Miracle-dz/UniFAR-FTUs huggingface dataset:
Active Voltage Sharing Module for Input-Series Connected Modular DC/DC Converters

Since both the input-series–output-series system and the input-series–output-parallel system have a circuit configuration in which the input sides are in series, it is very suitable for applications with high input voltages. This article proposes a simple active voltage sharing module (AVSM) that allows two closed-loop dc/dc converters to be combined directly into an input-series system as power devices to meet various voltage requirements. An AVSM, consisting of one coupled inductor and two metal–oxide–semiconductor field-effect transistors, is connected on the input side of the two submodules. By adopting a control method with fixed frequency and duty cycle, accurate input voltage sharing can be achieved, enabling voltage isolation sampling of the submodules and the voltage sharing regulators of the system to be eliminated, thus greatly simplifying the design process of the input-series system. This article introduces the AVSM working principle and discusses the stability of the proposed input-series system. It then describes a simulation performed to verify the theoretical analysis results and addresses the influences of the AVSM parameters on the system performance. Finally, the use of a prototype to test the steady-state and dynamic performances of the proposed scheme is discussed.
Comparison of escitalopram with citalopram in treatment of depression:a randomized,double-blind,multicenter study

AIM To evaluate the efficacy and safety of escitalopram in treating depression.METHODS In this randomized,double-blind,double-mimicry,citalopram parallel controlled multicenter study,the patients were randomized in two groups who were treated with escitalopram oxalate tablet 10-20 mg·d~(-1) or citalopram hydrobromide tablet 20 - 40 mg ? d~(-1) respectively.The primary efficacy variable was Hamilton Depression Scale 17-item(HAMD-17) while Clinical Global Impression(CGI) and Hamilton Anxiety Scale (HAMA) were used as secondary variables.Adverse events observation,lab examination and vital signs check were taken to assess the safety.RESULTS In FAS(235 patients),the amount of patients belonged to escitalopram group or citalopram group was 119 vs.116;in PPS(218 patients),110 vs.108. At the end of wk 1,2,4 and 6 in treatment,there were statistically significant reductions in HAMD-17 or HAMA total scores in both groups compared with their baseline(P0.01),however,there was no significant difference between the two groups(P0.05). After 6 weeks treatment,the reduction in HAMD-17 total score of escitalopram group was(13.28±4.30),while the reduction of citalopram group was(13.67±5.29) by FAS analysis. For escitalopram group and citalopram group,the response rate was 79.8%and 81.9%,the remission rate was 66.4%and 62.9%,respectively,with no significant difference between the two groups(both P0.05). Similar findings were found in CGI and HAMA(P0.05). Safety assessment showed there was no statistically significant difference between the symptoms and incidence of adverse reactions(P0.05). CONCLUSION Escitalopram is effective,safe and comparable to citalopram in treatment of patients with depression.
Comparative Analysis of Magnet Thermal and Magnetization State Monitoring in PMSMs Based on High-Frequency Signal Injection

Thermal and magnetization state monitoring of permanent magnet synchronous machines (PMSMs) is important for reliability purposes. Use of magnet high-frequency (HF) resistance has been proposed both for thermal and magnetization state monitoring, as it directly depends on PM temperature and magnetization state. Machine d-axis HF inductance has been recently proposed for thermal state monitoring, though its use for magnetization state estimation remains to be explored yet. This article reviews the use of HF-signal-injection-based methods for thermal and magnetization state monitoring on PMSMs, including the use of the HF inductance for magnetization state monitoring.
Energy and Error Analysis Framework for Approximate Computing in Mobile Applications

In this brief, we propose a framework that enables us to analyze energy and error for mobile applications when run on systems with approximate circuits. Approximate circuits have conventionally been used in image/video processing applications, which are mostly limited to 8-bits. To the best of our knowledge this is the first work where approximate circuits have been evaluated on a 32-bit processor running real mobile applications. We observe that in approximate adders where Carry is approximated, with 2-bit approximation in LSB, the absolute average error in image processing applications is ~ 3. However, in mobile applications approximation in Carry can lead to an overflow. Hence, approximate adders with Carry approximation are not suitable for mobile computing. We also show the role of data-dependent switching in energy consumption and highlight which input pattern should not be approximated to obtain lesser error. In this brief, we also propose design of three energy-efficient approximate hybrid CMOS full-adders with varying levels of inaccuracies. The adder designs are implemented in UMC 65-nm technology using Cadence Virtuoso. Compared to existing approximate adders, on an average, the proposed adders consume 44% lesser energy and have ${2\times }$ lesser energy delay product. Our proposed adder designs have similar leakage power as compared to the existing adders.
Attitude Estimation Using Inertial and Magnetic Sensors Based on Hybrid Four-Parameter Complementary Filter

A complementary filter is presented for the attitude estimation using inertial and magnetic sensors. The proposed filter is based on a new attitude representation, where 4-D parameters (a 3-D unit vector and one angle quantity) are used. The proposed representation has an intuitive interpretation and the proposed filter has a separation property (magnetic disturbance does not affect pitch and roll angle estimation). Kinematics of the 4-D parameters and other properties are investigated. The proposed filter is verified through simulation and experiments.
Flight performance monitoring with optimal filtering applications

ABSTRACT This work presents an alternative methodology for monitoring flight performance during airline operations using the available inboard instrumentation system. This method tries to reduce the disadvantages of the traditional specific range monitoring technique where instrumentation noise and cruise stabilisation conditions affect the quality of the performance monitoring results. The proposed method consists of using an unscented Kalman filter for aircraft performance identification using Newton’s flight dynamic equations in the body X, Y and Z axis. The use of the filtering technique reduces the effect of instrumentation and process noise, enhancing the reliability of the performance results. Besides the better quality of the monitoring process, using the proposed technique, additional results that are not possible to predict with the specific range method are identified during the filtering process. An example of these possible filtered results that show the advantages of this proposed methodology are the aircraft fuel flow offsets, as predicted in the specific range method, but also other important aircraft performance parameters as the aircraft lift and drag coefficients (CL and CD), sideslip angle (β) and wind speeds, giving the operator a deeper understanding of its aircraft operational status and the possibility to link the operational monitoring results to aircraft maintenance scheduling. This work brings a cruise stabilisation example where the selected performance monitoring parameters such as fuel flow factors, lift and drag bias, winds and sideslip angle are identified using only the inboard instrumentation such as the GPS/inertial sensors, a calibrated anemometric system and the angle-of-attack vanes relating each flight condition to a specific aircraft performance monitoring result. The results show that the proposed method captures the performance parameters by the use of the Kalman filter without the need of a strict stabilisation phase as it is recommended in the traditional specific range method, giving operators better flexibility when analysing and monitoring fleet performance.
Do Robots Have Race?: Race, Social Construction, and HRI

In a paper presented at the 2018 ACM/IEEE International Conference on Human Robot Interaction (HRI 2018), Bartneck and colleagues (myself included) argued that people attribute race to humanoid robots [1]. The experiments we conducted suggested that people are willing to identify robots as being of different races when asked and that, at least when confronted with the shooter bias test [2], people also behave in ways that suggest they attribute race to robots. This article joins a small number of other articles in providing evidence that people attribute racial and/or ethnic identities to robots [3], [4]. While the methods we used in our research have come in for some criticism [5], the article has at least highlighted this question as a topic for future research.
Equivalent Acceleration Imitation for Single Wheel of Manned Lunar Rover by Varying Torque on Earth

Owing to different gravities, the same manned lunar rover shows different acceleration properties on the earth and the moon; therefore, it is of great significance for astronauts to be trained on the earth under the condition of the acceleration properties found on the moon. In this article, a novel acceleration imitation method focused on a single wheel is proposed to obtain equivalent acceleration when using the same acceleration driver input under different gravities, and the acceleration imitation algorithm is derived based on a mechanical model of a special metal wheel with a mesh surface. To reduce the complexity and improve the real-time properties of the algorithm, a fitting function for the imitation torque ratio is proposed to adjust the relationship between the acceleration driver input and the driving torque of the wheel. Finally, experiments were conducted to verify the acceleration imitation algorithm, and the results revealed that the wheel with an imitation torque ratio could effectively approximate on the earth the same acceleration experienced by a single wheel of a manned lunar rover on the moon, given equivalent acceleration driver inputs.
Wheel Slip Control for the Electric Vehicle With In-Wheel Motors: Variable Structure and Sliding Mode Methods

The article introduces four variants of the controller design for a continuous wheel slip control (WSC) system developed for the full electric vehicle equipped with individual in-wheel motors for each wheel. The study includes explanation of the WSC architecture, design of controllers, and their validation on road tests. The investigated WSC design variants use variable-structure proportional-integral, first-order sliding mode, integral sliding mode controllers as well as continuous twisting algorithm. To compare their functionality, a benchmark procedure is proposed based on several performance factors responsible for driving safety, driving comfort, and control quality. The controllers are compared by the results of validation tests done on low-friction road surface.
Damage Visualization of Scattered Ultrasonic Wavefield via Integrated Highspeed Camera System

In this study, a damage was successfully visualized through scattered guided acoustic wavefield reconstructed via an integrated high-speed camera scanning system. By employing a sample interleaving and an image stitching technique, the data requisition rate for the high-speed camera was enhanced nearly 250 times in order to overcome the current limited performance due to inadequate on both spatial resolution and temporal resolution, i.e., sampling frequency, for guided wavefield measurement. Further, many experimental parameters, e.g., specimen design, field of view, speckle size and signal frequency, as well as the camera system were carefully designed, integrated and optimized to enable capture of propagating guided waves excited by a piezo actuator on a surface of the structure. As such the in-plane wave displacements could be maximized and extracted using digital image correlation (DIC). A very compliant HDPE plate with an added mass for mimicking damage was chosen for the proof of concept. The first fundamental SH and S0 guided wave modes under continuous wave excitation frequency of 14 kHz were successfully detected by the camera and extracted by DIC, and the disturbance at the damage region was clearly observed in the reconstructed scattered wavefield. A damage imaging condition named wavenumber index (WI) that was previously developed and applied to visualizing the hidden delamination in composites was further adapted and improved for the wavefield reconstructed via high-speed DIC.
Output Voltage Range of a Power-Loaded Series–Series Compensated Inductive Wireless Power Transfer Link Operating in Load-Independent Regime

The article proposes an in-depth analysis of a series–series compensated resonant inductive wireless power transfer (WPT) link, operating at load-independent frequency while feeding a power load. It is shown that due to the presence of equivalent series resistances in practical systems, a load-independent operation point is only an approximation. The output voltage is still affected by the load, obtaining minimum and maximum values under rated load and no-load operation, respectively. While the output voltage value under rated load is typically well predicted by the commonly used first-harmonic-approximation-based equivalent circuit, the latter is unsuitable for obtaining the output voltage value under light loading due to nonlinearity caused by the discontinuous conduction mode of the secondary. Time-domain analysis is, therefore, used to accurately predict the WPT output voltage value under zero-load operation and accurately derive the expected WPT output voltage range in the load-independent regime. Simulations and experiments based on a 400-V 1-kW WPT link demonstrate excellent matching, validating the proposed analysis.
Minimization of Losses in Power Systems by Reactive Power Dispatch using Particle Swarm Optimization

Due to the high cost of electric power, achieving the optimal reduction of active (real) losses during power transmission is very important. The reduction of these losses is crucial in Peru because the values of leakage losses in coastal lines are very high and produce large transverse active losses. In this work it has been investigated the reduction of active power losses through the optimal dispatch of reactive power and the optimal control of voltages using the Particle Swarm Optimization (PSO) technique. This work has been implemented using Matlab, and MATPOWER has been used as an engine to solve the load flow.The efficiency of the process is confirmed using the 14-bar IEEE test power system achieving a loss reduction of 8.38%. The loss of active power converges after 100 iterations from 13,393 to 12.27 MW.During the investigation it was confirmed that the PSO can solve with great efficiency problems where the objective function is very complex, so it can be applied to the problem of reducing losses in the national network and it will also be able to solve major problems such as reactive power planning and planning of the expansion of the transmission network.
Lipoprotein-associated phospholipase A2 activity and risk of heart failure: The Rotterdam study

Aims: Evidence is accumulating that inflammation plays a role in the pathophysiology of heart failure. Lipoprotein-associated phospholipase A2 (Lp-PLA2) has pro-inflammatory properties. We investigated whether Lp-PLA2 activity is associated with heart failure. Methods and results: Lp-PLA2 activity was determined in a random sample of 1820 subjects from the Rotterdam Study, a population-based cohort study among persons aged 55 years and over. During a mean follow-up of 6.7 years, 94 heart failure cases occurred. We excluded participants with heart failure or coronary heart disease at baseline and we accounted for incident coronary heart disease during follow-up. We used Cox proportional hazard models to compute hazard ratios adjusted for age, sex, non-HDL cholesterol, HDL cholesterol, body mass index, systolic blood pressure, diastolic blood pressure, hypertension, diabetes mellitus, smoking, and C-reactive protein. The hazard ratio per unit increase of Lp-PLA2 activity was 1.03 [95%confidence interval (95%CI) 1.01-1.05]; P for trend was 0.011. Hazard ratios for the second, third, and fourth quartiles were 1.06 (95%CI 0.55-2.04), 1.43 (95%CI 0.73-2.81), and 2.33(95%CI 1.21-4.49), respectively, using the lowest quartile of Lp-PLA2 activity as the reference category. Conclusion: This study suggests that Lp-PLA2 activity is independently associated with incident heart failure.
Design and Implementation of a System-on-Chip for Self-Calibration of an Angular Position Sensor

In this study, a novel signal processing algorithm and hardware processing circuit for the self-calibration of angular position sensors is proposed. To calibrate error components commonly found in angular position sensors, a parameter identification algorithm based on the least mean square error demodulation is developed. A processor to run programs and a coprocessor based on the above algorithm are used and designed to form a System-on-Chip, which can calibrate signals as well as implement parameter configuration and control algorithm applications. In order to verify the theoretical validity of the design, analysis and simulation verification of the scheme are carried out, and the maximum absolute error value in the algorithm simulation is reduced to 0.003 %. The circuit’s Register-Transfer Level simulation shows that the maximum absolute value of the angular error is reduced to 0.03%. Simulation results verify the calibration performance with and without quantization and rounding error, respectively. The entire system is prototyped on a Field Programmable Gate Array and tested on a Capacitive Angular Position Sensor. The proposed scheme can reduce the absolute value of angular error to 4.36%, compared to 7.68% from the experimental results of a different calibration scheme.
Decoding EEG in Motor Imagery Tasks with Graph Semi-Supervised Broad Learning

In recent years, the accurate and real-time classification of electroencephalogram (EEG) signals has drawn increasing attention in the application of brain-computer interface technology (BCI). Supervised methods used to classify EEG signals have gotten satisfactory results. However, unlabeled samples are more frequent than labeled samples, so how to simultaneously utilize limited labeled samples and many unlabeled samples becomes a research hotspot. In this paper, we propose a new graph-based semi-supervised broad learning system (GSS-BLS), which combines the graph label propagation method to obtain pseudo-labels and then trains the GSS-BLS classifier together with other labeled samples. Three BCI competition datasets are used to assess the GSS-BLS approach and five comparison algorithms: BLS, ELM, HELM, LapSVM and SMIR. The experimental results show that GSS-BLS achieves satisfying Cohen’s kappa values in three datasets. GSS-BLS achieves the better results of each subject in the 2-class and 4-class datasets and has significant improvements compared with original BLS except subject C6. Therefore, the proposed GSS-BLS is an effective semi-supervised algorithm for classifying EEG signals.
Measurement and Analysis of SSD Reliability Data Based on Accelerated Endurance Test

In recent years, NAND Flash-based solid-state drives (SSDs) have become more widely used in data centers and consumer markets. Data centers generally choose to provide high-quality storage services by deploying a large number of SSDs, but there are no effective preventive measures to reduce the impact of SSD failures currently. Some existing studies have analyzed the relevant factors related to SSD failures from different angles, but the characteristics of reliability changes exhibited by SSD throughout the life cycle have not been explored in depth. On the other hand, although the 3D manufacturing process has increased the storage density of the SSD, the mutual influence between the flash units has also increased, resulting in severe degradation of the performance and lifetime of the SSD. Therefore, in order to fully understand the reliability varying process of SSD throughout the life cycle, we first designed an SSD lifetime endurance test method, then conducted the endurance test and collected the reliability data for the entire life cycle of the 3D TLC SSD in the laboratory environment with reference to the JEDEC standard. Through the analysis of experimental data and its statistical correlation, it is found that SSD will produce a large number of uncorrectable errors before reaching the endurance limit, and there will be a phenomenon of continuous high operating temperature, as well as showing some intrinsic relationships about SSD reliability data. The findings in this paper are valuable for identifying whether an SSD is going to fail.
Deep Language Learning

Email: steven@siliconspeech.com Technology Is Transforming How Students Learn a Foreign Language In Star TrekTM and other science fiction, alien civilizations communicate via a universal translator that seamlessly translates from one tongue to another, making alien-language instruction superfluous. Unfortunately, such flawless universal translation is unlikely to arrive anytime soon (despite recent advances).
Exploring Characteristics for Effective EFL Teachers From the Perceptions of Junior High School Students in Tainan

The purpose of this study was to investigate junior high school students’ perceptions of the characteristics of effective English teachers. The focuses included: (1) junior high school students’ general perceptions about English teacher characteristics, (2) whether gender has an effect on the perceptions, and (3) whether students with different academic achievement perceive differently in terms of characteristics for effective English teachers. This study was conducted via a questionnaire with 198 junior high school students in Tainan area. The data came from students’ responses to a 50-item questionnaire, classifying into instructional competence, personality, and teacher-student relationship, and were analyzed with descriptive statistics, independent t-test and one-way ANOVA. The findings of the study indicated that students generally perceived teachers’ personality and