Miracle-dz/UniFAR-FTUs huggingface dataset:
A wearable mechanism to assist the knee during the loading response

Exoskeletons are assistive devices that have been evolving in the last years, being mostly applied in the military, rehabilitation and ergonomics fields. In addition, they are also being used to increase the human endurance capabilities, by reducing the muscle fatigue and metabolic rate. The aim of this thesis was, in fact, to study a new design for a wearable and passive mechanism that solves those last aspects. In particular, the mechanism is intended to assist the knee during the loading phase of the human gait cycle. The state of art of such passive assistance is typically based on the use of springs (that store and release energy), while, here, a damping-based device was designed, being the damper mechanism responsible for dissipating energy. Moreover, the spring approach does not allow for an easy individual adaptability, as springs must be replaced. In contrast, the damper solution includes a regulator screw, facilitating customization. Two different solutions were thought and analyzed: a pneumatic one, and another based on a commercial damper. Only the last was further studied due to its higher potential of success. Before conceptualizing any device, it was necessary to analyze kinetic and kinematic data of the human gait, available in the literature. This data was used to estimate the required damping coefficient of the system, so it could mimic the human knee joint. Regarding the pneumatic solution, it was, first, designed as a pneumatic spring (stroke of 100mm and initial pressure of 6.9bar) and, afterwards, a simulation using Simulink was used to test the influence of the flow control valve. The simulation showed that the system provided a similar torque to the one produced by the muscles which support the knee. Although these results were promising, the system was not further investigated, due to possible leaks of air and overweight. For the other solution, a commercial rotary damper was selected, with 40Nm of maximum torque and low weight (352g). However, its damping characteristics had to be determined experimentally, as no complete datasheet was available. From the mathematical model obtained (damping coefficient as a negative exponential function of the angular velocity), it was concluded that the damper does not provide a similar torque to the knee one. Nevertheless, it can bring energetic reductions, only evaluated with future additional tests. Moreover, the mechanical components, and relevant electronic components, were selected. A 3D model was built in Solidworks and used to explain the device operation.
Toward a Calculable Standard Shunt for Current Measurements at 10 A and Up To 1 MHz

Electrical current shunts are widely used as a resistance standard in metrology laboratories and precision instruments with the aim of measuring a high level of alternative and direct currents (ac and dc) with high accuracy. These ac current sensors are characterized by a broadband operating frequency bandwidth and are commonly calibrated up to 100 kHz. The use of a current shunt requires the preliminary knowledge of its magnitude deviation from dc and phase angle according to the frequency. The determination of these parameters is challenging at high frequencies and for high levels of current: typically beyond 100 kHz and 1 zA. For a current level of 10 A, existing current shunts exhibit a strong variation in magnitude and phase. The best magnitude performances of 10-A current shunt standards published so far are limited to <inline-formula> <tex-math notation="LaTeX">$2~\mu \Omega /\Omega $ </tex-math></inline-formula> at 100 kHz. In this paper, we detail the theoretical basis of innovate shunts for current measurements from 50 mA to 10 A up to 1 MHz. The electrical modeling is valid from 50 mA to 10 A: only the <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {dc}}$ </tex-math></inline-formula> value must be changed to get the electromagnetic response of any shunt standards designed for this range of current levels. For a 10-A shunt standard, the relative deviation from dc obtained by calculation is less than 0.2 and <inline-formula> <tex-math notation="LaTeX">$20~\mu \Omega /\Omega $ </tex-math></inline-formula> in magnitude at 100 kHz and 1 MHz, respectively. The design as well as the electromagnetic modeling of the shunt is profoundly described in this paper.
SA-Loc: Scenario Adaptive Localization in Highly Dynamic Environment using Adversarial Regressive Domain Adaptation

Localization based on signals from cellular base stations (BSs) or WiFi access points is important particularly in urban environments where street canyon effects impair GPS reception. A popular implementation is based on fingerprinting, where associations between channel characteristics and location of a moving terminal (MT) are measured in a training phase, and later (in the testing of operating phase) used to localize an MT measuring a particular channel. This paper considers the combination of labeled and unlabeled channel state information (CSI) for such finger-printing based localization, in particular to account for the fact that moving objects like cars can change the CSI between training and testing. To enhance the robustness of the localization against these and other “unseen” scenarios, we propose a solution approach based on a deep domain adaptation (DA) framework. The proposed method contains an unsupervised domain adaptation regression and an adversarial training module. The first component aims to learn discriminative fingerprinting representations jointly with data collected from seen and unseen scenes. The second one alleviates the distribution divergence of fingerprints collected from seen and unseen scenes, which eventually enables effective knowledge transfer. Finally, we evaluate the performance of the proposed method in a challenging setup, the recently released dynamic scenario in the DeepMIMO dataset. The results demonstrate that the proposed method can provide robust and accurate location estimation over variable numbers of the time-varying scenarios, with superior performance over other compared methods.
Risk Factors for Nonalcoholic Fatty Liver Disease in Postmenopausal Women with Type 2 Diabetes Mellitus and the Correlation with Bone Mineral Density at Different Locations

Objective To explore the risk factors for nonalcoholic fatty liver disease (NAFLD) in postmenopausal women with type 2 diabetes mellitus (T2DM) and the correlation with bone mineral density (BMD) in different areas of the body. Methods A total of 434 postmenopausal women with T2DM were enrolled and categorized as 198 patients in the NAFLD group and 236 patients in the non-NAFLD group based on color Doppler ultrasound of the liver. The BMD of the lumbar spine, femoral neck, and total hip were measured by dual-energy X-ray absorptiometry. Results In postmenopausal women with T2DM, the prevalence of NAFLD was 45.6%. The body mass index (BMI), systolic blood pressure (SBP), glycosylated hemoglobin (HbA1c), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), triacylglycerol (TG), uric acid (UA), and homeostatic model assessment for insulin resistance (HOMA-IR) C-peptide (CP) were significantly higher in the NAFLD group than in the non-NFALD group, and the duration of diabetes, and high-density lipoprotein cholesterol (HDL-C) were lower than in the non-NAFLD group (P < 0.05). Logistic regression analysis revealed that BMI (odds ratio [OR] = 1.303, 95% confidence interval [CI]: 1.152–1.346), HbA1c (OR = 1.263, 95% CI: 1.095–1.392), TG (OR = 1.263, 95% CI: 1.031–1.601), and SUA (OR = 1.005, 95% CI: 1.001–1.007) were correlated with NAFLD (P < 0.05). The BMD of the total hip and femoral neck in the NAFLD group was higher than in the non-NAFLD group (P < 0.05). Conclusion Complicated NAFLD in postmenopausal women with T2DM is associated with weight gain, poor blood glucose control, abnormal lipid metabolism, and elevated UA levels. In addition, the NAFLD group had higher femoral neck and total hip BMD than the non-NAFLD group, suggesting NAFLD in postmenopausal women with T2DM may reduce the risk of osteoporosis.
Influence of Circulation Patterns on The Visitor Distribution in A Shopping Mall Case Study Palembang Icon Shopping Center, Palembang City

Physiological needs are the most basic human needs. Shopping is one of the measures to fulfill physiological needs, such as clothing, foods, and drinks. Most people prefer to shop in shopping centers as it is more convenient and secure due to its regular spatial pattern, forming a good circulation pattern for their visitors. Palembang Icon is a shopping center in Palembang, located on Jl. POM IX, Lorok Pakjo, Ilir Barat I District, Palembang City, South Sumatra which considered has a good circulation pattern. Palembang Icon has a mall circulation pattern, namely a linear circulation pattern, one lane intended so that all retailers get a strategic place and the circulation orientation becomes clear. This research discusses the Palembang Icon shopping center's circulation pattern and analyzes its influence on the distribution of visitors by using the space syntax method with simulation using the DepthMapX application. The result shows that the circulation space's shape is closed, and the configuration of the circulation path is entirely a linear circulation pattern.
Structure Elucidation, Hirshfeld Surface Analysis, Molecular Docking and Computational Studies of a Jahn-Teller Distorted Octahedral Cobalt (II) Complex with Saccharin Ligand

Abstract A Jahn-Teller distorted octahedral cobalt(II) complex with saccharin and water ligands was synthesized and characterized using single-crystal X-ray diffraction, density functional theory calculation, surface analysis (MEP and Hirshfeld) and molecular docking studies. Co(II) center is six-coordinated in a distorted octahedral arrangement, with the two water O atoms located in the axial positions, and the two water O atoms and the saccharin N atoms located in the equatorial plane. Theoretical molecular modeling was carried out with Density Functional Theory (DFT) using UB3LYP with hybrid function LANL2DZ. To support intra-molecular and inter-molecular bondings in crystal structure, molecular electrostatic potential (MEP) and Hirshfeld surfaces are generated and visualized. The molecular docking analysis was investigated between cobalt complex ligand and the receptor of breast cancer mutant PDB: 3HB5-oxidoreductase.
Thermal and Electrical Energy Converters and Interfaces for the Internet of Humans

The emerging Internet of Humans (IoH) can shape future healthcare and consumer devices. The energy supply of IoH devices and unobtrusive interfacing with the human body remain fundamental challenges yet to be resolved. To address these obstacles, this work investigates thermal energy harvesting of body heat and soft thermal and electric skin interfaces. The thermal harvesting potential of the human body is assessed over the mechanisms of heat generation and thermoregulation. Experimental verification is provided through a user study with 56 participants. The study demonstrates that 2 mW cm−2 to 40 mW cm−2 of thermal energy are available for harvesting, depending on the subject, body location, environment, and activity. A significant decrease of thermal energy with age is observed and can be correlated to an increase in thermal skin resistance. To access the available energy, three wearable thermoelectric energy converters for different IoH applications are presented. A user-centered design approach, incorporating the complete pathway from body core to application, is pursued to combine performance with wearability. Special attention is paid to the critical interaction between thermal and electric energy conversion. A miniaturized thermal harvester for IoH sensor nodes generates μW, a wristband harvester supplying a multi-sensor bracelet hundreds of μW and a forehead harvester designed for a medical wearable mW of power. With a power density of 18.75 μW cm−3 at room temperature, the forehead harvester delivers the highest power output per volume compared to existing systems and demonstrates that wearability can be drastically improved without compromising the performance. The wearability and performance of body heat harvesters is also defined by the thermal interfaces with the skin and the environment. A soft composite of silver particles and PDMS (Ag = 25 vol.%, λ = 1.42 W m−1 K−1) improves the comfort of skin interfaces without considerable power losses by adopting to the irregular body surface. A heat sink incorporating biomimetic microactuators with high temperature sensitivity (SD = 0.053 K−1) extends the applicable temperature range of thermal harvesters by dynamically changing the thermal interface resistance to the ambient. Lastly, to interface the human body electrically, soft, skin-conformal, and selfadhesive biopotential electrodes are presented. The dry skin interfaces show similar or superior performance in terms of skin-contact impedance (47 kΩ cm2) and motion artifact rejection (RMS = 30 μV) as compared to clinical standard gel elec-
Exploratory text data analysis for quality hypothesis generation

Abstract Freestyle text data such as surveys, complaint transcripts, customer ratings, or maintenance squawks can provide critical information for quality engineering. Exploratory text data analysis (ETDA) is proposed here as a special case of exploratory data analysis (EDA) for quality improvement problems with freestyle text data. The EDTA method seeks to extract useful information from the text data to identify hypotheses for additional exploration relating to key inputs or outputs. The proposed four steps of ETDA are: (1) preprocessing of text data, (2) text data analysis and display, (3) salient feature identification, and (4) salient feature interpretation. Five examples illustrate the methods.
Case Report: Pulmonary Tuberculosis Reactivation in Patients with Human Immunodeficiency Virus: A Case Report

We present one case of co-infection with Mycobacterium tuberculosis (MTB) in a patient with Human Immunodeficiency Virus (HIV). It`s a case of a 27-year-old woman admitted at the Clinical Hospital of Infectious Disease and Pneumology ”Dr. Victor Babeș” Timișoara. The patient was known to be HIV-positive since 2019 and developed pulmonary tuberculosis during the therapy. The patient was non-compliant at antiretroviral therapy and developed pulmonary tuberculosis first time in December 2020. One year later, the same patient was admitted in the hospital with pulmonary manifestations and a reactivation of pulmonary tuberculosis was once again confirmed.
Sensorless Maximum Power Extraction Control of a Hydrostatic Tidal Turbine Based on Adaptive Extreme Learning Machine

In this paper, a hydrostatic tidal turbine (HTT) is designed and modeled, which uses more reliable hydrostatic transmission to replace existing fixed ratio gearbox transmission. The HTT dynamic model is derived by integrating governing equations of all the components of the hydraulic machine. A nonlinear observer is proposed to predict the turbine torque and tidal speeds in real time based on extreme learning machine (ELM). A sensorless double integral sliding mode controller is then designed for the HTT to achieve the maximum power extraction in the presence of large parametric uncertainties and nonlinearities. Simscape design experiments are conducted to verify the proposed design, model, and control system, which show that the proposed control system can efficiently achieve the maximum power extraction and has much better performance than conventional control. Unlike the existing works on ELM, the weights and biases in the ELM are updated online continuously. Furthermore, the overall stability of the controlled HTT system including the ELM is proved and the selection criteria for ELM learning rates are derived. The proposed sensorless control system has prominent advantages in robustness and accuracy, and is also easy to implement in practice.
The Impact of Pedagogical Agents' Gender on Academic Learning: A Systematic Review

Virtual learning environments often use virtual characters to facilitate and improve the learning process. These characters, known as pedagogical agents, can take on different roles, such as tutors or companions. Research has highlighted the importance of various characteristics of virtual agents, including their voice or non-verbal behaviors. Little attention has been paid to the gender-specific design of pedagogical agents, although gender has an important influence on the educational process. In this article, we perform an extensive review of the literature regarding the impact of the gender of pedagogical agents on academic outcomes. Based on a detailed review of 59 articles, we analyze the influence of pedagogical agents' gender on students' academic self-evaluations and achievements to answer the following questions: (1) Do students perceive virtual agents differently depending on their own gender and the gender of the agent? (2) Does the gender of pedagogical agents influence students' academic performance and self-evaluations? (3) Are there tasks or academic situations to which a male virtual agent is better suited than a female virtual agent, and vice versa, according to empirical evidence? (4) How do a virtual agent's pedagogical roles impact these results? (5) How do a virtual agent's appearance and interactive capacities impact these results? (6) Are androgynous virtual agents a potential solution to combatting gender stereotypes? This review provides important insight to researchers on how to approach gender when designing pedagogical agents in virtual learning environments.
An improved Dueling Deep Q-network with optimizing reward functions for driving decision method

Aiming at poor effects and single consideration factors of traditional driving decision-making algorithm in high-speed and complex environment, a method based on improved deep reinforcement learning (DRL) is proposed in this paper. We innovatively design and optimize the reward function of the Dueling Deep Q network (Dueling DQN), and the factors such as safety, comfort, traffic efficiency and altruism are taken into account. The weight of each influencing factor is determined by the Analytic Hierarchy Process (AHP), which makes the influence of each factor on driving behavior decision-making more acceptable. Subsequently, a decision-making model of autonomous vehicles (AVs) is built by using improved Dueling DQN. Furthermore, the action space is enriched and combined with the trajectory planner, so that AVs can take appropriate behaviors in the longitudinal and lateral directions according to the environment. The output of the decision model can be combined with the underlying controller with a view to make the AVs maneuver reasonably. The driving decision-making method in two different traffic scenarios is simulated. Moreover, the improved method compares with other methods. The results illustrate that the improved Dueling DQN can make the AVs take safe, comfortable, efficient, and altruistic behavior.
Optimising Cloud Data Storage with Secure and Reliable Source Side Deduplication

: loud computing is an prevalent data interactive paradigm for processing of large amounts of data and storage without considering the local infrastructure limitations. The advent of cloud storage enables the organizations and enterprises to outsource their data to third party cloud service providers (CSP). Though the services provided by Cloud has many advantages, the users voluntarily give up the physical possession of their outsourced data which inevitably poses new security and privacy risks and yet another challenge is the management of ever increasing volume of data for CSP. In order to deal with these security issues, a new secure storage with deduplication scheme has been adopted. In order to provide security of outsourced data against malicious users and curious CSP’s, a new convergent encryption technique is proposed. Every Client encrypts the file before uploading and the encrypted file is input to Hash algorithm which generates a unique identifier for every file. The Client specifies the authorized users and their access rights in a metafile uploaded to the cloud and user can decrypt the downloaded file with his secret key.
Compact Shortwave Infrared Imaging Spectrometer Based on a Catadioptric Prism

This article demonstrates a compact prism imaging spectrometer method. A catadioptric curved prism is located at the secondary mirror position of the spectrometer and used to balance the aberrations, enlarge the dispersion width, and decrease the volume. A mathematical model of the prism and spectrometer is derived, which provides an optimal initial structure for a non-coaxial spectrometer, simplifying the optical design process and reducing the system volume. Using this method, a compact shortwave infrared imaging spectrometer with a 16° field of view is designed with an F-number/3, and the measured spectrum ranges from 0.95 to 2.5 μm. The performance is analyzed and evaluated. Laboratory testing results prove the excellent optical performance, and under the same specifications, the spectrometer length decreases by 40%.
AN EXPERIMENT ON THE LIMITS OF QUANTUM ELECTRO-DYNAMICS

The limitations of previously performed or suggested electrodynamic cutoff experiments are reviewed, and an electron-electron scattering experiment to be performed with storage rings to investigate further the limits of the validity of quantum electrodynamics is described. The foreseen experimental problems are discussed, and the results of the associated calculations are given. The parameters and status of the equipment are summarized. (D.C.W.)
Optimization and Evaluation of Sensor Angles for Precise Assessment of Architectural Traits in Peach Trees

Fruit industries play a significant role in many aspects of global food security. They provide recognized vitamins, antioxidants, and other nutritional supplements packed in fresh fruits and other processed commodities such as juices, jams, pies, and other products. However, many fruit crops including peaches (Prunus persica (L.) Batsch) are perennial trees requiring dedicated orchard management. The architectural and morphological traits of peach trees, notably tree height, canopy area, and canopy crown volume, help to determine yield potential and precise orchard management. Thus, the use of unmanned aerial vehicles (UAVs) coupled with RGB sensors can play an important role in the high-throughput acquisition of data for evaluating architectural traits. One of the main factors that define data quality are sensor imaging angles, which are important for extracting architectural characteristics from the trees. In this study, the goal was to optimize the sensor imaging angles to extract the precise architectural trait information by evaluating the integration of nadir and oblique images. A UAV integrated with an RGB imaging sensor at three different angles (90°, 65°, and 45°) and a 3D light detection and ranging (LiDAR) system was used to acquire images of peach trees located at the Washington State University’s Tukey Horticultural Orchard, Pullman, WA, USA. A total of four approaches, comprising the use of 2D data (from UAV) and 3D point cloud (from UAV and LiDAR), were utilized to segment and measure the individual tree height and canopy crown volume. Overall, the features extracted from the images acquired at 45° and integrated nadir and oblique images showed a strong correlation with the ground reference tree height data, while the latter was highly correlated with canopy crown volume. Thus, selection of the sensor angle during UAV flight is critical for improving the accuracy of extracting architectural traits and may be useful for further precision orchard management.