An Improved Clustering Using by Likely Attributable Function and Informed Selection in WSN for Science of Management and Engineering

Wireless sensors networks (WSNs) are traditionally composed of large number of tiny homogenous sensors nodes connected through a wireless network that gather data to be treated locally or relayed to the sink node through multi-hop wireless transmission. The low-energy adaptive clustering hierarchy (LEACH) protocol is one of the Famous protocols used in the wireless sensor networks (WSNs). The LEACH protocol in wireless sensor network suffers from many Bugs and many researchers proposed different methods to mitigate them. In this paper, we propose two ideas in a format for improving leach protocol. For Cluster head selection we used a Likely Attributable Function that in this function used from a factor. This factor that we called the informed selection factor helps to farther nodes not selection for cluster head. This significantly decreases the energy consumption and increases the lifetime of associated nodes. Simulation is conducted in using MATLAB results are analyzed for energy consumption.

Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals

Adaptive immunity's success relies on the extraordinary diversity of protein receptors on B and T cell membranes. Despite this diversity, the existence of public receptors shared by many individuals gives hope for developing population wide vaccines and therapeutics. Yet many of these public receptors are shared by chance. We present a statistical approach, defined in terms of a probabilistic V(D)J recombination model enhanced by a selection factor, that describes repertoire diversity and predicts with high accuracy the spectrum of repertoire overlap in healthy individuals. The model underestimates sharing between repertoires of individuals infected with SARS-CoV-2, suggesting strong antigen-driven convergent selection. We exploit this discrepancy to identify COVID-associated receptors, which we validate against datasets of receptors with known viral specificity. We study their properties in terms of sequence features and network organization, and use them to design an accurate diagnosis tool for predicting SARS-CoV-2 status from repertoire data.

Evaluating Technological Innovation of Media Companies from the Perspective of Technological Ecosystem

The evaluating indicators on the benefits of innovative technology to media companies are preliminarily analyzed and evaluated, according to the research review and evaluating criteria of self-organization and ecosystem selection. Factor analysis and structural equation modeling are used to further explore and select the indicators. According to the results, from the perspective of technology ecosystem, innovative technology performance of media companies can be measured through a two-factor structure—the input of innovative technology and its output. On this basis, ANP (analytic network process) is used to establish a weighted evaluation of indicators. At the end of the paper, a complete set of evaluation systems was created to measure the performance of technology innovation.

Didactics: Peculiarities of Programmed Teaching of a Cartwheel to Boys Aged 14

The purpose of the study was to determine the peculiarities of programmed teaching of a cartwheel to boys aged 14. Material and methods. The study participants were 20 boys aged 14. The children and their parents were fully informed about all the features of the study and gave their consent to participate in the experiment. To solve the tasks set, the following research methods were used: study and analysis of scientific and methodological literature; pedagogical observation, timing of training tasks; pedagogical experiment, methods of mathematical statistics, factor analysis. Results. The analysis of similarities revealed that the program components are interrelated. Series of training tasks I, II and IV are combined into one group and provide conditions for teaching boys aged 14 a cartwheel. Conclusions. As a result of factor analysis, the study obtained a two-factor model of the teaching program where training tasks are closely connected with one another, which indicates their effective selection. Factor models of the teaching program explain 69.371% and 75.394% of the variation of results. The study found that the effectiveness of the program depends on the modes of exercise repetition. The use of the mode of exercise repetition of 6 sets 2 times each with a rest interval of 60 s increases the effectiveness of the proposed program (p <0.05).

An Effective Congestion and Interference Secure Routing Protocol for Internet of Things Applications in Wireless Sensor Network

This paper provides an effective Wireless Sensor Network(WSN) routing solution for Internet of Things(IoT) applications cognizant of congestion, security, and interference. Because several sources try to deliver their packets to a destination simultaneously, which is a common case in IoT applications. The proposed congestion and interference aware safe routing protocol is claimed to work in networks with high traffic. The signal to interference ratio (SINR), congestion level, and survival factor is used in our suggested procedure to estimate the cluster head selection factor first. The adaptive fuzzy c-means clustering method clusters the network nodes based on the cluster head selection factor. After that, data packets are encrypted using Adaptive Quantum Logic-based packet coding. Finally, the Adaptive Krill Herd (AKH) optimization method identifies the least congested corridor, resulting in optimal data transmission routing. The exploratory findings show that the provided strategy outperforms previous methodologies in network performance, end-to-end delay, packet delivery ratio, and node remaining energy level.

Light-Fuelled Dissipative Replication and Selection in Adaptive Biomimetic Chemical Networks

<p>Evolvability of the chemical replicator systems requires non-equilibrium energy dissipation, effective death pathways and transfer of structural information in the autocatalytic cycles. We engineered a chemical network with peptidic foldamer components, where UV light fuelled dissipative sequence-dependent exponential replication and replicator decomposition. The light-harvesting formation-recombination cycle of the thiyl radicals was coupled with the molecular recognition steps in the replication cycles. Thiyl radical-mediated chain reaction was responsible for the replicator death. The competing and kinetically asymmetric replication and decomposition processes led to light intensity-dependent selection and competitive exclusion. Dynamic adaptation to the energy input and the selection factor maximised the dissipation rate in the regime of exponential growth. The results contribute to the development of chemically evolvable replicator systems.</p>

Light-Fuelled Dissipative Replication and Selection in Adaptive Biomimetic Chemical Networks

<p>Evolvability of the chemical replicator systems requires non-equilibrium energy dissipation, effective death pathways and transfer of structural information in the autocatalytic cycles. We engineered a chemical network with peptidic foldamer components, where UV light fuelled dissipative sequence-dependent exponential replication and replicator decomposition. The light-harvesting formation-recombination cycle of the thiyl radicals was coupled with the molecular recognition steps in the replication cycles. Thiyl radical-mediated chain reaction was responsible for the replicator death. The competing and kinetically asymmetric replication and decomposition processes led to light intensity-dependent selection and competitive exclusion. Dynamic adaptation to the energy input and the selection factor maximised the dissipation rate in the regime of exponential growth. The results contribute to the development of chemically evolvable replicator systems.</p>

The government spending on education and health, and its impact on sustainable development in Sudan between (1995 - 2015): الإنفاق الحكومي على التعليم والصحة وأثره في التنمية المستدامة في السودان الفترة ما بين 1995 - 2015م

The study dealt with government spending on education and health and its impact on sustainable development, and limits of the study were Sudan between 1995 and 2015 sustainable. The study aims to know the effect of education and health in supporting sustainable development in Sudan. The study followed the descriptive analytical approach in terms of information collection, presentation of relevant data, and the views standard economy The most important findings of the study were the lack of government spending on education and health through the weakness of the selection factor in the two equations which led to the failure of education to harmonize the demands of the labor market and the lower expectation of age rates, the higher the government expenditure on education and health, the higher the rate of economic and social growth with a healthy environment and reduced illiteracy, leading to increased rates of sustainable government. The study made several recommendations, the most important of which were the need to increase government spending on education and health to achieve sustainable government in Sudan.