To examine relationship of SUPERVISORs and students with respect to learning improvement, dissertation and knowledge production is of great importance. To choose a SUPERVISOR is one of important decisions made by doctoral candidates. Consequences of this SELECTION as well as proper relationship with SUPERVISOR may affect dissertation assessment and continuation of future research guided by the same SUPERVISOR.The present study aimed to improve this process and examine its consequences. Initially, through literature review and interview with experienced SUPERVISORs of doctoral candidates 20 indicators were identified. Then, a questionnaire developed on the basis of the indicators was administered to 31 PhD graduates in education. Results indicated that SUPERVISOR SELECTION and student-SUPERVISOR relationship were found to be relatively satisfactory. Significant differences were also found between graduates in terms of their dissertation marks, tendency to work under the same SUPERVISOR for future research, and satisfaction of their choice and relationship. Finally, based on content analysis of open-ended questions some suggestions were made towards improvement of SUPERVISOR SELECTION and relationship of students and SUPERVISORs. Results were discussed in the final section of the paper.

Dissertation SUPERVISOR SELECTION is one of the most important and crucial decisions in doctoral programs. Typically, SELECTION process is based on a set of criteria such as SUPERVISORs’ reputation, number of dissertations guided, continues supervision, etc. However, the application of these criteria is often subjective and intuitive and it can cause dissatisfaction, delay on completion time, and quality reduction of dissertations. This article proposes a new model for doctoral dissertation SUPERVISOR SELECTION by using multi criteria decision making (MCDM) method. In order to identify the key criteria, a review of literature and purposive sampling were used. By means of purposive sampling 37 senior doctoral students of Tarbiat Modarres University were selected and key criteria were identified through a questionnaire. Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach were utilized for prioritization and identification of criteria’s level of importance. The finding showed significant differences between priority expectations of sample and selected sample. In addition, the findings revealed that SUPERVISOR’s reputation was first priority for the sample and continuous supervision was main concern for selected sample.

Determining medical students' attitudes towards the topic SELECTION and choosing the SUPERVISOR can be helpful in assisting programmers to better reform and promote the level of research in the field of health in the country. The goal of this study is the investigation of criteria which medical students of Shahid Beheshti University of Medical Sciences select for choosing the thesis topic and SUPERVISOR. In this descriptive-analytical study, 123 medical students that most of them being in the internship stage were surveyed. Data gathering tool was a questionnaire. Data were analyzed by using Chi-square test or Fisher's exact test with SPSS software.65.9% of students disinterest to dissertation writing. The most prevalent criterion for choosing the thesis topic and SUPERVISOR of students was "uncomplicated and short-term topic" and "cooperator SUPERVISOR for finishing dissertation". Interest to dissertation writing, time of the topic SELECTION by students and topic SELECTION by students themselves were factors influenced students' attitudes. Majority of medical students want to finish their dissertations as soon as possible. Disinterest to dissertation writing, military services and residency exam are some reasons of this fact. Financial and spiritual supports and making basic changes in planning of medical education, military service and residency exam has positive influence on the attitudes of medical students and improve the quality of their dissertations.

Purpose: Managers are one of the important elements of an organization, for this reason, in order to draw the future of the organization, it is necessary for the planners to specify the conditions of their SELECTION and appointment. Therefore, the current research has been done with the aim of identifying and analyzing the components of selecting future principals.Method: In this research, comparative and benchmarking method is used as a prospective approach. This approach is based on the belief that today's advanced organizations/countries can be considered as a model for the future of another organization/countries in their respective subjects. For this, first, the fields of comparison and benchmarking were determined using Brody's four-step comparison method; then the countries of Canada, Finland, Australia, South Africa, and Japan were selected according to the qualitative balance value in the international advanced TEAMS test, human development index, life quality index(health, instruction, and welfare), education quality index, and other scientific-scholarly indexes; finally, by extracting the criteria for the SELECTION and appointment of principals through content analysis and comparison with Iran, the proposed framework for Iran has been presented.Findings: A total of 61 components for the SELECTION of secondary school principals were identified from among the studies conducted in the selected countries in this article. By extracting the commonalities and differences of each of the components among the countries, it was found that the highest index of manager SELECTION and appointment belongs to Japan and the lowest one is related to Finland.Conclusion: There are similarities between the components of SELECTION of principals of secondary schools in Iran and selected countries. In Iran, special attention should be paid to important components such as adherence to religious principles, appropriate personality traits, creativity and innovation, motivation to develop capabilities, professional growth, power of supervision and accountability, social image, leader skills, and purposefulness and foresight.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature SELECTION is a common approach to tackle this issue by choosing prominent features. Multi-label feature SELECTION is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

The aim of this study was a strain-improvement program for Trichoderma reesei PTCC 5142 by using a combination of UV light and NTG (N-methyl-N'-nitro-N-nitrosoguanidine) for enhanced cellulase production. Following mutagenesis after several rounds, mutant A6: 2 was selected from a total of 6500 colonies. Results obtained after 4 days were: Enzyme activity 1.26 U/ml and 0.82 U/ml for exoglucanase and endoglucanase, respectively. The comparative results showed increased production exoglucanase and endoglucanase by mutant A6: 2 than Trichoderma reesei PTCC 5142 to amount 130% for exoglucanase and 156% for endoglucanase.

Background: SUPERVISORs should have certain characteristics and adequate preparation for their roles. Yet, there are nowell‑educated experts knowing about the SUPERVISOR’s role and responsibilities and how to train them. So, this research wasconducted with the purpose of finding the factors affecting nursing SUPERVISOR training.Materials and Methods: This research is an inductive content analysis. Participants were 25 in number, consisting of nurses andSUPERVISORs in Shahid Sadoughi University hospitals. The participants were chosen by a purposive sampling method. Data collectionwas done by semi‑structured interviews and reviewing documents. Data were analyzed using conventional content analysis.Results: Findings included two main themes: Firstly, establishment of a SUPERVISORy infrastructure that includes “making theappointments and retention of SUPERVISORs, clarifying the duties and authority of SUPERVISOR, developing SUPERVISORy culture, specializing supervision, and conducting practice‑based training” and secondly, comprehensive SUPERVISORy competencies thatinclude “acquiring scientific, managing, communicative, professional, ethical, pedagogical, and supporting adequacy. ”Conclusions: Clinical SUPERVISOR has a major role in ensuring the quality of nursing care. This leads to improvements in patientcare and nurses’ personal and professional development. So, it is necessary that for effective supervision in nursing, first aninfrastructure is provided for supervision and then the comprehensive competency of a SUPERVISOR is enhanced to apply effective supervision.