To Be Connected, or Not to Be Connected: That is the Minimum Inefficiency Subgraph Problem

We study the problem of extracting a selective connector for a given set of query vertices $Q \subseteq V$ in a graph $G = (V,E)$. A selective connector is a subgraph of $G$ which exhibits some cohesiveness property, and contains the query vertices but does not necessarily connect them all. Relaxing the connectedness requirement allows the connector to detect multiple communities and to be tolerant to outliers. We achieve this by introducing the new measure of network inefficiency and by instantiating our search for a selective connector as the problem of finding the minimum inefficiency subgraph. We show that the minimum inefficiency subgraph problem is NP-hard, and devise efficient algorithms to approximate it. By means of several case studies in a variety of application domains (such as human brain, cancer, and food networks), we show that our minimum inefficiency subgraph produces high-quality solutions, exhibiting all the desired behaviors of a selective connector.Comment: In Proceedings of the 26th ACM conference on Information and Knowledge Management (CIKM 2017

Learning Parities in the Mistake-Bound model

We study the problem of learning parity functions that depend on at most $k$ variables ($k$-parities) attribute-efficiently in the mistake-bound model. We design a simple, deterministic, polynomial-time algorithm for learning $k$-parities with mistake bound $O(n^{1-frac{c}{k}})$, for any constant $c > 0$. This is the first polynomial-time algorithms that learns $omega(1)$-parities in the mistake-bound model with mistake bound $o(n)$. Using the standard conversion techniques from the mistake-bound model to the PAC model, our algorithm can also be used for learning $k$-parities in the PAC model. In particular, this implies a slight improvement on the results of Klivans and Servedio cite{rocco} for learning $k$-parities in the PAC model. We also show that the $widetilde{O}(n^{k/2})$ time algorithm from cite{rocco} that PAC-learns $k$-parities with optimal sample complexity can be extended to the mistake-bound model

Validation of Matching

We introduce a technique to compute probably approximately correct (PAC) bounds on precision and recall for matching algorithms. The bounds require some verified matches, but those matches may be used to develop the algorithms. The bounds can be applied to network reconciliation or entity resolution algorithms, which identify nodes in different networks or values in a data set that correspond to the same entity. For network reconciliation, the bounds do not require knowledge of the network generation process

Efficacy of a dilemma-focused intervention for unipolar depression : study protocol for a multicenter randomized controlled trial

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedDepression is one of the more severe and serious health problems because of its morbidity, disabling effects and for its societal and economic burden. Despite the variety of existing pharmacological and psychological treatments, most of the cases evolve with only partial remission, relapse and recurrence. Cognitive models have contributed significantly to the understanding of unipolar depression and its psychological treatment. However, success is only partial and many authors affirm the need to improve those models and also the treatment programs derived from them. One of the issues that requires further elaboration is the difficulty these patients experience in responding to treatment and in maintaining therapeutic gains across time without relapse or recurrence. Our research group has been working on the notion of cognitive conflict viewed as personal dilemmas according to personal construct theory. We use a novel method for identifying those conflicts using the repertory grid technique (RGT). Preliminary results with depressive patients show that about 90% of them have one or more of those conflicts. This fact might explain the blockage and the difficult progress of these patients, especially the more severe and/or chronic. These results justify the need for specific interventions focused on the resolution of these internal conflicts. This study aims to empirically test the hypothesis that an intervention focused on the dilemma(s) specifically detected for each patient will enhance the efficacy of cognitive behavioral therapy (CBT) for depressionPeer reviewe

Haemoparasites in endemic and non-endemic passerine birds from central Mexico highlands

Haemosporidian parasites of birds are found worldwide and include the genera Haemoproteus, Plasmodium and Leucocytozoon. Infection with haemosporidian parasites can affect host physical condition and reproductive success. The aim of this study was to identify the blood parasites and parasitaemia in endemic and non-endemic passerine birds from central Mexico highlands. This study included 157 passerines representing 29 species from 17 families. Overall, 30.6% (48/157) of the birds were infected with blood parasites. Of those, Haemoproteus spp. were found in 14.0% (n = 22), Leucocytozoon spp. 12.1% (n = 19) and microfilariae 0.6% (n = 1). Blood parasites were found in 71.4% (5/7) of endemic bird species and 45.4% (10/22) of non-endemic species. Medium to high parasitaemia (number of parasites/number erythrocytes) was observed in birds with infections of Haemoproteus spp. and Leucocytozoon spp. Co-infections 3.8% (n = 6) were observed in two species of endemic birds. This study contributes to the knowledge of haemoparasites in endemic and non-endemic passerine birds from central Mexico highlands. Additional investigation on the molecular identification of haemosporidian parasites, pathogenicity and health status of these birds is necessary

Neuregulin 4 downregulation alters mitochondrial morphology and induces oxidative stress in 3T3-L1 adipocytes

Neuregulin 4 (Nrg4) is an adipokine that belongs to the epidermal growth factor family andbinds to ErbB4 tyrosine kinase receptors. In 3T3-L1 adipocytes, the downregulation of Nrg4 expressionenhances inflammation and autophagy, resulting in insulin resistance. Here, we searched for thecauses of this phenotype. Nrg4 knockdown (Nrg4 KD) adipocytes showed a significant reduction inmitochondrial content and elongation, along with a lower content of the mitochondria fusion proteinmitofusin 2 (MFN2), and increased H2O2 production compared to the control scrambled cells (Scr).The antioxidant N-acetylcysteine reversed the oxidative stress and reduced the gene expression of thepro-inflammatory cytokine tumor necrosis factor α (TNFα). Nrg4 KD adipocytes showed enhancedlipolysis and reduced lipogenesis, in addition to a significant reduction in several intermediatesof the Krebs cycle. In summary, Nrg4 downregulation in adipocytes affects mitochondrial contentand functioning, causing impaired cellular metabolism, which in turn results in oxidative stress,inflammation, and insulin resistance