Linear Assignment (LAM) is one of the Multi-Attribute Decision Making (MADM) methods that uses integer programming models in the solution process. In this method, only the final priority of the alternatives is determined and the distance between the alternatives is not clear. The purpose of this paper is to modify this method so that instead of the final priority of the alternatives, the final weight of the alternatives is presented. This is done using a linear programming model of Data Envelopment Analysis (DEA). In this paper, we propose a hybrid MADM-DEA method called Linear Assignment Voting (VLAM). The new method is explained with a numerical example. The method will then be implemented on a problem in the real world to demonstrate the application of the method. In this case study, VLAM demonstrates the prioritization of models proposed by experts for the purchase of excavators in a road construction company. Also, based on the results of this method, the weight of the first, second and third priorities are 0.39, 0.35 and 0.26, respectively. These results increase the decision maker's power in making the final decision and choice.

The purpose of this paper is to enhance the quality of private hospitals in Egypt. The health care field, especially in the private hospital in Egypt has acquired huge importance lately because of its great contribution to the fast handling of patients. Today, customers of the private hospitals complain from slow handling during registration process, which may lead to making the patient condition worse and may refers to bad performance of the hospital at all. In view of the importance of these complains, the researcher selected the (PATH) as a tool to improve the quality in emergency department at hospital. Using that tool structural and organizational changes such as: quality committees; multidisciplinary teams and technology investments. The study found that applying the (PATH) in the emergency department leads to decrease the patient waiting time and leads to improve the overall performance of the ( Sina  hospital).

This research is conducted with the aim of providing an effective advertising pattern based on social networks in educational businesses industry. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study was a group of experts including senior managers of private sector educational institutions, university professors and marketing consultants familiar with the private educational services industry that in-depth interviews were conducted with them. The selection of experts and doing interview with them continued until the theoretical saturation was reached and then stopped. Snowball sampling method was used in this research and this process continued until reaching the theoretical saturation. 9 interviews were conducted in total. Due to using the data foundation theory in this research, the main data collection tool was unstructured in-depth interviews with experts. Finally, after three open, axial and selective kinds of coding, the conceptual model of the research was designed based on a paradigm model. Also, in this study, using AHP decision method, research variables were prioritized according to experts.

Due to the increasing importance of marketing, entrepreneurship and the role of organizational structure in their application, the purpose of this research is to predict entrepreneurial marketing using an organizational structure in the insurance industry. For this purpose, for marketing, seven indicators and for organizational structure, three indicators are defined, then prediction of entrepreneurial marketing indicators has been done by organizational structure indicators using lazy learning algorithm. In the proposed method, after predicting each data by K vector from its closest neighbor, the algorithm database is enriched for better prediction of future data. The proposed algorithm is simulated and compared in five different modes by MATLAB software, also, three insurance (Iran, Karafarin and Parsiyan) companies are selected in Mazandaran province. In total, the statistical population in this study is 588 cases. The results of simulation indicate the proper accuracy of entrepreneurial marketing forecasting based on validation parameters MSE and NRMSD. In this research, Lazy Learning method can predict future without modeling the problem with previous information processing.

Background: High-intensity interval training has recently gained popularity at improving cardiometabolic health. However, a close investigation of high-intensity interval training reveals that the exercise duration is similar to moderate-intensity continuous exercise. Objective: To compare the effect of the time-efficient ‘Gear’ exercise programmes to traditional exercise on cardiometabolic risk factors in persons with an elevated risk of cardiovascular disease. Methods: The study implemented a six-week, randomised controlled trial. The variables were low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, total cholesterol, glycated haemoglobin (HbA1c), blood pressure and body composition. Forty-eight participants completed the study. Participants were randomly assigned to either the ‘Gear’ exercise programme repeated at different times during the day (GEP-DT): cycled for 90 seconds, repeated three times/day, for three days/week (n = 12); ‘Gear’ exercise programme at one point in time (GEP-OT): cycled for 90 seconds followed by 4 minutes and 30 seconds rest, repeated three times at one point in time, for three days/week (n = 14); 30 minutes of moderate-intensity continuous cycling repeated three days/week at 55-69% HRmax (n = 11); and the controls, who were encouraged not to exercise (n = 11). Results: The 90-second GEP-DT intervention reduced HbA1c post six-weeks of training (MD = ­0.1±0.4, % Δ = -1.3%, d = ˗0.70). The GEP-OT group decreased blood triglycerides with a large effect size (MD = ­0.6±1.3, % Δ = ˗31.9%, d = ˗0.83). Conclusion: The novel 90-second ‘Gear’ exercise programme moderately reduced HbA1c and the 18-minute GEP-OT lowered blood triglycerides. ‘Gear’ exercise programmes will encourage future research in persons with non-communicable diseases, and it should be considered as a public health initiative to promote exercise in clinical, home and work environments.

Introduction  Flap reconstructions of upper extremity defects are challenging procedures. It is important to understand the surgical outcomes of upper extremity flap reconstruction, as well as associations between preoperative/perioperative variables and complications. Materials and Methods  The National Surgical Quality Improvement Program (NSQIP) database was queried for patients from 2005 to 2016 who underwent flap reconstruction of an upper extremity defect. Patient and perioperative variables were collected for identified patients and assessed for associations with rates of any complication and major complications. Results  On multivariate analysis, American Society of Anesthesiologists (ASA) classification >2, bleeding disorder, preoperative steroid use, free flap reconstruction, wound classification other than clean, and nonplastic surgeon specialty were independently associated with any complications. Bleeding disorder, ASA classification >2, male gender, wound classification other than clean, and preoperative anemia were independently associated with major complications. Free flap reconstruction was associated with increased length of stay, operative time, any complications, transfusions, and unplanned reoperations. Conclusion  There is an association between complications in patients undergoing upper extremity free flap reconstruction and ASA classification >2, preoperative anemia, preoperative steroid use, bleeding disorders, and contaminated wounds. Male patients may require more thorough counseling in activity restriction following reconstruction. Free flaps for upper extremity reconstruction will require increased planning to reduce the chance of complications.