The boosting algorithm is a hybrid algorithm to reduce variance, a family of machine learning algorithms in supervised learning. This algorithm is a method to transform weak learning systems into strong systems based on the combination of different results. In this paper, mixture models with random effects are considered for small areas, where the errors follow the AR-GARCH model. To select the variable, machine learning algorithms, such as boosting algorithms, have been proposed. Using simulated and tax liability data, the boosting algorithm's performance is studied and compared with classical variable selection methods, such as the step-by-step method.

Background: Common variable immune deficiency (CVID) is the commonest symptomatic primary immunodeficiency and represents a heterogenous collection of disorders resulting mostly in antibody deficiency and recurrent infections. The syndrome includes impaired B-cell maturation, impaired somatic hyper mutation, reduced numbers of circulating memory and isotype-switched memory B cells, and absent or reduced plasma cells. B cell maturation antigen (BCMA) is a tumor necrosis family receptor superfamily member 17 (TNFRSF17), expressed only on B cell lines, and is essential for survival of long-lived plasma cells. The aim of this study was to evaluate mutations in BCMA in patients with CVID in compare with normal individuals in Isfahan, Iran.Methods: Blood samples were collected from 10 CVID patients with substitutive immunoglobulin therapy before immunoglobulins (Ig) infusion and 10 normal controls in ethylenediaminetetraacetic acid (EDTA) tubes then DNA samples were extracted and after the polymerase chain reaction (PCR) was done, samples were sequenced.Findings: After reviewing the results of the sequence and alignment of the sequences, no mutations in the gene were seen.Conclusion: In addition to the study of mutation in BCMA gene, BCMA gene and protein expression level should be considered to understand more aspects of this disease.

The Effect of different culture conditions on growth and production of antimicrobial agents by Oudemansiella spp, using the Variable Size - Simplex Design, were investigated. The results obtained from the experiments indicated that the optimum condition for growth and production of antimicrobial agents, situated at pH between 5.6 and 6.8, temperature between 28°C and 30.6 ºC, shaking rate between 137 and 170 rpm. The results also showed the fungus grow and produced antimicrobial agents at a very wide range of glucose concentration. Increasing the concentration of glucose over 15 g/L, resulted in decreasing the activity of the fungus.

Dynamic Analysis of an axially moving cable with time dependent tension and velocity is studied in this paper. Tension force and the moving speed are assumed to be harmonic. It is found that there exists a specific value of speed in which natural frequency of the system approaches zero. This specific speed for such a critical condition is called critical speed and it will be proved that increasing the cable tension increases critical speed of the moving cable. Multiple-Scales perturbation technique is used to discretize the nonlinear equations of motions. Critical speeds are then obtained in which vibrations of motion become unstable. Stability analysis is carried out for different sets of excitation frequency. Dynamic responses of the system are calculated using Galerkin’s method. A comprehensive parametric study is carried out and effects of different parameters like the moving speed and tension force on the responses are studied both in frequency and time domain.

The sled system is used to test anti-penetration structures, ejection seat, and spacecraft equipment that its technology is owned by a few developed countries. In this research, the dynamic analysis of applied forces on the system has been investigated. The effective forces on the sled include propulsive force, drag force, lift force, and friction force, which are all variable. To obtain the propulsive force according to the functional and geometric specifications of the designed sled, the grain engine design has been carried out to reach 0. 85 Mach in a second. After extracting the governing equations for extracting the propulsive force, the changes of the propulsive force during the combustion time were obtained and formulated. At the next step, numerical simulation is used to obtain the lift and drag forces and after validating the numerical solution with experimental research, the values of drag and lift forces at different speeds are extracted and formulated. Next, due to sled mass variations during the combustion step, the friction force between the rail and the slipper is obtained. Finally, the differential equation and dynamic behavior of the system are analyzed. The results show the highest pressure is applied to the inner part of the slipper, which can lead to wear and damage of the rail surface at high speeds and lead to the sled deviating from the rail track. Also, the amount of friction force is negligible in comparison with other forces.

In this paper coupled nonlinear equations of motion of a suspended cable with time dependent tension and velocity are derived by using Hamilton’s principal. A modal analysis for a stationary sagged cable is initially carried out in order to identify the dynamic system. The natural solution is directed to compute the natural frequencies and mode shapes of the free vibration of a suspended cable.Natural frequencies and mode shapes are plotted versus a dimensionless parameter l, known as static sag character. In case of moving cable, the tension force and the rotary speed of the pullies are assumed to be sinusoidal functions. Galerkin mode summation approach is utilized to discretize the nonlinear equations of motions. Numerical simulations are carried out in the time domain. A frequency analysis is then carried out and effects of the frequency of tension force and rotary speed on the belt dynamic responses are studied.

Background: A common way for computing test-retest reliability is Intra Class Correlation which was developed for continuous variables. But it widely used to assess test-retest reliability in questionnaires with Likert scales. Most of the time consecutive numbers regarded as option labels of a question. If the probability of choosing options be the same, using this method is logic, otherwise it is not. Therefore, in this study a modified estimator of ICC is proposed to improve the estimation of ICC for ordinal scale by using latent variable model. Method: In this method test-retest answers were considered as bivariate variables and cumulative Probit latent variable model was fitted. A simulation study with N=1500 replicates was conducted to compare the ICC estimations of Likert scale approach with a latent variable approach. Different sample sizes (n=20, 30) was generated with different correlation parameters. The simulations were repeated for questions with 3 and 5 options with different probability of selecting options of a question.  After that the two approaches were run on Beck for suicidal ideation questionnaire. Result: In general the difference between Likert scale approach and latent variable approach were higher in 3 question options compared to 5 and also by increasing sample size and correlation between bivariate data, Root Mean Square Errors and bias were decreased. Assuming different probabilities for options, there was a considerably difference between Root Mean Square Errors, bias and standard deviation of estimation of ICC in two models. Using latent variable approach resulted less bias, SD and Root Mean Square Errors especially in lower sample sizes. Conclusion: Simulations showed when the probability of choosing options of a question are skewed, using this method reduced Root Mean Square Errors especially when the options are less. This method was affected more on standard deviation compare to bias of estimations.