Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of the effectiveness of virtual reality with medication on the memory of attention deficit hyperactivity disorder students

Aims: The purpose of this study was to compare the effectiveness of virtual reality (VR) with medication on the memory of attention deficit hyperactivity disorder (ADHD) students. Materials and Methods: The research method was quasi-experimental with pretest, posttest, control and follow-up design. The statistical population consisted of 7–12-year-old elementary school students with ADHD in Isfahan city in the school year of 2018–2019 which 48 of them were selected through purposive sampling. Data were collected using the Swanson Parent Form SNAP-4, Memory Subscale of Wechsler's Intelligence Quotient (IQ), and Raven's Colored IQ Test. The VR group received ten sessions of intervention and the medication group received medicines. Then, posttest and follow-up were performed for all the three groups. Multivariate tests were used to analyze the scores. Results: The results showed that there was a significant difference in memory variables in the posttest stage between the control and VR groups (P < 0.001) and the control and medication groups (P < 0.05). Conclusions: In a general conclusion, it seems that VR therapy and medication have been effective in improving the memory of elementary ADHD students and the effects of these treatments remain in the follow-up stage, but the therapeutic approach of VR has been more effective than medication in both the posttest and follow-up stages.
Expression of Heat Shock Protein 70 in Oral Epithelial Dysplasia and Oral Squamous Cell Carcinoma: An Immunohistochemical Study

Introduction: Heat shock proteins are biomarkers regulating the degree of differention and aggressiveness in oral carcinogenesis. The study was carried out to evaluate the expression of HSP 70 in histological grades of epithelial dysplasia and oral squamous cell carcinoma using immunohistochemistry. Methodology: A sample of 40, which included 10 (Normal), 15 (epithelial dysplasia) and 15 (oral squamous cell carcinoma) were selected. The biopsy samples were stained using H and E staining and HSP 70 IHC. Results: There was a statistical significant difference in expression of HSP 70 between normal oral mucosal tissue, leukoplakia and OSCC. Discussion and Conclusion: This study concludes the critical role of HSP70 as an oncogene in the development of oral cancer. HSP70 inhibition is, therefore a promising therapeutic approach for cancer treatment.
Phytochemical profile of the aerial parts of Rehmannia glutinosa liboschitz var. purpurea Makino

Background: The roots of Rehmannia glutinosa (RG) or Rehmanniae Radix are a well-known medicinal material in the Oriental medicine, and its phytochemical profile has been extensively studied with more than 100 individual compounds from Rehmannia species. In contrast, bioactive components of the aerial part of the title plant are largely unknown as only several compounds reported up to date. Objective: The objective was to study on chemical constituents of the aerial parts of the title plant and evaluate the aerial parts as a supplementary source for Rehmanniae radix. Materials and Methods: Solvent extraction, partition, and column chromatography was used to separate individual compounds; spectroscopic data including nuclear magnetic resonance and mass spectrometry were analyzed to determine the chemical structure of the isolates. Results: Eight compounds including five ursane-type triterpenoids for the first time from RG (ursolic acid [1], pomolic acid [2], 2β-hydroxypomolic acid [3], asiatic acid [4] and 7β,24-dihydroxy ursolic acid [5]) and three main glycosides (ajugol [6], aucubin [8], and acteoside [7]) were characterized from the aerial parts of the title plant. Their structures were identified on the basis of spectroscopic data and comparison with those reported in the literature. Conclusion: The current study reveals various ursane triterpenes in the organic portion beside the main hydrophilic glycosides in the RG aerial parts. The occurrence of various ursane triterpenes contributed in part to phytochemical database and evidence of the biological activity associated with potential in use as a medicinal material of the RG leaves.
A case of Stanford type B acute aortic dissection presenting as acute abdomen

Acute aortic dissection is a medical emergency with high mortality. It presents mostly with typical features of sudden onset chest pain that is tearing in nature and radiates to the back, neck, or the abdomen. However, it may present with atypical features like abdominal pain, nonspecific abdominal or chest discomfort, altered bowel habit, vomiting, and features of acute renal dysfunction leading to diagnostic dilenma. These atypical features are mostly reported in western population. We report a case of 48-year old man with Stanford type B acute aortic dissection that was initially diagnosed as acute abdomen.
Tracheostomy creation leading to innominate artery pseudoaneurysm: A case report

1. Kar-binh Ong BA, Sashidharan R. Combined spinal-epidural techniques. Contin Educ Anaesth Crit Care Pain 2007;7:38-41. 2. Sakuma N, Hori M, Suzuki H, Hashimoto Y, Kameyama E, Horinouchi T, et al. A sheared off and sequestered epidural catheter: A case report. Masui, 2004;53:198-200. 3. Whitty RJ, Lazinski D, Carvalho JC. Large subcutaneous fluid collection attributed to suspected epidural catheter leak. Anesth Analg 2007;104:230-1.
A Study on the relationship between college students' emotional management ability and mental health

Objectives: The objective of this study is to explore the relationship between college students' emotion management ability and mental health. Methods: A total of 1000 college students from four universities in our city were selected as the object of the study. The emotion management ability of 1000 college students was analyzed by means of questionnaire, and the mental health status of college students was measured with symptom checklist (SCL)-90. The average scores of the five dimensions of college students' emotional management ability are classified as follows: Controlling negative vent >rational regulation >seeking outside support >controlling negative suggestion >positive remedy. Results: The results showed that there were obvious negative correlations between the three factors and the SCL-90 factors, such as the rational control of college students, the control of negative implications, and the control of negative venting. However, there is only a negative correlation between college students' seeking outside help and interpersonal, paranoid, psychotic, and depressive factors. Positive remedies were negatively correlated with the symptoms of compulsion, psychosis, and depressive factors, while positive remedies and paranoia factor and hostile factor are obviously related. Conclusions: In the investigation of college students' emotional management ability, the five dimensions are closely related to their mental health status. Therefore, we should pay attention to the cultivation of college students' emotional ability and encourage them to participate in some meaningful activities to improve their mental health.
Effect of hypothyroidism on cognitive status: Evidence from stroop task

Background: Very less work has been done in the past to assess cognition in hypothyroid patients using classical color-word Stroop task. The Stroop color-word task is a well-recognized tool which estimates cognitive inhibition. Stroop task is based on the fact that reading words and identifying color of written words are two different information and they process with a common response channel but with different speeds. The aim of this study was to assess the cognitive inhibition process in drug-naïve hypothyroid patients and their comparison with the same patients after the attainment of euthyroid status and also with euthyroid controls using classical color-word Stroop task. Materials and Methods: Thirty drug-naïve newly diagnosed hypothyroid patients were study cases who underwent Stroop task once before initiating treatment and then after the attainment of euthyroid state. We performed the same test in euthyroid controls twice at an interval of 3 months for comparison purpose. Correlation analysis was also done for hypothyroidism and cognition. Results: The reaction time of Stroop task was decreased in all the three conditions of each block, i.e., neutral, incongruent, and congruent conditions after the attainment of euthyroid state, and the finding confirms posttreatment modulation of the attention processes in hypothyroid patients. Reaction time of Stroop task in hypothyroid patients was positively correlated with the serum thyroid-stimulating hormone levels. Processing of color identification was suppressed than reading words in hypothyroid patients as evidenced by increased reaction time of Stroop task. This increase in reaction time can be reversed by earlier identification of drug-naïve hypothyroid cases so that they can get timely treatment to restore their cognitive status. Conclusions: Stroop task scores are reduced in overt hypothyroid patients, but improve after thyroid replacement therapy.
Extraction of Novel Features Based on Histograms of MFCCs Used in Emotion Classification from Generated Original Speech Dataset

This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from speech signals, and the other – our new multi-lingual and multi-personal speech database, which has three emotions. In this study, Berlin Database (BD) (in German) and our custom PAU database (in English) created from YouTube videos and popular TV shows are employed to train and evaluate the test results. Experimental results show that our proposed features lead to better classification of results than the current state-of-the-art approaches with Support Vector Machine (SVM) from the literature. Thanks to our novel feature, this study can outperform a number of MFCC features and SVM classifier based studies, including recent researches. Due to the lack of our novel feature based approaches, one of the most common MFCC and SVM framework is implemented and one of the most common database Berlin DB is used to compare our novel approach with these kind of approaches.
Counterparty Risk: Implications for Network Linkages and Asset Prices

We study the relation between trade credit, asset prices, and production-network linkages. Empirically, firms extending more trade credit earn 7.6% p.a. lower risk premiums and maintain longer relationships with customers. Using a production-based model, we quantitatively explain these novel facts. Trade credit reduces the departure probability of high-quality customers, thereby reducing firms’ exposures to systematic costs incurred in finding new customers. The mechanism predicts that the aggregate amount of trade credit proxies for customer-search costs and that suppliers with shorter-duration links to customers command higher expected returns. We confirm these and other novel predictions in the data.
A comparative study of three different chloride currents in rat sympathetic neurones.

Cl* ions are the most abundant anion in cells. Cl' conducting channels have been proposed to be involved in several cellular processes. These include the modulation of electrical excitability and synaptic inhibition, the regulation of intracellular pH and the regulation of cell volume. In this thesis three types of Cl* channels in rat superior cervical ganglion neurones have been investigated. These are a Ca^ ̂and protein kinase C-dependent Cl* current ( I c i ( m ) ) , a hyperpolarization-activated Cl* current ( I c k h p ) ) and a swelling-activated Cl* current ( I c i( s w e ii) ) . These three currents differ in several properties including biophysical characteristics, sensitivity to pharmacological agents, anion permeability, Ca^^-dependence and involvement of second messenger pathways. Ici(m) is induced synergistically by Ca^ ̂and diacylglycerol. Consequently it can be activated by the actions of the excitatory neurotransmitter, acetylcholine, which causes a rise in intracellular Ca^ ̂via the activation of Ca^^-permeable nicotinic ionotropic receptors, and generates diacylglycerol by stimulating muscarinic receptors. The hyperpolarization-activated Cl current, ( I c i(h p ) ) , shows strong voltageand time-dependence, is Ca^^-independent and is sensitive to block by the divalent cations, Cd"" and Zn"\ Ic i(sw c ii) is activated in response to hypotonicity-induced cell swelling. The movement of Cl* ions out of the cell is accompanied by water which thus leads to a reversal of cell swelling (Regulatory Volume Decrease mechanism). I have shown that Ici(swcii) is different to previously identified Cl* currents in these cells but shares several properties with swelling-activated Cl* currents in other cell types. To conclude, I have studied three types of neuronal Cl* currents which are distinct from one another. Ici(m) and Ici(hp) may have a physiological role in the regulation of electrical excitability, and Ic i(sw c ii) in the response of cells to osmolarity changes under both physiological and pathological conditions.
Discrimination of Different Levels of Adhesion in a Bi Layer Aluminum/Epoxy Structure Using Lamb Waves

The aim of this work is to bring a new knowledge of the quality of the adhesion through a collaboration between physical-chemists and acousticians. Bi layers Aluminum/epoxy samples are manufactured with different surface treatments at the interface aluminum/epoxy and with different cures of the epoxy coating in order to obtain different and controlled levels of adhesion. The treatments are mechanical (sand blasting) and/or chemical (silanization). Two cross linking of the epoxy are considered : 80% or 100%. The goal is to discriminate acoustically each level of adhesion using guided Lamb waves, by measuring the wave-number shift for a given frequency and the attenuation of the propagating modes. The experimental study is realized using a contact transducer as an emitter and a laser vibrometer as a receiver to measure the time dependent normal displacement at the aluminum surface of the propagating waves. Results show that, depending on the propagating mode, the different samples can be discriminated either by the shift of the experimental dispersion curves or the attenuation of the mode.
Approximating Hamiltonian dynamics with the Nyström method

Simulating the time-evolution of quantum mechanical systems is BQP-hard and expected to be one of the foremost applications of quantum computers. We consider classical algorithms for the approximation of Hamiltonian dynamics using subsampling methods from randomized numerical linear algebra. We derive a simulation technique whose runtime scales polynomially in the number of qubits and the Frobenius norm of the Hamiltonian. As an immediate application, we show that sample based quantum simulation, a type of evolution where the Hamiltonian is a density matrix, can be eﬃciently classically simulated under speciﬁc structural conditions. Our main technical contribution is a randomized algorithm for approximating Hermitian matrix exponentials. The proof leverages a low-rank, symmetric approximation via the Nyström method. Our results suggest that under strong sampling assumptions there exist classical poly-logarithmic time simulations of quantum computations.
Bias, Precision, and Accuracy of Skewness and Kurtosis Estimators for Frequently Used Continuous Distributions

Several measures of skewness and kurtosis were proposed by Hogg (1974) in order to reduce the bias of conventional estimators when the distribution is non-normal. Here we conducted a Monte Carlo simulation study to compare the performance of conventional and Hogg’s estimators, considering the most frequent continuous distributions used in health, education, and social sciences (gamma, lognormal and exponential distributions). In order to determine the bias, precision and accuracy of the skewness and kurtosis estimators for each distribution we calculated the relative bias, the coefficient of variation, and the scaled root mean square error. The effect of sample size on the estimators is also analyzed. In addition, a SAS program for calculating both conventional and Hogg’s estimators is presented. The results indicated that for the non-normal distributions investigated, the estimators of skewness and kurtosis which best reflect the shape of the distribution are Hogg’s estimators. It should also be noted that Hogg’s estimators are not as affected by sample size as are conventional estimators.
Fuzzy Logic Applied to Sustainable Development Goals and Human Trafficking

In 2015, the leaders of all the UN’s Member States agreed to the 2030 Agenda for Sustainable Development. The 17 Sustainable Development Goals and their 169 associated targets address five areas of critical importance: people, planet, prosperity, peace, and partnership. The purpose of this paper is to take the metrics and data provided and transform them into a fuzzy logic setting. This allows for the analysis of the results in SDG Index and Dashboards Report 2019 by using the techniques of fuzzy logic. Many of these 17 Sustainable Development Goals are related to the terrible crime of human trafficking. We also examine these goals in a fuzzy logic setting.
Analyse des sentiments et des émotions de commentaires complexes en langue française. (Sentiment and emotion analysis of complex reviews)

Les definitions des mots « sentiment », « opinion » et « emotion » sont toujours tres vagues comme l’atteste aussi le dictionnaire qui semble expliquer un mot en utilisant le deux autres. Tout le monde est affecte par les opinions : les entreprises pour vendre les produits, les gens pour les acheter et, plus en general, pour prendre des decisions, les chercheurs en intelligence artificielle pour comprendre la nature de l’etre humain. Aujourd’hui on a une quantite d’information disponible jamais vue avant, mais qui resulte peu accessible. Les megadonnees (en anglais « big data ») ne sont pas organisees, surtout pour certaines langues – dont la difficulte a les exploiter. La recherche francaise souffre d’une manque de ressources « pret-a-porter » pour conduire des tests. Cette these a l’objectif d’explorer la nature des sentiments et des emotions, dans le cadre du Traitement Automatique du Langage et des Corpus. Les contributions de cette these sont plusieurs : creation de nouvelles ressources pour l’analyse du sentiment et de l’emotion, emploi et comparaison de plusieurs techniques d’apprentissage automatique, et plus important, l’etude du probleme sous differents points de vue : classification des commentaires en ligne en polarite (positive et negative), Aspect-Based Sentiment Analysis des caracteristiques du produit recense. Enfin, un etude psycholinguistique, supporte par des approches lexicales et d’apprentissage automatique, sur le rapport entre qui juge et l’objet juge.
A Novel Surface Inset Permanent Magnet Synchronous Motor for Electric Vehicles

Aiming to successfully meet the requirements of a large output torque and a wide range of flux weakening speed expansion in permanent magnet synchronous motors (PMSM) for electric vehicles, a novel surface insert permanent magnet synchronous motor (SIPMSM) is developed. The method of notching auxiliary slots between the magnetic poles in the rotor and unequal thickness magnetic poles is proposed to improve the performance of the motor. By analyzing the magnetic circuit characteristics of the novel SIPMSM, the notching auxiliary slots between the adjacent magnetic poles can affect the q-axis inductance, and the shape of magnetic pole effects the d-axis inductance of the motor. The combined action of the two factors not only weakens the cogging torque, but also improves the flux weakening capability of the motor. In this paper, the response surface methodology (RSM) is used to establish a mathematical model of the relationship between the structural parameters of the motor and the optimization objectives, and the optimal design of the motor is completed by solving the mathematical model. Experimental validation has been conducted to show the correctness and effectiveness of the proposed SIPMSM.
Weakly Supervised and Semi-Supervised Semantic Segmentation for Optic Disc of Fundus Image

Weakly supervised and semi-supervised semantic segmentation has been widely used in the field of computer vision. Since it does not require groundtruth or it only needs a small number of groundtruths for training. Recently, some works use pseudo groundtruths which are generated by a classified network to train the model, however, this method is not suitable for medical image segmentation. To tackle this challenging problem, we use the GrabCut method to generate the pseudo groundtruths in this paper, and then we train the network based on a modified U-net model with the generated pseudo groundtruths, finally we utilize a small amount of groundtruths to fine tune the model. Extensive experiments on the challenging RIM-ONE and DRISHTI-GS benchmarks strongly demonstrate the effectiveness of our algorithm. We obtain state-of-art results on RIM-ONE and DRISHTI-GS databases.
Determination of Blood Flow Characteristics in Eye Vessels in Video Sequence

Accurately measuring blood flow in eye is an important challenge, as blood flow reflects the health of eye and is disrupted in many diseases. Existing techniques for measuring blood flow are limited due to the complex assumptions and calculations required. Digital image and video processing techniques started to be used for eye vessels analysis and evaluation during last decades. In this paper, we propose a method for determining the characteristics of blood flow in the vessels of eye conjunctiva, such as linear and volumetric blood speed, and topological characteristics of vascular net. The method first analyses image frame by frame sequentially and then builds integral optical flow for video sequence. Dynamic characteristics of eye vessels are introduced and calculated. These characteristics make it possible to determine changes in blood flow in eye vessels. We show the efficiency of our method in real eye vessels scenes.
A 12-bit 30 MS/s Successive Approximation-Register Analog-to-Digital Converter with Foreground Digital Calibration Algorithm

This paper presents a foreground digital calibration algorithm based on a dynamic comparator that aims to reduce comparator offset and capacitor mismatch, as well as improve the performance of the successive approximation analog-to-digital converter (SARADC). The dynamic comparator is designed with two preamplifiers and one latch to facilitate high speed, high precision, and low noise. The foreground digital calibration algorithm provides high speed with minimal area consumption. This design is implemented on a 12-bit 30 MS/s SARADC with a standard 0.13 μm Complementary Metal Oxide Semiconductor (CMOS) process. The simulation Nyquist 68.56 dB signal-to-noise-and-distortion ratio (SNDR) and 84.45 dBc spurious free dynamic range (SFDR) at 30 MS/s, differential nonlinearity (DNL) and integral nonlinearity (INL) are within 0.64 Least Significant Bits (LSB) and 1.3 LSB, respectively. The ADC achieves an effective number of bits (ENOB) of 11.08 and a figure-of-merit (FoM) of 39.45 fJ/conv. -step.