In this case study, we describe a 25 year-old male who showed the symptoms of diabetes after a period of heavy drinking. (HbA1c=13%). Treatment was started with 120 units of insulin. After stopping alcohol consumption and taking an appropriate diet, insulin was tapered down. Five months after the start of treatment, insulin was stopped (HbA1c=5%). The results showed that he was in a good metabolic control after 18 months (HbA1c=5.9%).

Purpose: The purpose of this study was to systematically examine dimensions, aspects, and levels of search stopping in the literature in order to identify gaps in the field.Methods: Research reports on the subject published between 1961-2020 were identified in databases. The contents of 60 studies found were thematically analysed in terms of basic, organizing, and comprehensive concepts.Findings: The reviewed studies have identified two stopping levels, namely session-level stopping and Query-level/ result- summary- level stopping. At the latter level, the search session does not stop permanently, but the user continues searching after refining the query. The studies also referred to another stopping method labeled as “search- engine- result- page- level stopping” in which the user leaves the result page without clicking on any result after making a general inference of the search results. Then, the user may or may not continue searching after refining the query. Here, we are not dealing with another level of stopping, but only the time of making decision to stop is changed. Most of the 60 studies we identified dealt with session-level stopping. Identifying stopping rules, examining the application of stopping rules in various contexts, identifying the factors affecting search stopping or query stopping, checking search- engine- result- page- level stopping, examining the depth of users' search, distinguishing between stopping due to satisfaction or frustration, and exploring search stopping signs were dimensions of search stopping studied in the literature.  stopping rules included satisfaction and frustration, magnitude threshold, difference threshold, representational stability, mental list, and single criterion. Also, factors affecting stopping search included time constraints, search task structure, information scent, user interface features, importance of the task to the users, motivation, domain knowledge, interest in the topic, need for closure and need for cognition.Conclusion: Our review showed that studies each dealt with some specific aspect(s) of search stopping behavior and sought to identify the rules or factors affecting it. Research gaps we identified include not investigating the impact of variables such as search language, task difficulty, and individual differences on stopping behavior, the detailed differentiation of the signs of good abandonment from bad ones, and the use of eye tracking technology and recording electrical activity of the brain (Electroencephalography) to better understand the stopping behavior.

The aim of this study is to propose a modification of TWINSPAN algorithm with introducing new stopping rules for TWINSPAN. Modified TWINSPAN combines the analysis of heterogeneity of the clusters prior to each division to prevent the imposed divisions of homogeneous clusters and it also solved the limitation of classical TWINSPAN in which the number of clusters increases power of two. For this purpose, ecological groups of Box tree stands in Farim forests were classified with using classical and modified TWINSPAN basis of plant species cover percentage of 60 plots with 400 m2 surface area which were made by releve method (by consideration of indicator stand concept). In this relation, five different heterogeneity measures including Whittaker’s beta diversity and total inertia, Sorensen, Jaccard and Orlo'ci dissimilarity indices which representing diversity and distance indices respectively were involved. Sample plots were also classified from basis of topographical properties using cluster analysis with emphasizing Euclidean distance coefficient and Wards clustering method. Results showed that using of two sets of heterogeneity indices lead to different classification dendrograms. In this relation, results of Whittaker’s beta with total inertia as diversity indices were similar and the other three dissimilarity indices have shown similar behavior. Finally, our results reiterated that modified TWINSPAN did not alter the logic of the TWINSPAN classification, but it increased the flexibility of TWINSPAN dendrogram with changing the hierarchy of divisions in the final classification of ecological groups of Box tree stands in Farim forests.