Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of COVID-19 Pandemic on the Relationship between India’s Volatility Index and Nifty 50 Returns

The paper intends to re-examine the relationship between India‟s Implied Volatility Index (IVIX) and Nifty 50 Returns during this COVID-19 pandemic. The study results are important for two reasons, one is to understand whether Indian VIX is fulfilling the purpose of measuring the near future volatility of Nifty 50 during this pandemic, and secondly, it reports the impact of COVID-19 on the investors‟ perceptions about the returns and its volatility. The study results documented that the Nifty return and IVIX are moving independently during the COVID-19 pandemic and there is no association between market size and the market move. The one period lagged Nifty returns have a significant influence on the future market volatility. The combined impact of negative and positive Nifty returns on IVIX is not significant during the COVID-19 period. This implies that the Indian investors are not much worried about the fluctuation in the market price or size of the market during the COVID-19 pandemic period. The investors might be taking the market decline as an opportunity to invest and market rise as an opportunity to sell the stocks. Indian investors are much focused on the fundamentals than the market movements during this pandemic. The study results are important for the fund managers, policymakers, and analysts to understand the dynamics of emerging market volatility and the trading behavior of Indian investors.
PREDICTION OF THE PERFORMANCE OF BITUMINOUS MIXES USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMS

Accurately forecast performance and durability is a critical issue for improving the design of new and existing pavements. The poor pavement performance increases traffic congestion, compromises safety, and raises maintenance costs due to frequent repairs. The resilient modulus is one of the most critical unbound material property inputs in several current pavement design procedures. Recent studies have addressed the problem of resilient modulus prediction using different methods, including computational intelligence approaches. In this paper, a hybrid intelligent system called ANFIS (Adaptive Neuro-Fuzzy Inference System) is used for predicting the resilient modulus from an experimental database of 270 distinct compositions. ANFIS achieved superior performance when estimating the resilient modulus of bituminous mixes, which can potentially save laboratory resources.
In-silico study of some natural compounds used as antifungal agents against Candida albicans

Fungal diseases are very common these days, so there is a high need to design and develop new antifungal drugs that can counter these diseases. Candida albicans is one of the opportunistic pathogenic yeasts that can cause serious diseases such as oropharyngeal candidiasis, vulvovaginal (genital) candidiasis, and invasive candidiasis (candidemia). This article focuses on the in-silico evaluation of anti-candidal activity of some natural compounds like ajoene, allicin, curcumin, gingerol, nimbin, nimbolide, nimonol and 6-Shogaol. Binding affinity of these compounds have been determined against the most common targets in C. albicans viz. cytochrome p450, lanosterol synthase, serine/threonine protein kinase, squalene monooxygenase, sterol-14-demethylase and thymidylate synthase. PatchDock and FireDock web servers were used to carry out the docking studies. The proposed targets of ajoene, allicin, curcumin, gingerol, nimbin, nimbolide, nimonol and 6-Shogaol are sterol 14-demethylase, cytochrome p450, cytochrome p450, cytochrome p450, cytochrome p450, squalene monooxygenase, lanosterol synthase and squalene monooxygenase respectively based upon the binding energies obtained by the docking studies. This study opens new avenues in the usage of the natural compounds as potential antifungal agents. DOI: http://dx.doi. org/10.5281/zenodo.3911299
EXPLORING NASA’S HARMONIZED LANDSAT AND SENTINEL-2 (HLS) DATASET TO MONITOR DEFORESTATION IN THE AMAZON RAINFOREST

Abstract. Deforestation is a threat to biodiversity and the world’s climate. As agriculture and mining areas grow, forest loss becomes unbearable for the environment. Consequently, monitoring deforestation is crucial for decision makers to create polices. The most reliable deforestation data about the Amazon forest is generated by the Brazil’s National Institute for Space Research (INPE) through its PRODES project. This effort is labor and time intensive because it depends on visual interpretation from experts. Additionally, frequent Amazon’s atmospheric phenomena, such as clouds, difficult image analysis which induces alternative approaches such as time series analysis. One way to increase the number of images of an area consists of using images from different satellites. NASA provides the Harmonized Landsat and Sentinel-2 (HLS) dataset solving spectral dissimilarities of satellite sensors. In this paper, the possibilities of HLS for forest monitoring are explored by applying two deforestation detection methods, Break Detection for Additive Season and Trend (BFAST) monitor and Random Forest, over four different vegetation indices, NDVI, EVI, GEMI and SAVI. The SAVI index used as input for BFAST monitor performed the best in this data setup with 95.23% for deforested pixel, 53.69% for non-deforested pixels. Although the HLS data is described as analysis ready, further pre-processing can enhance the outcome of the analysis. Especially, since the cloud and cirrus cover in the Amazon causes gaps in the dataset, a best pixel method is recommended to create patched images and thus a continuous time series as input for any land cover and land use classification.
Investigation and analysis of effect of tear phenomenon of hydraulic hoses of road construction machineries on loss and profits of projects

This research study aimed at evaluating the effect of tear phenomenon of the hydraulic hoses of the road construction machineries on loss and profits of the projects. One of the important and main challenges of the heavy and semi-heavy machineries which are used in the road construction industry is the hose tear phenomenon. This incident depends on several factors including, the performance amount of machinery, weather conditions, natural and artificial factors, quality and kind of the hose, pressing method of the hose, and specially the skill of the operator. The consequences of the hose tear include the sleep of machineries regarding to their heavy expenses of purchasing or hiring, reduction of the efficiency of the other machineries, lag behind the time scheduling for completing the project, inappropriate performance quality of the project, and economic, social and political consequences. In this research, a real comparison between the expenses in two conditions of presence and non-presence of the hose pressing device in the workshop of the section 4 of the Arak-Khoramabad freeway, located at the 30 km of the Biranshahr-Khoramabad road was investigated to achieve the best condition, maximum profit and minimum loss. After evaluating all the conditions of the hose tear in the studied machineries, the results demonstrated that the presence of hose pressing device in the workshop was appropriate and cost-effective regarding to the economical aspect, performance quality of project, time scheduling of the project, social and political views. Therefore, it is suggested that the hose pressing device can be used in all constructive projects where the machineries play a considerable role in their performance.
Investigation of some biochemical mechanisms involved in the resistance of faba bean (Vicia faba L.) varieties to Orobanche spp.

Broomrapes are weedy root parasitic plants that cause important damage to the faba bean production. Genetic resistance is considered as the most desirable control method. In this study, we investigated some of the mechanisms involved in the resistance to Orobanche crenata and O. foetida for two Tunisian resistant varieties Najeh and Chourouk in comparison with the susceptible variety Badi. The results showed that, for Najeh and Chourouk, the Orobanche infestation did not significantly influence the plant growth as indicated by inconsiderable changes in the shoot and root dry weights, pod setting and chlorophyll and carotenoid contents. In comparison to Badi, both resistant varieties showed a reduced Orobanche attachments/tubercles number and dry weights, low H2O2 and malondialdehyde (MDA) accumulation with increased levels of peroxidase activity in the roots. An Orobanche infestation was found to induce a significant decrease in the total lipid content and lipid unsaturation in the Badi leaves only. For resistant varieties, no significant changes were observed in these two parameters, which may indicate conservation and stability in the membrane fluidity. The resistance of Najeh and Chourouk was mainly associated with a relatively more efficient enzymatic antioxidative response and reduced lipid peroxidation that helped the plants to avoid the damaging effect of an Orobanche attack. Therefore, these two varieties could be used as a component of an integrated control strategy to improve the plant growth and productivity under an Orobanche infestation.
Evaluation of Golgi Protein-73 as a Tumor Marker in Patients with Hepatocellular Carcinoma

Background and study aim: Hepatocellular carcinoma (HCC) is the most common type of primary liver tumors. In Egypt, it is the second most common cancer in men, and the sixth most frequent cancer in women. Prognosis of HCC depends on tumor stage, with curative therapies effective only in early stage; thus, new and appropriate HCC markers are highly required. The aim was to evaluate serum diagnostic value Golgi Protein 73 in Egyptian HCC patients. Patients and Methods: This study included 30 HCC patients, 30 cirrhotic patients and 20 healthy controls. For all groups clinical data and imaging results were studied; serum alpha-fetoprotein and Golgi Protein 73 were identified. Evaluation of the tumor characteristics including size, number and location. Okuda, CLIP and Tokyo staging methods used in tumor staging. Results: GP73 was significantly higher in HCC patients compared to cirrhotic patients and controls. Its sensitivity and specificity in HCC diagnosis were 95% and 83.3%, respectively, at cut-off 5.8%. There is a positive correlation between GP73 and Okuda score and ClIP score and no correlations with number and size of the tumor, child's classification, MELD, uMELD and Tokyo stages. Conclusion: GP73 could be a useful diagnostic marker for detection and screening of HCC.
Chromon-3-aldehyde derivatives restore mitochondrial function in rat cerebral ischemia

Objective(s): This work aimed to assess the effect of 10 new chromon-3-aldehyde derivatives on changes of mitochondrial function under the conditions of brain ischemia in rats. Materials and Methods: The work was executed on BALB/c male-mice (acute toxicity was evaluated) and male Wistar rats, which were used to model cerebral ischemia by permanent middle cerebral artery occlusion. The test-substances, 10 derivatives of chromon-3-aldehyde and the reference drug, N-acetylcysteine, were injected after modeling of ischemia for 3 days. After that, neurological symptoms, the area of cerebral infarction, and change in mitochondrial function were evaluated. Results: It was established that use of all chromon-3-aldehyde derivatives contributed to the recovery of mitochondrial function, which was reflected in enhanced ATP-generating activity, maximum respiration level, respiratory capacity, as well as reduction in the intensity of anaerobic reactions, apoptosis, and normalization of the mitochondrial membrane potential. The most pronounced changes were noted with the use of 6-acetyl substituted chromon-3-aldehyde derivative, the administration of which decreased neurological symptoms and size of brain necrosis area. Conclusion: The obtained data may indicate the most pronounced neurotropic effect in a number of test-objects has the 6-acetyl substituted derivative of chromon-3 aldehyde, realized by restoration of mitochondrial function, which may be the basis for further study of chromon-3-aldehyde derivatives.
Pre-eclampsia – An excessive maternal immune response in Egyption wommen.

Preeclampsia is a stressful condition in which many physiological and metabolic functions are altered to a considerable extent.Although pre eclampsia causes high maternal /fetal morbidity, the etiology of this multisystem disorder is still unknown. We have detected the cytokine levels inpreeclamptic women compared to normotensive pregnant and non-pregnant women.This study aimed to understand immunological network , and physiological parameters for the pathogeneses of preeclampsia.Serum levels of tumor necrosis factor alpha (TNFα ) and interleukin 10(IL-10 )were measured by enzyme-linked immunosorbent assay (ELISA) . C reactive protein (CRP) was evaluated as inflammatory marker in preeclampsia.Our findings demonstrated that pre eclamptic state is associated with high levels of pro inflammatory cytokine TNFα (p < 0.05) and C.R. P. By contrast, normotensive pregnancy evolved high levels of regulatory cytokine Il-10 . The present study supports the hypothesis of altered immune response in preeclampsia.
Real Time Face Recognition using Raspberry Pi

Face recognition is a fast growing and challenging area in the ﬁeld of computer vision and real time applications. A lot of techniques and algorithms are available with varying degrees of accuracy and speed. Face recognition has a lot of applications in the ﬁeld of advertising, healthcare, security, accessibility, and even payments. Hence, there is a need for low cost, reliable and accurate face recognition systems in todays world [3]. The aim is to implement a face recognition system using a Raspberry Pi device. This system is part of an assistive device created by us for visually impaired people. The setup consists of a Rasp-berry Pi 3 Model B device with a camera module attached to it. The Raspberry Pi has a 1.2 GHz 64-bit CPU along with 1 GB RAM and the camera module has a resolution of 5 MP.
Caught somewhere in time

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ANTIMICROBIAL ACTIVITY OF A SYNTHETIC BACTERIOCIN FOUND IN THE GENOME OF LACTOBACILLUS CASEI ON THE MICROBIOTA OF ANTIOQUIAN SOFT CHEESE (QUESITO ANTIOQUEÑO)

Background: Lactic Acid Bacteria (LAB) are of special interest in the food industry due to their ability to produce metabolites. Among them, bacteriocins, which can inhibit the growth of altering microorganisms, and pathogens in a wide variety of foods, are considered safe for human consumption and are used as preservatives. Objectives: Evaluate the effect of a bacteriocin found by in silico methods on the microbiota present in Antioquian soft cheese. Methods: In this research, we design a synthetic bacteriocin, called Bac 22, found in the genome of Lactobacillus casei using the genomic mining methodology and bioinformatics tools. We also conducted a preliminary biological and hemolytic activities studies of the Bac 22 toward the microbiota present in the Antioquian soft cheese (Quesito Antioqueño). Results: The bacteriocin Bac 22 at a concentration of 100 μM presented a hemolytic capacity lower than 1% and reduced the CFU / g of total coliforms significantly when added to Antioquian soft cheese for eight days. Conclusions: The Bac 22 demonstrated a positive potential effect over the shelf life of a dairy product, such as the Antioquian soft cheese.
Effect Of Temperature And Storage Time On The Nutritional Quality Of Olive Drupes: A Case Study

In this study we evaluated the effect of temperature and time storage on the quality parameters of mono cultivar olive oil drupes. In particular, analyses of total free phenols, fatty acids, lipophilic and hydrophilic antioxidant capacity, sensory analysis, at different temperatures and different times of post harvest storage, were performed. All data obtained have been singularly processed by Functional Mathematical Index (FMI).
Generic Classification of Modern North American Lycopodiaceae

Generic classification of North American Lycopodiaceae is analyzed in terms of the general factors that govern the recognition of the rank of genus, the character states that determine affinities, the hypothetical common ancestral groundplan, a tree based on these data, and a translation of this information into a classification scheme. The genera segregated here are based primarily on numerous characters of anatomy, chromosomes, spores, and gametophytes. Those groups that are recognized as genera have many distinguishing features, strong gaps separating them from other groups, monophylesis, uniquely derived states, inability to hybridize, and a level of segregation consistent and comparable with generic division in other pteridophytes (.)
‘I FEEL LIKE I GO BLANK’: IDENTIFYING THE FACTORS AFFECTING CLASSROOM PARTICIPATION IN AN ORAL COMMUNICATION COURSE

This paper reports on a case study of seven undergraduate students’ classroom participation in an English-medium university in an EFL context, with a focus on their perceptions about the factors affecting their involvement in interactional opportunities in a specific speaking course. Results suggest that student participation in a foreign language learning setting is a complicated and dynamic process strongly influenced by multiple factors. Students’ participation in the language practices of the classroom and their agentive choices for L2 speaking appear to be contingent on the various individual (psychological and social) factors and contextual and classroom-oriented factors. Therefore, this current piece supports the importance of a holistic understanding of multiple factors to arrive at an in-depth picture of students’ involvement, engagement, and participation.
Toys with Historical References as Part of a Material Culture: An Ethnographic Study on Children's Bedrooms

This paper explores the dimension of toys as part of a historical culture approaching the relationship that children have with the past and with their own past in the form of toys. An Austrian ethnographic research on children's bedrooms in the age between 8 to 11 years can bring a realistic insight to the realm of toys currently used and keepsakes with historical references. The main aim of this study, which is part of a larger project in history education on the private use of public history, is to understand children's lifeworld as informal learning environment. A case study will proof this.
Effect of Incorporation of Self-Healing Microcapsules to Experimental Resin Composite on Some Mechanical Properties

Purpose: The present study aimed to investigate the effect of incorporation of the new Triethylene glycoldimethacrylate and N,N-Bis(2-hydroxyethyl)-p-toluidine (TEGDMA)- (DHEPT) in polyurea formaldehyde (PUF) micro-capsules into an experimental dental resin composite on the flexural strength and fracture toughness and the evaluation of its self- healing efficacy. Materials and Methods: Polyurea formaldehyde microcapsules were synthesized by insitu polymerization technique, encapsulating a triethylene glycol dimethacrylate and dihydroxy ethyl para toluidine (TEGDMA–DHEPT) as a healing liquid, then experimental composite resin is prepared. Microcapsules are incorporated in the resin composite with concentrations 0%, 2.5%, 5%, 7.5% and 10%, then experimental resin composite specimens were fabricated. Fracture toughness and flexural strength were examined by three point loading using universal testing machine till fracture. The fracture toughness was evaluated by using single edge V-notched beam method, self healing efficacy is evaluated as the ratio between the healed fracture toughness and the virgin fracture toughness. Results: Regarding flexural strength results, it was found that the 0% group has the highest flexural strength while the 10% group had the lowest flexural strength. On the other hand, on evaluating the results, of 7.5% group it was found that this concentration did not affect the flexural strength remarkably. Regarding the virgin fracture toughness results, 0% group has the highest flexural strength, while the 10% group the lowest flexural strength, specimens were fractured and healed, then fractured again to measure the healed fracture toughness, on examining the results of the healed fracture toughness, it was found that no significant difference between 0% and 2.5% as no healing occur at such specimen, Also the results showed that the highest healed fracture toughness was in 5%, followed by 7.5%, followed by 10%. The self-healing efficacy increased to a recovery of about 75% in KIC when the microcapsule mass fraction was increased from 5% to 7.5% till reaching 10% concentration. Conclusions: In light of restoration fracture as one of the primary failure reasons, the novel self-healing dental composite may be promising to heal crack damages and to prolong the durability of the restoration clinically.
A new application of exact nonparametric methods to long-horizon predictability tests

Empirical results from long-horizon regression tests have been influential in the finance literature. Yet, it has come to be understood that traditional long-horizon tests may be unreliable in finite samples when regressors are persistent and when the horizon is long relative to sample size. Recent research has provided valid alternative inference procedures in long-horizon regression in the case for which the regressor follows a near-unit root autoregressive process. However, in small samples, such processes may sometimes be difficult to distinguish with confidence from other persistent data generating processes, such as those displaying long-memory or structural breaks. In this paper, we demonstrate a simple means by which existing nonparametric sign and signed rank tests may be applied to provide exact inference in long-horizon predictive tests, without requiring any modelling assumptions on the regressor. Employing this robust approach, we find evidence of stock return predictability at moderate horizons using short-term interest rates, but little evidence of either short or long-run predictability using dividend-price ratios. JEL Classification: C12,C22,G14
An Ellipsoid Object Model of the Refraction Surface

Geometric image distortions appear when cameras register the image from behind a refractive object – e.g. a car windshield. To ensure the reliability of 3D perception algorithms, a distortion model is necessary. The model has to be general enough to capture the variety of possible refractive object geometries. We propose a method where we directly model the refractive media as a thick ellipsoid, and compute the resultant distortions by tracing individual light rays as they refract on the inner and outer surface of the object. With this new ellipsoid model provides flexibility and via the model parameters we are able to capture all important factors influencing distortions, namely the curvature of the surfaces, position relative to the camera, and thickness of the refractive material. We test the proposed model on a synthetic dataset, analyzing the advantages and possible failure cases of our method.