Ordering of Omics Features Using Beta Distributions on Montecarlo p-Values

The current trend in genetic research is the study of omics data as a whole, either combining studies or omics techniques. This raises the need for new robust statistical methods that can integrate and order the relevant biological information. A good way to approach the problem is to order the features studied according to the different kinds of data so a key point is to associate good values to the features that permit us a good sorting of them. These values are usually the p-values corresponding to a hypothesis which has been tested for each feature studied. The Montecarlo method is certainly one of the most robust methods for hypothesis testing. However, a large number of simulations is needed to obtain a reliable p-value, so the method becomes computationally infeasible in many situations. We propose a new way to order genes according to their differential features by using a score defined from a beta distribution fitted to the generated p-values. Our approach has been tested using simulated data and colorectal cancer datasets from Infinium methylationEPIC array, Affymetrix gene expression array and Illumina RNA-seq platforms. The results show that this approach allows a proper ordering of genes using a number of simulations much lower than with the Montecarlo method. Furthermore, the score can be interpreted as an estimated p-value and compared with Montecarlo and other approaches like the p-value of the moderated t-tests. We have also identified a new expression pattern of eighteen genes common to all colorectal cancer microarrays, i.e., 21 datasets. Thus, the proposed method is effective for obtaining biological results using different datasets. Our score shows a slightly smaller type I error for small sizes than the Montecarlo p-value. The type II error of Montecarlo p-value is lower than the one obtained with the proposed score and with a moderated p-value, but these differences are highly reduced for larger sample sizes and higher false discovery rates. Similar performances from type I and II errors and the score enable a clear ordering of the features being evaluated.

ExPro as psycho-affective stimulators through experiential marketing in nonprofit organizations

This article aims to analyze the relationship of experience providers (ExPro) as phyco-affective stimulators in experiential marketing in non-profit organizations in the Colombian Caribbean region, it was framed in the complementary methodology, under the type of correlational studies and was carried out under a non-experimental, transactional and field design. The facts were also studied from January 1/2018 to November 30/2018, where a questionnaire with a Likert scale was applied, which was validated at the discretion of 5 experts with an alpha coefficient of Cronbach 0.85 (Very high), aimed at a population of 273 young people between 18-25 years in the departments of Córdoba and Sucre which are intervened socially for 5 foundations, statistical data was processed in Microsoft Excel2010, SPSS v25 and @risk (Montecarlo method), subsequently 3 marketing experts were discussed and interpreted through the hermeneutic or interpretive method using it as a tool for qualitative analysis Atlas.ti8 software, generating criteria for weighting and design of inference rules in the fuzzy logic module (Matlab2017), to obtain the following results: standard deviation of 0.23982, correlation between variables of 0.666 (moderately positive). Consequently, 7 rules were generated for the inference module under the simplification of 5 categories of the Likert scale to 3 categories according to proportionality: Strong: 3.41 - 5.00, Medium: 2.61 - 3.40 and Weak: 1.00 - 2.60; as a significant find, the internal staff (Expro) generates greater influence among the psycho-affective stimulators in nonprofit organizations.

Dual Output Sinusoidal Oscillator Using Second Generation Current Controlled Conveyor

Second Generation Current Controlled Conveyor (CCCII) based tunable Dual Output Sinusoidal Oscillator (MSO) is proposed. It consists of three CCCIIs, a resistor and two grounded capacitors. By tuning external DC bias current, the oscillator frequency and commencement of its oscillations are controlled electronically. The proposed circuit is verified using PSPICE simulator and also on laboratory breadboard using commercially available integrated circuits Current Feedback Operational Amplifier (AD844AN) and Operational Transconductance Amplifier (LM13600) at a supply rail voltage of ±6 V. Further its nonlinearities, sensitivities, performance characteristics are also verified. Comparison of the proposed topology with the ongoing methods are also undertaken. PSPICE simulation results are verified with a low supply voltage of ±1 V, temperature analysis, analysis by using Montecarlo method and finally Total Harmonic Distortion (THD) is also demonstrated.

Application of the Montecarlo method for the validation of the budget of a suezmax type ship

As the name suggests, the budget for the construction of a ship, in this case a Suezmax, means to specifically pre-suppose in economic terms, the activities and movements to carry out during the construction of said ship. The importance of this essential phase of the construction process lie one hand in budgeting a competitive price in the market, but without causing economic losses for the shipyard, in order to make a profit for the company. This study proposes the use of the Monte Carlo method to obtain a greater reliability in the valuation of the Suezmax vessel; in this case, the triangular method will be used, which starting point is based on results obtained from previous research and from which the most likely, most pessimistic and most optimistic ship budget is obtained in order to later perform a simulation. For the realization of said simulation the ship is divided into different items, that will be assigned an optimistic and pessimist percentage based on a likely budget, according to the degree of trust of the shipyard in said concept.The final scope will be the calculation of the management reserve used to rectify any unforeseen item(s) in the construction of the ship.

Analytical models of unstable rarefied gas flow in channels and nozzles: simulation and comparison

Three different analytical models of unstable rarefied gas flows in channels and nozzles are compared using numerical simulations by MonteCarlo method. Numerical results have demonstrated the chaotic behavior of constructed nonlinear dynamic system and the limit properties of corresponding trajectories, attractors, and bifurcations of rarefied gas flows in channels. Flow conditions satisfying the experimental requirements are indicated where the instability of considered type can be detected. The advantages and the drawbacks of the considered approximations are detected and the features of obtained solutions are indicated. Recommendations are given for applying the results in practical applications and in numerical calculations of rarefied gas flows.

MODELLING OF AN A+B → A REACTION KINETICS IN CASE OF PARTICLES BIG FREE MEAN PATH

The aim of the work is to develop model and program for particle simulations working on laws of particle diffusion in expansion mode and, using approach of MonteCarlo, allows analyzing regularity in two-dimensional A+B → A reactions in case of B particle large mean free path, providing visualization of results and handy further processing of results, using data export ability. In the work are examined regularities in A+B → A reactions, special issues of these reactions, found approximate formula to determine velocity of reaction on centre of absorption surface using simulated data, developed program and made a lot of simulations of different reaction environments. Examined specific features of processed data and ways to enhance credibility and precision of results, also performed filtration of processed data to decrease specific of MonteCarlo method. Found out, that in comparison with nowadays personal computers, there is need for higher performance computing power to process simulation of particle interaction in acceptable timing.

The Montecarlo Method in Application of Fatigue Life Reliability Analysis

Based on the probability theory, combined with the deterministic method for estimating the fatigue fracture mechanics, the formula was deduced to calculate the fatigue crack propagation life of examples components. The uncertainty and randomness of main assessment parameters were considered:initial crack size, practical working load,fracture toughness, mechanical intensity and coefficients. Since there are not many data, Weibull distribution was adopted to denote the life distribution of equipment approximately. A computer program was developed by using numerical integration method, and the fatigue life under given reliability and credit degree was solved. Analysis result shows that MonteCarlo simulation method can reflect objectively the uncertainty of assessment parameters and overcome the shortcomings of certainty assessment methods.