Proteins are sources of many peptides with diverse biological activity. Some of them are considered as valuable components of foods and drug targets with desired and designed biological activity. We are now entering an era rich in biological data in which the field of bioinformatics is poised to exploit this information in increasingly powerful ways. There are currently many Databases all over the world housing information that floods from the genome project. Nevertheless, as Databases become more comprehensive, as the volume of sequence data expands and search outputs become more complex, the different Databases play an increasingly major role in the post genomic era. However, the rate of sequence generation and overwhelmingly proliferation of Databases have made it difficult to keep up with developments. Researchers now need rapid, easy to use, reliable tools for their use in functional characterization of newly determined sequences. This paper aims to provide a comprehensive overview on the status of protein Databases available in the World Wide Web. As this is a fast moving area, a list of all the mentioned Databases along with their current URLs are presented ill a table at the end of the article.

This study aimed to present Climatic Research Unit (CRU) data and assess the accuracy of this data with the latest GPCC updates against the synoptic stations data during 2014-1985. For this purpose, monthly precipitation from GPCC Full Data Version 7, monthly precipitation and temperature from CRU TS3. 23 with 0. 5 × 0. 5 degree spatial resolution, monthly total precipitation, and average of minimum, maximum and mean daily temperature of 88 synoptic stations with proper distribution in Iran were gathered and analyzed. To assess the Databases that mentioned R square, RMSE, IA, Bias, slope of the regression and EF indicators was used. Statistical comparisons revealed that, although accuracy of CRU precipitation dada in Iran, especially in the western half of country, is well, but in some regions, especially coastal areas, is less reliable. Because the R square in these areas is less than 0. 5, while the accuracy of GPCC data in all areas of Iran even coastal stations is very high. So, the amount of its precipitation in different regions of Iran is very close to the amount of precipitation recorded in the synoptic stations. Temperature components (average, minimum and maximum) assessment shows that although CRU amounts in the Caspian coastal area have more deviation than other areas, but, more than 95% of the observed data variance across the country explained by CRU and most of the CRU data distributed around the regression line. This term represents very high accuracy and reliability of CRU gridded temperature data in Iran. Based on the results of this study suggested that in the regions with no data, GPCC precipitation data and CRU temperature data to be used.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of Statistical energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the Statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Background and Aim: The main challenge in each organization, in particular healthcare organizations deal is effective utilization of information stored in their various information systems. Large amounts of data will have organizational value as they convert to a knowledge which help the organizations in cost controlling, profit increasing as well as maintaining the quality of patient care. The aim of this study was to determine initiatives and methods for effective utilization of data and information stored in Databases of healthcare organizations in developed countries. Materials and Methods: Through systematic review, the articles regarding KDD published since 1990 were reviewed. After studying books and journals related to data and Databases in the libraries of Iran University of medical sciences, central library of Amir Kabir University, library of Science and Industry University, articles published by Databases such as ScienceDirect, Pubmed, Proquest, Blakwell as well as the sites of international organizations working on knowledge discovery and data mining were also reviewed. Results: Necessity for effective utilization of large amount of data has been the subject of a field called Knowledge Discovery in Databases (KDD). Extensive initiatives have been done in developed countries and distinctive steps have been determined for knowledge discovery since 1989. Fraud detection, marketing and customer retention are some examples of KDD applications in several industries. Similar applications regarding patient-oriented and quality improvement in healthcare are examples of KDD applications in the healthcare industry. Using capabilities of various sciences, several approaches have been developed by which current soft wares are extracting hidden knowledge from large Databases. Quantitative approaches such as Probabilistic and Statistical approaches, classification approaches such as Bayesian, decision tree and other methods including deviation and Trend Analysis, generic algorithms, neural networks and hybrid methods which use two or more techniques are used in KDD tools. Conclusion: Healthcare organizations can discover hidden knowledge in Databases by using software programs developed based on one or more KDD techniques, and along with cost reduction, they can use its interesting results for decision making in their activities.

The last three decades the use of Databases and registries in the field of medicine has created, along with the use of personal computers and the internet, a major revolution in the way of learning and practicing medicine and surgery.