Miracle-dz/UniFAR-FTUs huggingface dataset:
Abstract—Continuous and unobtrusive blood pressure (BP) monitoring provides significant advantages in predicting the onset of cardiovascular disease. Bio-impedance sensing is a prominent method for continuous BP monitoring in a wearable form factor that can effectively measure blood pulsations

Continuous and unobtrusive blood pressure (BP) monitoring provides significant advantages in predicting the onset of cardiovascular disease. Bio-impedance sensing is a prominent method for continuous BP monitoring in a wearable form factor that can effectively measure blood pulsations from the arteries and translate them into BP. However, assessing the quality of the bio-impedance signal captured from small electrodes placed on the skin is required to determine the accuracy of BP estimation. In wearable devices, frequent movements of the electrodes on the skin are expected which cause non-optimal contact quality between the electrodes and the skin. This can lead to high skin-electrode impedance which can cause saturation of the current injection module of the bioimpedance device. This phenomenon degrades the signal quality In this paper, we present an automatic gain control (AGC) circuit that controls the amplitude of the current injection into the body based on sensing the skin-electrode impedance to ensure injection of maximum current to maximize the signal-tonoise ratio (SNR) while avoiding saturation of the current injection module. In this work, the proposed AGC method shows higher quality of blood pulsation from bio-impedance signal measured from a human subject with 1.59 dB improvement in SNR which leads to a better estimation of blood pressure. Clinical Relevance— The proposed automatic gain control (AGC) circuit establishes a more accurate method of continuous blood pressure monitoring using bio-impedance.
Validation of Spectral Indices of Electrodermal Activity with a Wearable Device

Electrodermal activity (EDA) has been found to be a highly sensitive, accurate and non-invasive measure of the sympathetic nervous system’s activity and has been used to extract biomarkers of various pathophysiological conditions including stress, fatigue, epilepsy, and chronic pain. Recently, various robust signal processing techniques have been developed to obtain more reliable and accurate indices that capture the meaningful characteristics of the EDA using data collected from laboratory-scale devices. However, EDA also has the potential to monitor such physiological conditions in active ambulatory settings, for which the developed tools must be deployed in wearable devices. In this paper, we studied the feasibility of obtaining the highly-sensitive spectral indices of EDA using a wearable device. EDA signals were collected from left hand fingers using a wearable device and a laboratory-scale reference device, while N=18 subjects underwent the Head up Tilt test and the Stroop test to stimulate orthostatic and cognitive stress, respectively. We computed two time-domain indices, the skin conductance level (SCL) and nonspecific skin conductance responses (NS.SCRs), and two spectral indices, the normalized sympathetic components of the EDA (EDASympn), and the time-varying EDA index of sympathetic control (TVSymp). The results showed similar performances for EDASympn and TVSymp indices across both devices. While spectral indices obtained from both devices performed similarly in response to orthostatic and cognitive stress, time-domain exhibited large variation when obtained by the wearable device. Further research is required to develop and refine such devices, as well as the indices used to analyze EDA results.Clinical Relevance— This study proves the feasibility of obtaining spectral indices of EDA using a wearable device, which can be used to develop wearable tools to detect pain, stress, fatigue, between others
Comparison of Machine Learning Classifiers for Reducing Fitness Evaluations of Structural Optimization

Metaheuristic algorithms have been widely used to solve structural optimization problems. Despite their powerful search capabilities, these algorithms often require a large number of fitness evaluations. Constructing a machine learning classifier to identify which individuals should be evaluated using the original fitness evaluation is a great solution to reduce the computational cost. However, there is still a lack of a thorough comparison between machine learning classifiers when integrating into the optimization process. This paper aims to evaluate the efficiencies of different classifiers in eliminating unnecessary fitness evaluations. For this purpose, the weight optimization of a double-layer grid structure comprising 200 members is used as a numerical experiment. Six machine learning classifiers selected for assessment in this study include Artificial Neural Network, Support Vector
Statistical Modeling to Forecast Odor Levels of Biosolids Applied to Reuse Sites

Proper use or disposal of wastewater solids is an important responsibility of wastewater treatment plants. At present, there are several options for wastewater solids, including agriculture, forestry, and mine reclamation reuse; production of marketable products such as compost and dried pellets; and disposal in landfills and incinerators. Land application of biosolids products is beneficial as part of recycling efforts on local farms, forests, tree farms, and mines and has gained greater acceptance of late. Coupled with these beneficial aspects are odors, which must be managed relative to the receiving populations. In this paper we present several statistical models that predict biosolids odor levels based on processing and management variables as well as ambient conditions. Such models are useful to managers at advanced wastewater treatment plants in helping them to better forecast the biosolids odors and minimize the "odor footprint," thus making these biosolids products better received.
Convex Optimization for Spring Design in Series Elastic Actuators: From Theory to Practice

Natural dynamics, nonlinear optimization, and, more recently, convex optimization are available methods for stiffness design of energy-efficient series elastic actuators. Natural dynamics and general nonlinear optimization only work for a limited set of load kinetics and kinematics, cannot guarantee convergence to a global optimum, or depend on initial conditions to the numerical solver. Convex programs alleviate these limitations and allow a global solution in polynomial time, which is useful when the space of optimization variables grows (e.g., when designing optimal nonlinear springs or co-designing spring, controller, and reference trajectories). Our previous work introduced the stiffness design of series elastic actuators via convex optimization when the transmission dynamics are negligible, which is an assumption that applies mostly in theory or when the actuator uses a direct or quasi-direct drive. In this work, we extend our analysis to include friction at the transmission. Coulomb friction at the transmission results in a non-convex expression for the energy dissipated as heat, but we illustrate a convex approximation for stiffness design. We experimentally validated our framework using a series elastic actuator with specifications similar to the knee joint of the Open Source Leg, an open-source robotic knee-ankle prosthesis.
FEATURES OF THE THEORY OF A TWO- MASS SYSTEM WITH A RIGIDLY CONNECTED END OF THE BRIDGE, IN CONSIDERATION OF SEISMIC INFLUENCE ON HIGH-SPEED RAILWAYS

Annotation. This article discusses a two-mass system with a rigid fixation of the end part (foundation) of the bridge on high-speed railways. The results of selecting the optimal parameters of dynamic vibration dampers (DVDs) for setting stiffness and damping in the case of a two-mass system with a rigidly fixed end part of the bridge are presented. It is shown that such a solution is recommended for the case when the bridge is located in a steep gorge, the intermediate supports are high and flexible, and the end supports are quite rigid, since they give the designer a wide opportunity to choose the dimensions and rigidity of the designed seismic protection elements.
Decolourization of Azo Dye Direct Blue 15 Using Batch Culture of Klebsiella sp.

Nowadays, the development of textile industries are mushrooming and the pollution resulting from the dye-wastewater is alarming. Colour is recognized as the first contaminant from the dye containing wastewater. The present study reports the decolourization of Direct Blue 15 by Klebsiella sp. , originated from textile wastewater plant. The important parameters, including co-substrates, aeration, starting pH of culture and temperature for decolourization, were investigated. Mechanism of colour removal either by bioadsorption or biodegradation was determined. Amongst the co-substrates, glucose (0.2% w/v) was the preferred co-substrate for decolourization of Direct Blue 15. The optimal decolourization occurred under partial anaerobic condition at starting pH of about 6.0. Decolourization of Direct Blue 15 was most efficient at 45 o C. Under the optimum conditions, it was found that the COD removal was 53.6%. Dye decolourization (81.9%) was successfully achieved within 24 hours; 0.03% was due to the bioadsorption and 81.87% was due to the biodegradation by Klebsiella sp. , while the product of degradation of azo dye, sulfanilic acid, was detected using HPLC.
Synthesizing Scene-Aware Virtual Reality Teleport Graphs (Supplementary Material)

1.1 Comparing SP Graphs with HOI Graphs While our definition of SP graphs are inspired by the notion of HOI graphs, we discuss two major differences in this section. First, in the HOI detection task, an image shows how people physically interact with objects from a third-person view. In an HOI graph, depending on the number of detected objects, there could be multiple human nodes and object nodes; and edges could be densely generated such that the whole graph is a complete graph. In contrast, in an SP graph, a panoramic image corresponds to the first-person view of an observer who does not explicitly show up in the image. Instead of modeling physical human-object contacts, we model the observer’s visual interaction with objects by perceiving his surroundings, which fits with our notion of scene perception. Therefore, edges are only generated for human-object pairs. Second, HOI graphs relies on visual features (e.g., visual representations of human gestures and object shapes) extracted from RGB images using convolutional neural networks to classify the types of interactive activities between people and objects. While visual features could capture low-level visual details, in SP graphs, we propose to use high-level semantic features, which allow our method to work in more general cases. In our implementation, we use the category features and depth features for general and robust representations of SP graphs.
A Comparison of Apparel Garment Prices By National, Retail, And Private Labels

Although it is generally acknowledged that brand name merchandise costs consumers more than private label merchandise, the reason for this difference is unclear. Are brand name items priced higher because they have different characteristics than private labels? Also, if items have similar characteristics, how much more do consumers pay for brand name merchandise? The purpose of this research was to examine the effect of brand name on the price of apparel while accounting for variations in product attributes. Based on the characteristics model of demand, a hedonic price equation was estimated using data collected on a sample of sweaters from moderately priced stores in a midwestern town. The results indicated that, while holding fiber content, styling, and country of origin constant, both national name brands and retail-store brands were priced higher, on average, than private labels. These results have implications for consumers and retailers. In particular, it may behoove private label retailers to augment their efforts to inform consumers about the attributes of their product relative to brand or retail-store names, given the price differential.
A discussion on the universality of inversion layer mobility in MOSFET's

An obvious discrepancy exists in published research results concerning the universality of MOS inversion layer electron mobility in nonuniform substrate doping profile cases. By thorough analysis of the data and the parameter extraction method, it is demonstrated that the discrepancy is simply due to the different definition of depletion layer charge and the invalid extraction of parameters from experimental data. Studies in this work show that inversion layer carrier mobility experiences the same universality feature in nonuniform doping substrates as in uniform ones.
A Scalable Readout IC Based on Wideband Noise Cancelling for Full-Rate Scanning of High-Density Microelectrode Arrays

This paper presents a highly scalable readout IC for high-density microelectrode arrays (MEAs). Although the recent development of large-scale high-density MEAs provides opportunities to achieve sub-cellular neural recording over a wide network area, it is challenging to implement the readout IC that can operate with such MEAs. The requirement of high-speed recording in large-scale arrays induces wideband-noise folding, which makes it challenging to achieve a good noise performance for high-fidelity neural recording. Moreover, for the wideband readout, the major noise contributor changes from the readout circuit to the cell-electrode interface. In this paper, we first show why the interface noise becomes the dominant noise source and elucidate its component that contributes the most: sealing resistance. Then, we propose a new readout circuit structure, which can effectively cancel the wideband interface noise. As a result, the signal-to-noise ratio of input neural spike signals is improved dramatically in all cell-attachment or sealing conditions. Particularly, it is shown that under weakly sealed conditions, the spikes can be detected only when the proposed wideband noise cancellation technique is applied.
Formulation of Factors Developing Social Entrepreneurial Intention of Students: (Grounded Theory Approach)

Citation:, Farshid Karimi Hesari , Alireza Rousta , Saeed Moradi, Formulation of Factors Developing Social Entrepreneurial Intention of Students: (Grounded Theory Approach)2021; 12(1): Abstract Introduction and objectives: The present study aims to investigate and formulate factors that develop the social entrepreneurial intention of tourism students. Methodology: Semi-structured in-depth interviews with two groups of university professors and industry practitioners were applied in order to gather data. To analyze the data, the qualitative approach of Grounded Theory was taken into account. Following the Charmaz’s (2006) method, Constructionist version of grounded theory including Initial and Focused coding and also following the Strauss and Corbin’s (1998) framework, the categories of Causal conditions, Context condition, Main phenomenon, Intervening condition, and Consequences were applied so as to present a new paradigmatic model. Results: According to the findings, applied and academic university education, perceived self-efficacy, cultural empathy, attitude towards social entrepreneurship, desirability, and feasibility are of the important causal factors for developing the social entrepreneurial intention of tourism students. Implication: Even though there are various intention models in the area of entrepreneurship literature, the variables introduced in the current study, cover their key variables holistically in a single model.
Men and Women With First Episode Psychosis Present Distinct Profiles of Social Cognition and Metacognition

Deficits in social cognition and metacognition impact the course of psychosis. Gender differences in social cognition and metacognition could explain heterogeneity in psychosis. 174 (58 females) patients with first-episode psychosis completed a clinical, neuropsychological, social cognitive and metacognitive assessment. Subsequent latent profile analysis split by gender yielded 2 clusters common to both genders, a specific male profile characterized by presenting jumping to conclusions and a specific female profile characterized by cognitive biases. Males and females in the homogeneous profile seem to have a more benign course of illness. Males with jumping to conclusions had more clinical symptoms and more neuropsychological deficits. Females with cognitive biases were younger and had less self-esteem. These results suggest that males and females may benefit from specific targeted treatment and highlights the need to consider gender when planning interventions.
Immune escape facilitation by mutations of epitope residues in RdRp of SARS-CoV-2

SARS-CoV-2 has considerably higher mutation rate. SARS-CoV-2 possesses a RNA dependent RNA polymerase (RdRp) which helps to replicate its genome. The mutation P323L in RdRp is associated with the loss of a particular epitope (321-327) from this protein which may influence the pathogenesis of the concern SARS-CoV-2 through the development of antibody escape variants. We consider the effect of mutations in some of the epitope regions including the naturally occurring mutation P323L on the structure of the epitope and their interface with paratope using all-atom molecular dynamics (MD) simulation studies. P323L mutations cause conformational changes in the epitope region by opening up the region associated with increase in the radius of gyration and intramolecular hydrogen bonds, making the region less accessible. Moreover, the fluctuations in the dihedral angles in the epitope:paratope (IgG) interface increase which destabilize the interface. Such mutations may help in escaping antibody mediated immunity of the host.
A COMPACT MICROSTRIP BANDSTOP FILTER

In this paper, a novel microstrip bandstop fllter by etching a square split ring in the center of microstrip line is proposed. Low insertion loss in the passband, high rejection level and integrated structure should be mentioned as advantages for this resonator. A transmission line model for this resonator is introduced and its resonant frequency is calculated analytically. Good agreement between the experimental results, full-wave simulation, transmission line model and analytical result has been achieved.
Extrusion Process Optimization for Soluble Dietary Fibers Production from Agrocybe Cylindracea Using Response Surface Methodology

Extrusion is an effective technology to increasing the contents of soluble dietary fibers (SDF). Response surface methodology (RSM) was applied to optimize operational parameters of extrusion. The determination coefficient (R2) was 0.80, and the results show that the regression models could explain the data variation and represent the actual relationships between the parameters and responses. The optimal operational parameters were: ratio of water 28%, zone temperature119.7 °C and rotation rate of screw 159.0 r/min. Under the optimal conditions, the maximum yield of SDF of 0.078 g/g in theory and 0.076 g/g in the experiment were obtained, with an increase of 15.1 % compared to the original yield (0.066 g/g) without extrusion process.
Analysis of the Effect of Wearing Extensible and Non-Extensible Lumbar Belts on Biomechanical Factors of the Sit-to-Stand Movement and Pain-Related Psychological Factors Affecting Office Workers with Low Back Pain

This study aimed to investigate the effects of wearing extensible and non-extensible lumbar belt (LB) on biomechanical factors of the sit-to-stand (STD) movement and pain-related psychological factors affecting office workers with low back pain. Among 30 office workers, 15 with low back pain (LBP) were assigned to the experimental group and 15 healthy adults were assigned to the control group. The participants performed STD movement in random order of three different conditions: without LB (Condition 1), with extensible LB (Condition 2), and with non-extensible LB (Condition 3). Biomechanical variables of STD movement in each condition were measured using a three-dimensional motion analysis system and force plate. Pain-related psychological factors were measured only in the experimental group. Among the biomechanical factors of STD movement, an interaction effect was found in the maximum anterior pelvic tilt angle and total-phase range of motion of the trunk (p < 0.05). Pain intensity, pain-related anxiety, and pain catastrophizing were decreased in the conditions with lumbar belts (Conditions 2 and 3) compared to the condition without LB (Condition 1) (p < 0.05). Extensible and non-extensible lumbar belts engender biomechanically beneficial effects during STD movement in both office workers with LBP and healthy office workers. Further, pain intensity, pain-related anxiety, and pain catastrophizing were decreased in office workers with LBP. Therefore, both types of extensible lumbar belts may be helpful in the daily life of patients with LBP and office workers.
Vigilance Estimating in SSVEP-Based BCI Using Multimodal Signals

Brain-computer interface (BCI) is a communication system that allows a direct connection between the human brain and external devices. With the application of BCI, it is important to estimate vigilance for BCI users. In order to investigate the vigilance changes of the subjects during BCI tasks and develop a multimodal method to estimate the vigilance level, a high-speed 4-target BCI system for cursor control was built based on steady-state visual evoked potential (SSVEP). 18 participants were recruited and underwent a 90-min continuous cursor-control BCI task, when electroencephalogram (EEG), electrooculogram (EOG), electrocardiography (ECG), and electrodermal activity (EDA) were recorded simultaneously. Then, we extracted features from the multimodal signals and applied regression models to estimate vigilance. Experimental results showed that the differential entropy (DE) feature could effectively reflect the change of vigilance. The vigilance estimation method, which integrates DE and EOG features into the support vector regression (SVR) model, achieved a better performance than the compared methods. These results demonstrate the feasibility of our methods for estimating vigilance levels in BCI.
Development of a Phase Lag Approach for the Numerical Evaluation of Unsteady Flows

The importance of the knowledge of the unsteady interaction physics in modern gas turbines has grown during the last years following the improvements of the design tools. The numerical simulation of the flow field inside the turbines could provide the required information during the design process, but any steady assumption must be discarded. In fact, the stator/rotor interaction is mainly a 3D unsteady phenomenon driven by the wake/shock/rotor interaction, the secondary flows development and chopping and the hot fluid redistribution on the rotating and stationary parts. A number of numerical methods have been proposed to threat the unsteady interaction on the stage interfaces and the periodic boundary conditions due to the different blade number of the compressor and turbine rows. In this paper, the most important methods for the unsteady stator/rotor interaction are described and commented. Furthermore, a new unsteady method based on the “phase lag” assumption is implemented in the in-house HybFlow code and applied on a 2D linear test case obtained from the CT3 test case, experimentally investigated at the von Karman Institut in the frame of EU funded TATEF2 project. The results obtained in the numerical analysis are reported and commented with respect to the experimental data.