Abstract

Nowadays, scientists consider the world as a combination of some systems that work in a self –organizing way and the result of such a way is unpredictable and accidential states. Compulsory Natural rules are affective In such circumstances. Also it is known that systems work in a circular form in which order ends in disorder and vice versa. The idea of world as something simple has already replaced by a complicated and contradictory world.
The new science is called the theory of complication or nonlinear dynamisms. one aspect of this science, attracting attentions, is named the theory of chaos or order in disorder. The theory of chaos is a total set which examines and processes the treatment of nonlinear complicated systems.
The growth of environmental turbulences, the instability resulted from it , and the capability of knowledge-based organizations in learning yields a new type of organizations we can entitle as chaordics organizations. The chaos theory is one of theories that specifies the quality of disorder and the way managers cope with it. Chaordics organizations are systems within them they show disorder along with a sort of order, and their activities are between order and disorder or stability and instability.
The study aim is to survey chaordic organizations characters of sport organizations, and for this purpose we used a standard questionnaire with appropriate reliability and validity.
The statistical population of the study are whole staff of sport and youth head-quarter of w.Azarbaijan province that are 89 (sample number is equal to the population\'s).
According to the results of this study and t-table we can deduce that sport organizations are chaordic organization.

Speckle noise is a characteristic artifact in breast ultrasound images since it hinders substantive information which assists the physician in diagnosing breast cancer accurately. Removing speckle noise while retaining finer details of the image is a prerequisite for breast ultrasound Computer Aided Diagnosis (CAD) systems. A modified Non Local Means (NLM) model using FCM clustering based pre classification and RIBM for removing speckle noise from breast ultrasound images is proposed in this article. The computationally intensive NLM filters have never been suitable candidates for real time image processing due to their sulky performance. Considering the NLM’s robustness against noise, it can be an appropriate filter for speckle degraded breast ultrasound images, if processing speed is improved. In this work, we have integrated FCM clustering based pre classification for reducing the processing time of NLM and Rotationally Invariant Block Matching (RIBM) for improved noise removal performance. The performances of the proposed framework is tested on synthetic images with artificially introduced speckle and evaluated using statistical parameters such as MSE, PSNR and SSIM. We have also utilized a Breast Ultra Sound (BUS) image database of 32 images including 17 benign cysts and 15 malignant tumors for the quantitative evaluation of the method. The experiment results are numerically evaluated using EPI and ENL as parameters and a comparative study is also performed with another state of the art method. The results produced an EPI of 0.2184 and ENL of 6.122 on the BUS image database which evidenced the superior performance of proposed method in preserving the finer details of the tumor while removing speckle noise.

The main aim of present research is knowing and preference of public sport needs of medical emergency staff in Guilan province. The research methodology is descriptive and statistical society research of medical emergency\'s staff of Guilan province that its number is more than 300 people. From these numbers on basis of Koukaran Formula 201 person are selected randomly as statistical sample. The measurement\'s device in this research is a questionnaire that involved in 33 questions in method of likert square 5 points yes-no and in a face of open answer is divided.
Narrative of this total questionnaire in method of countable Sigma with looking at 12 tones from experts of this location in university 0.89 and it strengthen in a method of testing 0.83. For analysis of data in according to measurement, aims and questions of research from descriptive statistics like profusion, profusion percentage and column diagrams for ranking is used and giving results show that sport equipments in a center of medical emergencies of Guilan province was so less and getting some equipments for fields and different sport salons is known as the most important needs of staff.

A survey on the efficiency of an integrated system consisting of Fenton oxidation followed by up flow aerobic reactor in treatment of petroleum wastewater

Background and aim. The Haemoglobin Constant Spring (HbCS) mutation is one of the most common non-deletion variants causing Alpha-Thalassaemia disease. High Resolution Melting analysis was developed to detect HbCS mutation on HbA2 gene effectively to decrease the alpha-thalassaemia hereditary for offsprings. Materials and Methods. Two healthy non-pregnant DNA samples and seven HbCS positive DNA samples was collected and detected by a real-time PCR SYRBGreen assay. The Realtime PCR assay was optimized based on the concentration of PCR reagents like DNA template, DMSO, Mg2+. The DNA fragment containing alleles of the mutation is amplified from the assay and will be analyzed by melting curve. Results. According to the normalized melting curve and the temperature shifted different plot, the difference in melting curve shapes present and the genotype of each individual which is related to the disease will be indicated clearly. The HRM method was optimized and developed successfully. The condition with 5% of DMSO and 2.5mM of MgCl2 is the best PCR condition and gave out the best separated melting curve shape in discriminating three various genotypes. Conclusion. This study showed that the HRM analysis is a reliable, simple tool and effective cost method for identifying HbCS variant in alpha globin genes and could be applied in clinical diagnostics.