Coronaviruses are viruses that infect the respiratory system of humans. Besides high mortality rates among the population, they brought about several economic crises on a global scale. Methods. To ...study and identify features in the genetic composition of the nucleotide sequences of various coronaviruses, we applied copyright algorithms and visualization, which allowed us to compare the biochemical parameters of diverse RNA coronaviruses in a visual form. Results. The article provides examples of different approaches to imaging coronaviruses. We have provided examples of coronavirus RNA structure visualization in various parametric spaces (1-D and 2-D). We employed various visualization types, including structural, integral, and frequency. The research discussed methods of visualization. Our team developed visualization and comparative analysis of coronavirus serotypes and visualization of SARS-CoV-2 coronavirus datasets. Discussion followed on the visualization results. The presented techniques and the results allowed for displaying the structure of RNA sequences of coronaviruses in spaces of various dimensions. Conclusions. According to our findings, the proposed method contributes to the visualization of the genetic coding of coronaviruses. We discussed the issues of machine learning and neural network technology concerning the analysis of coronaviruses based on the presented approach. The described line of research is essential for the study and control of complex quantum mechanical systems, such as RNA or DNA.
This paper presents and visualizes examples of large amounts of genetic information using a new class of cognitive computer graphics algorithms. These algorithms are related to the semiotics of ...perception and allow the interpretation of those properties of nucleotide sequences that are difficult to perceive by simple reading or by standard means of statistical analysis. This article summarizes previously presented algorithms for visualizing long nucleic acids based on the primary Hadamard–Walsh function system. The described methods allow us to produce one-dimensional mappings of nucleic acids by levels corresponding to their scale-integral physicochemical parameters and construct a spectral decomposition of the nucleotide composition. An example of the spectral decomposition of parametric representations of molecular genetic structures is given. In addition, a multiscale composition of genetic functional mappings visualizing the structural features of nucleic acids is discussed.
We study the proposed statistical kinetic model for describing the pre- and consciousness structures based on the cognitive neural networks. The method of statistics of the growth graph systems and a ...possible transition to symmetric structures (a kind of phase transition) is applied. With the complication of a random Erdőos-Rényi (ER) graph during the percolation transition from the tree structure to the large cluster structures is obtained. In the evolutionary model two classes of algorithms have been developed. The differences between the cycle parameters in the obtained neural network models can reach thousands or more times. This is due to the tree-like architecture of the neural graph, which mimics the columnar structures of the neocortex. These cluster and cyclic structures can be interpreted as the primary elements of consciousness and as a necessary condition for the effect of consciousness itself. The comparison with other known theoretical mainly statistical models of consciousness is discussed. The presented results are promising in neurocomputer interfaces, man-machine systems and artificial intelligence systems.
Adequate dietary iron (Fe) intake is crucial for preventing Fe-deficient anemia, a recognized global public health concern which is important in Armenia. This study aimed to analyze the intake of Fe, ...both heme (from animal tissues) and non-heme (more prevalent, but less efficiently absorbed), as well as the Fe dietary sources, among adults in a representative national sample in Armenia. The study was conducted on 1400 individuals aged 18-80 and above, who were enrolled from all regions of Armenia. The Fe intake was assessed through a 24 h dietary recall survey, while Fe occurrence was determined through atomic absorption spectrophotometry (AAS). The results showed a high proportion of adults with a Fe intake lower than the average requirements set by EFSA (65%, 80% and 85% of males, total females and females at fertile age, respectively). Main Fe sources were bread, fruits and vegetables; heme Fe accounted only for <5% of total Fe intake. Compared to males, females had a lower intake of all forms of Fe (
< 0.05). Significant differences were observed in the intake of different forms of Fe between regions (
< 0.05), while the age-group 36-55 years had higher intakes of total Fe. Our data call for comprehensive nutritional security strategies in order to reduce iron deficiency in Armenia, that represents a public health concern.
New molecular genetic algorithms, as tools for the visualization and analysis of big data, have made it possible not only to illustrate the internal structure of DNA molecules within their parameters ...but also to explore the field of chaos theory, particularly to display processes and signals close to chaotic ones. This provides a new perspective on the problem of determining criteria for borderline states between order and chaos. This article demonstrates the differences between chaotic and quasi-chaotic signals when visualized with molecular genetic algorithms. It presents examples of molecular genetic mappings of signals generated using various pseudorandom noise generators, as well as acoustic signals. This article considers structural and integral (folded) mappings as one-dimensional and two-dimensional projections of the pattern. The authors illustrate the internal structure of the reconstructed signal mappings in spaces of fractional dimensionality, which is considered as a visualization of the entropy structure based on functional mappings in spaces of the fractional dimension. As a result of this research, it was found that the use of molecular genetic algorithms for visualizing information signals makes it possible to identify the so-called entropy structure of these signals. At the same time, the entropy structure of chaotic signals is absent.
To determine the prevalence and serotype of oropharyngeal Group B Streptococcal (GBS) colonization of mothers, their family & friends, and health care providers of recently delivered patients as a ...potential reservoir of neonatal exposure to GBS.
This is a prospective, single-center observational study of: (1) patients, (2) their family and friends, and (3) health care providers all of whom may come in close contact with neonates. Oropharyngeal GBS colonization and serotype was determined.
Three hundred and seventy three samples were collected. The prevalence of oropharyngeal GBS colonization among all study participants was 23.1% (N = 86). The most commonly found serotypes were 1b (12.8%, N = 11), III (27.9%, N = 24), and V (17.4%, N = 15). The prevalence of oropharyngeal GBS colonization among mothers was 26% (N = 31/121), 22% (N = 39/178) in family and friends, and 21.6% (N = 16/74) in health care providers.
Group B Streptococcus colonizes the oropharynx in 1 in 5 mothers, family and friends, and health care providers who come in direct contact with neonates. Further research is needed to determine if this potential reservoir for neonatal exposure could lead to early or late onset neonatal GBS colonization or infection.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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A method of adaptive control that is not reduced to the Markov decision-making process under conditions of an unknown model of the environment is discussed. Intelligent agents can face similar ...problems. The adaptation of machine learning with reinforcement of the fact that processes have memory and of the adaptive search for a set of recognizable states of the environment to be the key features of the proposed method is considered. The proposed method has been tested on problems of reconstruction of
N
-ary Boolean functions defined by tables. The results of application of the method to exchange rate forecasting are given. Because of weak regularities in the time series of exchange rates, the problem of controlling the generalizing ability of a learning system (combating overfitting) is urgent. In our experiments, the problem of overfitting has been fundamentally eliminated by online-training of the neural network. Each training example was presented to the network once, after which it was “forgotten.”
This paper mainly studies evolutionary operations of interneuron synaptic structure search based on the developed structure synthesis algorithm for feed-forward multilayer network trained with a ...teacher. The decomposition of neural network learning tasks into a series of subtasks is proposed. During evolutionary search the neural network is not converted to a genotype and all the transformations of synaptic structures are performed directly. This differs from a classical approach to genetic algorithms involving coding phenotype of individuals (structure) to genotype (code string).
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