Let the system consist of n of the same type and independent biological individuals with the same indicator p survival at a given interval [0,T] time [1]. Let us assume that a population is subject to an epidemic that leads to the death of some of the individuals.
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This is a short opinion article pointing out the importance of examining more precisely the intimate relationship between structure and function that arises for all complex systems. It is claimed that this relationship is highly asymmetrical, which has many unforeseen consequences. The presented claims are made based on intuition and inductive reasoning. Although some claims may be only partially valid, for instance, under yet to be specified conditions, they can inspire new research directions to investigate in future
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Genes are considered as segments of DNA that provide instructions for the production of specific proteins or RNA molecules. Genes can be related to one another in a variety of ways. These relationships can play important roles in the regulation of cellular processes and functions, as well as in the development and evolution of organisms. Gene relation refers to the relationship between two or more genes in terms of their function, location, or sequence similarity. In studying the expression and relationship of genes, researchers can get a sense of how gene-information is used to know cell functions and how changes in gene expression or regulation can lead to disease. As an example, co-expression analysis can help to determine gene-groups that are functionally related and may be involved in specific biological processes or diseases. Also, network analysis can be used to identify regulatory relationships between genes as well as to build gene regulation networks that control specific cellular processes. See also Allocco et al. [1], Elise et al. [2], Ruan et al. [3] & Song et al. [4], By interacting with each other, genes form a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. Since the accessibility of the large gene expression data, several methods have been developed to analyze the gene-to-gene relationship. Copula approach is being used to study the relationship between the expression profiles of pairs of genes, since a copula is a multivariate model that can be used for explaining gene-gene dependence.
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Biological rhythms are one of the components of the endogenous time of an organism as a set of all its temporal processes. Circadian, ultra- and intracardiac rhythms have such temporal parameters as latency, speed, period, duration and frequency, i.e., are temporary processes. They are superimposed on the directed time of ontogenesis and, together with monophasic processes, trends and cycles, determine the biochemical and physiological specifics of its certain periods. Numerous studies of the past three decades have contributed to the understanding of the types of molecular oscillators that shape cellular rhythms. These include: an oscillator of impulse activity in neurons and some endocrinocytes; an oscillator that reflects the circadian rhythms of the cAMP and Ca2+ content; redox oscillator and finally PER - oscillator, working on the basis of interactions of clock proteins [1-5]. The specificity of the interaction of these oscillators in cells of different tissues is gradually becoming clear: in endocrinocytes, in blood cells, in hepatocytes and adipocytes. However, the essence of the functions of the rhythms themselves as time processes is not clear enough.
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In
the attention-deficit hyperactivity disorder (ADHD) study, children are
prescribed different stimulant medications. The height measurements are
recorded longitudinally along with the medication time. Differences among the
patients are captured by the parameters suggested the Superimposition by Translation
and Rotation (SITAR) model using three subject-specific parameters to estimate
their deviation from the mean growth curve. In this paper, we generalize the
SITAR model in a Bayesian way with time-invariant covariates. The
time-invariant model allows us to predict latent growth factors. Since patients
suffer from a common disease, they usually exhibit a similar pattern, and it is
natural to build a nonlinear model that is shaped invariant. The model is
semi-parametric, where the population time curve is modeled with a natural
cubic spline. The original shape invariant growth curve model, motivated by
epidemiological research on the evolution of pubertal heights over time, fits
the underlying shape function for height over age and estimates
subject-specific deviations from this curve in terms of size, tempo, and
velocity using maximum likelihood. The usefulness of the model is illustrated
in the attention deficit hyperactivity disorder (ADHD) study. Further, we
demonstrated the effect of stimulant medications on pubertal growth by gender.
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The problem of innovative transformation of railway power supply networks Is Investigated and the direction of researchrelates to the organization of differential mathematical models of optimization of procedures by control of high-speed technological processes of power supply of railways. A graphis proposed, whose logical structure adequately reflects the architecture of the computerized network for managing the power supply system and developed its differential mathematical model. On the basis of the principle of minimax, the optimal strategy of intellectualization of the power supply processes in each of the nodes of the computer network was developed for the cases of the worst combination of the intensity of the requests and the intensity of their service. Hereis a way to ensure that the specified performance of the individual no desands egments of theintelligent computer control network by exploring the extremum off unctionality, implemented in the field of T-images using differential spectra.
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Introduction of Improved Maize Variety and Applying its Integrated Stem Borer Management Techniques in Ethiopian Somali Region by Fano Dargo in Open Access Bio statistics & bioinformatics
The stem borer is one of the most destructive pests of maize crop. Research experimentations were carried out on maize to control stem borer. The experiment was 2x3 factorial experiments using randomized complete block design with ten replications. A total of two maize varieties (Melkassa hybrid 130 and local varieties) and three different stem borer management packages (Control, inter-cropping with cowpea and inter-cropping with Cowpea and Sudan Grass) were used. Data was collected on Days to maturity, Plant height, Ear length, Grain yield, Biomass yield, Harvest index, Biomass production rate and Grain yield per day. The results of analysis revealed that the interaction effect of Control mechanisms of stem borer and Maize varieties was significantly (P≤0.05) affected in all agronomic traits recorded except DTM, PH, EL and HI which is not significant. While, they were significantly (P≤0.05) affected by the maize variety. Treatment combination Improved Maize Variety (MH-130) mono-cropping gave the highest grain yield (4.70 t∙ha-1) of all the test treatment combination. While, the minimum grain yield (2.15 t∙ha-1) were observed in treatment combination Local Maize variety Mono-cropping. Grain yield had strong significant positive correlations with plant height (r=0.66**), Ear length (r=0.0.58**), Biomass yield (r=0.76**), harvest index (r=0.0.74**), biological yield rate (r=0.0.73**) and grain yield per day (r=0.96**). Based on objectively measured traits, farmers’ preferred Treatment 4 Improved Maize Variety (MH-130) mono-cropping was ranked the first (1.1), followed by Treatment 5 Improved Maize Variety (MH-130) inter-cropping with Cowpea (2.3) and Treatment 6 Improved Maize Variety (MH-130) inter-cropping with Cowpea and Sudan Grass (2.8). Therefore, it can be concluded that the use of treatment combination 4 Improved Maize Variety (MH-130) mono-cropping could be recommend for optimum yield and yield related traits of maize even though further testing is required to put the recommendation on a strong basis.
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