Discriminative Density-ratio Estimation

The covariate shift is a challenging problem in supervised learning that results from the discrepancy between the training and test distributions. An effective approach which recently drew a considerable attention in the research community is to reweight the training samples to minimize that discrepancy. In specific, many methods are based on developing Density-ratio (DR) estimation techniques that apply to both regression and classification problems. Although these methods work well for regression problems, their performance on classification problems is not satisfactory. This is due to a key observation that these methods focus on matching the sample marginal distributions without paying attention to preserving the separation between classes in the reweighted space. In this paper, we propose a novel method for Discriminative Density-ratio (DDR) estimation that addresses the aforementioned problem and aims at estimating the density-ratio of joint distributions in a class-wise manner. The proposed algorithm is an iterative procedure that alternates between estimating the class information for the test data and estimating new density ratio for each class. To incorporate the estimated class information of the test data, a soft matching technique is proposed. In addition, we employ an effective criterion which adopts mutual information as an indicator to stop the iterative procedure while resulting in a decision boundary that lies in a sparse region. Experiments on synthetic and benchmark datasets demonstrate the superiority of the proposed method in terms of both accuracy and robustness

Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce

The kernel $k$-means is an effective method for data clustering which extends the commonly-used $k$-means algorithm to work on a similarity matrix over complex data structures. The kernel $k$-means algorithm is however computationally very complex as it requires the complete data matrix to be calculated and stored. Further, the kernelized nature of the kernel $k$-means algorithm hinders the parallelization of its computations on modern infrastructures for distributed computing. In this paper, we are defining a family of kernel-based low-dimensional embeddings that allows for scaling kernel $k$-means on MapReduce via an efficient and unified parallelization strategy. Afterwards, we propose two methods for low-dimensional embedding that adhere to our definition of the embedding family. Exploiting the proposed parallelization strategy, we present two scalable MapReduce algorithms for kernel $k$-means. We demonstrate the effectiveness and efficiency of the proposed algorithms through an empirical evaluation on benchmark data sets.Comment: Appears in Proceedings of the SIAM International Conference on Data Mining (SDM), 201

Chiral nanoemitter array: A launchpad for optical vortices

A chiral arrangement of molecular nanoemitters is shown to support delocalised exciton states whose spontaneous decay can generate optical vortex radiation. In contrast to techniques in which phase modification is imposed upon conventional optical beams, this exciton method enables radiation with a helical wave-front to be produced directly. To achieve this end, a number of important polarisation and symmetry-based criteria need to be satisfied. It emerges that the phase structure of the optical field produced by degenerate excitons in a propeller-shaped array can exhibit precisely the sought character of an optical vortex – one with unit topological charge. Practical considerations for the further development of this technique are discussed, and potential new applications are identified

Building an Agile, Competitive and Dynamic Entrepreneurial Ecosystem to Create a Startup Culture, Startup Nation, and a Startup Region: Case of Egypt and the MENA Region

In today’s economic, business and social spaces, communities and societies around the world constantly face a set of challenges related to growing unemployment, economic development, changing market dynamics and tough business conditions amongst others. However, these societies and spaces are also regularly presented with a variety and spectrum of opportunities, given the continuous development of new markets, the growing role of cutting-edge technology platforms, especially with the growing penetration and impact of the fourth industrial revolution, the evolution of the digital economy and the global widespread of entrepreneurial initiatives and activities around the world in both the developed world and in emerging economies

On the integral solutions of the diophantine equation x4 + y4 = z3

This paper is concerned with the existence, types and the cardinality of the integral solutions for diophantine equation x4y4z3+ = where x , y and z are integers. The aim of this paper was to develop methods to be used in finding all solutions to this equation. Results of the study show the existence of infinitely many solutions to this type of diophantine equation in the ring of integers for both cases, x=y and x y. For the case when x=y, the form of solutions is given by (x,y,z)=(4n3,4n3,8n4), while for the case when x y, the form of solutions is given by (x,y,z)=(un3k-1,vn3k-1,n4k-1). The main result obtained is a formulation of a generalized method to find all the solutions for both types of diophantine equations

Transcriptional responses of Biomphalaria pfeifferi and Schistosoma mansoni following exposure to niclosamide, with evidence for a synergistic effect on snails following exposure to both stressors.

BackgroundSchistosomiasis is one of the world's most common NTDs. Successful control operations often target snail vectors with the molluscicide niclosamide. Little is known about how niclosamide affects snails, including for Biomphalaria pfeifferi, the most important vector for Schistosoma mansoni in Africa. We used Illumina technology to explore how field-derived B. pfeifferi, either uninfected or harboring cercariae-producing S. mansoni sporocysts, respond to a sublethal treatment of niclosamide. This study afforded the opportunity to determine if snails respond differently to biotic or abiotic stressors, and if they reserve unique responses for when presented with both stressors in combination. We also examined how sporocysts respond when their snail host is treated with niclosamide.Principal findingsCercariae-producing sporocysts within snails treated with niclosamide express ~68% of the genes in the S. mansoni genome, as compared to 66% expressed by intramolluscan stages of S. mansoni in snails not treated with niclosamide. Niclosamide does not disable sporocysts nor does it seem to provoke from them distinctive responses associated with detoxifying a xenobiotic. For uninfected B. pfeifferi, niclosamide treatment alone increases expression of several features not up-regulated in infected snails including particular cytochrome p450s and heat shock proteins, glutathione-S-transferases, antimicrobial factors like LBP/BPI and protease inhibitors, and also provokes strong down regulation of proteases. Exposure of infected snails to niclosamide resulted in numerous up-regulated responses associated with apoptosis along with down-regulated ribosomal and defense functions, indicative of a distinctive, compromised state not achieved with either stimulus alone.Conclusions/significanceThis study helps define the transcriptomic responses of an important and under-studied schistosome vector to S. mansoni sporocysts, to niclosamide, and to both in combination. It suggests the response of S. mansoni sporocysts to niclosamide is minimal and not reflective of a distinct repertoire of genes to handle xenobiotics while in the snail host. It also offers new insights for how niclosamide affects snails