Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Agent Decision-Making Modes in Uncertain Interactive Traffic Scenarios via Graph Convolution-Based Deep Reinforcement Learning

As one of the main elements of reinforcement learning, the design of the reward function is often not given enough attention when reinforcement learning is used in concrete applications, which leads to unsatisfactory performances. In this study, a reward function matrix is proposed for training various decision-making modes with emphasis on decision-making styles and further emphasis on incentives and punishments. Additionally, we model a traffic scene via graph model to better represent the interaction between vehicles, and adopt the graph convolutional network (GCN) to extract the features of the graph structure to help the connected autonomous vehicles perform decision-making directly. Furthermore, we combine GCN with deep Q-learning and multi-step double deep Q-learning to train four decision-making modes, which are named the graph convolutional deep Q-network (GQN) and the multi-step double graph convolutional deep Q-network (MDGQN). In the simulation, the superiority of the reward function matrix is proved by comparing it with the baseline, and evaluation metrics are proposed to verify the performance differences among decision-making modes. Results show that the trained decision-making modes can satisfy various driving requirements, including task completion rate, safety requirements, comfort level, and completion efficiency, by adjusting the weight values in the reward function matrix. Finally, the decision-making modes trained by MDGQN had better performance in an uncertain highway exit scene than those trained by GQN.
The role of lung ultrasound in procalcitonin-guided antibiotic discontinuation in ventilator-associated pneumonia

Background and Aims: Starting antibiotic therapy at the proper time is the cornerstone of the management of ventilator-associated pneumonia (VAP). However, using antibiotics for a long duration of therapy in intensive care leads to increased bacterial resistance, financial burden and adverse drug reactions. We hypothesised that lung ultrasound may have a role in guiding antibiotic discontinuation in patients with VAP that will help to reduce the antibiotic duration and decrease the resistance. Methods: This was a prospective blinded cohort study from October 2020 to September 2021 in which 62 VAP patients were recruited. Antibiotics were started, procalcitonin (PCT) level and clinical pulmonary infection score were estimated and lung ultrasound (US) was performed on day 1 and repeated on day 7. On day 7, discontinuation of antibiotics was recommended if the PCT level was <0.25 μg/L. A lung reaeration score was recorded. Results: Based on the PCT levels, antibiotics were discontinued in 40 patients. The computed tomography findings of VAP had improved in all. The ultrasound reaeration score showed a highly significant negative correlation with the PCT on day 7 (-0.718, P < 0.001). A cut-off of 5 for the US score showed a sensitivity of 92.5%, specificity of 95.5%, positive predictive value of 97.4% and negative predictive value of 87.5% in detecting a low PCT score on day 7. Conclusion: Lung US is a non-invasive and safe method that can be used to guide antibiotic therapy in VAP.
Multiple Reference Frame Based Torque Ripple Minimization for PMSM Drive Under Both Steady-State and Transient Conditions

Torque ripple has been a critical issue for high-performance applications using permanent magnet synchronous machines (PMSMs). An efficient approach to minimize torque ripple is to control the stator current to follow an optimized current reference, which will produce an extra torque ripple to cancel the existing one. This paper proposes a multiple reference frame (MRF) based controller for torque ripple minimization (TRM), in which the measured speed ripple is explored as the feedback control signal. The proposed MRF-based controller consists of a TRM controller whose task is to find the optimal current reference and a current controller whose task is to control the actual current to follow the optimized current reference. In TRM controller, the control of reference current magnitude and phase angle is decoupled, and proportional integral (PI) controller is able to achieve TRM control. In current controller, MRF is adopted to convert harmonic current control into dc current control; thus, PI controller is able to achieve harmonic current control with the use of MRF. Compared with existing approaches, the proposed controller is capable of TRM under both steady-state and transient conditions. The proposed controller is experimentally evaluated on a laboratory PMSM drive system.
ANTIGONE: Accurate Navigation Path Caching in Dynamic Road Networks leveraging Route APIs

Navigation paths and corresponding travel times play a key role in location-based services (LBS) of which large-scale navigation path caching constitutes a fundamental component. In view of the highly dynamic real-time traffic changes in road networks, the main challenge amounts to updating paths in the cache in a fashion that incurs minimal costs due to querying external map service providers and cache maintenance. In this paper, we propose a hybrid graph approach in which an LBS provider maintains a dynamic graph with edge weights representing travel times, and queries the external map server so as to ascertain high fidelity of the cached paths subject to stringent limitations on query costs. We further deploy our method in one of the biggest on-demand food delivery platforms and evaluate the performance against state-of-the-art methods. Our experimental results demonstrate the efficacy of our approach in terms of both substantial savings in the number of required queries and superior fidelity of the cached paths.
Strategies for Retaining Key IT Professionals

Retaining IT professionals is a key and challenging issue for IT managers. There is no “silver bullet,” and retention actions must be tailored to the profile of each employee the organization wants to retain. IT professionals have different reasons for changing jobs, determined by their career goals, relationships within the organization and current attitude to the job. We show how IT employees can be classified into seven types and describe the retention actions that will work best for each type.
Battery energy storage integration via DC/AC converter in grid connected wind turbines

The growing need of battery energy storage to support the increase in renewable production in the electricity mix has brought the attention to the modular multilevel converter (MMC) for medium voltage applications. Modular multilevel converters have been verified as most promising battery interface as it has very high efficiency, excellent AC waveforms, scalable and modular structure and it allows for the use of low rating semiconductors. In addition it provides redundancy due to the ability of distributing the batteries into each submodule. A drawback with the MMC, is that when half-bridge submodules are used, the converter cannot handle DC faults, hence it is necessary to understand the dynamics of the converter during various fault scenarios. In this thesis, a MMC interfacing a 1 MW battery to the grid is built in Matwork’s Matlab/Simulink. Both the converter and control system are evaluated and designed to evaluate post-fault currents and voltages. The converter was designed with a DC voltage of 15 kV and five submodules in each arm. The degree of complexity chosen for this model is the submodule level switched model type, including IGBT, reverse diodes and SM capacitors. A high carrier frequency and phase-shifted pulse-width modulation eliminate the need of submodule energy balancing. Five short circuit fault locations have been investigated, two inside the submodule, over one arm, on the DC link and between two phases on the AC side of the converter. No fault handling strategies, AC or DC breakers are implemented in the model. The simulation of short circuit faults inside the submodules reviled that five submodules are not enough to ensure redundancy. The importance of developing fast responding DC breakers was demonstrated as the upper converter arm on phase a was short-circuited. As this fault only includes one phase, the first post fault zero-crossing appears too late to prevent damage on the converter. DC breakers are also necessary to prevent the extremely high discharge current from the battery to the fault during the short circuit fault on the DC link. During the short circuit fault between two phases, all semiconductors will be damaged by the large current if no fault handling is applied, but on the other hand the zero-crossing appears fast enough to isolate the converter from the grid before the damage is done. The most critical faults are the short circuit faults across one arm and across the DC link because they both requires DC circuit breakers, which is not yet commercialized.
Robustness Analysis of Sliding Mode on DC/DC for Fuel Cell Vehicle

The energy conversion efficiency of fuel cell electric vehicle is high. However, the output characteristics of the current fuel cell tend to be weak and the output voltage fluctuation is apparent, so the DC/DC converter is used for voltage matching and transformation. Through the study on the characteristics of fuel cell in this paper, the main function and topology structure of the on-board DC/DC converter in fuel cell electric vehicle is introduced and the sliding mode control structure is established according to sliding mode control theory. The simulation of the sliding mode controller is performed by MATLAB. The simulation results show that, under the changes in input voltage and load, the fast response and stable output of the on-board DC/DC converter in fuel cell electric vehicle can be realized.
Evaluation of New Polyclonal Antibody Developed for Serological Diagnostics of Tomato Mosaic Virus

Plant viruses threaten agricultural production by reducing the yield, quality, and economical benefits. Tomato mosaic virus (ToMV) from the genus Tobamovirus causes serious losses in the quantity and quality of tomato production. The management of plant protection is very difficult, mainly due to the vector-less transmission of ToMV. Resistant breeding generally has low effectiveness. The most practical approach is the use of a rapid diagnostic assay of the virus’ presence before the symptoms occur in plants, followed by the eradication of virus-infected plants. Such approaches also include serological detection methods (ELISA and Western immunoblotting), where antibodies need to be developed for an immunochemical reaction. The development and characterization of polyclonal antibodies for the detection of ToMV with appropriate parameters (sensitivity, specificity, and cross-reactivity) were the subjects of this study. A new polyclonal antibody, AB-1, was developed in immunized rabbits using the modified oligopeptides with antigenic potential (sequences are revealed) derived from the coat protein of ToMV SL-1. the developed polyclonal antibody. AB-1, showed higher sensitivity when compared with commercially available analogs. It also detected ToMV in infected pepper and eggplant plants, and detected another two tobamoviruses (TMV and PMMoV) and ToMV in soil rhizosphere samples and root residues, even two years after the cultivation of the infected tomato plant.
Influence of input power mismatch on time domain detection of solitonic components

The capacity of fiber optic transmission links is limited by nonlinearities due to the Kerr effect. Recently a new type of communication based on the Nonlinear Fourier Transform, which is offering the use of two types of spectra, a continuous one and a discrete one, was proposed. Coherent optical receivers are the enabler for this communication scheme as an extension of former eigenvalue communication using direct detection. A prerequisite of the theory is a lossless fiber channel. To cope with varying power along the real fiber link the path average method was introduced. Using the average gain along the fiber and its local deviation a correction coefficient for the nonlinear effects in the fiber is calculated. Nevertheless the sensitivity to input power mismatch is expected to be high. Therefore as a reference a 2 dimensional modulation format using a single eigenvalue with different magnitudes and phases of the discrete spectral amplitude is transmitted over 2639km and detected in time domain to prove the feasibility of this detection scheme with a BER of 6.1 10(exp -5) and give a reference for future nonlinear Fourier domain detection. A comparison with a short range pure NFT detection after 754 km do not exhibit such a strong input power dependence providing acceptable bit error rates.
Insulation protection and online stress agent identification for electric machines using artificial intelligence

Insulation failures are among the most important problems affecting electric machines. Although standard procedures are widely used to assess the insulation condition of these machines, no alternative is available to allow the identification of the stress agents affecting the insulation system. Another limitation of the standard procedures is the fact that they are based on tests that require the interruption of the operation of the machine. This study presents a technique that allows the online assessment and protection of the insulation of low- and medium-voltage electric machines, along with the identification of the stress agents responsible for the degradation of the insulation. The proposed technique is based on the use of a highly sensitive current transformer, an algorithm to identify the most affected phase, and an artificial neural network to indicate the stress agent affecting the machine. The presented experimental results show that the proposed system can identify thermal degradation, moisture absorption and contamination by oil. The low current levels that can be measured by the developed system enable the application of the proposed technique to low- and medium-voltage machines.
Carbon Footprint Modeling of a Clinical Lab

Modeling of a clinical lab carbon footprint is performed in this study from the aspects of electricity, water, gas consumption and waste production from lab instruments. These environmental impact indicators can be expressed in the form of the CO2 equivalent. For each type of clinical test, the corresponding consumption of energy resources and the production of plastics and papers are taken into consideration. In addition, the basic lab infrastructures such as heating, ventilation, air-conditioning (HVAC) systems, lights, and computers also contribute to the environmental impact. Human comfort is to be taken into account when optimizing the operation of lab instruments, and is related to the operation of HVAC and lighting systems. The detailed modeling takes into consideration the types of clinical tests, operating times, and instrument specifications. Two ways of disposing waste are classified. Moreover, the indoor environment is modeled. A case study of the Biochrom 30+ amino acid analyzer physiological system in Alder Hey Children’s Hospital is carried out, and the methods of mitigating the overall environmental impacts are discussed. Furthermore, the influence of climate on the results is investigated by using the climate data in Liverpool and Athens in October.
Global Fault-Tolerant Control of Underactuated Aerial Vehicles with Redundant Actuators

In this paper, we consider the fault-tolerant control problem for aerial vehicles with redundant actuators. The redundant actuator brings difficulty in fault identification and isolation. Active fault-tolerant control is adopted in this paper as it can detect actuator fault. The entire proposed fault-tolerant control algorithm contains a baseline controller, the fault detection and isolation scheme, and the controller reconstruction module. A robust parameter identification method is designed to identify the torque and thrust generated by the actuators. The feasibility of isolating the fault for the redundant actuators is analyzed through mathematical proof. Through the analysis, the practical fault isolation algorithm is also proposed. Two typical aerial vehicles with redundant actuators, an eight-rotor aircraft and a hexa-rotor aircraft, are adopted in numerical simulations to verify the effectiveness of the proposed fault-tolerant control approach.
Estimation non paramétrique adaptative pour les chaînes de Markov et les chaînes de Markov cachées

Dans cette these, on considere une chaine de Markov $(X_i)$ a espace d'etats continu que l'on suppose recurrente positive et stationnaire. L'objectif est d'estimer la densite de transition $\Pi$ definie par $\Pi(x,y)dy=P(X_{i+1}\in dy|X_i=x)$. On utilise la selection de modeles pour construire des estimateurs adaptatifs. On se place dans le cadre minimax sur $L^2$ et l'on s'interesse aux vitesses de convergence obtenues lorsque la densite de transition est supposee reguliere. Le risque integre de nos estimateurs est majore grâce au controle de processus empiriques par une inegalite de concentration de Talagrand. Dans une premiere partie, on suppose que la chaine est directement observee. Deux estimateurs differents sont presentes, l'un par quotient, l'autre minimisant un contraste moindres carres et prenant egalement en compte l'anisotropie du probleme. Dans une deuxieme partie, on aborde le cas d'observations bruitees $Y_1,\dots, Y_{n+1}$ ou $Y_i=X_i+\varepsilon_i$ avec $(\varepsilon_i)$ un bruit independant de la chaine $(X_i)$. On generalise a ce cas les deux estimateurs precedents. Des simulations illustrent les performances des estimateurs.
An Q‐factor calibration method for compensation of the I/Q signal imbalances in 5–6 GHz beamforming receiver

This article presents 5–6 GHz beamforming receiver with Q‐factor calibrated vector modulator to reduce phase error and amplitude mismatch. Q‐factor of vector modulator IQ network has to be 0.95–1.05 in 5–6 GHz to get under ±3° phase error. Proposed Q‐factor calibration circuit selects the best capacitance and resistance for proper Q‐factor in desired frequency range. Beamforming receiver prototype, which is implemented in 0.13‐μm CMOS, has 0.98–1.03 Q‐factor in 5–6 GHz. The prototype has improved performance than without calibration: its rms phase error is maximum 1.5° (4.5° improved), and amplitude mismatch is maximum 0.47 dB (0.73‐dB improved). In addition, noise figure is 3.8–4.6 dB at 5–6 GHz.
How to Beat Restrictions Imposed by no-Cloning Theorem and Relativity Theory?

We suggest a way to produce any number of clones of an unknown quantum state. We also suggest a way to transmit information from one place to other far away place exactly and almost instantaneously. This paper thus aims to suggest a method to produce “more than one clone” and a method to achieve “instantaneous and exact information transfer”.
Printed-Circuit Monopole Antenna for Super-Wideband Applications

A novel super-wideband (SWB) antenna is presented. It is designed in microstrip technology based on planar monopole antenna theory. In order to achieve acceptable high-frequency return loss, a gap is added between the radiator and the ground plane, and the microstrip line is narrowed down at the feeding point. The prototype is fabricated on standard Rogers 5880 substrate with thickness of 0.254 mm and εr = 2.2. Measurements of the return loss up to 110 GHz and measured patterns and gain up to 40 GHz show good agreement with results from full-wave simulations.
Distance Learning During COVID-19: EFL Students’ Engagement and Motivation from Teachers’ Perspectives

The present mixed-method study aimed to explore 114 female secondary-level English teachers’ perceptions of the effectiveness of distance education in public schools in the Kingdom of Saudi Arabia during COVID-19 using a Google Forms questionnaire. Additionally, the challenges teachers faced in distance education and their attitudes toward teacher-training programs during the pandemic were investigated in semi-structured interviews. The findings indicated an overall positive view toward the effectiveness of distance education. However, the interviewed participants expressed their preference for traditional in-class teaching due to their familiarity with it compared to distance teaching. Online classes gave students the opportunity to become more actively engaged. Distance education was also found to promote students’, especially shy students, motivation for learning and participating in class activities. Teachers indicated some challenges in distance teaching, such as a lack of internet connection and human interaction, technical issues, assessment reliability, increased workload, and students’ unwillingness to learn. Finally, recommendations for more effective distance education were provided, namely, technological and pedagogical training for teachers, the need for technical support, and proper training for students on online learning.
EFFECTS OF A SMALL-SIDED SOCCER PROGRAM ON HEALTH PARAMETERS IN OBESE CHILDREN

ABSTRACT Introduction: Childhood obesity is increasing and, as a consequence, it generates health complications resulting from sedentary behavior and low levels of physical fitness. There are few studies involving children, metabolic and cardiorespiratory profiles, and soccer. Objective: The purpose was to measure the effects of a 12-week recreational small-sided soccer program on cardiometabolic risk and individual responses to cardiometabolic risk factors in overweight or obese boys. Methods: Thirteen boys aged 8-12 years (34.9±11.6% body fat) participated in a 12-week recreational small-sided soccer training program with two 80-minute sessions per week at intensities over 80% of the maximal heart rate. Anthropometric characteristics, cardiorespiratory fitness, metabolic profile, individual responses to peak oxygen uptake (VO2peak), maximal workload (Wmax), fasting blood glucose, insulin, HOMA-IR, LDL-C, HDL-C, TC, and TG were measured both pre- and post-training. Results: Considering the individual responses of the participants, recreational soccer training was effective in improving variations in maximum power and exhaustion time, as well as promoting at least one beneficial change in cardiometabolic risk factors in 84% of the overweight or obese children. There were no differences between pre- and post-program anthropometric characteristics, metabolic profiles, or VO2peak values. Conclusion: Twelve-week recreational small-sided soccer programs were able to improve maximal power and anaerobic capacity and maintain cardiometabolic risk factor levels in overweight and obese boys. Level of evidence I; High-quality prospective study (all patients were enrolled at the same stage of disease, with >80% of patients enrolled) .