Implementing a Network Project for Pedagogical Workers Within the Framework of Continuing Education: A Case Study From Russia

The article presents the experience of Kursk State University and the department of education pedagogy of the International Children Center “Artek” for the implementation of a network project aimed at programs of continuing professional education of employees of Artek, including pedagogical workers. The authors present the result of providing a network project to implement additional professional programs for a new generation. The research aims at identifying new opportunities for everyone while implementing a network project for training pedagogical workers at Artek. The paper presents the experience of implementing continuing professional education programs at Artek when implementing a network project covering various training areas. All implemented programs are characterized by newness and modern approaches in educational practice. The research is based on the system-activity and personality-oriented approaches, the theory and methodology of vocational education. As a result of the study, the quality of the training program improved, and highly qualified specialists worked on implementing this project. Moreover, the massive coverage of students allowed them to improve their qualification level of education

Psycholinguistic Preconditions of Speech Formation of Children with General Speech Retardation

The article addresses psycholinguistic preconditions for development of the communicative component of speech activity in 5-year-olds with general speech retardation (GSR). The development of speech activity is analyzed through the lens of psycholinguistic motivation for the emergence of speech units. The authors for the first time identified psychological mechanisms that underlie disorders in the development of the communication component of speech activity in 5-year-olds with GSR and suggested effective interventions.The research involved a study of probability prediction within the structure of the communicative component of speech activity of 5-year-olds with GSR. The author-developed classification of non-verbal and verbal probability prediction formed the basis for a theory-based diagnostic tool to assess the communicative component of speech activity in 5-year-olds with GSR. The research demonstrated the importance of probability prediction as a dynamic process and indicator of practical realization of utterance and holistically developed coherent speech.The analysis of disorders in cognitive and speech operations and functions identified in the study points to the dominant role of weak probability prediction function at non-verbal and verbal levels. Weak probability prediction was defined as the cause of poorly developed communication component of speech activity in 5-year-olds with GSR.</p

Variations in the 6.2 μ\mum emission profile in starburst-dominated galaxies: a signature of polycyclic aromatic nitrogen heterocycles (PANHs)?

Analyses of the polycyclic aromatic hydrocarbon (PAH) feature profiles, especially the 6.2 $\mu$m feature, could indicate the presence of nitrogen incorporated in their aromatic rings. In this work, 155 predominantly starburst-dominated galaxies (including HII regions and Seyferts, for example), extracted from the Spitzer/IRS ATLAS project (Hern\'an-Caballero & Hatziminaoglou 2011), have their 6.2 $\mu$m profiles fitted allowing their separation into the Peeters' A, B and C classes (Peeters et al. 2002). 67% of these galaxies were classified as class A, 31% were as class B and 2% as class C. Currently class A sources, corresponding to a central wavelength near 6.22 $\mu$m, seem only to be explained by polycyclic aromatic nitrogen heterocycles (PANH, Hudgins et al. 2005), whereas class B may represent a mix between PAHs and PANHs emissions or different PANH structures or ionization states. Therefore, these spectra suggest a significant presence of PANHs in the interstellar medium (ISM) of these galaxies that could be related to their starburst-dominated emission. These results also suggest that PANHs constitute another reservoir of nitrogen in the Universe, in addition to the nitrogen in the gas phase and ices of the ISM

Comment on "Ab initio calculations of the lattice parameter and elastic stiffness coefficients of bcc Fe with solutes" Comp. Mat. Sci. v.126 pp.503-513 (2017)

In a recent paper, the authors propose to separately calculate the volumetric and chemical contributions to the elastic stiffness coefficients of systems containing solutes, as it is "computationally more efficient". We show that this is not the case and further that their methodology and hence their results are incorrect. There is no short cut for performing the desired calculations, if done rigorously, as we show in our 2012 work

Bayesian compositional regression with microbiome features via variational inference.

The microbiome plays a key role in the health of the human body. Interest often lies in finding features of the microbiome, alongside other covariates, which are associated with a phenotype of interest. One important property of microbiome data, which is often overlooked, is its compositionality as it can only provide information about the relative abundance of its constituting components. Typically, these proportions vary by several orders of magnitude in datasets of high dimensions. To address these challenges we develop a Bayesian hierarchical linear log-contrast model which is estimated by mean field Monte-Carlo co-ordinate ascent variational inference (CAVI-MC) and easily scales to high dimensional data. We use novel priors which account for the large differences in scale and constrained parameter space associated with the compositional covariates. A reversible jump Monte Carlo Markov chain guided by the data through univariate approximations of the variational posterior probability of inclusion, with proposal parameters informed by approximating variational densities via auxiliary parameters, is used to estimate intractable marginal expectations. We demonstrate that our proposed Bayesian method performs favourably against existing frequentist state of the art compositional data analysis methods. We then apply the CAVI-MC to the analysis of real data exploring the relationship of the gut microbiome to body mass index

Bayesian compositional regression with microbiome features via variational inference

The microbiome plays a key role in the health of the human body. Interest often lies in finding features of the microbiome, alongside other covariates, which are associated with a phenotype of interest. One important property of microbiome data, which is often overlooked, is its compositionality as it can only provide information about the relative abundance of its constituting components. Typically, these proportions vary by several orders of magnitude in datasets of high dimensions. To address these challenges we develop a Bayesian hierarchical linear log-contrast model which is estimated by mean field Monte-Carlo co-ordinate ascent variational inference (CAVI-MC) and easily scales to high dimensional data. We use novel priors which account for the large differences in scale and constrained parameter space associated with the compositional covariates. A reversible jump Monte Carlo Markov chain guided by the data through univariate approximations of the variational posterior probability of inclusion, with proposal parameters informed by approximating variational densities via auxiliary parameters, is used to estimate intractable marginal expectations. We demonstrate that our proposed Bayesian method performs favourably against existing frequentist state of the art compositional data analysis methods. We then apply the CAVI-MC to the analysis of real data exploring the relationship of the gut microbiome to body mass index

Study of the resistome of human microbial communities using a targeted panel of antibiotic resistance genes in COVID-19 patients

Aim. To study overall drug resistance genes (resistome) in the human gut microbiome and the changes in these genes during COVID-19 in-hospital therapy. Materials and methods. A single-center retrospective cohort study was conducted. Only cases with laboratory-confirmed SARS-CoV-2 RNA using polymerase chain reaction in oro-/nasopharyngeal swab samples were subject to analysis. The patients with a documented history of or current comorbidities of the hepatobiliary system, malignant neoplasms of any localization, systemic and autoimmune diseases, as well as pregnant women were excluded. Feces were collected from all study subjects for subsequent metagenomic sequencing. The final cohort was divided into two groups depending on the disease severity: mild (group 1) and severe (group 2). Within group 2, five subgroups were formed, depending on the use of antibacterial drugs (ABD): group 2A (receiving ABD), group 2AC (receiving ABD before hospitalization), group 2AD (receiving ABD during hospitalization), group 2AE (receiving ABD during and before hospitalization), group 2B (not receiving ABD). Results. The median number of antibiotic resistance (ABR) genes (cumulative at all time points) was significantly higher in the group of patients treated with ABD: 81.0 (95% CI 73.8–84.5) vs. 51.0 (95% CI 31.1–68.4). In the group of patients treated with ABD (2A), the average number of multidrug resistance genes (efflux systems) was significantly higher than in controls (group 2B): 47.0 (95% CI 46.0–51.2) vs. 21.5 (95% CI 7.0–43.9). Patients with severe coronavirus infection tended to have a higher median number of ABR genes but without statistical significance. Patients in the severe COVID-19 group who did not receive ABD before and during hospitalization also had more resistance genes than the patients in the comparison group. Conclusion. This study demonstrated that fewer ABR genes were identified in the group with a milder disease than in the group with a more severe disease associated with more ABR genes, with the following five being the most common: SULI, MSRC, ACRE, EFMA, SAT

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Impacts of the Tropical Pacific/Indian Oceans on the Seasonal Cycle of the West African Monsoon

The current consensus is that drought has developed in the Sahel during the second half of the twentieth century as a result of remote effects of oceanic anomalies amplified by local land–atmosphere interactions. This paper focuses on the impacts of oceanic anomalies upon West African climate and specifically aims to identify those from SST anomalies in the Pacific/Indian Oceans during spring and summer seasons, when they were significant. Idealized sensitivity experiments are performed with four atmospheric general circulation models (AGCMs). The prescribed SST patterns used in the AGCMs are based on the leading mode of covariability between SST anomalies over the Pacific/Indian Oceans and summer rainfall over West Africa. The results show that such oceanic anomalies in the Pacific/Indian Ocean lead to a northward shift of an anomalous dry belt from the Gulf of Guinea to the Sahel as the season advances. In the Sahel, the magnitude of rainfall anomalies is comparable to that obtained by other authors using SST anomalies confined to the proximity of the Atlantic Ocean. The mechanism connecting the Pacific/Indian SST anomalies with West African rainfall has a strong seasonal cycle. In spring (May and June), anomalous subsidence develops over both the Maritime Continent and the equatorial Atlantic in response to the enhanced equatorial heating. Precipitation increases over continental West Africa in association with stronger zonal convergence of moisture. In addition, precipitation decreases over the Gulf of Guinea. During the monsoon peak (July and August), the SST anomalies move westward over the equatorial Pacific and the two regions where subsidence occurred earlier in the seasons merge over West Africa. The monsoon weakens and rainfall decreases over the Sahel, especially in August.Peer reviewe