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Data for Analysis of Nano-Silica and Xanthan Gum as a High-Temperature Thixotropic Agent for Oil-Well Cement
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Supplementary materials corresponding to the identically named paper including R scripts, derived data sets, and the full statistical test results.
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The raw sequencing data obtained from hamsters treated with different interventions including 1) standard diet (control); (2) standard diet and monosodium glutamate (MSG) in drinking water (MSG); (3) high-fat and high-fructose diets (HFF), and (4) MSG+HFF.
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Total RNA was purified from E. pacifica using with an RNeasy Lipid tissue mini kit. The library of E. pacifica for next generation sequencing was made using with a TruSeq RNA library prep kit v2 (Illumina). RNA purification and library preparation were performed according to the manufacturers’ instructions. The library was analyzed by Miseq using a Miseq reagent kit v3 (600 cycle) (Illumina). The fastaq data was assembled by Trinity.
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The repository contains the ERP data for self-face, friend's face and other's face perception. Raw Data folder contain the EEG data in Brain Products format. Epoched Data folder contain processed EEG data in EEGLAB format. sLORETA files folder contain data of source mean amplitude within-cluster of significant correlations between ERP and heartbeat perception scores. Also, repository include subject description file with the antropometric and psychometric data.
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Geometric and energetic features of halogenated rotamers of the following backbone structures, C-C, N-N, P-P, O-O, S-S, N-P, O-S, C-N, C-P, C-O, C-S, N-O, N-S, P-O and P-S from quantum chemical calculations are presented. The data set is considered to be comprehensive combinations of non-metal elements in the form abcx-ydef whereby a,b,c,d,e,f are halogen (fluorine to iodine), hydrogen or a lone pair and x,y are carbon, nitrogen, phosphorus, oxygen and sulfur. Preliminary work on all possible halogenation of methane, ammonia, phosphine, water and hydrogen sulfide are also included.
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Data accompanied with the paper "Reliability and Validity of the Turkish Version of the Health Professionals Communication Skills Scale (HP-CSS)". The sample consisted of 394 health professionals in Turkey.
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resources from the w.p. 'Uncertainty and stochastic theories on derivatives and risk valuation', by C. Alexander Grajales, Santiago Medina, 2020 * Matlab code * output data * paper figures
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This dataset is about a systematic review of unsupervised learning techniques for software defect prediction (our related paper: "A Systematic Review of Unsupervised Learning Techniques for Software Defect Prediction" in Information and Software Technology [accepted in Feb, 2020] ). We conducted this systematic literature review that identified 49 studies which satisfied our inclusion criteria containing 2456 individual experimental results. In order to compare prediction performance across these studies in a consistent way, we recomputed the confusion matrices and employed MCC as our main performance measure. From each paper we extracted: Title, Year, Journal/conference, 'Predatory' publisher? (Y | N), Count of results reported in paper, Count of inconsistent results reported in paper, Parameter tuning in SDP? (Yes | Default | ?) and SDP references(SDPRefs OrigResults | SDPRefs |SDPNoRefs | OnlyUnSDP). Then from within each paper, we extracted for each experimental result including: Prediction method name (e.g., DTJ48), Project name trained on (e.g., PC4), Project name tested on (e.g., PC4), Prediction type (within-project | cross-project), No. of input metrics (count | NA), Dataset family (e.g., NASA), Dateset fault rate (%), Was cross validation used? (Y | N | ?), Was error checking possible? (Y | N), Inconsistent results? (Y | N | ?), Error reason description (text), Learning type (Supervised | Unsupervised), Clustering method? (Y | N | NA), Machine learning family (e.g., Un-NN), Machine learning technique (e.g., KM), Prediction results (including TP, TN, FP, FN, etc.).
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Smoke Test 17Feb2020 rdmmibtest1 (Dataset-1)
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