Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability of C-reactive protein as a predictor of early neurological deficit in acute ischemic stroke: is it only to be blamed? a retrospective observational study

Background: Ischemic Stroke is a common cause of morbidity and mortality. Various parameters, both clinical and laboratory have been studied as markers of Early Neurological Deterioration (END) out of which CRP has been the most important. This retrospective study of ours is an attempt to study its influence on END by minimizing other variables as much as possible. Methods: 50 patients were chosen retrospectively strictly according to laid down inclusion and exclusion criteria, their data recorded and analyzed with 17.0 SPSS software. Any p value <0.05 was taken as significant. Results: Significantly raised CRP values were found in elderly patients (p=0.0001) and in males (p=0.003). Higher incidences of ENDs were also found in elderly patients (p=0.326) and males (p=0.846) and patients with raised CRP levels (p=0.057). Conclusions: Higher Values of CRP are associated with increased frequency of ENDs. But in patients with multiple factors which can influence both CRP and END, CRP alone should not be thought of as the only culprit.
Connecting the Demons How connection choices of a Horde implementation affect Demon prediction capabilities

The reinforcement learning framework Horde, developed by Sutton et al. [9], is a network of Demons that processes sensorimotor data to general knowledge about the world. These Demons can be connected to each other and to data-streams from specific sensors. This paper will focus on how and if the capability of Demons to learn general knowledge is affected by different numbers of connections with both other Demons and sensors. Several experiments and tests where done and analyzed to map these effects and to provide insight in how these effects arose.
Software Piracy Detection using Deep Learning Approach

Software piracy can be referred as illegally stealing citations. Currently, every other installed software is pirated. There are many scenarios of this happening, the attacker may crack the original legal software and re-construct or re-design the logic into other programming language or may change minor details of the software. It is very exasperating to catch such assaulters malicious activities as all the programming language have their own syntax and semantic structures. Currently, software piracy is high risk for security of software. It may cause reputational and economic damages. Now a days every other software is pirated there are many scenarios in which it can occur, the programmer may crack the original legal software and reconstruct or re-design the logic into other programming languages or may change the minor details of the software so we proposed a combine Deep learning approach to detect the pirated software. The Tensor Flow deep neural network is proposed to identify pirated the techniques like Tokenization and weighting are used to filter noisy data. The dataset is collected from Google code Jam (GCJ) to find the software piracy. The process of software piracy is very exasperating to each such assaulter malicious activities as all the programming languages have their own syntax and semantic structure. The experiment result shows that how much percentage of software code is plagiarism which be effective from current available methods. Keywords— Deep Learning, Machine Learning, Tensor Flow, Piracy, Neural Network, Plagiarism, TF-IDF.
The Impact of Instagram Influencers for a Purchase Decision of Fashion Items from a Belgian Female Millennials' Perspective

The objective is to gain new insights in the impact of social media influencers for the purchase of fashion products. To be able to answer these objectives successfully, this research was conducted by applying a positivism and a deductive approach with a quantitative data collection and analysis. A questionnaire was used for the quantitative data collection. The nonprobability sample techniques in this research are a combination of self-selection sampling and snowball sampling. The analysis of the data showed that the higher the credibility of an social media influencer, the higher the purchase intention. Moreover, the most credible social media influencers where those from Belgium. However, the credibility of an social media influencer did not affect the conspicuous consumption of fashion products. Although as the millennials followed more social media influencers, the higher the conspicuous consumption. Therefore, this research tries to help fashion brands in determining the best possible way of reaching Belgian female millennials. Since this research is an quantitative study, it can be done using an qualitative approach to create more in-depth understanding about the reasons of a purchase intention or conspicuous consumption. In addition, this research can be applied again in other countries to see if the results differ.
Rcts to Scale: Comprehensive Evidence from Two Nudge Units

Nudge interventions have quickly expanded from academic studies to larger implementation in so‐called Nudge Units in governments. This provides an opportunity to compare interventions in research studies, versus at scale. We assemble a unique data set of 126 RCTs covering 23 million individuals, including all trials run by two of the largest Nudge Units in the United States. We compare these trials to a sample of nudge trials in academic journals from two recent meta‐analyses. In the Academic Journals papers, the average impact of a nudge is very large—an 8.7 percentage point take‐up effect, which is a 33.4% increase over the average control. In the Nudge Units sample, the average impact is still sizable and highly statistically significant, but smaller at 1.4 percentage points, an 8.0% increase. We document three dimensions which can account for the difference between these two estimates: (i) statistical power of the trials; (ii) characteristics of the interventions, such as topic area and behavioral channel; and (iii) selective publication. A meta‐analysis model incorporating these dimensions indicates that selective publication in the Academic Journals sample, exacerbated by low statistical power, explains about 70 percent of the difference in effect sizes between the two samples. Different nudge characteristics account for most of the residual difference.
Field behavior of potted seedlings of strawberry plants in different growing seasons

Brazil, the largest strawberry producer in South America, has yielded about 120,000 ton in approximately 4,000 ha, mostly located in Minas Gerais (MG), São Paulo (SP) and Rio Grande do Sul (RS) states, at latitudes between 20° and 32° S (Kirschbaum et al., 2017). However, most strawberry plants used in the country have been imported from Patagonia (Argentina and Chile), due to excellent local growing conditions (Antunes and Peres, 2013; Gonçalves et al., 2016), which enable high resource (carbohydrate) accumulation (Cocco et al., 2016). This situation has made producers get increasingly dependent on plant importation and has obliged them to adapt cultivation to the period of plant arrival, which is often not the recommended one for growing strawberries in Brazil (Dal Picio et al., 2013). An important factor that enables strawberry producers to show their productive potential is the right growing season (Rahman et al., 2014). Pelotas, RS, where the climate is mild, has temperatures that favor blooming and fructification. They range between 13oC and 26 oC, from May on. According to Passos et al. (2015), planting seasons should take place between March and April. However, it occurs in May and June lately, as the result of delay in the delivery of imported plants (Antunes and Peres, 2013). Thus, early production has been limited in winter months, which is the period with high sale prices due to low supply in the market (Cocco et al., 2015).
Exploring the capabilities of TM and AVIRIS sensor images for oil spill detection in marine and ocean waters

Oil spills are major water polluting sources. Due to its devastating effects on the sea and ocean ecosystem, detecting oil pollution in the shortest time and with the highest confidence level is necessary. Remote sensing being a suitable option, the capability of Landsat multispectral data and airborne hyper-spectral data from the AVIRIS sensor was investigated for study of the 2001 oil spill in the Gulf of Mexico. In this study, a part of the 2001 oil spill data was processed in terms of cloud spots,bad pixel and atmospheric correction. The pixel purity index was used to extract the end -members of water and oil spill and the linear spectral unmixing method was used for mapping of water from oil spills. The results show that the AVIRIS image is able to detect the type and thicknesses of oil spill, due to its ability to cover the diagnostic spectral signature of oil.Keywords: Monitoring, oil spill, remote sensing, Landsat, AVIRIS.
NetWarden: Mitigating Network Covert Channels while Preserving Performance

Network covert channels are an advanced threat to the security of distributed systems. Existing defenses all come at the cost of performance, so they present signiﬁcant barriers to a practical deployment in high-speed networks. We propose NetWarden , a novel defense whose key design goal is to preserve TCP performance while mitigating covert channels. The use of programmable data planes makes it possible for Net-Warden to adapt defenses that were only demonstrated before as proof of concept, and apply them at linespeed. Moreover, NetWarden uses a set of performance boosting techniques to temporarily increase the performance of connections that have been affected by covert channel mitigation, with the ultimate goal of neutralizing the overall performance impact. NetWarden also uses a fastpath/slowpath architecture to combine the generality of software and the efﬁciency of hardware for effective defense. Our evaluation shows that NetWarden works smoothly with complex applications and workloads, and that it can mitigate covert timing and storage channels with little performance disturbance.
Genetic Mutations in CFTR Protein Gene Cause Cystic Fibrosis- Its Symptoms, Treatment, and Incidence in Pakistan

Genetic mutations in the CFTR protein gene cause Cystic Fibrosis. For disease occurrence, individuals have to inherit two defective genes of CFTR from each parent. CFTR mutations are distributed into six classes. Though CF affects all ethnic as well as racial groups, but in Caucasians of North European origin, it is more common. The clinical representations of CF include raised NaCl cons. in sweat glands, deficiency of pancreatic enzymes, azoospermia in adult males, and decline in lung function which leads to pulmonary exacerbations. The therapies for CF are gene therapy, CFTR modulators, potentiators, correctors, and stop codon suppressors. The incidence of CF in Pakistan is low as it is more common in Caucasians. Due to lack of suitable diagnostic tools, this disease is often neglected in Pakistani population.
Anthopometry Data Measurement Methods of the Hand and Biomechanical Hand Model

The aim of this study was to suggest the measurement methods of anthropometric data for segment masses, centers of mass (COMs) of inertia segments, and gyration radii, which are required for the development of the biomechanical hand model. The segment masses were calculated based on the segment volumes using a density of 1.1 g/cm. The COMs for the proximal and middle segments, and the distal segment were determined by approximating the phalanx with the cone frustum and a cylindrical homogeneous rigid body, respectively. Proximal and middle segment moments of inertia were determined by approximating the phalanx with the frustum of a conical homogenous rigid body. The biomechanical hand model consists of multiple complex structures, and 26 degrees of freedom were considered in total. The coordinate system for calculating the angle of each joint followed the recommendations of the International Society of Biomechanics. Euler angles were used to define the three-dimensional relative joint angular motion, and the Newtonian laws of statics were used to describe the forces and moments acting on the thumb and finger segments. This model can be used to perform kinetic and kinematic analysis for human hand posture.
Use Of Electrochemical Activated Water During Propagation Of Biomaterials In Bio Factory

The introduction of advanced technologies in industry, the national and agricultural sectors, and thereby improving the economic performance of the state, is today one of the urgent problems. Pests are one of the factors that reduce crop yields. Today in the world there are more than 80 thousand pests, of which 10 thousand have very great harm to plants. Calculations show that as a result of exposure to pests in the world more than 30% of crops are lost annually. In this regard, the protection of plants from various pests is one of the urgent problems. Of great importance is the conduct of scientific research in the field of widespread use of biological methods of protecting plants from pests, as well as improving the effectiveness of the biomaterials used. The biological method is considered effective from both an economic and economic point of view. The article discusses the development of a new technology for the production of trichograms for use as a means of protection against cotton pests.
Politics in Space Methodological Considerations for Taking Space Seriously in Subnational Research

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On evapotranspiration and eddy covariance measurements corrections

Abstract. Eddy Covariance (EC) technique is one of the most used technique monitoring Green House Gases (GHG) fluxes such as H2O, CO2, CH4. Water vapor movement and corresponding air density fluctuations were corrected by Webb et al. (1980) but not water vapor formation. Classic EC technique supposes mean air vertical speed nullity when it cannot be the case because of water evaporation. Water is falling as a liquid, evaporating directly from soil surface, from shallow soil subsurface or either through vegetation transpiration and becomes a gas which corresponds to a notable volume expansion. Water vapor is mounting through atmosphere, compensating in a cloud and falling as a rain (liquid) again. Evaporation and corresponding volume expansion make mean vertical air speed positive (upgoing) and influence more or less a flux balance following concerned gas or energy. A simple accessing and corresponding correction for the half hourly summation is given and applied to a 11-month real set of data. These corrections allow to explain, in part, most observed eddy covariance discrepancies.
Constructing knowledge graph from unstructured text

A knowledge graph is a structured graphical representation of semantic knowledge and relations where nodes in the graph represent the entities and the edges represent the relation between them. Constructing a knowledge graph involve extracting relations from unstructured text followed by eﬃcient storage in graphical databases.In this project, we propose a method for extracting relations using semantic regularity in the distributed word vector embedding space. Such a semi-supervised approach is independent of language syntax and can be used to extract relations from any language. We also investigate various similarity metrics to annotate each extracted relation with a conﬁdence score. We use ’Neo4j’ graphical database for eﬃcient storage of extracted relations and constructing a knowledge graph. We further build a question answering system that parses the natural language queries using regular expressions and extracts answers from the knowledge graph.
Leukocyte Telomere Length Independently Predicts 3-Year Diabetes Risk in a Longitudinal Study of Chinese Population

Cellular aging markers, including telomere length and mitochondrial function, as well as oxidative stress and inflammation markers influence each other and form a complex network, which is affected in diabetes. However, it remains unknown whether these markers could independently predict future diabetes after adjustment for their mutual effects. We conducted a 3-year longitudinal study in a Chinese cohort that comprised 108 nondiabetic individuals at baseline. The 2-hour 75 g oral glucose tolerance tests were performed at baseline and at 3-year follow-up. At baseline, leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNAcn) in leukocytes were determined using the polymerase chain reaction method. Tumor necrosis factor (TNF-α), interleukin-6, 8-hydroxy-2-deoxyguanosine levels, and superoxide dismutase (SOD) activity were measured by the enzyme-linked immunosorbent assay. Participants who developed diabetes at the 3-year follow-up (n = 28) had shorter LTL and higher levels of TNF-α and SOD activity at baseline. Baseline LTL was found to be independently associated with the development of diabetes at the 3-year follow-up after the adjustment for mtDNAcn, markers of oxidative stress and inflammation, and conventional diabetes risk factors. Our findings suggest that LTL is an independent predictor for 3-year diabetes risk, which might inform timely prevention and treatment of diabetes. Telomere shortening might be involved in the pathogenesis of diabetes independently of conventional diabetes risk factors, mtDNAcn, or oxidative stress and inflammation pathways.
Development of Parametric and Time Dependent Reduced Order Model for Diffusion and Convection-Diffusion Problems Based on Proper Orthogonal Decomposition Method

Simulation and numerical analysis of physical phenomena, especially for unstable problems, due to dependency of the numerical algorithms on the computer hardware to the increasing of the number of computational nodes, is the most important features of their solutions. For this reason, increases the number of computations then increased computational costs. The order reduction method is one that has been widely used in recent years to reduce computational time. In this way, by reducing the constraints of the system, without changing the inherent features of the problem, the computational efficiency will dramatically increase. In this study, using the basic concepts of dynamical systems, two problems of thermal diffusion and convection-diffusion are investigated independently and by using the proper orthogonal analysis method, a reduced order model is established for the equations governing these phenomena created. Accordingly, for each of the problems, based on the projection of the governing equation in the vector space of modes, by using more energetic modes, a reduced order model is obtained with respect to the orthogonal basis properties. The model obtained in order to simulate the process time variations can properly replace the original equation and predict the behavior of the system with very good accuracy.
From subduction to collision in the Parautochthon and autochthon of the NW Variscan Iberian Massif

Abstract. A stacking of nappes forms the Parautochthonous Domain located beneath the Allochthonous Complexes of the NW Iberian Massif. Lower Paleozoic metasedimentary and felsic metavolcanic rocks, including some riebeckite gneiss, form the uppermost nappe of the Parautochthon. Micaschists of this nappe may contain albite porphyroblasts with aligned mineral microinclusions defining a relic internal schistosity. Thermobarometric estimates on the relic mineral assemblage suggest an early M1 stage of High-Pressure, Low-Temperature (HP-LT) metamorphism (11–14 kbar; 450–500 °C), probably related to the same continental subduction process that affected the overlying Lower Allochthon nappes or Basal Units. This uppermost nappe was emplaced onto its relative autochthon by a broad, ductile shear zone that shows top-to-the-E/ENE shear-sense and whose exposure has lateral continuity through to the basal thrust of the Lower Allochthons in the Braganca Complex. The HP-LT metamorphism and its hanging wall position relative to the basal thrust of the Allochthonous Complexes, suggest a re-interpretation of this uppermost parautochthonous nappe as another nappe of the Lower Allochthon. In turn, the other parautochthonous nappes comprise both, Lower Paleozoic pre-orogenic rocks, with no M1 relics, and Upper Paleozoic syn-orogenic rocks. Shear-sense criteria related to the current juxtaposition of the Parautochthon Domain onto the Central Iberian autochthon show contrasting top-to-the-S/SE kinematics. The whole orogenic section was affected by an M2 episode of recrystallization under intermediate P/T conditions during the first stages of collision. P-T estimates on kyanite-bearing schists from the upper sections of the autochthon (9.0 kbar; 425–450 °C) are consistent with a geothermal gradient somewhat lower than the classical Barrovian one at the beginning of collision. Thermobarometric calculations on schists from the lower parautochthonous nappes yield peak metamorphic conditions around 7.5 Kbar and 600–700 °C, constraining the original thickness of the allochthonous/parautochthonous pile to about 22.5–27.0 km. Schists sampled from deeper sections of the autochthon yield M2 conditions around 11–12 kbar and 700–725 °C, matching those registered by correlative regions from Central Iberia. Subsequent M3 syn-collisional recrystallization under High-Temperature and Low-Pressure conditions is associated with top-to-the-N/NW and top-to-the-S/SE extensional flow. The early metamorphic evolution of the autochthons, Parautochthon and Allochthonous Complexes of NW Iberia recorded a transition in P/T regimes and appears as a model case of a change from subduction to collision.
Draft Label Free Proteomic Analysis Reveals Large Dynamic Changes to the Cellular Proteome Upon Expression of the miRNA-23 a27 a-24-2 MicroRNA Cluster

Journal: Biochemistry and Cell Biology Manuscript ID bcb-2019-0014.R1 Manuscript Type: Article Date Submitted by the Author: 17-Apr-2019 Complete List of Authors: Piragasam, Ramanaguru; University of Alberta, Biochemistry Hussain, S; University of Alberta, Medicine Chaulk, Steven; University of Alberta, Biochemistry Siddiqi, Zaeem; University of Alberta, Medicine Fahlman, Richard P.; University of Alberta, Biochemistry Keyword: miRNA, miR-23~24, label free proteomics, miR23a, miR27a Is the invited manuscript for consideration in a Special Issue? : Ribowest RNA
Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

AuTODocK is a molecular docking application that consists of a genetic algorithm coupled with the Solis-Wets local-search method. Despite its wide usage, its power consumption on heterogeneous systems has not been evaluated extensively. In this work, we evaluate the energy efficiency of an OpenCL-accelerated version of AUTODOCK that, along with the traditional SolisWets method, newly incorporates the ADADELTA gradient-based local search. Executions on a Nvidia V100 GPU yielded energy efficiency improvements of up to 297x (Solis-Wets) and 137x (ADADELTA) with respect to the original AUTODOCK baseline.