Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Relationship between Faith and Spiritual Health on Controlling Stress in Female Students in District 4 of Tehran

Article Type Analytical Review Purpose: One of the problems of the present age is stress among human beings, which will cause many problems in human life, to the extent that psychological stress has been called the disease of the new civilization. This study was conducted to determine the relationship between faith and spiritual health with stress control in female students. Materials and Methods: This was a descriptive-correlational study. The statistical population of the study included all female high school students in Tehran in 2018. Using cluster random sampling method, 250 people were selected and completed the religious faith questionnaire [1], the spiritual health questionnaire [2] and the perceived stress questionnaire [3]. In order to predict the contribution of stress management data using descriptive statistics, Pearson correlation coefficient and multivariate regression were analyzed simultaneously using SPSS version 26. Findings: The average age of female students participating in the study was 15.67 to 18.76 years. The results showed that there is a negative and significant relationship between spiritual health and its dimensions including existential health and religious health with perceived stress in female students (P <0.05). There was a negative and significant relationship between faith and perceived stress (P <0.05). Also, simultaneous regression analysis showed that the predictor variables together were able to explain 39% of the variance of the stress inhibition score. Conclusion: According to the results, it is recommended that schools and institutions that deal with adolescents in the form of educational-recreational programs to strengthen religious beliefs and spirituality. Aurhors Fatemeh Khosravi*,
Design and Evaluation of Digital Filters for Non-Contact Measuring of HRV using Medical Radar and Its Application in Bedside Patient Monitoring System

A non-contact bedside monitoring system using medical radar is expected to be applied to clinical fields. Our previous studies have developed a monitoring system based on medical radar for measuring respiratory rate (RR) and heart rate (HR). Heart rate variability (HRV), which is essentially implemented in advanced monitoring system, such as prognosis prediction, is a more challenging biological information than the RR and HR. In this study, we designed a HRV measurement filter and proposed a method to evaluate the optimal cardiac signal extraction filter for HRV measurement. Because the cardiac component in the radar signal is much smaller than the respiratory component, it is necessary to extract the cardiac element from the radar output signal using digital filters. It depends on the characteristics of the filter whether the HRV information is kept in the extracted cardiac signal or not. A cardiac signal extraction filter that is not distorted in the time domain and does not miss the cardiac component must be adopted. Therefore, we focused on evaluating the interval between the R-peak of the electrocardiogram (ECG) and the radar-cardio peak of the cardiac signal measured by radar (R-radar interval). This is based on the fact that the time between heart depolarization and ventricular contraction is measured as the R-radar interval. A band-pass filter (BPF) with several bandwidths and a nonlinear filter, locally projective adaptive signal separation (LoPASS), were analyzed and compared. The optimal filter was quantitatively evaluated by analyzing the distribution and standard deviation of the R-radar intervals. The performance of this monitoring system was evaluated in elderly patient at the Yokohama Hospital, Japan.
Identity-based PSK in WPA2 and WPA3 Networks

Wireless local area networks have become an essential component of many households today. The widely used wireless encryption standards WPA2 and WPA3 oﬀer comprehensive protection against attacks originating from outside the network. However, entities within a network have numerous possibilities to violate the conﬁdentiality, authenticity and integrity of data transmitted by other network participants. This thesis addresses the problem by proposing an amendment of the above mentioned protocols that enforces the use of identity-based keys. It is shown that many insider attacks are no longer feasible due to the protocol modiﬁcation, while the impact on performance and usability remains moderate.
Quantifying Steps During a Timed Up and Go Test Using a Wearable Sensor System: A Laboratory-Based Validation Study in Healthy Young and Older Volunteers

Mobility is an important factor in maintaining health and independence in an aging population. Facilitating community-dwelling older adults to independently identify signs of functional decline could help reduce disability and frailty development. Step-count from a body-worn sensor system was compared with a criterion measure in healthy young (n = 10) and healthy older adults (n = 10) during a Timed Up and Go test under different conditions. Spearman’s rank correlation coefficient indicated strong agreement between the sensor-obtained step-count and that of the criterion measure in both age groups, in all mobility tests. A body-worn sensor system can provide objective, quantitative measures of step-count over short distances in older adults. Future research will examine if step-count alone can be used to identify functional decline and risk of frailty.Clinical Relevance—This demonstrates the correlation between step-count derived from a wearable sensor and a criterion measure over a short distance in older adults.
PSR_2100085 1..19

doi:10.1017/S000305542100085X © The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political Science Association. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
An Inverse Problem Approach for Parameter Estimation of Cardiovascular System Models

Left ventricular assist devices (LVADs) are mechanical pumps that help patients with chronic heart failure waiting for a heart transplant. Mathematical models of these devices can be used along cardiovascular system (CVS) models to evaluate the assistance performance under different operating modes. The estimation of the CVS model parameters for a particular patient and numerical simulations allow the implementation of adequate LVAD operation mode. This work presents a method to estimate the parameters of a CVS model using only one hemodynamic variable: the systemic arterial pressure (Ps). Synthetic signals of Ps are used to solve this ill-posed inverse problem partially, and the results show the high accuracy of the proposed method, which achieves 0.5%. Clinical relevance— The measurements of hemodynamic variables using noninvasive techniques avoid many clinical problems arising from invasive measures such as infections.
Determination of mechanical resonances in induction motors by random modulation and acoustic measurement

Acoustic noise emission from PWM-VSI inverter driven induction motors is a well-known problem. The generated noise depends mainly on two factors: the harmonic content of the supply voltage waveform; and the mechanical resonance frequencies of the induction motor. It is necessary to know the mechanical resonances to optimize the switching scheme of the inverter to reduce the noise emission. Measuring the resonance frequencies is normally a laborious process. This paper introduces a new method for estimating the mechanical resonances from acoustic noise measurements. Employing random modulation of the output voltage of the inverter, the voltage spectrum can be spread over a wide frequency range. Using the spectrum analysis of the measured acoustic noise, the resonances can easily be estimated as the dominant frequencies of the acoustic noise spectrum. The method was tested on a 2.2 kW induction motor at no load and full load. Some of the mechanical resonances of the motor at no load were calculated by the Holzer method. The calculations showed good agreement with the sound measurements. The influence of the fan cowl was investigated and it is concluded that this is an important factor in the acoustic noise emission. Finally, it was observed that new mechanical resonances appeared when the induction motor was loaded by a pump drive system, and they were estimated by the measurement technique. >
IMAGING-2021.00033_proof 1..8

Coronary computed tomography angiography has an emerging role in the diagnostic workup of coronary artery disease. Due to its high sensitivity and negative predictive value, coronary computed tomography angiography can rule out obstructive coronary artery diseases and substitute invasive coronary angiography in many cases. In addition, coronary computed tomography angiography provides a unique information beyond stenosis grading as it can visualize atherosclerosis and quantify its extent. Qualitative and quantitative plaque assessment provides an incremental value in the prediction of future major adverse cardiac events. Moreover, determining adverse plaque features has a potential to identify advanced atherosclerosis and patients at increased risk of acute coronary syndrome. Nevertheless, challenges may emerge with the process of quantifying coronary plaques due to limited reproducibility, lack of automated, standardized and validated techniques. Therefore, reliable quantified data are scarce due to the various computed tomography scanners and software platforms and investigations with small sample sizes. Radiomics and machine learning-based image processing methods are relatively new in the field of cardiovascular plaque imaging. These techniques hold the promise to improve diagnostic performance, reproducibility and prognostic value of computed tomography based plaque assessment.
Less Reward is More: Improved Reinforcement Learning Control of a Mobile Manipulator using Clamped Joints

Many robotic path planning problems are continuous, stochastic, and high-dimensional. The ability of a mobile manipulator to coordinate its base and manipulator in order to control its whole-body online is particularly challenging when self and environment collision avoidance is required. Re-inforcement Learning techniques have the potential to solve such problems through their ability to generalise over environments. We study joint penalties and joint limits of a state-of-the-art mobile manipulator whole-body controller that uses LIDAR sensing for obstacle collision avoidance. We propose directions to improve the reinforcement learning method. Our agent achieves signiﬁcantly higher success rates than the baseline in a goal-reaching environment and it can solve environments that require coordinated whole-body control which the baseline fails.
Tolerancing microlenses using ZEMAX

This paper demonstrates a new tolerancing technique that allows the prediction of microlens optical performance based on metrology measurements taken during the fabrication process. A method for tolerancing microlenses to ensure operating performance using the optical design code ZEMAX(R) is presented. Parameters able to be measured by available metrology tools are assigned tolerances. The goal of the tolerance analysis is to assess the sensitivity of a microlens design to changes in the shape of the lens surface with regard to specific optical performance criteria related to the intended application. Two designs are presented with the tolerance analysis results. In the first design, the radius of curvature and conic constant are varied for an aspheric lens, and the change in the spot size is determined. For the second design, fiber-coupling efficiency is tabulated for a biconic lens. In each case, a metric can be produced showing the ability of the design to meet performance goals within the specified tolerances. A fabrication technician can then use this tolerancing metric with appropriate metrology data to determine if the device will yield acceptable performance. The metric can also determine if a design is overly sensitive to expected tolerances, thereby allowing the optical designer to evaluate the design from a manufacturing perspective.
Typography as Image: Experiments on Typographic Portraits

Over the time, they are also explored as a graphical object per se, by several artists and designers. An approach that is set to increase even further with the democratisation of the computer and desktop publishing tools. In this work, we seek to develop text composition shapes as images, particularly as portraits. This goal is aligned with the development of an interactive installation to integrate a permanent exhibition dedicated to Portuguese literature. This installation aims to involve the audience in the exhibition allowing visitors to create their portraits composed of typographic elements. We conducted three experiments to test different approaches towards the creation of typographic portraits. In all experiments, we map the darkness of the input image into typographic structures with more or less visual emphasis. However, each experiment explores a different composition mechanism. In the first experiment, we implement a text compositor where each glyph changes its weight dynamically to create images with different shades of grey. In the second experiment, we implement a partitioning algorithm to create images consisting of an adaptable layout of words. In the third experiment, we implement an approach where glyphs with different sizes and densities are positioned to create different shades of grey. The obtained outcomes demonstrate that it is possible throughout generative processes to create typographic compositions where typography is not only a communication tool, but it can also be shaped as an image.
Chapter 12-Focal cortical dysplasia

Focal cortical dysplasia (FCD), first described by Taylor and colleagues in 1971, is a malformation of cortical development (MCD) characterized by a localized region of abnormal cerebral cortex (Blumcke et al., 2011; Taylor et al., 1971). Over the past several decades, the classification of FCD has evolved and the term “focal cortical dysplasia” has been used to refer to a range of MCDs. In 2011, the International League Against Epilepsy (ILAE) proposed the currently accepted three-tiered clinicopathologic classification: FCD I refers to an isolated lesion with abnormal cortical lamination, FCD II refers to an isolated lesion with abnormal cortical lamination and specific abnormal cell types, and FCD III is associated with another principal lesion (Blumcke et al., 2011). Patients with FCD usually present in childhood with focal epilepsy, with the seizure semiology dependent on the location of the lesion (Gaitanis and Donahue, 2013; Maynard et al., 2017). Magnetic resonance imaging (MRI) is the main imaging modality used for diagnosis and commonly shows localized blurring of the gray matterewhite matter junction and increased cortical thickness (Palmini and Holthausen, 2013). Although patients with FCD and focal epilepsy are initially managed with antiepileptic drugs (AEDs), FCD is one of the most common causes of intractable epilepsy in children (Bast et al., 2006). Thus, patients often undergo surgical resection for attempted seizure control, and FCD is the most common cause of surgically treated intractable epilepsy in children (Bast et al., 2006; Blumcke et al., 2017). The etiology of FCD has remained a mystery for several decades, and an important advance in the past decade has been the identification of genetic causes of FCD. Multiple studies have identified mutations, mainly somatic, in genes in the mammalian target of rapamycin (mTOR) pathway in patients with FCD, mainly FCD II (Poduri et al., 2012; Scheffer et al., 2014). The mutations lead to abnormal activation of the mTOR pathway, which is critical for cell growth and proliferation. The identification of genetic causes of FCD has led to progress in understanding pathogenic mechanisms using animal models and single-cell technologies and in developing potential targeted therapies. In this chapter, we will review the classification and pathology, electroclinical presentation, imaging, etiology, and management and outcomes of FCD and discuss challenges for the future.
Evaluation of sorghum populations for morphological traits related fodder yield and stem borer resistance

Evaluation of segregating populations for stem borer resistance is one of the best ways to select RILs that mitigate adverse effect of stem borer. The present study was initiated to evaluate sorghum segregating populations, estimate the genetic variability, and identify the best performing genotypes for yield and stem borer resistance. The study was conducted during 2017 at Forage Research area of Department of Genetics & Plant breeding CCS Haryana Agricultural University, Hisar. F3 population was obtained from crossing two parents HJ513 (susceptible) and IS 2205(resistance) with contrasting morphological traits for stem borer resistance. A total of 202 RILs were evaluated using augmented design. RILs 3, 4, 13, 21, 26, 54, 55, 56, 60, 83, 85, 86, 89, 90, 91, 96, 99, 100, 104, 108, 109, 118, 119, 189, 129, 139, 151 were recorded as top performing among F3 population for green fodder yield. The less no. of dead heart and stem-tunneling were registered in RIL s 47, 48, 49, 72, 74, 144, 154, 155, 160, 166, 169. High heritability coupled with genetic advance as percent of mean was noted for green fodder yield and plant height. Good pogress is expected from selection of morphological traits for borer resistance in sorghum population. These RILs appear well suited for further specific area for stem borer resistance breeding and research.
Personal Identification Using Gait Spectrograms and Deep Convolutional Neural Networks

Human gait can serve as a useful behavioral trait for biometrics. Compared to fingerprint, face, and iris, the most commonly used physiological identifiers, gait can be unobtrusively monitored from a distance without requiring explicit involvement and physical restraint from people. Advances in wearable technology facilitate direct and faithful measurement of gait motions with easy-to-use and low-cost inertial sensors. This study aimed to propose an approach to using kinematic gait data collected with wearable inertial sensors for reliable personal identification. Sixty-nine individuals ranged in age from 24 to 62 years old participated in this study. The 3-axis acceleration and the 3-axis angular velocity signals were measured using the inertial measurement units attached to the feet, shanks, thighs, and posterior pelvis while walking. The gait spectrograms were acquired by applying time-frequency analyses to the lower body movement signals measured in one stride. Among each participant's 15 strides, 12 strides were used in the 4-fold cross validation of the deep convolutional neural network-based classifiers, and the remaining three strides were used to evaluate the classifiers. An accuracy of 99.69% was achieved by using the foot, shank, thigh, and pelvic spectrograms, and the accuracy was 96.89% using only the foot spectrograms. This study has the potential to be applied in behavior-based biometric technologies by confirming the feasibility of the proposed kinematic and spectrographic approaches in identifying personal behavioral characteristics.
Coupling control in microstrip lines using nonuniform bidefected ground structures

Nonuniform bidefected ground structures (NB‐DGS) are introduced in this paper. By using NB‐DGS, compact frequency‐selective microstrip lines (FML) are designed and measured. The measurements demonstrated a 30‐dB coupling reduction for three‐port FML and a 25‐dB coupling reduction for intersecting FML. © 2005 Wiley Periodicals, Inc. Microwave Opt Technol Lett 44: 475–477, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20671
Nonlinear Effects of Diet on Broiler Production 1

Summary Many factors interact and many objectives compete in the optimal production of broilers. This paper summarizes the nonlinear effects of dietary balanced protein and dietary energy on feed intake, growth curves, and yield dynamics for one strain of broilers. Sex, prestarter nutrition, and subsequent dietary energy and protein levels had significant nonlinear effects on broiler feed intake, growth rates and yield dynamics. These effects have been quantified using previously available and novel nonlinear models. Feed is the largest single cost in broiler production, but predicting intake has proved challenging for the animal science community. Therefore modeling growth profiles has received much attention in recent years. In this paper, a nonlinear mixed model that describes scenario-specific growth curves, crucial for the timing of processing, is presented. Yield dynamics are explored under various nutritional scenarios aiming at the prediction of carcass value. This paper provides an integrated generalized nonlinear model that can be applied to a wide range of supply chain optimization problems. Data specific to strain, production conditions, or particular environments, will improve the value of the model in commercial applications.
Neuromorphic Instantiation of Spiking Half-Centered Oscillator Models for Central Pattern Generation

In both invertebrate and vertebrate animals, small networks called central pattern generators (CPGs) form the building blocks of the neuronal circuits involved in locomotion. Most CPGs contain a simple half-center oscillator (HCO) motif which consists of two neurons, or populations of neurons, connected by reciprocal inhibition. CPGs and HCOs are well characterized neuronal networks and have been extensively modeled at different levels of abstraction. In the past two decades, hardware implementation of spiking CPG and HCO models in neuromorphic hardware has opened up new applications in mobile robotics, computational neuroscience, and neuroprosthetics. Despite their relative simplicity, the parameter space of GPG and HCO models can become exhaustive when considering various neuron models and network topologies. Motivated by computational work in neuroscience that used a brute-force approach to generate a large database of millions of simulations of the heartbeat HCO of the leech, we have started to build a database of spiking chains of multiple HCOs for different neuron model types and network topologies. Here we present preliminary results using the Izhikevich and Morris-Lecar neuron models for single and pairs of HCOs with different inter-HCO coupling schemes.
Analysis of Dexterity Motion by Singular Value Decomposition for Hand Movement Measured Using Inertial Sensors

Finger movements play an important role in many daily human actions. Among the studies on the dexterity of fingers required for various tasks in neurology and simple evaluation tests, few have focused on detailed finger movements themselves. Therefore, in this study, we improved the hand motion measurement system using inertial sensors and the motion analysis method developed in our previous study and measured the motion of the upper limbs (including the fingers) during a general finger dexterity test. By applying singular value decomposition to the obtained joint angles and decomposing them into simpler movement units, we obtained the timing of each movement unit and the purpose of each movement as the coordination state of the joints. By applying hierarchical clustering to multiple trials in a finger dexterity test, we also determined the similarity between trials and investigated the characteristics of movements with higher dexterity. We investigated the motor characteristics in finger dexterity by analyzing our results.