Purpose: The aim of this study is to report a successful management of a sever nonspecific chronic low back pain relating to visceral stiffness and altered respiratory pattern. Clinical Findings: A 33-year-old female with nonspecific low back pain, with abnormal visceral stiffness, pain in the right abdominal side, pain and tenderness in areas of pelvic and respiratory diaphragms and inability in diaphragmatic breathing. Pain severity was reported as 10 based on VAS. MRI findings showed intervertebral disc protrusion at L5-S1 level. Diagnosis: Pain derived from visceral spasms. Management: Four sessions of visceral manipulation with diaphragmatic breathing exercises and general stretching exercises. Results: At the end of 1st session, the pain severity was improved for 80%, at the end of 2nd session the patient was able to perform perfect diaphragmatic breathing and pain severity was reported 3 based on Visual Analogue Scale (VAS). After 3rd session, pain was felt only at the time of wake up.

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.

Managers accomplish earning management through real earning manipulation and accrual earning manipulation. Accomplishment of both options of earnings management has relative restrictions and relative costs. The problem is whether earning management choices accomplish simultaneously or one option accomplished before another. Therefore, the aim objective of this paper is to determine the substitutive relation between earning management choices (i.e. real earning management and accrual management). For hypothesis test in this study, data for 117 listed companies on Tehran Stock Exchange for period of 1380–1388 is used. To test research hypotheses, Hausman test and multiple regression model approach is applied. The results of this research indicate a substitutive relation between accrual earning management and real earning management. Also the results indicate that managers determine real earning management before accrual earning management.

Public confidence in the fairness of stock markets increases their efficiency and liquidity. Manipulating stock market destroys its coherence and decreases public confidence about the authenticity of the market. Manipulation of market leads to false and nominal prices and creates misleading appearance of market activity trend.To support the capital market investors, legal systems principally banned manipulation of stock market and have set penalty.Elements of market manipulation crime and prescribed penalties are different in different legal systems with the approval of stock market law in 2005 and according to Article 46 of this law, manipulation of stock market was considered a crime and its punishment was determined.

Extended Abstract Background: Honeybees have an important role in the pollination of plants. Apis florea Fabricius, 1787, has been described over the last two centuries.   A. florea is distributed in Vietnam, south-eastern China, India, Nepal, southern Thailand, Sri Lanka, Sudan, southern Iran, Pakistan, Saudi Arabia, and Oman. The climatic zones of A. florea change from tropical rainforest in the east to savannah in the west. Furthermore, westwards, the climatic zones change from tropical to subtropical steppe and semi-desert. Morphometric data were used in addition to analyses of molecular data to study the honeybees. Morphometric analyses are flexible tools employed by users in different areas of the world. The geometric morphometric method uses landmarks that can be located precisely on the vein junctions of wings. The geometric morphometric method has been used to compare the populations of A. florea. In addition, traditional or standard morphometric methods have been used to study the populations of A. florea in various areas of the world. The landmark configurations eliminate the effects of position, orientation, and size of shapes. Data on shapes are converted into Procrustes coordinates using the geometric morphometric method. Regression analysis between centroid size and Procrustes coordinates creates new data on the residuals, which can be applied in other analyses. No published research has utilized residual coordinates (residual data) to compare the populations of A. florea. Therefore, the current research aimed to compare the performance efficacy of residual and Procrustes coordinates in differentiation and relationships among the populations of A. florea in various areas of the world. Methods: Samples of the A. florea honeybee species were prepared from their distributed areas. The right forewings of honeybees were used to study the relationships among the various populations. Eighty samples were selected from each area. A tps file was built by importing the right forewing pictures into TpsUtil V. 1. 64 software. Then, the tps file was loaded into tpsDig V. 2. 18. Twenty landmarks were digitized in the vein junctions of the forewings. This was followed by the raw data obtained from landmarks, loaded into the MorphoJ software V. 1. 06d, and converted into Procrustes coordinates for use in future analyses, followed by analyzing the Procrustes coordinates. Mahalanobis distances and canonical variates were obtained using permutation tests. The regression between Procrustes data and centroid sizes was calculated, and an allometry test was performed afterward. The residual coordinates (residual data) were obtained after the removal of the size effect (size correction) from shape variables. The residual and Procrustes data were imported into PAST software v. 3. 19, and the populations of A. florea were compared using Canonical Variate Analysis (CVA). Moreover, clusters were drawn with the residual and Procrustes data using SAS v. 8 software. Results: Multivariate (MANOVA) and pair-wise analyses of residual and Procrustes data were tested for the populations of A. florea. The Procrustes and residual data of the populations showed statistically significant differences using MANOVA (p < 0. 001). Moreover, the tested pairwise comparisons indicated that all populations were significantly different in Procrustes and residual data (p < 0. 001). The landmark configurations of forewings were superimposed, and variations were obtained between the populations. The highest variation was found in the vein junction of R and Rs, landmark 19 (S2 = 0. 0000622). The lowest variation was observed in the vein junction of Cu and 1m-cu, landmark 8 (S2 = 0. 0000109). The populations of various areas were compared using Canonical Variate Analysis (CVA). In the CVA of Procrustes data (Procrustes coordinates), the first and second components included 75. 94% of all variation (CV1 = 28. 74% and CV2 = 47. 20%). In addition, in the CVA of residual data, the first and second components included 83. 06 % of all variation (CV1 = 31. 46 % and CV2 = 51. 60 %). The CVA results of Procrustes data showed that the Pakistan samples overlapped with the Iranian samples, except for the Kerman population. Sudan samples overlapped with the Iranian samples of Bushehr, Shiraz, and Sistan and Balochestan. Additionally, Oman samples showed partial overlapping with South India and Kerman (Iran). The CVA results of residual data showed that the Pakistan samples overlapped with the Iranian samples, except for the Kerman population. Sudan samples were differentiated from Iranian samples. In addition, the Oman samples showed partial overlapping with South India. Both Procrustes and residual data differentiated the populations of Thailand and Vietnam from the other populations. Cluster analysis was used to compare the populations of A. florea in various areas. The cluster derived from Procrustes data indicated that Sri Lanka was closer to the populations of Iran, except for the Kerman samples. Furthermore, the Sudan and Pakistan populations were categorized under one group. In addition, the cluster derived from the residual data indicated that the Pakistan population was closer to the populations of Iran, except for the Kerman samples. The Sri Lankan population indicated a closer relationship with India, and the Sudanese population was differentiated from the other populations.    Conclusions: The recent findings showed that residual data revealed greater efficacy than Procrustes data in differentiation and relationships between the populations of A. florea. The results of the derived cluster from residual data indicated closer relationships of A. florea populations from Pakistan and Sri Lanka with Iran and South India, respectively.

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.

This research explores the manipulation of biomedical big data and diseases detection using automated computing mechanisms. As efficient and cost effective way to discover disease and drug is important for a society so computer aided automated system is a must. This paper aims to understand the importance of computer aided automated system among the people. The analysis result from collected data contributes to finding an effective result that people have enough understanding and much better knowledge about big data and computer aided automated system. Finally suggestions have been developed for further research related to computer technology in manipulation of big data, disease detection and drug discovery.