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The distinction between ethnic tourism and cultural tourism, though blurry at first sight, can be clarified with the help of two key-elements: ethnic tourism tends to focus on a certain group of people for whom exoticism is, obviously, the main tourism attraction; ethnic tourism turns the natives rather into performers on a special “stage” for tourists than background performers facilitating “exotic experiences”. Instead of looking for historical monuments, for nature wonders, or for a local “cultural environment”, the ethnic tourist needs to see people whose way of life differs considerably from their own way of living. Thus, ethnic tourism depends, mainly, on the relationship between tourists and the natives, an encounter that is mediated by a third party that represents the tourism industry.

Farm tourism can be an alternative to agricultural jobs in rural communities with real agri-tourism potential. To improve destination management, we need to implement a type of management based on knowledge management. A second type of management that is a must in farm tourism is the integrated management of agri-tourism destination quality based on a code of good practices in the integrated management of quality. In order to improve agri-tourism management quality, we need to apply best management practices, i.e. 15 basic principles that contribute to the improvement of farm tourism management. These three types of management, if implemented on any agri-tourism farm, can contribute to the improvement of destination management.

Among the many activities man contributes to environmental damage are tourism activities, carried out irrationally and uncontrolled, in the land. Unlike other negative impacts on the environment of some activities such as agricultural ones – whose effects can be, hopefully, rather limited – tourism can contribute significantly not only to stop the degradation of the natural landscape, but also to protect and conserve the environment by adopting specific, efficient regulations.

Given an n-element point set in the plane, in how many ways can it be peeled off until no point remains? Only one extreme point can be removed at a time. The answer obviously depends on the point set. If the points are in convex position, there are exactly n! ways, which is the maximum number of ways for n points. But what is the minimum number?

We study the selection problem, namely that of computing the ith order statistic of n given elements. Here we offer a data structure called selectable sloppy heap that handles a dynamic version in which upon request (i) a new element is inserted or (ii) an element of a prescribed quantile group is deleted from the data structure. Each operation is executed in constant time—and is thus independent of n (the number of elements stored in the data structure)—provided that the number of quantile groups is fixed. This is the first result of this kind accommodating both insertion and deletion in constant time. As such, our data structure outperforms the soft heap data structure of Chazelle (which only offers constant amortized complexity for a fixed error rate 0 < ε ≤ 1 / 2 ) in applications such as dynamic percentile maintenance. The design demonstrates how slowing down a certain computation can speed up the data structure. The method described here is likely to have further impact in the field of data structure design in extending asymptotic amortized upper bounds to same formula asymptotic worst-case bounds.

Let S be a set of n points in Rd. A Steiner convex partition is a tiling of conv(S) with empty convex bodies. For every integer d, we show that S admits a Steiner convex partition with at most ⌈(n-1)/d⌉ tiles. This bound is the best possible for points in general position in the plane, and it is the best possible apart from constant factors in every fixed dimension d≥3. We also give the first constant-factor approximation algorithm for computing a minimum Steiner convex partition of a planar point set in general position.Establishing a tight lower bound for the maximum volume of a tile in a Steiner convex partition of any n points in the unit cube is equivalent to a famous problem of Danzer and Rogers. It is conjectured that the volume of the largest tile is ω(1/n). Here we give a (1-\epsilon)-approximation algorithm for computing the maximum volume of an empty convex body amidst n given points in the d-dimensional unit box [0,1]d.

Let A1,A2,…,An be the vertices of a polygon with unit perimeter, that is Σi |Ai Ai+1|=1. We derive various tight estimates on the minimum and maximum values of the sum of pairwise distances, and respectively sum of pairwise squared distances among its vertices. In most cases such estimates on these sums in the literature were known only for convex polygons.In the second part, we turn to a problem of Braß regarding the maximum perimeter of a simplen-gon (n odd) contained in a disk of unit radius. The problem was recently solved by Audet et al. 2009, who gave an exact formula. Here we present an alternative simpler proof of this formula. We then examine what happens if the simplicity condition is dropped, and obtain an exact formula for the maximum perimeter in this case as well.

According to a classical result of Szemerédi, every dense subset of 1,2,…,N contains an arbitrary long arithmetic progression, if N is large enough. Its analogue in higher dimensions due to Fürstenberg and Katznelson says that every dense subset of {1,2,…,N}d contains an arbitrary large grid, if N is large enough. Here we generalize these results for separated point sets on the line and respectively in the Euclidean space: (i) every dense separated set of points in some interval [0,L] on the line contains an arbitrary long approximate arithmetic progression, if L is large enough. (ii) every dense separated set of points in the d-dimensional cube [0,L]d in Rd contains an arbitrary large approximate grid, if L is large enough. A further generalization for any finite pattern in Rd is also established. The separation condition is shown to be necessary for such results to hold. In the end we show that every sufficiently large point set in Rd contains an arbitrarily large subset of almost collinear points. No separation condition is needed in this case.