Bayesian Processing of Data on Bursts of Pressure Vessels

Two alternative Bayesian approaches are proposed for the prediction of fragmentation of pressure vessels triggered off by accidental explosions (bursts) of these containment structures. It is shown how to carry out this prediction with post-mortem data on fragment numbers counted after past explosion accidents. Results of the prediction are estimates of probabilities of individual fragment numbers. These estimates are expressed by means of Bayesian prior or posterior distributions. It is demonstrated how to elicit the prior distributions from relatively scarce post-mortem data on vessel fragmentations. Specifically, it is suggested to develop priors with two Bayesian models known as compound Poisson-gamma and multinomial-Dirichlet probability distributions. The available data is used to specify non-informative prior for Poisson parameter that is subsequently transformed into priors of individual fragment number probabilities. Alternatively, the data is applied to a specification of Dirichlet concentration parameters. The latter priors directly express epistemic uncertainty in the fragment number probabilities. Example calculations presented in the study demonstrate that the suggested non-informative prior distributions are responsive to updates with scarce data on vessel explosions. It is shown that priors specified with Poisson-gamma and multinomial-Dirichlet models differ tangibly; however, this difference decreases with increasing amount of new data. For the sake of brevity and concreteness, the study was limited to fire induced vessel bursts known as boiling liquid expanding vapour explosions (BLEVEs).

Explosions of Cylindrical Pressure Vessels Subjected to Fire: Probabilistic Prediction of a Number of Fragments

The aim of this study was to propose a procedure for a prediction of the number of fragments generated by fire induced explosions of cylindrical pressure vessels. The prediction is carried out in terms of probabilities of individual fragment numbers. The prevailing numbers of two to four fragments are considered. The fragment number probabilities are estimated by applying data on vessel fragmentations acquired in investigations of past explosion accidents. The pressure vessel explosions known as BLEVEs are considered. The Bayesian analysis is used for the estimation of the fragment number probabilities. This analysis is carried out on the basis of Poisson-gamma model. An approach to developing a gamma prior distribution for the average number of fragments per explosion accident is proposed. The assessment of the fragment number probabilities is carried out by propagating uncertainty related to the average number of fragments to uncertainty in the fragment number probabilities. The stochastic (Monte Carlo) simulation is used for this propagation. Findings of this study are viewed as a possibility to improve the assessment of risk posed by pressure vessel explosions.

Proteomic Database Search Engine for Two-Dimensional Partial Covariance Mass Spectrometry

<div>We present a protein database search engine for the automatic identi?cation of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Since 2D-PC-MS measurement reveals correlations between fragments stemming from the same or consecutive decomposition processes, the ?first-of-its-kind 2D-PC-MS search engine is based entirely on the direct matching of the pairs of theoretical and the experimentally detected correlating fragments, rather than of individual fragment signals or their series. We demonstrate that the high structural speci?city a?orded by 2D-PC-MS fragment correlations enables our search engine to reliably identify the correct peptide sequence, even from a spectrum with a large proportion of contaminant signals. While for peptides the 2D-PC-MS correlation matching procedure is based on complementary and internal ion correlations, the identi?cation of intact proteins is entirely based on the ability of 2D-PC-MS to spatially separate and resolve the experimental correlations between complementary fragment ions.</div>

Proteomic Database Search Engine for Two-Dimensional Partial Covariance Mass Spectrometry

<div>We present a protein database search engine for the automatic identi?cation of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Since 2D-PC-MS measurement reveals correlations between fragments stemming from the same or consecutive decomposition processes, the ?first-of-its-kind 2D-PC-MS search engine is based entirely on the direct matching of the pairs of theoretical and the experimentally detected correlating fragments, rather than of individual fragment signals or their series. We demonstrate that the high structural speci?city a?orded by 2D-PC-MS fragment correlations enables our search engine to reliably identify the correct peptide sequence, even from a spectrum with a large proportion of contaminant signals. While for peptides the 2D-PC-MS correlation matching procedure is based on complementary and internal ion correlations, the identi?cation of intact proteins is entirely based on the ability of 2D-PC-MS to spatially separate and resolve the experimental correlations between complementary fragment ions.</div>

Comparative psycholinguistic analysis of the communicative styles of the american TV presenters (on the example of tv shows by Oprah Winfrey and Larry King)

This article analyzes the psycholinguistic features of communicative behavior, speech style of two popular American TV hosts: Oprah Winfrey and Larry King. The material for the study was the interview of TV presenters, based on 50 interviews. A person’s personality can be considered as a carrier of a certain culture, an individual fragment or a part of а society, thus, speech behavior of the person, and specifically – the texts produced by him, can and should be searched in national-cultural, socially conditioned and individual components. The research is carried out in the direction of the actual modern science – gender linguistics and reveals the linguistic, psychological and ethnospecific features of the communicative style of American TV hosts. The author develops an interdisciplinary approach to solving problems at the intersection of Humanities: linguistics, psychology, cognitive science, genderology, journalism.As a result of the linguistic analysis, the author comes to the conclusion that the male style of interviewing Larry King is characterized by restraint, official style, clear structure of the interview; Oprah Winfrey’s speech style is characterized by emotionality, openness, characteristic of the conversational style of communication. However, the revealed gender features of the analyzed interviews do not affect the success of achieving the goals set by the interviewer. The presenter receives information through the use of psycholinguistic techniques. The result was a success regardless of the chosen tactics of negotiating in the analyzed interviews.

Bioinformatic analysis of endogenous and exogenous small RNAs on lipoproteins

To comprehensively study extracellular small RNAs (sRNA) by sequencing (sRNA-seq), we developed a novel pipeline to overcome current limitations in analysis entitled, “Tools for Integrative Genome analysis of Extracellular sRNAs (TIGER)”. To demonstrate the power of this tool, sRNA-seq was performed on mouse lipoproteins, bile, urine, and liver samples. A key advance for the TIGER pipeline is the ability to analyze both host and non-host sRNAs at genomic, parent RNA, and individual fragment levels. TIGER was able to identify approximately 60% of sRNAs on lipoproteins, and >85% of sRNAs in liver, bile, and urine, a significant advance compared to existing software. Results suggest that the majority of sRNAs on lipoproteins are non-host sRNAs derived from bacterial sources in the microbiome and environment, specifically rRNA-derived sRNAs from Proteobacteria. Collectively, TIGER facilitated novel discoveries of lipoprotein and biofluid sRNAs and has tremendous applicability for the field of extracellular RNA.

Pars pro toto: film interpretation according to the documentary method

Using the example of a short film shot by students, insights are provided as to how films can be interpreted on the basis of the documentary method. It is shown that the film’s meaning, which the documentary method aims to explore, can be found as a homologous structure in different filmic dimensions. It permeates the document both in the individual fragment and as a whole in the sense of “pars pro toto.” The study's interpretive results are characterized and validated by the homologies identified in the analysis.