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Background: Respiratory motion causes thoracic movement and reduces targeting accuracy in radiotherapy. Objective: This study proposes an approach to generate a model to track lung tumor motion by controlling dynamic multi-leaf collimators. Material and Methods: All slices which contained tumor were contoured in the 4D-CT images for 10 patients. For modelling of respiratory motion, the endexhale phase of these images has been considered as the reference and they were analyzed using neuro-fuzzy method to predict the magnitude of displacement of the lung tumor. Then, the predicted data were used to determine the leaf motion in MLC. Finally, the trained algorithm was figured out using Shaper software to show how MLCs could track the moving tumor and then imported on the Varian Linac equipped with EPID. Results: The root mean square error (RMSE) was used as a statistical criterion in order to investigate the accuracy of neuro-fuzzy performance in lung tumor prediction. The results showed that RMSE did not have a considerable variation. Also, there was a good agreement between the images obtained by EPID and Shaper for a respiratory cycle. Conclusion: The approach used in this study can track the moving tumor with MLC based on the 4D modelling, so it can improve treatment accuracy, dose conformity and sparing of healthy tissues because of low error in margins that can be ignored. Therefore, this method can work more accurately as compared with the gating and invasive approaches using markers. Citation: Rostampour N, Jabbari K, Nabavi Sh, Mohammadi M, Esmaeili M. Dynamic MLC Tracking Using 4D Lung Tumor Motion Model- ling and EPID Feedback. J Biomed Phys Eng. 2019;9(4):417-424. https://doi.org/10.31661/jbpe.v0i0.769.

"nBackground: Overactive bladder (OAB) is one of the most prevalent diseases of lower urinary system. OAB disease is defined by the Standardization Subcommittee of the International Continence Society as urinary urgency, with or without urge incontinence, usually with frequency and nocturia with no proven infection or other obvious pathology. Treatment with the antimuscarinic agents tolterodine and oxybutynin is the mainstay of therapy for overactive bladder. The study was undertaken to compare the efficacy and side-effects of tolterodine and oxybutynin in a number of Iranian women."n "nMethods: This study consisted of two trials and done in Imam Khomeini Hospital in 2009; in one trial, 50 patients with overactive bladder were randomized to 4 weeks of treatment with 2 mg of twice-daily tolterodine, and in the other to 5 mg of three times a day oxybutynin. Urodynamic investigations, Episodes of urge urinary incontinence and adverse events were also evaluated."n "nResults: The results showed a good association between the questionnaire and cystometry data but urodynamic studies showed significant differences in efficacy. Tow groups showed significant improvements in all Symptoms, but The results showed that the two drugs had no significant differences in efficacy."n "nConclusion: The data obtained by questionnaire indicated that both drugs increased quality of life but there were no significant differences between the two in symptom cure. Dry mouth was the most common side-effect in the two groups but unlike other studies it was higher in the tolterodine group. Therefore, our study did not show any preference between oxybutynin and tolterodine.

The purpose of this study was the utilization of different methods of tissue culture in proliferation of epithelial cells and autologous graft to cover surface areas without skin specifically, which is due to thermal burns more than 50%. In this experience we performed from rabbits and success to cover almost 24 times original donor site with autograft.

Hurricanes are among the most destructive and costly extreme weather events. The intensity of future hurricanes is generally expected to increase due to climate change effects. In this work, a simulation method based on a comprehensive statistical analysis of historical data is developed to account for the changes in climatological conditions and their effects on the frequency and intensity of hurricanes. This method is applied to simulate hurricane wind speed distributions under different climatological conditions in the US Atlantic basin from Texas to Maine, which is one of the regions in the world most vulnerable to hurricane hazards. To this end, regression models for several different hurricane parameters are fit to the historical hurricane data. The proposed model is validated by comparing its predicted hurricane-induced wind speeds with available historical data and other existing models based on physics-based hurricane path simulation. This new model is found to reproduce very well historical wind speed distributions and to provide wind speed projection results that are consistent with those of more computationally expensive models based on the simulation of hurricane tracks. The statistical characteristics of future potential hurricanes are simulated using the proposed model along with the climate projections presented in the Fifth Assessment Report of the Intergovernmental Panel for Climate Change. The results of this study indicate that by the year 2060 and depending on the considered projection scenario, the design wind speeds along the US Gulf and Atlantic Coasts corresponding to the different mean return intervals considered by ASCE 7 are expected to increase on average between 14% and 26%, which corresponds to an average increase in the design wind-induced loads of between 30% and 59%.

Suppliers as one of the main sources of vulnerability may lead to disruption and risk in supply chains. Thus, resilient supplier selection can lead to an increase in the resilience of the supply process, especially in automotive supply chains. The goal of this study is to select a set of resilient suppliers and optimal demand allocation in an automotive supply chain under risk. For this purpose, a bi-objective two-stage stochastic programming model is presented. In contrast to previous mathematical models, our model includes a new objective function to consider the supplier’s delivery performance as one of the criteria of resilient supplier selection and also the k-means clustering method is used to cluster and decrease the number of disruption scenarios. In the proposed model, due to the uncertainty of demand, chance-constrained programming approach has been utilized. The augmented Ɛ-constraint method is implemented to solve the presented model. Finally, sensitivity analysis has been done to determine the effect of parameter changes on the final results. The results of the research indicate that contingency planning can reduce the effect of disruption risks. The findings also show that the strategy of the supply chain regionalization is important in reducing the effects of environmental disruption. [ABSTRACT FROM AUTHOR]

Preservation of historic buildings is a main challenge in the civil engineering field. One of the main concerns about this subject is to be sure of environmental effects like noise and vibration on monuments. To overcome these problems, a wide range of noise and vibration mitigation measures could be applied. To reach a proper evaluation, in this paper, a detailed assessment is made on the efficiency of various vibration mitigation measures by a series of field tests and sensitivity analysis in Isfahan metro lines close to some vibration-sensitive cultural structures. The sensitivity analysis was performed in possible ranges of vertical stiffness of track superstructure materials. Results showed that vertical track stiffness equal to 5 kn/mm would lead to a 5 db reduction with regarding 4 millimeters limit of rail deflection. [ABSTRACT FROM AUTHOR]