Due to the explosive increment of data in recent application, available data storage cannot respond to this volume of data, for this reason molecular memory have been suggested in recent research. DNA is molecular data storage that can store a large amount of data in a limited space with high endurance. Storing data in low volumes can be provided using appropriate mapping. In this paper, a new method for mapping digital data to DNA have been proposed with the aim of simple coding, omitting the decoding faults, increasing the speed of coding and storing digital data and sign-digit with sufficient compression. Studies show that the proposed method can guarantee long-term retrieval of information from DNA compared to previous methods. It also uses less compression to store digital data as compared to the previous methods.

The neoclassical growth model is tested by use of panel data procedure in this research. In the econometric test, simoultanously time series and cross detection will be compared on the basis of panel data method through which their observed points increase and consequently the estimation efficiency will be increased. The examination of neoclassical growth theory has been done with reference to external & internal factors of 52 selected countries from 1960 to 2000. The independent variable of model has been selected on the basis of the result of previous research which explains the result in three separate models: developed countries, developing countries, and whole countries. These factors are such as: Gross National Products with lag of period, work force age, growth rate, education level, the change of capital accumulation and economic trade volum. The consequences of this research is that: neoclassical growth model can explain the major part of economic growth of the countries with use of internal variables. Also with the use of panel procedure of fixed effect, we can see the fundamental differences and structure of the growth process for different countries; and show how the economic, and social conditions affect on the growth.

Background and Objectives: Platelet activation occurs for a variety of reasons from the moment of sampling to that of injection. Activation of the platelets leads to activation of mitochondria. They move toward the membrane, sprouting and shedding freely from it, leading to the release of pro inflammatory mediators and mtDNA. Therefore, mtDNA level is considered as one of the parameters of platelet activity. The aim of this study was to compare mtDNA levels during storage. Materials and Methods: This experimental study was performed on 22 PRP products. We obtained consent of all donors referring to Iran Innovation Center of Iranian Blood Transfusion Organization. Samples were taken from the PRP bags on day 1, 3 and 5. Then, the fold change of mtDNA was assessed by Real time PCR. The results were analyzed by paired t-test and the P value of less than 0. 05 was considered significant. Results: The rate of mtDNA decreased 0. 8-fold on day 3 to 1, 0. 6-fold on day 5 to 3, and 0. 49 on day 5 to 1. These changes were significant on days 5 to 1 (p= 0. 003) and they were not significant on days 3 to 1 (p= 0. 4). Conclusions: The amount of mtDNA increased on the first day, and then decreased during the storage of PRP products.

We present a novel approach to data storage based on holographic principles that encodes information in geometric structures rather than discrete units. Building on recent advances in geometric error correction and holographic duality, we develop a mathematical framework for storing and retrieving information using topological invariants that provide natural error protection. We prove that this approach achieves information preservation without active error correction, leading to inherently robust memory systems. Our framework provides explicit constructions for encoding classical and quantum data in geometric structures while maintaining error protection through topological invariance. We demonstrate theoretical bounds showing superior error resistance compared to traditional storage methods, along with practical implementation strategies using current technology.

Background: The characteristics of medical data in Precision Medicine (PM), the challenges related to their storage and retrieval, and the effective facilities to address these challenges are importantly considered in implementing PM. For this purpose, a secured and scalable infrastructure for various data integration and storage is needed.Objective: This study aimed to determine the characteristics of PM data and recognize the challenges and solutions related to appropriate infrastructure for data storage and its related issues.Material and Methods: In this systematic study, coherent research was conducted on Web of Science, Scopus, PubMed, Embase, and Google Scholar from 2015 to 2023. A total of 16 articles were selected and evaluated based on the inclusion and exclusion criteria and the central search theme of the study.Results: A total of 1,961 studies were identified from designated databases, 16 articles met the eligibility criteria and were classified into five main sections: PM data and its major characteristics based on the volume, variety and velocity (3Vs) of medical big data, data quality issues, appropriate infrastructure for PM data storage, cloud computing and PM infrastructure, and security and privacy. The variety of PM data is categorized into four major categories. Conclusion: A suitable infrastructure for precision medicine should be capable of integrating and storing heterogeneous data from diverse departments and sources. By leveraging big data management experiences from other industries and aligning their characteristics with those in precision medicine, it is possible to facilitate the implementation of precision medicine while avoiding duplication.

Todays gamma knife radiosurgery is used widely for treatment of very small brain tumors. In order to investigate accuracy of dosimetry and treatment planning calculations, using Monte Carlo simulation with dedicated code named as beamnrc including non-CT data and CT data options is necessary. The aim of this study is choosing the best options in order to have an accurate tools based on their advantages and disadvantages. In this study, gamma knife unit 4C along with standard water equivalent phantom and EBT3 films were used to obtain dose distributions. Monte Carlo simulation was done with non-CT data and CT data options of the code and their resulting dose were compared. Comparison the calculated and measured dose distributions at X, Y and Z axis showed gamma value below 1 which verified Monte Carlo simulations. Also comparing the dose distributions from both non-CT data and CT data with each other implies that there is no significant difference between two methods. Based on the obtained results using non-CT data and CT data results in the same dose distribution. So for simplicity, using non CT data for regular phantom shapes is preferred.