Miracle-dz/UniFAR-FTUs huggingface dataset:
Positioning Performance Assessment of Geodetic, Automotive, and Smartphone GNSS Receivers in Standardized Road Scenarios

Intelligent transport system applications use the global navigation satellite systems (GNSSs) to deliver the information on position, velocity, and time. With the expected deployment of critical road services, GNSS-based positioning terminals will have to be sufficiently accurate and their service will have to be available under any environmental condition. As the answer to the absence of standards and certification procedures of positioning terminals in road transport services, the European COST Action SaPPART was launched and the European norm EN 16803-1 was accepted. They provide the methodology and the guidelines for the terminal performance assessment. Section I presents the data collection methodology based on European norm EN 16803-1 with the definition of performance metrics and classification, operational scenarios, standardized GNSS environments, and field test guidelines. It is followed by the description of the measurement setup, including the trajectories, experimental vehicle with a reference trajectory system, and 17 tested GNSS receivers. The performance assessment of geodetic, automotive, and smartphone GNSS receivers was carried out through the extensive data collection campaign in Nantes, France. The campaign covered four types of environments: clear-sky, rural, peri-urban, and urban. The presented results focus on the basic performance features of accuracy, availability, and the classification of positioning terminals according to SaPPART methodology. The final conclusion is that for achieving a sub-meter accuracy at 95% confidence level in mixed road scenarios, a hybrid multi-sensor positioning approach is required for the majority of mass-market receivers.
A Dielectric Constant Measurement System for Liquid Based on SIW Resonator

A self-sustained dielectric constant (i.e., permittivity) measurement system for liquid is proposed. A tunable substrate integrated waveguide (SIW) resonator is exploited to form a feedback-type voltage controlled oscillator (VCO) that is further embedded into a phase locked loop (PLL)-based frequency synthesizer. The SIW resonator acts as the feedback element of the VCO. When the SIW resonator is exposed to liquid, its frequency response and the corresponding VCO oscillation frequency change accordingly because of electromagnetic field perturbation. Due to the presence of the PLL, the eventual frequency of synthesizer is kept constant, while this potential frequency shift is translated into the output voltage of the PLL loop filter. This voltage is readily measured by a digital multi-meter. Principles and design considerations of the SIW resonator as well as implementations of the VCO and the PLL synthesizer are discussed in detail. In addition, a prototype sensing platform is devised. Correlations between the dielectric constant of liquid MUT and the physical parameters, such as the SIW resonant frequency, the VCO oscillation frequency, and the PLL output voltage are analyzed comprehensively. According to the experimental results of several organic liquids, the proposed system can achieve an accuracy better than 4% for permittivity characterization.
Analysis of insulation performance and polar effect of CF3I/CO2 mixtures

SF6 gas is widely used in power systems, however, it has a strong greenhouse effect. The search for a new environmentally friendly alternative gas has become an urgent task for the power industry. In this paper, CF<sub>3</sub>I/CO<sub>2</sub> gas mixtures in the ratio of 3:7 was tested based on a lightning impulse experimental platform. The 50% impulse breakdown voltage of CF<sub>3</sub>I/CO<sub>2</sub> gas mixtures was determined under various pressures (0.1~0.3MPa) and gaps (5~30mm) and compared to pure SF<sub>6</sub> gas. The results indicate that CF<sub>3</sub>I/CO<sub>2</sub> gas mixtures has good insulation properties, reaching 0.84 times that of SF<sub>6</sub> gas under slightly non-uniform electric field and 0.65 times that of SF<sub>6</sub> gas in extremely inhomogeneous electric field. The polar effect of CF<sub>3</sub>I/CO<sub>2</sub> gas mixtures was also analyzed and the coefficient K is proposed to describe and compare the differences of 50% breakdown voltages under different electric field. The results show that the polar effect of CF<sub>3</sub>I/CO<sub>2</sub> gas mixtures under extremely inhomogeneous electric field is more obvious than that under slightly non-uniform electric field, and the polar reversal phenomenon occurs only under extremely inhomogeneous electric field. Considering various factors, CF<sub>3</sub>I/CO<sub>2</sub> mixtures has the capability of replacing SF<sub>6</sub> gas in power equipment such as GIL.
On the Design of Downlink Multiuser Transmission for a Beam-Group Division 5G System

To accommodate the ever-increasing data traffic, the 5G system has adopted the enormous swathes of unlicensed spectrum at millimeter-wave band. The millimeter-wave band however exhibits orders-of-magnitude more path loss than the microwave band. The upcoming 5G system thus necessitates the use of large-scale antenna arrays to compensate for the notable path loss with beamforming gain. Nevertheless, the large number of antenna elements also poses some challenges. For example, it is impractical to assign one dedicated transceiver unit (TXRU) for each individual element and the complexity of channel estimation on spatial (antenna) domain is prohibitively high. In this paper, we design low complexity multiuser transmission on beam domain at millimeter-wave band. Specifically, we propose the beam channel set selection and user grouping schemes to significantly lower the complexity of channel estimation and precoder design by exploiting the salient feature of channel sparsity. Moreover, 2-D TXRU virtualization together with beam sweeping strategies is presented as the TXRU number is less than the number of columns of planar antenna array. Simulation results show that the proposed beam-group division 5G system can significantly reduce the complexity and keep the system throughput.
Individual Characterization of Fast Intracortical Facilitation With Paired Biphasic-Wave Transcranial Magnetic Stimulation

We characterized the short-interval intracortical facilitation (SICF) via modulation of transcranial magnetic stimulation (TMS) induced motor evoked potentials (MEPs) using paired-pulse stimulation, and analyzed the interactions with known SICF I-wave behavior. The objective was to optimize individual SICF to enhance TMS effects for motor mapping and therapeutic stimulations. We applied navigated TMS in nine healthy volunteers to study SICF. MEPs were measured for baseline using single-pulse TMS, and subsequently, paired-pulse TMS was applied to study SICF. The interstimulus interval (ISI) between the paired pulses was varied between 1.2 and 4.3 ms at 0.1 ms intervals. Ten MEPs were measured from three muscles (FDI, APB, and ADM) in the dominant hand of the volunteer. We then fitted a 3-peak Gaussian model to the individual paired-pulse MEP vs. ISI curves to characterize each peak by latency, amplitude, and width. Individual SICF I-wave interaction characteristics were successfully determined. The average peak latencies were 1.36 ms (I1-wave), 2.80 ms (I2-wave), and 4.29ms (I3-wave) for the targeted FDI muscle. The peak amplitudes differed depending on the muscle ( ${p} = {0.001}$ ), with ADM muscle exhibiting greatest SICF effect, but no significant difference between the three peaks. In addition, the peak widths differed between all muscles ( ${p} < {0.001}$ ), second peak being the widest. In conclusion, the individual SICF I-wave interaction characteristics were successfully determined revealing significant differences in peak features. This could enable application of SICF for enhancement of TMS effects in therapy, cortical mapping, and basic neuroscience applications.
Science Education Through Accessible Video Content

Science education for the school learners who are hearing impaired is a multi-layered problem. It is found that from the teachers who can teach using sign language only few have science background. In such a case, use of online resources is a solution; however, there is a dearth of educational content created using sign language. We have created video content with an objective of bridging this gap. The videos explain the making of science toys (designed by Arvind Gupta) in a conversational format. Teacher training was conducted to explain the application of the videos in classroom. Results of preliminary tests with Teachers and learners reveal that they find these videos useful from the content as well as the access perspective.
Increased levels of RECQ5 shift DNA repair from canonical to alternative pathways

RECQ5 (RECQL5) is one of several human helicases that dissociates RAD51-DNA filaments. The gene that encodes RECQ5 is frequently amplified in human tumors, but it is not known whether amplification correlates with increased gene expression, or how increased RECQ5 levels affect DNA repair at nicks and double-strand breaks. Here, we address these questions. We show that RECQ5 gene amplification correlates with increased gene expression in human tumors, by in silico analysis of over 9000 individual tumors representing 32 tumor types in the TCGA dataset. We demonstrate that, at double-strand breaks, increased RECQ5 levels inhibited canonical homology-directed repair (HDR) by double-stranded DNA donors, phenocopying the effect of BRCA deficiency. Conversely, at nicks, increased RECQ5 levels stimulated 'alternative' HDR by single-stranded DNA donors, which is normally suppressed by RAD51; this was accompanied by stimulation of mutagenic end-joining. Even modest changes (2-fold) in RECQ5 levels caused significant dysregulation of repair, especially HDR. These results suggest that in some tumors, RECQ5 gene amplification may have profound consequences for genomic instability.
Motion Modeling and Localization of Skid-Steering Wheeled Rover on Loose Terrain

The motion behavior of a skid-steering rover on loose terrain is modeled experimentally, and a position estimation method based on the model is proposed. Skid steering is a steering method adopted for various vehicles and robots. In this method, the vehicles steer by controlling a ratio between the rotational velocities of their left and right wheels. For controlling a skid-steering rover, whose wheels can slip on the lunar and planetary surfaces, which are covered with loose regolith, it is important to model accurately the rover's motion behaviors on loose terrain. To this end, we conducted traveling tests using a four-wheeled rover in a sand field and analyzed the motion behaviors of the rover on loose terrain. In the tests, the velocities of the rover's left and right wheels were controlled, and the rover traveled with various turning patterns. From the test datasets, we derived a mathematical model that expresses a relationship between the input and output velocities of the rover's wheels. Furthermore, the effectiveness of a position and motion estimation method based on the model was confirmed from experiments conducted in the sand field.
Multimodal Recognition of Emotions with Application to Mobile Learning

A great variety of emotional recognition systems have been implemented, but few have been applied in the real world due to the high cost of the necessary technology and due to the low percentage of recognition effectiveness, when one does not work with spontaneous emotions. This paper presents the initial implementation of a system of multimodal recognition of emotions using mobile devices and the creation of an affective database through a mobile application. The recognizer works into a mobile educational application to identify user's emotions as they interact with the device. The emotions that the system recognizes are engagement and boredom. The affective database was created with spontaneous emotions of students who interacted with an educational mobile application called Duolingo and a mobile information gathering application called EmoData. The developed system has a regular percentage of effectiveness for audio recognition and position recognition. The corpus used for training is still small. We believe that as the number of registrations in the affective database increases, the precision will improve.
Failure Predictor Factors of Conservative Treatment in Pediatric Forearm Fractures

The aim of this study is to evaluate the predictive efficacy of the radiographic parameters and the relationship between the radiographic results and the clinical data. We carried out a retrospective study analyzing the data of 225 pediatric patients with forearm fractures treated conservatively. Two orthopaedists examined 4 different radiographic parameters. They compared CI and radial translation parameters at T0, in terms of indication of type of treatment and predictive efficacy. Afterwards, the two orthopaedists analyzed X-rays performed at T1, evaluating radiographic results according to radial shortening and angle parameters. From the analysis of the CI measured by Observer 1, 135 patients out of 225 had retrospective indication to conservative treatment; the frequency of failure was 18/135 (13.3%). Observer 2 indicated conservative treatment in 144 patients out of 225 and the proportion of failure was 21/144 (14.6%). As regards the radial translation, Observer 1 reported a frequency of failure of 78/225 (34.7%) and Observer 2 reported 75/222 (33.8%). Furthermore the authors detected a deficit of pronosupination for the patients considered to have failure according to radiographic results. The authors defined the greater reliability of CI with respect to the radial translation parameter and the direct relationship between radiographic failure and clinical-functional data.
Reliability Oriented Control of DC/DC Converters for More Electric Aircraft

With the goal to decrease weight and increase overall efficiency, power electronics is proliferating in the aircraft applications. The on-board ac and dc distribution systems enable new opportunities for controlling the stress for the modular power converters and therefore the wear-out of individual converter cells. This work considers the failure mechanisms of the most sensitive devices in the system, the power semiconductors, and predicts their remaining useful lifetime. Based on this remaining useful lifetime, an optimization of the system loading is performed in order to maximize the time to the next failure in dependence of the prior sensed mission profile. A study case is shown in order to demonstrate the lifetime increase of the system with the proposed algorithm. Moreover, a test bench implementation for controlling the loading is shown for demonstrating the capability of the system loading control.
IMU-Based Classification of Parkinson's Disease From Gait: A Sensitivity Analysis on Sensor Location and Feature Selection

Inertial measurement units (IMUs) have a long-lasting popularity in a variety of industrial applications from navigation systems to guidance and robotics. Their use in clinical practice is now becoming more common, thanks to miniaturization and the ability to integrate on-board computational and decision-support features. IMU-based gait analysis is a paradigm of this evolving process, and in this study its use for the assessment of Parkinson's disease (PD) is comprehensively analyzed. Data coming from 25 individuals with different levels of PD symptoms severity and an equal number of age-matched healthy individuals were included into a set of 6 different machine learning (ML) techniques, processing 18 different configurations of gait parameters taken from 8 IMU sensors. Classification accuracy was calculated for each configuration and ML technique, adding two meta-classifiers based on the results obtained from all individual techniques through majority of voting, with two different weighting schemes. Average classification accuracy ranged between 63% and 80% among classifiers and increased up to 96% for one meta-classifier configuration. Configurations based on a statistical preselection process showed the highest average classification accuracy. When reducing the number of sensors, features based on the joint range of motion were more accurate than those based on spatio-temporal parameters. In particular, best results were obtained with the knee range of motion, calculated with four IMUs, placed bilaterally. The obtained findings provide data-driven evidence on which combination of sensor configurations and classification methods to be used during IMU-based gait analysis to grade the severity level of PD.
Osteoradionecrosis of the Temporal Bone: An Evidence-Based Approach.

OBJECTIVES To perform a systematic review evaluating etiologies, associated complications, and management of osteoradionecrosis of the temporal bone (ORNTB). METHODS The authors searched the PubMed, Embase, and Cochrane Library databases for relevant literature. Patient demographics, etiologies, treatments, and other clinical characteristics were obtained. Treatment success was defined as resolution of symptoms at last follow-up. Results were reported using the preferred reporting systems for systematic reviews and meta-analysis (PRISMA) guidelines. RESULTS Thirty-eight studies encompassing 364 patients with ORNTB were identified. The most common etiologies necessitating radiotherapy included: nasopharyngeal carcinoma (n = 133 [36.8%]), parotid tumors (n = 73 [20.2%]), and external auditory canal pathology (n = 59 [16.3%]). The mean dose of radiation was 58.0 Gy. The mean lag time between radiotherapy and osteoradionecrosis (ORN) symptoms was 7.9 years. The most common presenting symptoms were purulent otorrhea (33.3%), hearing loss (29.1%), and otalgia (17%). ORNTB complications included tympanic membrane perforation (n = 102 [63.8%]) and chronic otitis media (n = 16 [10%]). Treatments included lateral temporal bone resection (n = 99 [28.3%]), conservative treatment (n = 92 [26.3%]), and mastoidectomy (n = 82 [23.5%]) with 90.9, 89.13, and 59.76% considered successful, respectively. CONCLUSIONS ORNTB is a rare complication of radiotherapy that may present years after initial radiation exposure. Management should be aimed at relief of presenting symptoms and treatment of ORNTB associated complications. Both conservative and surgical measures may adequately control the disease process and symptomatology; however, randomized controlled studies comparing treatments would serve to further corroborate these findings.
Feasibility of 5G mm-wave communication for connected autonomous vehicles

The internet-of-things (IoT) environment holds different intelligent components networked together and will enable seamless data communication between the connected components. Connected autonomous vehicles or CAVs are major components of the IoT, and the smooth, reliable, and safe operation of CAVs demands a reliable wireless communication system, which can ensure high connectivity, high throughput and low communication latency. The 5G millimeter-wave or mm-wave communication network offers such benefits, which can be the enabler of CAVs, especially for dense congested areas. In this research, we have evaluated the 5G mm-wave and Dedicated Short Range Communication (DSRC) for different CAV applications in a Network Simulator-3 (ns-3). For the CAV applications, we have evaluated the end-to-end latency, packet loss, and data rate (for both the CAV receiver and transmitter) of the 5G mm-wave. We have found that 5G mm-wave can support CAV safety applications by ensuring lower latency compared to the required minimum latency of 200 milliseconds for the forward collision warning application. For mobility applications, we have found that 5G mm-wave can support multiple CAVs with a high data receive rate, which is enough for real-time high definition video streaming for in-vehicle infotainment, with mean packet delay of 13 milliseconds. The findings from this study establish that 5G mm-wave can be the enabler of future CAVs in congested areas. Using the evaluation framework developed in this paper, public agencies can evaluate 5G mm-wave to support CAVs in congested areas, such as heavy pedestrian areas like downtown, commercial zones, under their jurisdiction.
Cellular V2X Communications in Unlicensed Spectrum: Harmonious Coexistence With VANET in 5G Systems

With the increasing demand for vehicular data transmission, limited dedicated cellular spectrum becomes a bottleneck to satisfying the requirements of all cellular vehicle-to-everything (V2X) users. To address this issue, unlicensed spectrum is considered to serve as the complement to support cellular V2X users. In this paper, we study the coexistence problem of cellular V2X users and vehicular ad hoc network (VANET) users over the unlicensed spectrum. To facilitate the coexistence, we design an energy sensing-based spectrum sharing scheme, where cellular V2X users are able to access the unlicensed channels fairly while reducing the data transmission collisions between cellular V2X and VANET users. In order to maximize the number of active cellular V2X users, we formulate the scheduling and resource allocation problem as a two-sided many-to-many matching with peer effects. We then propose a dynamic vehicle-resource matching algorithm and present the analytical results on the convergence time and computational complexity. Simulation results show that the proposed algorithm outperforms existing approaches in terms of the performance of the cellular V2X system when the unlicensed spectrum is utilized.
Dual-level attention-aware network for temporal emotion segmentation

Abstract. Human emotions are known to always have four phases in the temporal domain: neutral, onset, apex, and offset. This has been demonstrated to be of great benefit for emotion recognition. Therefore, temporal segmentation has attracted considerable research interest. Although state-of-the-art techniques use recurrent neural networks to highly increase the performance, they ignore the relevance of each frame (time step) of a video, and they do not consider the changing contribution of different features when fusing them. We propose a framework called dual-level attention-aware bidirectional grated recurrent unit, which integrates ideas from attention models to discover the most important frames and features for improving temporal segmentation. Specifically, it applies attention mechanisms at two levels: frame and feature. A significant advantage is that the two-level attention weights provide a meaningful value to depict the importance of each frame and feature. The experiments demonstrated that the proposed framework outperforms state-of-the-art methods.
Two-Stage Privacy-Preserving Mechanism for a Crowdsensing-Based VSN

Vehicular social networks (VSNs) are moving from infancy to maturity. However, the characteristics of wireless channel availability and the high mobility of vehicles in the VSNs create new challenges for privacy preservation; the corresponding solutions require a combination of technologies. A common theme in this paper is the combination of crowdsensing (CS) and the VSNs. We first design a three-layer CS-based VSN architecture that includes a CS layer, mobile management layer, and core control layer. Then, we propose a two-stage privacy-preserving (TSPP) algorithm to protect identity and location privacy for the CS-based VSN. In TSPP algorithm, to protect identity privacy, we design a way of identity management. Simultaneously, by correlation analysis, we design a suppression strategy to satisfy $\varepsilon $ -privacy with no information loss for location privacy protection. The simulation results show that our proposed TSPP algorithm better protects identity and location privacy than current algorithms. The results are based on four metrics: average processing time, identity privacy, location privacy, and information loss.