TernausNetV2: Fully Convolutional Network for Instance Segmentation

The most common approaches to instance segmentation are complex and use two-stage networks with object proposals, conditional random-fields, template matching or recurrent neural networks. In this work we present TernausNetV2 - a simple fully convolutional network that allows extracting objects from a high-resolution satellite imagery on an instance level. The network has popular encoder-decoder type of architecture with skip connections but has a few essential modifications that allows using for semantic as well as for instance segmentation tasks. This approach is universal and allows to extend any network that has been successfully applied for semantic segmentation to perform instance segmentation task. In addition, we generalize network encoder that was pre-trained for RGB images to use additional input channels. It makes possible to use transfer learning from visual to a wider spectral range. For DeepGlobe-CVPR 2018 building detection sub-challenge, based on public leaderboard score, our approach shows superior performance in comparison to other methods. The source code corresponding pre-trained weights are publicly available at https://github.com/ternaus/TernausNetV

An overview of angiogenesis in bladder cancer

Purpose of the review: Angiogenesis plays a key role in bladder cancer (BC) pathogenesis. In the last two decades, increasing number of publications depicting a multitude of novel angiogenic molecules and pathways have emerged. The growing complexity necessitates evaluation of the breadth of current knowledge to highlight key findings and guide future research. Recent findings: Angiogenesis is a dynamic biologic process that is inherently difficult to assess. Clinical assessment of angiogenesis in BCs is advancing with the integration of image analysis systems and dynamic contrast-enhanced and magnetic resonance imaging (DCE-MRI). Tumour associated macrophages (TAMs) significantly influence the angiogenic process and further research is needed to assess their potential as therapeutic targets. A rapidly growing list of non-coding RNAs affect angiogenesis in BCs, partly through modulation of vascular endothelial growth factor (VEGF) activity. Vascular mimicry (VM) has been repeatedly associated with increased tumour aggressiveness in BCs. Standardised assays are needed for appropriate identification and quantification of VM channels. Summary: This article demonstrates the dynamic and complex nature of the angiogenic process and asserts the need for further studies to deepen our understanding

Characteristics Of The Marble Industry In Egypt: Structure, Conduct, And Performance

This paper analyzes marble extraction and production in Egypt from an applied industrial economics point of view. The marble industry in Egypt could be a promising sector if regulated properly. Market structure, conduct and performance is analyzed including degree of differentiation, nature of competition, barriers to entry, and needed regulations. Technically, production matches increasing returns of a Cobb Douglas form while cost structure follows declining average cost with entry . Factor inputs in production are non-complementary with $1000 of capital substitutable by 7.5 units of labor. Efficiency concerns necessitate deep technological segmentation with declining profitability. Critically needed regulations are related to technological use in extraction and labor allocation in production. For higher efficiency, the industry should become more capital intensive even though the Egyptian economy is undeniably labor abundant

Capacity management of migrant accommodation centers using approximate dynamic programming

Irregular migration has become a major macro-economic and political challenge. Due to rising political conflicts and income inequality across the world, the number of migrants is expected to increase exponentially over the coming decade. Thus, it is of critical importance to effectively use the limited resources allocated to humanitarian operations for irregular migration. In this paper we model the problem of capacity management and migrant transfers within a network of migrant accommodation centres with stochastic dynamic programming. Our study extends the literature on stochastic modelling and humanitarian operations by applying Approximate Dynamic Programming (ADP) into a new context. The model is translatable in other similar migratory routes and locations around the world where governments need to deal with uncertain numbers of irregular migrants. We test our approach on five Greek islands which have been the main migrant arrival points during the European Migrant Crisis. The results show that ADP provides a better computational performance than a simple myopic heuristic. The sensitivity analysis gives insights to the decision-makers about the impact of parameter values on the policies