Analysis causes of the incidence and compare social, economic, physical characteristics of informal settlements, case study: city of Marivan in Kurdistan province

Informal settlements are one of the problems of urban management in developing countries. Various theories about the causes and management of these settlements have been proposed. The most important of these theories, new socialist, liberal and dependency can be noted. The theory that argues for mandatory clearing informal settlement is not logical. Empowerment approach to be interested by countries and international organizations, and successful examples of this approach, with emphasis on the internal dynamics of these communities has been experienced. This paper tries to analyze the causes of marginalization and social, economic and spatial characteristics of informal settlement of Marivan city in Kurdistan province. Research areas consist of 4 region of Marivan informal settlement (Kosar,tape Mosk, sardoshiha, Tefine) sample size based on Cochran formula is 320 samples that Randomly and in four districts have been selected. Reasons for residents that they living in such places and social, economic characteristics of marginalized communities collected and entered into SPSS software and have been analyzed. The results show that more than 50 percent of residents in informal settlement areas of the city have come to this neighborhood. The main factor in the development of these four areas is not rural migrants. The highest levels of rural migrants from the neighborhood Tefin are that only 47% of residents are immigrants. The results suggest the great differences in social, economic and physical characteristics of slums. Among neighborhoods communities tapa Mosk and Tefini in the index close to each other and compare to two other neighborhoods are poor

The tyrosine phosphatase SHP2 controls TGFβ-induced STAT3 signaling to regulate fibroblast activation and fibrosis

Uncontrolled activation of TGFβ signaling is a common denominator of fibrotic tissue remodeling. Here we characterize the tyrosine phosphatase SHP2 as a molecular checkpoint for TGFβ-induced JAK2/STAT3 signaling and as a potential target for the treatment of fibrosis. TGFβ stimulates the phosphatase activity of SHP2, although this effect is in part counterbalanced by inhibitory effects on SHP2 expression. Stimulation with TGFβ promotes recruitment of SHP2 to JAK2 in fibroblasts with subsequent dephosphorylation of JAK2 at Y570 and activation of STAT3. The effects of SHP2 on STAT3 activation translate into major regulatory effects of SHP2 on fibroblast activation and tissue fibrosis. Genetic or pharmacologic inactivation of SHP2 promotes accumulation of JAK2 phosphorylated at Y570, reduces JAK2/STAT3 signaling, inhibits TGFβ-induced fibroblast activation and ameliorates dermal and pulmonary fibrosis. Given the availability of potent SHP2 inhibitors, SHP2 might thus be a potential target for the treatment of fibrosis

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

We consider the problem of finding a near-optimal policy in continuous space, discounted Markovian Decision Problems given the trajectory of some behaviour policy. We study the policy iteration algorithm where in successive iterations the action-value functions of the intermediate policies are obtained by picking a function from some fixed function set (chosen by the user) that minimizes an unbiased finite-sample approximation to a novel loss function that upper-bounds the unmodified Bellman-residual criterion. The main result is a finite-sample, high-probability bound on the performance of the resulting policy that depends on the mixing rate of the trajectory, the capacity of the function set as measured by a novel capacity concept that we call the VC-crossing dimension, the approximation power of the function set and the discounted-average concentrability of the future-state distribution. To the best of our knowledge this is the first theoretical reinforcement learning result for off-policy control learning over continuous state-spaces using a single trajectory

Toward understanding the post-collisional evolution of an orogen influenced by convergence at adjacent plate margins; Late Cretaceous-Tertiary thermotectonic history of the Apuseni Mountains

The relationship between syn- to post-collisional orogenic shortening and stresses transmitted from other neighboring plate boundaries is important for understanding the kinematics of mountain belts, but has received little attention so far. The Apuseni Mountains are an example of an orogen in the interference zone between two other subduction systems located in the external Carpathians and Dinarides. This interference is demonstrated by the results of a combined thermochronological and structural field study that quantifies the post-collisional latest Cretaceous-Tertiary evolution. The exhumation history derived from apatite fission track and (U-Th)/He thermochronology indicates that the present-day topography of the Apuseni Mountains originates mainly from latest Cretaceous times, modified by two tectonic pulses during the Paleogene. The latter are suggested by cooling ages clustering around ∼45 Ma and ∼30 Ma and the associated shortening recorded along deep-seated fault systems. Paleogene exhumation pulses are similar in magnitude (∼3.5 km) and are coeval with the final collisional phases recorded in the Dinarides and with part of the Carpathian rotation around the Moesian promontory. These newly quantified Paleogene exhumation and shortening pulses contradict the general view of tectonic quiescence, subsidence and overall sedimentation for this time interval. The Miocene collapse of the Pannonian Basin did not induce significant regional exhumation along the western Apuseni flank, nor did the subsequent Carpathian collision. This is surprising in the overall context of Pannonian Basin formation and its subsequent inversion, in which the Apuseni Mountains were previously interpreted as being significantly uplifted in both deformation stages. Copyright 2011 by the American Geophysical Union

Towards Comprehensive Foundations of Computational Intelligence

Abstract. Although computational intelligence (CI) covers a vast variety of different methods it still lacks an integrative theory. Several proposals for CI foundations are discussed: computing and cognition as compression, meta-learning as search in the space of data models, (dis)similarity based methods providing a framework for such meta-learning, and a more general approach based on chains of transformations. Many useful transformations that extract information from features are discussed. Heterogeneous adaptive systems are presented as particular example of transformation-based systems, and the goal of learning is redefined to facilitate creation of simpler data models. The need to understand data structures leads to techniques for logical and prototype-based rule extraction, and to generation of multiple alternative models, while the need to increase predictive power of adaptive models leads to committees of competent models. Learning from partial observations is a natural extension towards reasoning based on perceptions, and an approach to intuitive solving of such problems is presented. Throughout the paper neurocognitive inspirations are frequently used and are especially important in modeling of the higher cognitive functions. Promising directions such as liquid and laminar computing are identified and many open problems presented.

Simulation of hybrid forest tree breeding strategies

Computer simulation is the only realistic method of evaluating alternative methods of breeding hybrid forest trees. Empirical tests would be very long term and expensive. This paper describes the development of a simulation program, called XSIM, which generates two different but closely related outcrossing tree species. The genetic correlation between performance in each parental species and performance in the resulting hybrid can be set, in addition to the amounts and types of variances in each parental species. The breeding strategies available for testing include conventional reciprocal recurrent selection, reciprocal recurrent selection with forward selection, recurrent selection within each pure species, and the creation of a synthetic species. XSIM allows the strategies to be compared using the same base populations, equivalent selection intensities, and comparable mating patterns. Innovative best linear unbiased prediction procedures allow all ancestral and current progeny generation data, from both parental species and the hybrid, to be analysed together. The theoretical basis for the simulation is given, and genetic and statistical models are described. In summary, XSIM allows rigorous comparisons of the strategies in terms of genetic gain per time and provides useful insight into hybrid forest tree breeding