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Register a new userCicadas wings as determinant factor for the sound emission: The case of textit{Quesada gigas}
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Cicadas (Homoptera:Cicadidae) are insects able to produce loudly songs and it is known that the mechanism to produce sound of tymballing cicadas works as a Helmholtz resonator. In this work we offer evidence on the participation of the wings in a high quality resonating process which defines the details of the acoustic properties of the calling song. The study is carry on textit{Quesada gigas} species and it is dividied in three stages: (i) the acoustical characterization of the abdominal cavity, (ii) the record and calculation of frequency spectrum of the calling song, and (iii) the measurement of the vibration modes of the wings. The comparison between all the results unequivocally show the dramatic influence of the wings in the moment in which the insect emits its calling song.
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It is shown that there is a sense in splitting Genetic Code Table (GCT) into three parts using the harmonic mean, calculated by the formula H (a, b) = 2ab / (a + b), where a = 63 and b = 31.5. Within these three parts, the amino acids (AAs) are positioned on the basis of the validity of the evident regularities of key parameters, such as polarity, hydrophobicity and enzyme-mediated amino acid classification. In addition, there are obvious balances of the number of atoms in the nucleotide triplets and corresponding amino acid groups and/or classes.
In addition to their unusually long life cycle, periodical cicadas, {it Magicicada} spp., provide an exceptional example of spatially synchronized life stage phenology in nature. Within regions (broods) spanning 50,000 to 500,000 km$^2$, adults emerge synchronously every 13 or 17 years. While satiation of avian predators is believed to be a key component of the ability of these populations to reach high densities, it is not clear why populations at a single location remain entirely synchronized. We develop nonlinear Leslie matrix-type models of periodical cicadas that include predation-driven Allee effects and competition in addition to reproduction and survival. Using both analytical and numerical techniques, we demonstrate the observed presence of a single brood critically depends on the relationship between fecundity, competition, and predation. We analyze the single-brood, two-brood and all-brood equilibria in the large life-span limit using a tractable hybrid approximation to the Leslie matrix model with continuous time competition in between discrete reproduction events. Within the hybrid model we prove that the single-brood equilibrium is the only stable equilibrium. This hybrid model allows us to quantitatively predict population sizes and the range of parameters for which the stable single-brood and unstable two-brood and all-brood equilibria exist. The hybrid model yields a good approximation to the numerical results for the Leslie matrix model for the biologically relevant case of a 17-year lifespan.
The CoHSI (Conservation of Hartley-Shannon Information) distribution is at the heart of a wide-class of discrete systems, defining the length distribution of their components amongst other global properties. Discrete systems such as the known proteome where components are proteins, computer software, where components are functions and texts where components are books, are all known to fit this distribution accurately. In this short paper, we explore its solution and its resulting properties and lay the foundation for a series of papers which will demonstrate amongst other things, why the average length of components is so highly conserved and why long components occur so frequently in these systems. These properties are not amenable to local arguments such as natural selection in the case of the proteome or human volition in the case of computer software, and indeed turn out to be inevitable global properties of discrete systems devolving directly from CoHSI and shared by all. We will illustrate this using examples from the Uniprot protein database as a prelude to subsequent studies.
Large volume of Genomics data is produced on daily basis due to the advancement in sequencing technology. This data is of no value if it is not properly analysed. Different kinds of analytics are required to extract useful information from this raw data. Classification, Prediction, Clustering and Pattern Extraction are useful techniques of data mining. These techniques require appropriate selection of attributes of data for getting accurate results. However, Bioinformatics data is high dimensional, usually having hundreds of attributes. Such large a number of attributes affect the performance of machine learning algorithms used for classification/prediction. So, dimensionality reduction techniques are required to reduce the number of attributes that can be further used for analysis. In this paper, Principal Component Analysis and Factor Analysis are used for dimensionality reduction of Bioinformatics data. These techniques were applied on Leukaemia data set and the number of attributes was reduced from to.
Lockdowns imposed in most of the countries were lifted following a decline in the COVID-19 cases towards May-June 2020. A recent surge (second wave) in the COVID-19 cases in Europe and other temperate countries as compared to the tropical regions suggests the likely role of solar radiation. We hypothesized that ultraviolet radiations effect might be a significant factor moderating the spread of the COVID-19 across countries. Regression analysis was done for the UV radiation data for seven hotspot cities (New Delhi, Mumbai, Milan, Madrid, New York, Melbourne and Sydney) with the daily COVID-19 cases. Global erythemal UV radiation values were lower during winter and higher during summer. In general, the daily new COVID-19 cases registered were higher during the winter months having low UV radiation dose (0.5-3.7 kJ m-2). Cases began to decline with summer onset that corresponded to increased UV radiation (2.5-6.7 kJ m-2). Our studies suggest that the natural UV radiation could be a strong determining factor moderating the spread of COVID-19 cases. The importance of UV radiation in natural sunlight as a disinfectant for SARS-CoV-2 cannot be ignored since the lockdowns were lifted; further, it can be considered as a factor for COVID management.
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