Introduction & Objective: Shoulder joint is the most common articular dislocations in the body. There are many surgical techniques for the treatment of recurrent shoulder dislocation. The aim of the study is to evaluate the short-term results of surgical technique of modified Bankart repair for recurrent anterior shoulder instability.Materials & Methods: Twenty patients underwent an operation at Tabriz Shohada hospital, from May 2005 to December 2007 and were followed up for at least 18 months. The data was analyzed by descriptive statistical methods. Results: There were 85% male and 15% female participants in the study, with the average age of 24.7 years (14-46 years). The mean number of dislocation episode before surgery was 6 (3-11). Two had minor glenoid rim fracture. There was no case of rotator cuff tear. During the follow up after surgery, two patients had recurrence of dislocation. The mean Rowe score was 94 and no infection or neurological complication was reported. Average external rotation loss was 5°.Conclusion: According to the above-mentioned data, modified bankart procedure is an acceptable method for treatment of recurrent dislocation of the shoulder.

Diagnosing and controlling the level of stress in order to reduce the risks is so important. In this study, a system for detecting five levels of stress, i.e. physical stress, semi-emotional stress, emotional stress, cognitive stress, and resting state in people based on physiological signals, is presented. In the proposed method, the Non-EEG Dataset for Assessment of Neurological Status database, which is available on the Physionet website, is used. This database contains physiological signals from twenty people. These data were collected using non-invasive wrist biosensors. A set of statistical and frequency and wavelet features are calculated for electrodermal (EDA), temperature, acceleration, heart rate (HR) and arterial oxygen level (SpO2) signals. The determined features are applied as input to the classification units to detect the stress levels. Support vector machine (SVM), k nearest neighbor (kNN), decision tree (DT), ensemble learning and neural networks are evaluated as classification methods. Experimental results show that neural networks can separate different neural states of 5 classes with 97% accuracy.

Temporal changes in the earth magnetic field occur in the frequency band of millihertz to a few hertz. Amplitudes of variations above 0. 1 Hz are usually much smaller than 1 nT, changes of 50-100 nT over periods of a few hours are not uncommon. Total-field aeromagnetic surveys typically require days or weeks to complete. An airborne magnetometer measures variations in the magnetic field caused by flying over magnetic geological structures and by temporal variations in the earth magnetic field. The most common method of estimating and removing the effects of time variations is called leveling. The standard procedure of leveling the data requires additional tie-lines flown perpendicularly to the original lines. In this study, a leveling approach is used without the need for tie-lines. The method, used in this paper, utilizes nine-point Hanning filter to creat a smooth representation of the regional magnetic field. The leveling errors are the difference between the flight-line raw magnetic data and the derived regional magnetic field. The magnitude of the error is minimized through least square method with a firstdegree function, and the correction involves only a diurnal correction (DC) shift. The technique is applied to the aeromagnetic data set acquired in Moalleman area, Semnan, Iran. The results show that the stripy effects are removed and the unleveled data is improved....

Extended AbstractIntroduction In geodesy, three levels are considered: the physical surface of the earth on which mapping measurements are made, the ellipsoidal reference surface (geometric datum) which is the basis of mathematical calculations, the geoid physical surface (physical datum) which is the basis for measuring heights. Satellite positioning systems measure the height of points relative to the ellipsoid surface. The geoid is one of the equipotential surfaces of the earth's gravity field, which approximates the mean sea level (MSL) by least squares. Geoid is very important in geodesy as a representative of the physical space or the space of observations made on the earth and also as the base level of elevations. The separation between the geoid and the geocentric reference ellipse is called geoid height (N). Although there is only one equipotential surface called geoid, various methods are used to determine it. These methods include: geometric method, geoid determination by satellite method, Gravimetric methods and geoid determination using GPS/leveling. Materials and MethodsIn this paper, the aim is to estimate the height of the local geoid using machine learning models. To do this, artificial neural network (ANN), adaptive neuro-fuzzy inference model (ANFIS), support vector regression (SVR) and general regression neural network (GRNN) models are used. The geodetic coordinates of 26 GPS stations in the north-west of Iran along with their orthometric height (H0) and normal height (h) were obtained from the national cartographic center of Iran. In all stations, the difference of orthometric height and normal height is considered as geoid height (N). Therefore, the geodetic longitude and latitude of the GPS stations are considered as the input of the machine learning models, and the corresponding geoid height was considered as the output. In order to test the results of machine learning models, two modes of 4 and 7 test stations are considered. Also, the output of the models is compared with the local geoid model IRG2016 presented by Saadat et al. for the Iranian region and also the global geoid model EGM2008.Results and DiscussionDue to the availability of a complete set of observations of GPS stations along with orthometric height obtained from leveling in the north-west region of Iran, the study and evaluation of the models proposed in the paper has been carried out in this region. Observations of 26 GPS stations of North-west of Iran were prepared from the national cartographic center (https://www.ncc.gov.ir/). Two modes are considered for training and testing of ANN, ANFIS, SVR and GRNN models. In the first case, the number of training stations is 22 and the number of test stations is 4. But in the second case, by increasing the number of test stations to 7 stations, the error evaluation of the models has been done. It should be noted that the distribution of training and test stations is completely random.After the training step of machine learning models and choosing the optimal structure, the test step is performed in two different modes (4 and 7 stations). At this step, the value of the geoid height in the test stations is estimated and compared with the value obtained from the difference of orthometric height and normal height as a basis. Two statistical indices of relative error in percentage and RMSE in centimeters were calculated for all models and presented in Table (1) for the first case.Table 1. Relative error (%) of ANN, ANFIS, SVR, GRNN and IRG2016 models in the test stations considered for the first case   According to the results of Table (1) and comparing the relative error values of all models in the test stations, it shows that the ANFIS model was more accurate than other models. After ANFIS model, IRG2016 model has higher accuracy than ANN, SVR and GRNN models. It should be noted that the IRG2016 local model uses the observations of all Iranian plateau stations to model the local geoid, and therefore it is expected that this model will be more accurate in the study area than other models. ConclusionThe evaluations show that in the case of 22 training stations and 4 test stations, the RMSE of ANN, ANFIS, SVR, GRNN and IRG2016 models in the test step are 37.32, 19.83, 49.34, 53.82 and 29.65 cm, respectively. However, in the case of 19 training stations and 7 test stations, the error values of the models are 36.63, 58.31, 39.64, 41.29 and 24.68 cm, respectively. Comparison of RMSE shows that ANN model with less number of training stations provides higher accuracy than ANFIS, SVR and GRNN models. The results of this paper show that by using ANN and ANFIS models, geoid height can be estimated and used with high accuracy locally in civil and surveying applications.

Background: Flexor tendon injury is one of the unanswered problems in reconstructive surgery of the hand. Although pull out method is one of the best reconstructive approaches but still is controversial. Surgeons prefer immobilization to prevent laceration at the site of the suture but it may cause adhesion and lead to surgical failure. The aim of this study was to perform a new surgical method to achieve a tendon repair without these problems.Methods: In this case-series study, 80 fingers with flexor tendon impairment selected and divided into four groups (tendon laceration & avulsion, tendon graft reconstructed in 1 & 2 stages) then patients were surgically treated by the new technique. The most important aspect of the technique is the placement of the suture in the direction of strength therefore, following any tension the suture would be tighter and this point help us to mobilize the injured tendon immediately after the surgery then we analyzed the results depends on the patient’s group.Results: The pull out and surgical (functional) results were evaluated. 97% of the pull out results were good and 3% were poor and surgical results were 23.9% excellent, 52.2% good, 17.9% fair and 6% poor. Conclusion: Depend on the acceptable results, immobilization in these patients is unnecessary & active and passive range of motion would be gradually increased as soon as possible. However biomechanical studies would be beneficial to evaluate this suture influence and designing future studies to compare this technique with old methods would be essential.

This paper is an attempt to shed light on the effects of modernization, urbanization, monolingual educational system, and mass media as well as the process of globalization on dialect leveling among Persian dialects. In so doing, the first part of the paper elaborates on the relationship between globalization and sociolinguistics, and on the concept of standardization.Also, it discusses some factors accelerating dialect leveling among Persian dialects. The second part of the paper presents some empirical evidence for the change, based on the data collected from 3 Persian dialects, namely: Birjandi, Neyshaboori, and Yazdi. Three spoken language sample corpora from two age cohort groups in each speech community were collected.Having transcribed the data, the researchers juxtaposed the phonological, morphological, and syntactic conventions of the two groups of each speech community for further in-depth analysis. Comparing the speech samples of the two age cohorts in each corpus revealed significant movements towards standard dialect. However, the quality and quantity of the observed movements did not appear to be the same across the dialects in question.

In this paper the issue of leveling and centering of total stations have been considered and has been proved that if the goal is to obtain the coordinates and/or geometry of an object it is not necessary to level and occupy a station, but instead the formulas introduced based on the orthogonal frame imbedded in the total station can be used to obtain the coordinates and/or geometry of the object without leveling and centering. In this way the time, which is needed, for the observations would be drastically reduced and as such it would be possible to use the total stations in the industrial environments in which only very short observation time is permitted. The details of the idea along with the proof of the formulas that are prevailing the geometry of an unleveled total station are given in the paper.

The turmoil in the business environment has led to unpredictable changes that, on the one hand, have created new opportunities to gain value and, on the other hand, have hampered companies' competitive advantages and, in some cases, led to their disappearance. In such an environment, successful organizations, especially knowledge-based companies, seek to use strategic entrepreneurship, that is, taking advantage of current competitive advantages and discovering innovations that determine future competitive advantage, as a key factor in achieving success. The need for strategic management and entrepreneurship activities simultaneously in the form of strategic entrepreneurship leads to a significant impact on the success of the company, the development of competitive advantages, effective allocation of resources in proportion to current and future activities. This research has used the meta-combined method to explain and identify the indicators of strategic entrepreneurship which has led to the identification of 70 codes, 16 concepts and 6 categories and has leveled them using the interpretive structural modeling method. It has been the case that environmental factors at the fourth level, organizational factors, economic factors and innovative factors at the third level and individual and social factors at the second level and entrepreneurial opportunities and capabilities at the first level.

Tillage practices during several years will result in an unleveled soil surface on farms. At present, in most regions of Iran, land leveling operations on farms are performed by conventional levelers and this leveling method does not have high accuracy. In this study, for the first time in Ahwaz city in south west of Iran, Miskin laser leveler and conventional leveler (Deghat Kesht Shiraz Leveler) were compared from technical aspects. This study was conducted in agronomic year of 2008-2009 on a farm with soil texture of clay loam in Albaji village which is located 10 km north of Ahwaz in Khuzestan province. Measured factors were water consumption volume, leveling index (LI) and land leveling uniformity coefficient (LUC). Research in the field of land leveling methods needs plots with large area, because in large areas, the leveling accuracy of leveler machines can be measured and compared correctly. Thus, our experimental farm included 14 plots, each one hectare. Statistical method for analysis was T-Student with two treatments (leveling by laser and conventional levelers) and seven replications. Statistical analysis was done by SPSS software. Results of mean comparison indicated that there is a significant difference at 1% level between laser leveler and conventional leveler for water consumption volume. Laser leveler reduced irrigation time about 35% as compared with conventional leveler. Therefore, application of laser leveler decreased water consumption volume about 82 lit/s. Leveling index in laser leveler was closer to zero in comparison to conventional leveler. On the other hand, the value of this index for laser leveling was more acceptable and suitable than conventional leveling. Also, LUC value for laser leveling was closer to one in comparison with conventional leveling. Thus, LUC value of laser leveler was better and higher than conventional leveler. Generally, regarding the obtained results in this study, application of laser leveler instead of conventional leveler can be recommended for leveling agricultural lands in Ahwaz.