Distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, density-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian Density Distance (GDD) approach was proposed to optimize local criteria in terms of distance and density properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the density and distance properties of remaining unclustered samples. Here, we introduce Adaptive GDD (AGDD), which eliminates the inappropriate effect of clustered samples by adaptively updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

Background & Aim: There are several methods for determination of occlusal vertical dimension. The vertical dimension of rest position, interocclusal distance and closest speaking space are two important methods. The purpose of this study was comparison the variability of interocclusal distance and closest speaking space in denture wearers.Method &Materials: The subjects were 34 edentulous patients (18 males & 16 females with mean age of 56) who had received complete dentures in the prosthodontics department of Isfahan dental school. They had good residual ridges. The dentures had correct clinical vertical dimension with 1-2mm overjet and 0.5 -1mm overbite. There was no evidence of neuromuscular and TMJ problems. The TOM guage was used for measuring the vertical dimension of rest position and «S» position.Results: The results showed that the mean and standard deviation of interocclusal distance were smaller than closest speaking space. Paired T-test and Levene's test were used for statistical analysis. There was a statistically difference between interocclusal distance and closest speaking space, so the interocclusal distance was less variable than closest speaking space (P<0.05).Conclusion: The closest speaking space during S position is affected by the occlusion, vertical and horizontal overlap of anterior teeth. These factors are up to dentist's judgement in complete denture and can influence the variability of vertical dimension of S position. Because of this variability it is recommended to use several methods for determining of vertical dimension.

Determination of plant resistance to drought and salinity is very important for selecting the favorable plant species in rangelands. The aim of this study was to compare the salinity and drought tolerance of the two rangeland species namely puccinelia distance and Aeluropus Littoralis. In this study biomass production of these two species was also compared. The Experimental design of split-split plot in randomized block was excuted for the study. The main plots were allocated to the treatments of 7 and 14 days irrigation periods. The subplot were 4 level of salinity including 100, 150, 200 mmolar Cl.Na and normal irrigation water as control respectively. The morphological criterias such as water potential, wilting percentage of the plants and also dry biomass were evaluated in this study. In the context of plant anatomy, The density of stomata per unit area of leaves, vesicular structure, mesophyt tissues and epidermis were also investigated. The results showed that wilting percentage increased with increasing salinity and water deficit (drought). With increasing the time of drought and salinity stress, the weight of dry stem and total dry mass were decreased. The wilting percentage and reduction of total dry biomass in Aeluropus Littoralis was more than puccinelia distance. It was concluded that puccinelia distance is more resistante compare to Aeluropus Littoralis while Aeluropus Littoralis is more tolerate to salinity stress.

The distance eigenvalues of a connected graph $G$ are the eigenvalues of its distance matrix $D(G)$ . A graph is called distance integral if all of its distance eigenvalues are integers. Let $n$ and $k$ be integers with $n>2k , k\geq1$ . The bipartite Kneser graph $H(n,k)$ is the graph with the set of all $k$ and $n-k$ subsets of the set $[n]=\{1,2,...,n\}$ as vertices , in which two vertices are adjacent if and only if one of them is a subset of the other . In this paper , we determine the distance spectrum of $H(n,1)$ . Although the obtained result is not new \cite{12} , but our proof is new . The main tool that we use in our work is the orbit partition method in algebraic graph theory for finding the eigenvalues of graphs . We introduce a new method for determining the distance spectrum of $H(n,1)$ and show how a quotient matrix can contain all distance eigenvalues of a graph.

Distance education is a set of teaching and / or learning strategies to meet the learning needs of students separate from the traditional classroom setting that teachers and learners are in the same location.In an era that the number of nurses, qualified nurse faculty and especially nurse researchers is well below national need (AACN), technological advances are increasing opportunities to improve the quality of and access to nursing education. Technology affords increased collaboration among nursing faculties in teaching and research.Technological strategies can change the way teaching and learning occurs, challenging the traditional relationship of student to academic institutions.Technological advances have resulted to reach far beyond their own geographic areas and decreased costs of education. Distance education fight "brain drain" from rural areas students who learn within their own communities are more likely to practice there. Nurses use distance education in promoting their skills and increase service quality provided for patients.The technologies of distance learning can be mixed and matched endlessly, but essentially, the learning breaks down into two basic styles: "synchronous" and "asynchronous". Each presents advantages and constraints: with synchronous technology, student can learn in real time, through video conferencing or online "live" chats, and is ideal for coursework where interactive group discussion enhances the material. Asynchronous technology, where students download prepared materials at their convenience, works best for coursework that is more fixed. Part of the success of any educational program is the support and direction of leadership. Distance education requires not only educational innovation but also an environment that rewards risk-taking. Creativity, flexibility and willingness to learn new teaching methods are necessary for faculty engaged in distance education. Since educational technologies are likely to change rapidly in the next decade, it is imperative to consider the benefits of distance education versus the high cost of this investment.