Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Resting HRV during fMRI: A Comparison between Laboratory and Scanner Environment

Heart rate variability (HRV) is regularly assessed in neuroimaging studies as an indicator of autonomic, emotional or cognitive processes. In this study, we investigated the influence of a loud and cramped environment during magnetic resonance imaging (MRI) on resting HRV measures. We compared recordings during functional MRI sessions with recordings in our autonomic laboratory (LAB) in 101 healthy subjects. In the LAB, we recorded an electrocardiogram (ECG) and a photoplethysmogram (PPG) over 15 min. During resting state functional MRI, we acquired a PPG for 15 min. We assessed anxiety levels before the scanning in each subject. In 27 participants, we performed follow-up sessions to investigate a possible effect of habituation. We found a high intra-class correlation ranging between 0.775 and 0.996, indicating high consistency across conditions. We observed no systematic influence of the MRI environment on any HRV index when PPG signals were analyzed. However, SDNN and RMSSD were significantly higher when extracted from the PPG compared to the ECG. Although we found a significant correlation of anxiety and the decrease in HRV from LAB to MRI, a familiarization session did not change the HRV outcome. Our results suggest that psychological factors are less influential on the HRV outcome during MRI than the methodological choice of the cardiac signal to analyze.
Data Mining of Free-Text Responses: An Innovative Approach to Analyzing Patient Perspectives on Treatment for Chronic Rhinosinusitis with Nasal Polyps in a Phase IIa Proof-of-Concept Study for Dupilumab

Purpose Patient perspective is an important and increasingly sought-after complement to clinical assessment. The aim of this study was to transcribe individual patients’ experience of treatment in a dupilumab clinical trial through free-text responses with analysis using natural language processing (NLP) to obtain the unique perspective of patients on disease impact and unmet needs with existing treatment to inform future trial design. Patients and Methods Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) who were enrolled in a Phase IIa randomized controlled trial comparing dupilumab with placebo (NCT01920893) were invited to complete a self-assessment of treatment (SAT) tool at the end of treatment, asking, “What is your opinion on the treatment you had during the trial? What did you like or dislike about the treatment? ” Free-text responses were analyzed for the overall cohort and according to treatment assignment using natural language processing including sentiment scoring. In a mixed-methods approach, quantitative patient-reported outcome (PRO) results were utilized to complement the qualitative analysis of free-text responses. Results Of 60 patients enrolled in the study, 43 (71.6%) completed the SAT and responses from 37 patients were analyzed (placebo, n = 16; dupilumab, n = 21). Word analyses showed that the most common words were “smell,” “improve,” “staff,” “great,” “time,” and “good. ” Across the whole cohort, “smell” was the most common symptom-related word. The words “smell” and “experience” were more likely to occur in patients treated with dupilumab. Patients treated with dupilumab also had more positive sentiment in their SAT responses than those who received placebo. The results from this qualitative analysis were reflected in quantitative PRO results. Conclusion “Smell” was important to patients with CRSwNP, highlighting its importance as a patient-centric efficacy outcome measure in the context of clinical trials in CRSwNP. Trial Registration ClinicalTrials.gov, NCT01920893. Registered 12 August 2013, https://www.clinicaltrials. gov/ct2/show/NCT01920893.
An Explainable Approach Based on Emotion and Sentiment Features for Detecting People with Mental Disorders on Social Networks

Mental disorders are a global problem that widely affects different segments of the population. Diagnosis and treatment are difficult to obtain, as there are not enough specialists on the matter, and mental health is not yet a common topic among the population. The computer science field has proposed some solutions to detect the risk of depression, based on language use and data obtained through social media. These solutions are mainly focused on objective features, such as n-grams and lexicons, which are complicated to be understood by experts in the application area. Hence, in this paper, we propose a contrast pattern-based classifier to detect depression by using a new data representation based only on emotion and sentiment analysis extracted from posts on social media. Our proposed feature representation contains 28 different features, which are more understandable by specialists than other proposed representations. Our feature representation jointly with a contrast pattern-based classifier has obtained better classification results than five other combinations of features and classifiers reported in the literature. Our proposal statistically outperformed the Random Forest, Naive Bayes, and AdaBoost classifiers using the parser-tree, VAD (Valence, Arousal, and Dominance) and Topics, and Bag of Words (BOW) representations. It obtained similar statistical results to the logistic regression models using the Ensemble of BOWs and Handcrafted features representations. In all cases, our proposal was able to provide an explanation close to the language of experts, due to the mined contrast patterns.
Quality engineering (Taguchi methods) for the development of electronic circuit technology

Most technology development engineers use traditional reliability engineering methods to calibrate the objective functions of their new systems to meet various marketing requirements. These methods are marginally effective in reducing failure rates. To fundamentally improve quality, the engineers need to focus on improving the robustness of the basic functions of their new product or process technologies and apply parameter design methods to make the basic functions approach the ideal functions under real conditions. These robust design activities should be conducted by research and development departments before actual products are planned. The objective is to improve the downstream reproducibility of new technologies. The technical development of an electronic circuit is used to explain this proposition. >
DESIGN OF AIRFOIL USING BACKPROPAGATION TRAINING WITH PENALTY TERM

Here, we investigate a method for the inverse design of airfoil sections using artificial neural networks (ANNs). The aerodynamic force coefficients corresponding to series of airfoil are stored in a database along with the airfoil coordinates. A feedforward neural network is created with input as a aerodynamic coefficient and the output as the airfoil coordinates . In existing algorithm as an FNN training method has some limitation associated with local optimum and oscillation. In this paper new cost function is proposed for hidden layer separately. In the proposed algorithm the output layer is incorporated into to the cost function having linear and non linear error terms. The functional constraints penalty term at the hidden layer are incorporated into to the cost function having linear and nonlinear error terms. Results indicate that optimally trained ar tificial neural networks may accurately predict airfoil profile.
Performance Evaluation of Machine Learning Algorithms for Stock Price and Stock Index Movement Prediction Using Trend Deterministic Data Prediction

This experimental study addresses the problem of predicting the direction of stocks and the movement of stock price indices for three major stocks and stock indices. The proposed approach for processing input data involves the computation of ten technical indicators using stock trading data. The dataset used for the evaluation of all the prediction models consists of 11 years of historical data from January 2007 to December 2017. The study comprises four prediction models which are Long Short-Term Memory, XGBoost, Support Vector Machine ( and Random forests. Accuracy scores and F1 scores for each of the prediction models have been evaluated using this input approach. Experimental results reveal that a continuous data approach using ten technical indicators gives the best performance in the case of the Random Forest classifier model with the highest accuracy of 84.89% (average wise 83.74%) and highest F1 score of 89.33% (average wise 83.74%). The experiments also give us an insight into why a Naïve Bayes Classification model is not a suitable prediction model for the above task.
Development of a pre-ignition submodel for hydrogen engines

AbstractIn hydrogen-fuelled spark ignition engine applications, the onset of pre-ignition remains one of the prime limitations that needs to be addressed to avoid its incidence and achieve superior performance. This paper describes a new pre-ignition submodel for engine modelling codes. The effects of changes in key operating variables, such as compression ratio, spark timing, intake pressure, and temperature on pre-ignition limiting equivalence ratios are established both analytically and experimentally. With the established pre-ignition model, it is possible not only to investigate whether pre-ignition is observed with changing operating and design parameters, but also to evaluate those parameters' effects on the maximum possible pre-ignition intensity.
Single-mode silicon-on-insulator elliptical microdisk resonators with high Q factors

We propose and demonstrate a novel elliptical microdisk resonator which enables single-mode operation with high quality (Q) factor. Such elliptical microdisk resonators with pedestal, which consist of plenty of smoothly changing bends with modified curvature radii, can easily achieve single-mode operation due to selective losses introduced by mode transmission mismatches and small curvature radii portion inside the elliptical microdisks. We fabricated the devices on silicon-on-insulator (SOI) platform. Single-mode resonance with high quality factor (Q) of ~105 was experimentally realized. Besides, the proposed elliptical microdisk provides larger coupling strength compared to normal circular microdisk, and hence enables critical coupling with easy-to-fabricate gaps.
Exogenous Application of Alpha-Lipoic Acid Mitigates Salt-Induced Oxidative Damage in Sorghum Plants through Regulation Growth, Leaf Pigments, Ionic Homeostasis, Antioxidant Enzymes, and Expression of Salt Stress Responsive Genes

In plants, α-Lipoic acid (ALA) is considered a dithiol short-chain fatty acid with several strong antioxidative properties. To date, no data are conclusive regarding its effects as an exogenous application on salt stressed sorghum plants. In this study, we investigated the effect of 20 µM ALA as a foliar application on salt-stressed sorghum plants (0, 75 and 150 mM as NaCl). Under saline conditions, the applied-ALA significantly (p ≤ 0.05) stimulated plant growth, indicated by improving both fresh and dry shoot weights. A similar trend was observed in the photosynthetic pigments, including Chl a, Chl b and carotenoids. This improvement was associated with an obvious increase in the membrane stability index (MSI). At the same time, an obvious decrease in the salt induced oxidative damages was seen when the concentration of H2O2 and malondialdehyde (MDA) was reduced in the salt stressed leaf tissues. Generally, ALA-treated plants demonstrated higher antioxidant enzyme activity than in the ALA-untreated plants. A moderate level of salinity (75 mM) induced the highest activities of superoxide dismutase (SOD), guaiacol peroxidase (G-POX), and ascorbate peroxidase (APX). Meanwhile, the highest activity of catalase (CAT) was seen with 150 mM NaCl. Interestingly, applied-ALA led to a substantial decrease in the concentration of both Na and the Na/K ratio. In contrast, K and Ca exhibited a considerable increase in this respect. The role of ALA in the regulation of K+/Na+ selectivity under saline condition was confirmed through a molecular study (RT-PCR). It was found that ALA treatment downregulated the relative gene expression of plasma membrane (SOS1) and vacuolar (NHX1) Na+/H+ antiporters. In contrast, the high-affinity potassium transporter protein (HKT1) was upregulated.
Performance Analysis of the Low-Temperature Solar-Boosted Power Generation System—Part I: Comparison Between Kalina Solar System and Rankine Solar System

On the base of the two classical thermodynamic cycles (Kalina cycle and Rankine cycle), solar-boosted Kalina system (Kalina solar system) and solar-boosted Rankine system (Rankine solar system) with traditional nonconcentrating flat plate solar collector (FPSC) and evacuated tube solar collector (ETSC) are investigated in the present paper. The proposed solar systems are considered to be the hybrid of power generation subcycle and solar collector subcycle. Their electricity generating performances are compared under their respective optimal operating conditions to clarify which one is more competitive in solar utilization. Results show that ETSC is the better choice for the both solar systems. Further, the performance comparison shows that the low-temperature solar energy utilized in Kalina cycle is predominant to generate electricity. Meanwhile, the study also find that mass flow rate of the power generation subcycle, mass flow rate of the solar collector subcycle, mass fraction of ammonia and the regenerator performance are important operational parameters for high performance of the Kalina solar system. Finally, with the aid of the weather conditions of Kumejima Island in Japan, the perceptual knowledge for Kalina solar system by using an application case is shown in the paper.
Is language priced? evidence from bank loan contracting

ABSTRACT Previous studies document that firms in countries speaking languages with strong future time reference (FTR), which more sharply dissociates the future from the present, engage in less future-oriented corporate behaviors relating to their default and information risks. We find that strong FTR influences creditors’ pricing of bank loan contracts: banks design more unfavorable loan terms to strong-FTR borrowers, including larger loan spread, higher likelihood of collateral requirement, and more covenants. This effect can be mitigated by a country’s strong governance. We confirm that strong FTR is associated with higher default and information risks of borrowing firms. Overall, our findings suggest that language represents a distinctive risk to banks which is priced in the loan market.
Clinical and Genetic Study of X-Linked Juvenile Retinoschisis in the Czech Population

The aim of this study was to identify RS1 pathogenic variants in Czech patients with X-linked retinoschisis (XLRS) and to describe the associated phenotypes, including natural history, in some cases. Twenty-one affected males from 17 families were included. The coding region of RS1 was directly sequenced and segregation of the identified mutations was performed in available family members. In total, 12 disease-causing variants within RS1 were identified; of these c.20del, c.275G>A, c. [375_379del; 386A>T], c.539C>A and c. 575_576insT were novel, all predicted to be null alleles. The c.539C>A mutation occurred de novo. Three patients (aged 8, 11 and 19 years) were misdiagnosed as having intermediate uveitis and treated with systemic steroids. Repeat spectral domain optical coherence tomography examinations in four eyes documented the transition from cystoid macular lesions to macular atrophy in the fourth decade of life. Four individuals were treated with topical dorzolamide and in two of them, complete resolution of the cystic macular lesions bilaterally was achieved, while one patient was noncompliant. Rebound phenomenon after discontinuation of dorzolamide for 7 days was documented in one case. Misdiagnosis of XLRS for uveitis is not uncommon; therefore, identification of disease-causing variants is of considerable benefit to the affected individuals.
Cognitive stimulation has potential for brain activation in individuals with Rett syndrome.

BACKGROUND Knowledge regarding neuropsychological training in Rett syndrome (RS) is scarce. The aim of this study was to assess the outcome and the duration of the effect of cognitive stimulation on topographic electroencephalography (EEG) data in RS. METHODS Twenty female children diagnosed with RS were included in the analysis. Girls with RS conducted a cognitive task using an eye-tracker designed to evaluate access and choice skills. EEG data were acquired during the experimental procedure including two 10-min baseline stages before and after the task. Topographical changes of several EEG spectral markers including absolute and relative powers, Brain Symmetry Index and entropy were assessed. RESULTS Topographic significance probability maps suggested statistical decreases on delta activity and increases on beta rhythm associated with the cognitive task. Entropy increased during and after the task, likely related to more complex brain activity. A significant positive interaction was obtained between Brain Symmetry Index and age showing that the improvement of interhemispheric symmetry was higher in younger girls (5-10 years). CONCLUSIONS According to our findings, significant alterations of brain rhythms were observed during and after cognitive stimulation, suggesting that cognitive stimulation may have effects on brain activity beyond the stimulation period. Finally, our promising results also showed an increase brain symmetry that was especially relevant for the younger group. This could suggest an interaction of the eye-tracking cognitive task; however, further studies in this field are needed to assess the relation between brain asymmetries and age.
Ice valve for a mini/micro flow channel

We have developed a new ice valve to close or open liquid flow in a mini/micro channel. Unlike the traditionally used valve, no moving elements are needed in this normally open system. By freezing the working fluid running inside the channel using a thermoelectric cooling device (TECD), the flow can be blocked due to ice formation. If switching the TECD to heating, the frozen liquid becomes thawed and flow in the channel resumes its running state again. Several experiments were carried out to characterize the working performance of the ice valve for a micro tube. A theoretical model was established to analyze the time response constant of the ice valve. Without any leakage, being very clean, and easily controllable through electricity, this ice valve may find significant applications in microfluidics or nanofluidics.
Net Income Measurement, Investor Inattention, and Firm Decisions

This paper studies the interaction between investor inattention and firms’ capital allocation decisions by exploiting an accounting rule change that requires publicly traded firms to incorporate changes in unrealized gains and losses (UGL) from public stock investments into net income. We build a model with risk-averse investors who can be attentive or inattentive and managers who maximize firms’ stock prices. The model makes two main predictions. First, with inattentive investors, the rule change will cause firms’ stock prices to react more strongly to net income fluctuations from changes in UGL on financial assets. Second, under certain conditions, the rule can lead to higher stock price discount because of higher perceived residual uncertainty, and managers respond by cutting financial asset holdings. We use US insurance company data to test these predictions. We find that insurers’ stock returns react more strongly to UGL on equity securities after the rule change, and more so for firms with low analyst coverage. Using a difference-in-differences approach, we find that by 2020, publicly traded insurance companies cut investments in public stocks by $23 billion. Our results highlight the impact that investor inattention has on firm’s stock price and resource allocation decisions. JEL Code: G11, G14, G22, G30, M41
Flash flood disasters in Uttarakhand

Purpose – Up to now most of the research into flash flood disaster has examined scientific aspects of this natural phenomenon. This paper aims to focus on the flash flood disaster scenario of Uttarakhand, a newly created Himalayan State in India, on the basis of their severity and mechanism so that management efforts can be mounted by the disaster managers.Design/methodology/approach – Besides compiling the hazard‐ and risk‐related work done by the various research institutions and universities the paper attempts to understand the mechanism responsible for this natural hazard.Findings – Uttrakhand is a state highly prone to disasters. Flash floods are disasters that are seasonal in nature and strike during a certain period of the year in certain pockets of the state with high frequency.Research limitations/implications – The analysis is based on observations made in the entire state.Practical implications – Awareness amongst the masses regarding the flash flood disaster that is likely to affect them and t.
Static calibration of transducers using Gauss-function-based approximation

The problem of static calibration of measurement channels is considered under an assumption that the raw result of measurement depends both on a scalar measurand and on a scalar influence quantity. The methodology of calibration based on the Gauss-function approximation is developed and examined using synthetic data representing a measurement channel with a fiber-optic sensor. Various algorithms of calibration are compared; the accuracy of measurements, based on the results of calibration, is used as the main criterion of comparison. Some recommendations are formulated, concerning the applicability of the compared algorithms of calibration.
Embedded Security For High Risk Areas With Multiple Fault Tolerant

Embedded systems have been almost invisibly pervading our daily lives for several decades. These Embedded electronic devices plays vital role in almost the areas of human life, Decreased costing, increased production tends to use these devices with higher reliability areas. They facilitate smooth operation in sphere of human life, avionics, automotive electronics, or telecommunication. New problems arise by increasing employment, interconnections, EMI, RFI, harmonics, sag, and end of course thermal problems. These problems are not quick common but expected always due to the fast growing multi utilize service like induction machine, radio frequency devices, rotating machines and much more. The challenges unique to embedded systems require new approaches to security covering all aspects of embedded system design from architecture to implementation. This paper presents a design of fault - tolerant embedded system by piggyback method of two embedded processor. Both processors are involved in adaptive sharing with software module. The customized fault tolerant embedded system is designed by combining selective protection on both hardware and software. Security processing, which refers to the computations that must be performed in a system for the purpose of security, can easily overwhelm the computational capabilities of processors in both low- and high-end embedded systems.
24.1: Fingerprint Scanner Using a‐Si: H TFT‐Array

Two‐dimensional contact type fingerprint scanner with a resolution of 300 dpi (84 μm dot pitch) were fabricated for the fingerprint recognition. This sensor array consists of three parts; a sensor thin film transistor (TFT), storage capacitor and switch TFT. High quality of captured fingerprint image was obtained through the a‐Si:H TFT‐array with a high photo to dark current ratio of above 3 order of sensor TFT.