Background and purpose: Muscle spindle is responsible for the control of skeletal muscle fibers function at rest and movement cycle, and is known as servo agent for voluntary movement. Function of this kinetic neceptor is completely dependent on the γ- ring activity would bring activity of la fiber and group II spindle muscle afferent. Also, there is close functional of muscle relationship between α and γ motor fibers which are important in the regulation of redial fiber function. Aim of this research was to study the activity of γ-ring more accurately in one or two consecutive cord segments, and also determine the α-motor fiber activity considering α- γ -linkage. Because more understanding of physiological mechanisms of γ-ring, and knowing the mode (mannar) of their environmental control, may be a way of underslanding the reason of peripheral factors involved in the onset of involuntary and distonic disorders, so, to be able to help more these group of patients. Materials and Methods: In this study, fifteen normal male. Sprague-Dawely rats with mean weight of 500 mg were selected. And urethane as an an aesthesia (30g/100ml) with dosage of 170 mg/100g body weight of rat was injected intraperoninally. For the study of the nerve fibers, laminctomy was done at the humbosacral regeon and surgery was performed at the first half regon of the tail. Results: Activity of γ-moto-neurons at on one cord segment due to external ear mechanical stimulation coused, the activity of γ-ring on one or two sequential cord segments, Ipselaterally, In a way that, increasing deporalization in la (such) fibers and skeletal of group II afferent fiber on coudal regeon was followed by increasing activity of one or more than one γ fiber. Also, la fibers always have more activity on the activity of homonymous moto neurons, comparing with group II afferent fibers, while the activity of group III afferent fibers, due to stimulation of caudal skin. Did not couse the activity of this group γ-moto neurons. Considering the function of potential range of α-γ-linkage in motor α-fibers (in) during deep anaesthesia, was at the basal rhythem. Conclusion: Duo to external ear mechanical stimulation homonymous moto neurons on one or two sequential segments of cord, caused the more activity of la fiber Ipsilaterally, comparing with with the group II afferents in one or more than one skeletal spindle. But group III afferent fibers activated by caudal skin stimulation, did had no stimulation on homonymous moto neurons. Also, considering the α-γ-linkage no activity was observed on motor fibers.

Introduction With the advent of big data in the last two decades, to exploit and use this type of data, the need to integrate databases for building a stronger evidence base for policy and service development is felt more than ever. Therefore, familiarity with data linkage methodology as one of the data integration methods and machine learning methods to facilitate the process of recording records is essential. Material and Methods The record linkage process has five major steps including data pre-processing, indexing, record pair comparison, classification and evaluation step. There are two key methods (exact and probabilistic record linkage) for linking records. Exact linkage involves using a unique identifier that is present on both files to link records. In the presence of a unique identity number in a different data source, record linkage is easy to implement. Where a unique identifier is not available, or is not of sufficient quality, it is made by probabilistic record linkage which check the similarity of the features of each record that are common to both files to find records that are likely to belong to the same person. Classifying the compared record pairs based on their comparison vectors is a two-class (match or a non-match) or three-class (match, non-match or potential matches) classification task. In traditional data integration approaches, record pairs are classified into one of three classes, rather than only matches and non-matches and a manual clerical review is required to decide the final match status. Most research in record linkage in the past decade has concentrated on improving the classification accuracy of record pairs. Various machine learning techniques have been investigated, both unsupervised and supervised. In this paper, in addition to introducing the record linkage process and some related methods, machine learning algorithms are used to increase the speed of database integration, reduce costs and improve record linkage performance. Most classification techniques such as support vector machine, decision tree and bagging method, classify each compared record pair individually and independently from all other record pairs. From the classification point of view, each compared record pair is represented by its comparison vector that contains the individual similarity values that were calculated in the comparison step. These comparison vectors correspond to the feature vectors that are employed to train a classification model, and to classify record pairs with unknown match status. Results and Discussion In this paper, two databases of the Statistical Center of Iran and the Social Security Organization are linked. Three classification techniques including support vector machine, decision tree and bagging method, were used for data integration. In addition, ROC curves were plotted to find the best method of classification. The results showed that the support vector machine and decision tree method performed better than the bagging method. Conclusion Statistical organizations are challenged by the need to integrate diverse sets of inconsistent data and produce stable outputs. Instead of making the best possible statistics from a single data source, finding the best combination of sources is necessary to deliver the indicators or statistics that most efficiently satisfy the users’,needs.

When the comprehensive information about a topic is scattered among two or more data sets, using only one of those data sets would lead to information loss available in other data sets. Hence, it is necessary to integrate scattered information to a comprehensive unique data set. On the other hand, sometimes we are interested in recognition of duplications in a data set. The identification of duplications in a data set or the same identities in different data sets is called record linkage. linkage of data sets that their information is registered in the context of Persian language has special difficulties due to particular writing characteristics of the Persian language such as connectedness of letters in words, existence of different writing versions for some letters and dependency of writing shape of letters to their position in words.In this paper, usual difficulties in linkage of data sets that their information is registered in the context of the Persian language are studied and some solutions are presented. We introduced some compatible methods for preparing and preprocessing of files through standardization, blocking and selection of identifier variables. A new method is proposed for dealing with missing data that is a major problem in real world applications of record linkage theory.The proposed method takes into account the probability of occurrence of missing data. We also proposed an algorithm for increasing the number of comparable fields based on partitioning of .composite fields such as address. Finally, the proposed methods are used to link records of establishing censuses in a geographical region in Iran. The results show that taking into account the probability of the occurrence of missing data increases the efficiency of the record linkage process. In addition, using different codes and notations for data registration in different times, leads to information loss. Specially, it is necessary to design a general pattern for writing addresses in Iran, considering geographical and environmental situations.