Elaboration of the Recipe of the Fermented Milk Dessert for Child Food

Using the tabular processor MS Excel 2007 there was elaborated the recipe of the fermented milk dessert for child food. The recipe of this dessert consists of (mass. %, g): fermented milk curd – 54, jam – 23, honey – 8, sesame – 4, cream – 6, collagen hydrolyzate (gluten) – 5. This dessert is a source of vitamin C and covers near 40 % of a child daily need in it. At the expanse of introducing gluten in the dessert composition, protein content in the ready product increased that covers from 11,28 % to 22,56 % of a daily need. This dessert is also rich in calcium, so one portion of it covers 25 % of a child need.Based on theoretical qualimetry methods there was realized the complex estimation of the dessert quality. The hierarchic structure of ready product properties was presented, including organoleptic and physical-chemical parameters and also ones of the food and biological value at storage.The estimation of microbiological and organoleptic parameters at storage give a possibility to state, that the new fermented milk dessert will be competitive at the consumer market. The storage life of this product is 5 days at the temperature (4±2) °С

Microbial diversity in heavy-metal polluted waters

Indigenious water microflora as well as the presence of metal- and xenobiotic biotransforming bacteria were investigated in waters near the KCM Pb-Zn smelter, South Bulgaria. Content of As, Hg, Cd, Mn, Pb, Cu and Zn exceeded in times the maximum permission standart. Absence of some microbial groups demonstrated a change in the microbial community structure in the region. Ecotoxicology test ISO/DIS 10712.2 displayed toxic environmental effect of the polluted waters, especially one of them which demonstrated 72 % of ecotoxicity. More than 20 ecologically relevant new bacteria were cultured. Three of them demonstrated tolerance to Cd, Cu and Mn and five- a tolerance to 2,4-dichlorphenoxyacetic acid. Our result revealed that the heavy metal pollutions reduced the microbial diversity in the studied waters, are ecotoxic as well as that some of newly isolated bacteria possess a capacity for a clean-up biotechnologies in the region. . 1, . 2, 2., 3, 3, .

Modeling judgment of sequentially presented categories using weighting and sampling without replacement

In a series of experiments, Kusev et al. (Journal of Experimental Psychology: Human Perception and Performance 37:1874–1886, 2011) studied relative-frequency judgments of items drawn from two distinct categories. The experiments showed that the judged frequencies of categories of sequentially encountered stimuli are affected by the properties of the experienced sequences. Specifically, a first-run effect was observed, whereby people overestimated the frequency of a given category when that category was the first repeated category to occur in the sequence. Here, we (1) interpret these findings as reflecting the operation of a judgment heuristic sensitive to sequential patterns, (2) present mathematical definitions of the sequences used in Kusev et al. (Journal of Experimental Psychology: Human Perception and Performance 37:1874–1886, 2011), and (3) present a mathematical formalization of the first-run effect—the judgments-relative-to-patterns model—to account for the judged frequencies of sequentially encountered stimuli. The model parameter w accounts for the effect of the length of the first run on frequency estimates, given the total sequence length. We fitted data from Kusev et al. (Journal of Experimental Psychology: Human Perception and Performance 37:1874–1886, 2011) to the model parameters, so that with increasing values of w, subsequent items in the first run have less influence on judgments. We see the role of the model as essential for advancing knowledge in the psychology of judgments, as well as in other disciplines, such as computer science, cognitive neuroscience, artificial intelligence, and human–computer interaction

Judgments Relative to Patterns: How Temporal Sequence Patterns Affect Judgments and Memory

Six experiments studied relative frequency judgment and recall of sequentially presented items drawn from 2 distinct categories (i.e., city and animal). The experiments show that judged frequencies of categories of sequentially encountered stimuli are affected by certain properties of the sequence configuration. We found (a) a first-run effect whereby people overestimated the frequency of a given category when that category was the first repeated category to occur in the sequence and (b) a dissociation between judgments and recall; respondents may judge 1 event more likely than the other and yet recall more instances of the latter. Specifically, the distribution of recalled items does not correspond to the frequency estimates for the event categories, indicating that participants do not make frequency judgments by sampling their memory for individual items as implied by other accounts such as the availability heuristic (Tversky & Kahneman, 1973) and the availability process model (Hastie & Park, 1986). We interpret these findings as reflecting the operation of a judgment heuristic sensitive to sequential patterns and offer an account for the relationship between memory and judged frequencies of sequentially encountered stimuli

Classification of online toxic comments using the logistic regression and neural networks models

The paper addresses the questions of abusive content identification in the Internet. It is presented the solving of the task of toxic online comments classification, which was issued on the site of machine learning Kaggle (www.Kaggle.com) in March of 2018. Based on the analysis of initial data, four models for solving the task are proposed: logistic regression model and three neural networks models - convolutional neural network (Conv), long shortterm memory (LSTM), and Conv + LSTM. All models are realized as a program in Python 3, which has simple structure and can be adapted to solve other tasks. The results of the classification problem solving with help of proposed models are presented. It is concluded that all models provide successful solving of the task, but the combined model Conv + LSTM is the most effective, so as it provides the best accuracy. © 2018 Author(s)

NEW PRODUCT FROM BULGARIAN ROSE

The chemical composition of extract from rosa (Rosa damascena Mill.) by extraction with tetrafluoroethane was analyzed using GC and GC/MS. The main compounds (concentration higher than 3%) of extract were: phenylethyl alcohol (59.08%) and citronellol (12.31%).The chemical composition of extract from rosa (Rosa damascena Mill.) by extraction with tetrafluoroethane was analyzed using GC and GC/MS. The main compounds (concentration higher than 3%) of extract were: phenylethyl alcohol (59.08%) and citronellol (12.31%)

Impregnation as a method for preservation of relics used by the Christian Church

Relics are a special type of human body remains, which are venerated by the faithful due to the prominence the person had achieved during lifetime. Even if no such claims for incorruptibility are made, body relics have to be preserved in some fashion, in order to allow for their long-term viewing and veneration. The present report summarizes the available data regarding the impregnation as a method for body preservation, used by the Christian Church to conserve body relics. Impregnation is a widely used method, both by the Orthodox as well as by the Roman Catholic Church. It is known that bodies are treated with different protective mixtures on variable intervals after death. Public worship historically involved pouring of oil over relics. Moreover, small tissue fragments are embedded in wax blocks or are sealed with a mixture of molten wax and other resins. All of those methods are in fact impregnation with compounds with high molecular mass as a final stage of a preservation procedure. This impregnation of a tissue already reached some degree of dehydration or other preservation ensures longevity and protection of the relics by greatly slowing down the natural processes of decomposition and disintegration

GeTallele: A Method for Analysis of DNA and RNA Allele Frequency Distributions

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData Availability Statement: The data analyzed in this study is subject to the following licenses/restrictions: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Requests to access these datasets should be directed to [email protected] allele frequencies (VAF) are an important measure of genetic variation that can be estimated at single-nucleotide variant (SNV) sites. RNA and DNA VAFs are used as indicators of a wide-range of biological traits, including tumor purity and ploidy changes, allele-specific expression and gene-dosage transcriptional response. Here we present a novel methodology to assess gene and chromosomal allele asymmetries and to aid in identifying genomic alterations in RNA and DNA datasets. Our approach is based on analysis of the VAF distributions in chromosomal segments (continuous multi-SNV genomic regions). In each segment we estimate variant probability, a parameter of a random process that can generate synthetic VAF samples that closely resemble the observed data. We show that variant probability is a biologically interpretable quantitative descriptor of the VAF distribution in chromosomal segments which is consistent with other approaches. To this end, we apply the proposed methodology on data from 72 samples obtained from patients with breast invasive carcinoma (BRCA) from The Cancer Genome Atlas (TCGA). We compare DNA and RNA VAF distributions from matched RNA and whole exome sequencing (WES) datasets and find that both genomic signals give very similar segmentation and estimated variant probability profiles. We also find a correlation between variant probability with copy number alterations (CNA). Finally, to demonstrate a practical application of variant probabilities, we use them to estimate tumor purity. Tumor purity estimates based on variant probabilities demonstrate good concordance with other approaches (Pearson's correlation between 0.44 and 0.76). Our evaluation suggests that variant probabilities can serve as a dependable descriptor of VAF distribution, further enabling the statistical comparison of matched DNA and RNA datasets. Finally, they provide conceptual and mechanistic insights into relations between structure of VAF distributions and genetic events. The methodology is implemented in a Matlab toolbox that provides a suite of functions for analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies distributions. GeTallele is available at: https://github.com/SlowinskiPiotr/GeTalleleMcCormick Genomic and Proteomic Center (MGPC)George Washington UniversityWellcome TrustEngineering and Physical Sciences Research Council (EPSRC