Background: Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic Data is an important and difficult task.Objectives: The purpose of this study is to construct a two-way gene network based on parametric and nonparametric Correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value.Materials and Methods: In the foundation-application study, we constructed two-way gene networks using nonparametric Methods, such as Spearman’s rank Correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s Correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s Correlation, Spearman’s rank Correlation, and Blomqvist’s coefficient. Finally, these Methods were compared with Cytoscape, based onBIND, and Gene Ontology, based onmolecular function visual Methods; R software version 3.2 and Bioconductor were used to perform these Methods.Results: basedonthe Pearson and Spearman Correlations, the results were the same and wereconfirmedby Cytoscape and GOvisual Methods; however, Blomqvist’s coefficient was not confirmed by visual Methods.Conclusions: Some results of the Correlation coefficients are not the same with visualization. The reason may be due to the small number of Data.

Background and aims: The difficult tasks of firefighters' operational personnel, can determine the risk of hypertension and other acute cardiovascular and cerebrovascular diseases. Objective: This study aimed to determine the relationship between health literacy and self-care of hypertension among firefighters in Tehran. Methods: This cross-sectional descriptive-analytical study, which conducted in among 360 male firefighters, age of 18-60 years, working in the Tehran Fire Department in year 2019 was performed by two-stage sampling method in cluster and simple random. Data collection instruments were a demographic questionnaire together with the Standard Iranian Health Literacy in Adult questionnaire and the self-care checklist for hypertension. Data were analyzed in SPSS (version 22) using descriptive Methods and, analytical tests. Results: 57.5% of people were in the age group of 30-40. The mean score of health literacy was 73.96 with a standard deviation of 3.8. The highest mean score of health literacy was related to information perception and the lowest average score was related to reading skills. Among study sample, 44.2% had “good” and 26.7% had” very good” health literacy. Also, the mean score of self-care behaviors was 19.23 with a standard deviation of 3.4. About 14.4% of employees had a mean score of good self-care. There was a direct and significant Correlation between health literacy and self-care of 0/360 (p <0.0001 Conclusion: Health literacy and self-care behaviors were found to be not satisfactory. There was a significant positive Correlation between health literacy and self-care. Therefore, it is necessary to design an appropriate intervention.

This paper introduces a method of indoor positioning where multipath propagation exists due to reflective obstacles. In this method the fingerprint pattern is yielded by analyzing propagation delay Data. Unlike received signal strength (RSS) level Data needed for conventional RSS fingerprint method, propagation delay Data needed in this method is not altered by reflection from obstacles, meaning: while conventional RSS method requires actual measurements, using the proposed method, one can construct finger print pattern by mere analysis. Furthermore, the results from this method are more accurate and less ambiguous than those of RSS. This is due to the fact that whereas the signal strength level Data is received at one instance, the propagation delay Data as its nature suggests is received at a number of separate instances meaning it contains more information. The paper also provides an example to demonstrate the simplicity of the method and the accuracy of its results, which for the mentioned problem are of an average error of less than 3. 7cm and a variance of less than 6. 5cm.

In the last few years, the computer network technology has been improved by a large scale and therefore has influenced the application of distributed Data base systems for a better reliability, performance and inexpensive query processing. Hence, new application and Data base architecture for distributed Data base system need to be developed and several challenging issues have to resolved by research communities around the world. The major challenging issues for this new generation of Data base system deal with allocation, replication and portioning Data and influences of each other for a better design.In this paper, we present a heuristic and efficient algorithm to solve the problem of Data portioning and allocation at the same time. The Data portioning is vertically broken into two or more segments that are most efficiently allocated to Data base sites. To provide an efficient and cost effective portioning and allocation, an object function is developed and used for each iteration to intelligently getting closer to the optimized result. To examine the correctness of the algorithm, a typical problem is solved and then the results are discussed in this paper. A software package is implemented to be used for designing a distributed Data base system

Conventional Methods of velocity analysis are equivalent to modeling prestack seismic Data with events that have a hyperbolic moveout. Examples are included which demonstrate the depth, overlapping events and the details of the closed layers.Various types of measured coherency that can be used as attributes in computing velocity spectra are described here and some of them which are discussed in this paper are: Stacked amplitude (S), Normalized stacked amplitude (NS), Unnormalized cross-Correlation (CC), Energy-normalized cross-Correlation (EC), Semblance (NE) and AB Semblance. It is should be noted that all these Methods are based on the Correlation between the traces. The equations of different Methods are described and coded based on the corresponding literature and then applied to synthetic Data. The results of these Methods are compared in velocity and time with each other and their accuracy are examined. Four factors are introduced to compare the results of the velocity analysis Methods. The first factor is the contrast which means the ratio of the coherency in the exact velocity to the coherency of the near velocities. The second factor is the smearing on Data that measures the accuracy of the method used in detecting the velocity and the time of the events; it equals to the smearing in half of the difference between the coherency of the pick and the average coherency of the background. The third factor is the ability of the velocity distinction, it means how much a method can make difference between two near velocities. And the last factor is the ability of time distinction which indicates how much a velocity analysis method is able to detect two near layers with higher resolution. Fitness plots compare the performances of the six Methods when the velocity analysis is done on the same events in both time and velocity aspects. The sharpness of the fitness curves is in the relation with the velocity and time resolution. Then we introduced more noise to Data and discussed the effect of noise on the quality of the velocity analysis. Also the effect of the noise contamination is clearly explained and can be seen in another fitness plot. Additionally synthetic Data contains various multiples and overlapping events with different changes. Finally, CC, Semblance, and AB Semblance led to the best results, however; the AB Semblance proves its accuracy by maximizing a coherent measure in correct velocities and times and also by minimizing a coherent measure in incorrect velocities and times. Compared to the AB Semblance the vulnerability of the other Methods to the coherent noise is better understood.In the next step, these Methods were applied to real Data belonging to one of the southern oil fields in Iran and again the AB Semblance led to the best results. This method, in contrast to others, does not stretch velocities and displays shallow events as clear as deep events. We concluded that the AB Semblance method is able calculate the velocity and distinguish between the closed layers clearly better than the other Methods.

Technological development in production and use of materials has introduced growing demand to a powerful process kinetic Data-base. Opposite to the thermodynamic information’s available, rate processes suffer from complex formulation techniques and lack of a standard presentation method. Optimum metallurgical reactor design and control can only successfully be achieved via convenient compilation, standardization and recovery of the kinetic Data. Recent developments on creation of a comprehensive metallurgical kinetic Data-base utilizing a powerful search engine assisted with an electronic Data compilation system are discussed in this paper. The empirical/theoretical Data can be cross-checked through the application of the kinetic laws as well as the mathematical simulation models available. Electronic Data-transfer Methods are convenient routes for transfer of the collected information.

Background: Functional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging tool, used in brain function research and is also a low-frequency signal, showing brain activation by means of Oxygen consumption. Objective: One of the reliable Methods in brain functional connectivity analysis is the Correlation method. In Correlation analysis, the relationship between two timeseries has been investigated. In fMRI analysis, the Pearson Correlation is used while there are other Methods. This study aims to investigate the different Correlation Methods in functional connectivity analysis. Material and Methods: In this analytical research, based on fMRI signals of Alzheimer’, s Disease (AD) and healthy individuals from the ADNI Database, brain functional networks were generated using Correlation techniques, including Pearson, Kendall, and Spearman. Then, the global and nodal measures were calculated in the whole brain and in the most important resting-state network called Default Mode Network (DMN). The statistical analysis was performed using non-parametric permutation test. Results: Results show that although in nodal analysis, the performance of Correlation Methods was almost similar, in global features, the Spearman and Kendall were better in distinguishing AD subjects. Note that, nodal analysis reveals that the functional connectivity of the posterior areas in the brain was more damaged because of AD in comparison to frontal areas. Moreover, the functional connectivity of the dominant hemisphere was disrupted more. Conclusion: Although the Pearson method has limitations in capturing non-linear relationships, it is the most prevalent method. To have a comprehensive analysis, investigating non-linear Methods such as distance Correlation is recommended.