VTE events in 2,467,764 pediatric patients (including those with non-orthopaedic conditions), for a pooled VTE incidence of 20 events (95% confidence interval [CI] = 10.8 to 37.2) per 10,000. Four of the studies were excluded for incomplete data or high heterogeneity. The remaining 26 studies had 850,268 orthopaedic patients with 1,108 cases of VTE, for a pooled VTE incidence of 16.6 events (95% CI = 9.1 to 30.5) per 10,000. Studies with <10,000 patients and those involving a diagnosis of trauma had the highest VTE incidence when stratification was performed. The most frequently analyzed risk factors in 15 available studies included age, sex, obesity/body mass index, type of surgery, and use of a central venous catheter. Conclusions: This systematic review indicated that the risk of VTE associated with pediatric orthopaedic surgery or admission remains low, at <17 events per 10,000 cases. However, orthopaedic surgeons should be aware of the most common risk factors associated with pediatric orthopaedic VTE and should pay special attention to traumatic etiologies, as these yielded the highest incidence. Levels of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Development of an Unsteady Conjugate Heat Transfer Solver for Rotating Detonation Engines

The conjugate heat transfer problem between the RDC flow field and chamber wall was calculated utilizing the newly developed multi-region solver multiRegionBYRFoam, to fill the gap of fully coupled fluid-to-solid heat transfer simulation for rotating detonation chamber. The solution procedure and coupling method of the new solver were clarified. Then the radical, axial and temporal variations of RDC wall temperature in a single-wave case solved by multiRegionBYRFoam were analyzed. The fluid and solid regions are well coupled, and the maximal axial wall temperature was found to occur near the triple points and oblique shocks. This investigation provides insight into the transient heat load of rotating detonation chamber wall, and offers reference for thermal management of RDE and the efficient cooling considerations in the near future. Future work includes long duration simulation that equilibrium wall temperature can be achieved, and the study of effects of mass flow rate, equivalence ratio and chamber geometry on the thermal environment of RDE.
Decentralized Digital Clock Drift Compensation in Distributed Radar Sensor Networks Through Single-Tone Frequency Broadcasts

This paper presents a decentralized broadcast technique for estimating the clock drift of platforms cooperating in a distributed radar sensor network for the purpose of achieving frequency, phase, and time synchronization. The proposed method is advantageous for existing digital radar systems as it can be implemented entirely in software without the use of additional RF hardware required by other frequency synchronization techniques. The signal model for signals transmitted and received in various clock domains is presented to highlight the impact of clock drift on signal transfers and an estimation model is subsequently derived for estimating and correcting the clock drifts on each platform. A modified version of a previously developed phase and clock bias correction procedure is outlined for correcting time and phase after the frequency synchronization is completed. The technique is validated in simulation and results are demonstrated showing the clock drift estimation accuracy as a function of signal-to-noise ratio (SNR), carrier frequency, and network size, as well as a comparison in bias estimation to the drift-free case assumed by other techniques.
An EEG Signal Processing System Design with Approximate Operations

This paper presents an EEG signal processing system with an application to emotional recognition, which includes three primary modules: preprocessing, feature extraction, and emotion classification. A hardware stream control mode tailored for the system was devised to minimize redundant logic computations. Additionally, we used a piecewise linear approximation method for three non-linear operations utilized in the neural network (tanh activation function, sigmoid activation function, and square root function). The resulting hardware circuit achieves a dual-label classification of 16 emotions, with an average accuracy of 64.5% on the DEAP dataset. Compared to other state-of-art systems developed using DEAP dataset, this design exhibits superior real-time processing capabilities (latency of 0.02ms), while recognizing the maximum number of emotion classes without compromising additional power and area.
Field Oriented Control with Variable Switching Frequency for Symmetrical Six-Phase Induction Machines

The investigation in this study focuses on the advantages of symmetrical six-phase induction machines and introduces a novel control strategy, termed field-oriented control with a novel modulator (FOC-M). Six-phase machines provide the advantages of multiphase machines while implementing modular three-phase structures, resulting in a cost-effective and smooth transition. The proposed FOC-M method focuses on the control of symmetrical six-phase machines, providing a significant advantage by producing voltage vectors with high torque/flux production and null current harmonic distortion. The control algorithm is characterized by its simplicity, as it does not require system parameters, imposes a low computational burden, and exhibits excellent overall performance. These characteristics make it an attractive control option for this particular type of machines. The effectiveness of the proposed method is verified through experimental data.
Self-assessment and co-assessment to improve oral competence in university students in the remote education modality

In recent years, the use of remote teaching modality in higher education has become widespread. This has posed various challenges in different areas of learning, with one of them being associated with the development of oral competence. The objectives of this study were, first, to describe university students’ perceptions of their oral communicative competence, and second, to describe their perceptions regarding their processes of self-assessment and peer assessment of their oral communicative competence. This research corresponds to a qualitative descriptive study. The sample consisted of 45 first-cycle students from the Faculty of Health Sciences who, in the 2023-1 semester, were taking the Communication course in the remote education modality. To achieve this, two data collection techniques were employed: documentary analysis of the self-assessment and peer assessment forms completed by the students, and a focus group directed at them. Among the findings, it was identified that bodily, oral, and content-related resources pose greater difficulties for students, with issues such as pronunciation, tone of voice, facial gestures, and the development of solid arguments standing out. The categories that emerged from this analysis were metacognitive skills, time management, and pedagogical support. It was concluded that both self-assessment and peer assessment are highly beneficial activities for the formation and improvement of oral communicative competence, and these should be framed within the application of didactic strategies aimed at the development of each of its components.
Evaluating the Implementation of NFD, MW-NFD, and YaNFD in NDN-Base Video Streaming System

Named Data Network (NDN) is a future network that solves several problems with the existing internet network architecture. The main advantage of named data networks is that each NDN router utilizes content caching, which allows users to obtain requested data packets more quickly and efficiently. NDN operates by sending packets to specific destination addresses to retrieve material specified by name, eliminating the requirement for users to rely on IP addresses to access online content; instead, NDN uses content names. Today, internet network technology continues to evolve, resulting in a growth in demand for video content each year. As a result, optimizing and transmitting movies requires video access speed for clients seeking content from servers. This paper will investigate Network Forwarding Daemon (NFD), Multi Worker - Network Forwarding Daemon (MW-NFD), and Yet Another Networking Daemon (YaNFD) as forwarding algorithms for NDN-based video streaming. The main purpose of a forwarding system is to facilitate the transport of data packets that meet demand. This research emphasizes the varied findings while showing that the access speed will be increased or accelerated due to the caching capability in NDN networks by examining the differences between NFD, MW-NFD, and YaNFD.
Impact Of Water Harvesting Techniques On Growth Of Some Indigenous Tree Species In Jebel Awlia Locality, Sudan

The broad objectives of this study were to investigate the impact of water harvesting techniques on trees growth and soil moisture content. Field experiments were conducted for one rainy season (2010) around west Omdurman, Jebel Aulia Locality in Khartoum New International Air Port, 40 km south of Khartoum city and 25 km west of the White Nile River in south west direction . The study site lies in the semi desert region. The experimental design followed was the randomized block design. The water harvesting techniques used were strips, semi-circles, pits and control. The tree species grown were Acaia tortilis subsp raddiana, Acacia senegal and Zizphus spinachristi. The three tree species were planted by using seedlings. The shoot length, number of leaves and diameter of stem of seedlings of the three tree species were measured every three weeks after transplanting, during the rainy seasons. Soil moisture content was measured three times during the rainy seasons (beginning, middle and end). the soil samples taken from three different depths: 0-30cm, 30-60cm and 60-90cm. The results showed that the shoot length of Acacia senegal was more than Acacia tortilis subsp raddiana and Zizphus spina christi. The growth variables of the three tree species were significantly better (P <0. 001). The best height and number of leaves were recorded by Acacia senegal. The diameter of stem of seedlings of the three tree species showed variation in values. The growth variables of the three tree species planted in the pits were superior to those grown in the semicircles.
Spatial pattern of maize head smut in different localities of the State of Mexico

Con el fin de generar bases para el manejo del carbón de la espiga del maíz en zonas infestadas del Estado de México, se estudió el patrón espacial que presentó durante un cuarto año de estudio. La presente investigación se realizó para determinar la distribución espacial de esta enfermedad con técnicas geoestadísticas durante el año 2009. Su incidencia se determinó en 100 parcelas de cada una de las 25 localidades evaluadas, ubicándolas geográficamente con un dGPS. La determinación de la distribución espacial se realizó con el uso de herramientas Geoestadísticas, que fue validada a través del procedimiento de validación cruzada. Se elaboraron mapas de la distribución espacial por medio del kriging y se estimó la superficie infestada. Los resultados de la validación cruzada indicaron que los semivariogramas obtenidos se ajustaron al modelo esférico en 19 localidades, cuatro al exponencial y dos al gaussiano. Los diferentes modelos mostraron que el patrón espacial de la enfermedad se presenta de forma agregada o puntos específicos dentro de cada localidad. La agregación se visualizó de forma aleatoria dentro de cada localidad a través de los mapas elaborados. Dichos mapas permitieron estimar la superficie infestada, lo cual permitirá realizar su manejo con precisión a través del sitio-específico y detectar cambios en los patrones espaciales a través del tiempo. Abstract
Photonic-assisted Wideband Frequency Downconversion with Self-interference Cancellation and Image Rejection

A photonic-assisted wideband frequency downconversion with simultaneous self-interference cancellation (SIC) and image rejection (IR) based on a dual-polarization Mach-Zehnder modulator (DPol-MZM) is proposed. The SIC is achieved by combining the DPol-MZM, a polarization controller, and a polarizer. The IR is performed by using a wavelength division multiplexer, two photodetectors, and an electrical 90-degree hybrid coupler. Because the received and assisted signals are injected into the system independently of each other, the system has strong robustness. The performance of the system is demonstrated through simulation experiments. The SIC depth higher than 35 dB and the image rejection ratio larger than 55 dB within 1 GHz bandwidth are achieved. Besides, the recovery 16-QAM signal has a clear constellation diagram and an EVM of 8.4%.
The Role of Mass Wasting In the Progressive Development Of Submarine Channels (Espírito Santo Basin, Se Brazil)

A Pliocene–Quaternary submarine channel system, influenced by localized mass wasting, is investigated using high-resolution 3D seismic data from offshore Espirito Santo Basin, SE Brazil. Three abandoned channels, a channel belt, and a mass-transport deposit (MTD) are recognized in the channel system in a confluence region confined by salt diapirs. In this confluence region, the cross-sectional area (CSA) of the channel system can be up to 1.2 km2, i.e., 4 to 10 times larger than other parts of the study area. These significant changes in the architecture and morphology of the channel system resulted from the interaction between mass-wasting processes and turbidity flows. We postulate that a basal erosional scar created by mass-wasting processes was later filled with an MTD. This basal scar was then used as a preferential pathway for turbidity flows, which were captured by its headwall and lateral margins. The interpreted data show that the captured turbidity flows greatly widened the basal scar but caused only small modifications in scar height. This predominance of widening processes over channel incision occurred because part of the MTD in the basal scar was removed downslope by turbidity flows and replaced by channel-fill deposits. This paper shows that important flow-capture processes can predominate in channel-confluence regions of continental slopes. Basal scars can capture turbidity flows and facilitate flow channelization, which are key processes for submarine-channel initiation. Importantly, the replacement of MTDs by channel-fill deposits has profound implications for reservoir volumes and net-to-gross ratios in channel systems and partly depends on the properties of the turbidity flows, such as their erosive ability and frequency. The more erosive and frequent flows are captured by the basal scar, the larger is the accommodation space created for subsequent sand-prone turbidites.
Reduced Device Count Multilevel Inverter Topology for Renewable Energy Applications: A Brief Review

Modern power converters are an essential component in the real-time deployment of renewable energy which makes the renewable energy harness more efficient. In medium power applications, multilevel inverters (MLI) seem to be a viable alternative to conventional inverters. This article attempts to provide a brief overview of new reduced device count multilevel inverter topologies focusing on renewable energy applications. This review article examines the most recent topologies into two categories which are single-source and multiple-source multilevel inverters. In recent times, researchers have tried to employ a small number of components in multilevel inverters in order to achieve low voltage stress and increased efficiency. Moreover, the overall comparison of these topologies is shown in a tabular representation. This comparison is based on the needed number of switches, number of de supplies, Number of capacitors & diodes, and the number of levels (NL) that are achieved by the multilevel inverter topologies. In addition to this, the equivalent THD of the output and efficiency arc taken into consideration.
High-Resolution 2D MIMO Radars for Traffic Gesture Recognition

Autonomous driving places high demands on auto-motive sensor suites in terms of environmental perception. This includes radar sensors, which must offer ever better imaging performance. As a consequence, imaging radars with large apertures and 2D beamforming capabilities with high-angular resolutions have emerged in recent years. On the algorithm side, these sensors open up new possibilities for deep learning-based environmental perception. Hence, this paper explores radar-based traffic gesture recognition with a 192-channel radar sensor with a large virtual aperture. The sparse array has an angular resolution of 1.45° and 6.17° in azimuth and elevation, respectively, which provides accurate and detailed radar point clouds. Subsequently, a convolutional neural network (CNN) for spectrogram-based classification and a PointNet-based model (PointNet+LSTM) for direct point cloud processing are trained on a traffic gesture dataset with 20 participants. PointNet+LSTM reaches a single-sensor accuracy of 90.8 % with pretraining from simulation data, demonstrating the great potential of radars with high angular resolution for reliable gesture recognition.
A GaN-Based DC–DC Multistage Hybrid Converter for Step-Up Applications

This paper presents a multistage hybrid converter (MS-HC) designed for step-up applications, utilizing a combination of switched-inductor and switched-capacitor techniques. The proposed converter takes advantage of the controllability offered by switched-inductors and the multiplicity provided by switched-capacitors. To enhance efficiency and reduce size, Gallium Nitride (GaN) switches are employed in the design. The inductor's current frequency is increased to twice the switching frequency, resulting in a smaller inductor size. By incorporating multiple stages, the converter achieves a high step-up voltage gain. Additionally, the converter ensures low voltage stress on switches, limited to one-fourth of the output voltage. A comprehensive analysis is conducted to illustrate the operating principle of the converter. Finally, a practical implementation of a 300W two-stage converter is presented, demonstrating 95.7% efficiency and confirming the effectiveness of the proposed design.
Stability Analysis of Active Impedance Inverter based on Loss-compensated Passive Structure

An active impedance inverter, comprising negative (non-Foster) capacitors have been used recently in tunable bandpass filter designs. Those filters used a negative capacitor based on the well-known Linvill’s topology, while the design based on a loss-compensated passive structure has been proposed very recently. Here, we compare the stability properties of active impedance inverters based on both kinds of negative capacitor, loaded with commonly used complex loads.
Research on LPWAN Direct to Satellite IoT: A Survey Technology and Performance on LEO Satellite

The Internet of Things (IoT) is a rapidly growing field that necessitates long-range, low-power communication solutions, particularly in remote areas. Direct-to-satellite IoT (DTS-IoT) connectivity is an appealing option because it eliminates the need for ground-based intermediaries, thereby simplifying and accelerating the widespread implementation of IoT infras-tructure. Low Power Wide Area Network (LPWAN) technology, with its long-range connectivity and low power consumption, is well-suited for Massive Machine-Type Communication (mMTC), a key application of IoT. Furthermore, LPWAN technology shows potential for communication with Low Earth Orbit (LEO) satellites, which offer wide coverage and low latency, making them ideal for IoT device connection. This paper investigates the integration of LPWA technology with LEO satellite-based IoT, a crucial step toward advancing communication mechanisms in this domain. The paper provides a comprehensive survey of LPWAN technologies suitable for DTS-IoT applications. In the context of LEO satellite communications, it is essential to consider certain fundamental aspects. This includes the challenges faced by LPWAN technology in DTS-IoT on LEO satellites, such as the Doppler Effect, limited field of view, visibility windows, and random access. LoRa and LR-FHSS are two promising candidates for DTS-IoT on LEO satellites as they meet the link budget requirement at altitudes over 500 km. They also exhibit good Doppler resilience compared to other technologies; however, further research is necessary to confirm these findings. In summary, there is a need for future work in developing algorithms and implementing them in hardware to overcome the existing limitations.
HVAC System Fault Diagnosis via Feature Selection and Classification

Fault detection and diagnosis play a crucial role in energy savings in heating, ventilation, and air conditioning systems. It enables timely and appropriate repairs to prevent system malfunctioning and reduce energy waste. In this paper, a proposed feature selection algorithm or a neurodynamic optimization algorithm based on information gain is used for selecting a certain number of significant features, and then a stacking classifier is utilized to classify data into several different fault types by using the selected features. Experimental results are elaborated to demonstrate the superior performance of the proposed method against baselines in terms of accuracy on most of the datasets.