The experimental model of laboratory animals’ intoxication by polyacrylonitrile pyrolysis products

Purpose of research – To develop an experimental model of intoxication of laboratory animals by polyacrylonitrile pyrolysis products. Materials and methods. The study was performed on the rats. Pyrolysis of polyacrylonitrile fibers was carried out at temperature of 270–350 °C. The laboratory animals were exposed to static inhalation intoxication by pyrolysis products for 15 min. Vital signs were determined in animals before and 5 minutes after intoxication. Arterial blood oxygenation index and acid-base state parameters were evaluated at 10 min after exposure. Qualitative detection of cyanides in brain and myocardial samples obtained 15 minutes after intoxication was carried out by gas chromatography. Results and discussion. It was found that the weight of the material (containing 85 % polyacrylonitrile), which pyrolysis products lead to the death of 50 % of laboratory animals within 24 hours after exposure, was 0.81 ± 0.15 g. The animals showed signs of poisoning by substances interrupting the processes of cell bioenergy when exposed to pyrolysis products obtained under specified conditions. The evident bradycardia and bradypnea (p < 0,05), and significant decrease in rectal temperature was marked. The exposed animals did not differ (p > 0,05) from the rats of the control group by the parameters of oxygenation. The signs of decompensated metabolic acidosis were detected in blood. The cyanide peak was detected by gas chromatography with a retention time of 3.78 min in brain and heart muscle biopsies. The experimental model, in which inhalation exposure of pyrolysis products of polyacrylonitrile fibers led to severe intoxication of laboratory animals, was developed. The model can be used to search for means of etiotropic and pathogenetic therapy of poisoning by combustion products of nitrogen-containing polymeric materials

A Practical, Accurate, Information Criterion for Nth Order Markov Processes

The recent increase in the breath of computational methodologies has been matched with a corresponding increase in the difficulty of comparing the relative explanatory power of models from different methodological lineages. In order to help address this problem a Markovian information criterion (MIC) is developed that is analogous to the Akaike information criterion (AIC) in its theoretical derivation and yet can be applied to any model able to generate simulated or predicted data, regardless of its methodology. Both the AIC and proposed MIC rely on the Kullback–Leibler (KL) distance between model predictions and real data as a measure of prediction accuracy. Instead of using the maximum likelihood approach like the AIC, the proposed MIC relies instead on the literal interpretation of the KL distance as the inefficiency of compressing real data using modelled probabilities, and therefore uses the output of a universal compression algorithm to obtain an estimate of the KL distance. Several Monte Carlo tests are carried out in order to (a) confirm the performance of the algorithm and (b) evaluate the ability of the MIC to identify the true data-generating process from a set of alternative models

Evolution of a Signaling Nexus Constrained by Protein Interfaces and Conformational States

Heterotrimeric G proteins act as the physical nexus between numerous receptors that respond to extracellular signals and proteins that drive the cytoplasmic response. The Gα subunit of the G protein, in particular, is highly constrained due to its many interactions with proteins that control or react to its conformational state. Various organisms contain differing sets of Gα-interacting proteins, clearly indicating that shifts in sequence and associated Gα functionality were acquired over time. These numerous interactions constrained much of Gα evolution; yet Gα has diversified, through poorly understood processes, into several functionally specialized classes, each with a unique set of interacting proteins. Applying a synthetic sequence-based approach to mammalian Gα subunits, we established a set of seventy-five evolutionarily important class-distinctive residues, sites where a single Gα class is differentiated from the three other classes. We tested the hypothesis that shifts at these sites are important for class-specific functionality. Importantly, we mapped known and well-studied class-specific functionalities from all four mammalian classes to sixteen of our class-distinctive sites, validating the hypothesis. Our results show how unique functionality can evolve through the recruitment of residues that were ancestrally functional. We also studied acquisition of functionalities by following these evolutionarily important sites in non-mammalian organisms. Our results suggest that many class-distinctive sites were established early on in eukaryotic diversification and were critical for the establishment of new Gα classes, whereas others arose in punctuated bursts throughout metazoan evolution. These Gα class-distinctive residues are rational targets for future structural and functional studies

Cryptanalysis of Masked Ciphers: A not so Random Idea

A new approach to the security analysis of hardware-oriented masked ciphers against second-order side-channel attacks is developed. By relying on techniques from symmetric-key cryptanalysis, concrete security bounds are obtained in a variant of the probing model that allows the adversary to make only a bounded, but possibly very large, number of measurements. Specifically, it is formally shown how a bounded-query variant of robust probing security can be reduced to the linear cryptanalysis of masked ciphers. As a result, the compositional issues of higher-order threshold implementations can be overcome without relying on fresh randomness. From a practical point of view, the aforementioned approach makes it possible to transfer many of the desirable properties of first-order threshold implementations, such as their low randomness usage, to the second-order setting. For example, a straightforward application to the block cipher LED results in a masking using less than 700 random bits including the initial sharing. In addition, the cryptanalytic approach introduced in this paper provides additional insight into the design of masked ciphers and allows for a quantifiable trade-off between security and performance

Multi-rate Loss Model for Optical Network Unit in Passive Optical Networks

Nowadays, extensive research on passive optical network (PON) technology is being conducted. PON technology facilitates the use of inexpensive passive components and helps reduce the total length of optical fiber required. PON is a future optical technology that enables high-speed data transfer of multiservice traffic using optical fibers. This paper is concerned with multi-rate loss model for optical network units in PON like a queue system with a limited capacity buffer. The results obtained in the paper are applied to the calculation of the quality of service parameters of the network. © Springer International Publishing Switzerland 2014

Multi-rate Loss Model for Optical Network Unit in Passive Optical Networks

Nowadays, extensive research on passive optical network (PON) technology is being conducted. PON technology facilitates the use of inexpensive passive components and helps reduce the total length of optical fiber required. PON is a future optical technology that enables high-speed data transfer of multiservice traffic using optical fibers. This paper is concerned with multi-rate loss model for optical network units in PON like a queue system with a limited capacity buffer. The results obtained in the paper are applied to the calculation of the quality of service parameters of the network. © Springer International Publishing Switzerland 2014

Probability characteristic algorithm of upstream traffic in passive optical network

Nowadays, access network evaluation is being conducted in both directions: high bit rate access development for providing high quality of service and decrease length of cooper wiring in local line networks. It’s paid special attention to the networks, which are based on optical and optoelectronic components. Passive optical network (PON) is an all optical network, which is based on passive optical components only and excludes the conversion of electrical signal into optical form and vice versa. This paper is concerned with the algorithm for calculation of call blocking probability in upstream traffic multiservice model for PON considering the functioning process of optical network units and the principle of wavelength dynamic distribution. These results are used in the blocking probability analysis of the model. © Springer International Publishing Switzerland 2016