Some properties of Eulerian lattices

summary:In this paper, we prove that Eulerian lattices satisfying some weaker conditions for lattices or some weaker conditions for 0-distributive lattices become Boolean

An Evaluation of Pareto, Lognormal and PPS Distributions: The Size Distribution of Cities in Kerala, India

The Pareto-Positive Stable (PPS) distribution is introduced as a new model for describing city size data of a region in a country. The PPS distribution provides a flexible model for fitting the entire range of a set of city size data and the classical Pareto and Zipf distributions are included as a particular case

On QBF Proofs and Preprocessing

QBFs (quantified boolean formulas), which are a superset of propositional formulas, provide a canonical representation for PSPACE problems. To overcome the inherent complexity of QBF, significant effort has been invested in developing QBF solvers as well as the underlying proof systems. At the same time, formula preprocessing is crucial for the application of QBF solvers. This paper focuses on a missing link in currently-available technology: How to obtain a certificate (e.g. proof) for a formula that had been preprocessed before it was given to a solver? The paper targets a suite of commonly-used preprocessing techniques and shows how to reconstruct certificates for them. On the negative side, the paper discusses certain limitations of the currently-used proof systems in the light of preprocessing. The presented techniques were implemented and evaluated in the state-of-the-art QBF preprocessor bloqqer.Comment: LPAR 201

Non-pharmacological, non-surgical interventions for urinary incontinence in older persons : A systematic review of systematic reviews. The SENATOR project ONTOP series

This work was supported by the European Union Seventh Framework program (FP7/2007–2013) under grant agreement n° 305930Peer reviewedPostprin

Tissue invasion and metastasis: molecular, biological and clinical perspectives

Cancer is a key health issue across the world, causing substantial patient morbidity and mortality. Patient prognosis is tightly linked with metastatic dissemination of the disease to distant sites, with metastatic diseases accounting for a vast percentage of cancer patient mortality. While advances in this area have been made, the process of cancer metastasis and the factors governing cancer spread and establishment at secondary locations is still poorly understood. The current article summarizes recent progress in this area of research, both in the understanding of the underlying biological processes and in the therapeutic strategies for the management of metastasis. This review lists the disruption of E-cadherin and tight junctions, key signaling pathways, including urokinase type plasminogen activator (uPA), phosphatidylinositol 3-kinase/v-akt murine thymoma viral oncogene (PI3K/AKT), focal adhesion kinase (FAK), β-catenin/zinc finger E-box binding homeobox 1 (ZEB-1) and transforming growth factor beta (TGF-β), together with inactivation of activator protein-1 (AP-1) and suppression of matrix metalloproteinase-9 (MMP-9) activity as key targets and the use of phytochemicals, or natural products, such as those from Agaricus blazei, Albatrellus confluens, Cordyceps militaris, Ganoderma lucidum, Poria cocos and Silybum marianum, together with diet derived fatty acids gamma linolenic acid (GLA) and eicosapentanoic acid (EPA) and inhibitory compounds as useful approaches to target tissue invasion and metastasis as well as other hallmark areas of cancer. Together, these strategies could represent new, inexpensive, low toxicity strategies to aid in the management of cancer metastasis as well as having holistic effects against other cancer hallmarks.W.G. Jiang ... S.K. Thompson ... et al

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Automated Analysis in Feature Modelling and Product Configuration

The automated analysis of feature models is one of the thriving topics of research in the software product line and variability management communities that has attracted more attention in the last years. A recent literature review reported that more than 30 analysis operations have been identi ed and di erent analysis mechanisms have been proposed. Product con guration is a well established research eld with more than 30 years of successful applications in di erent industrial domains. Our hypothesis, that is not really new, is that these two independent areas of research have interesting synergies that have not been fully explored. To try to explore the potential synergies systematically, in this paper we provide a rapid review to bring together these previously disparate streams of work. We de ne a set of research questions and give a preliminary answer to some of them. We conclude that there are many research opportunities in the synergy of these independent areas.Ministerio de Ciencia e Innovación TIN2009- 07366Junta de Andalucía TIC-590

Tissue invasion and metastasis: Molecular, biological and clinical perspectives

Cancer is a key health issue across the world, causing substantial patient morbidity and mortality. Patient prognosis is tightly linked with metastatic dissemination of the disease to distant sites, with metastatic diseases accounting for a vast percentage of cancer patient mortality. While advances in this area have been made, the process of cancer metastasis and the factors governing cancer spread and establishment at secondary locations is still poorly understood. The current article summarizes recent progress in this area of research, both in the understanding of the underlying biological processes and in the therapeutic strategies for the management of metastasis. This review lists the disruption of E-cadherin and tight junctions, key signaling pathways, including urokinase type plasminogen activator (uPA), phosphatidylinositol 3-kinase/v-akt murine thymoma viral oncogene (PI3K/AKT), focal adhesion kinase (FAK), β-catenin/zinc finger E-box binding homeobox 1 (ZEB-1) and transforming growth factor beta (TGF-β), together with inactivation of activator protein-1 (AP-1) and suppression of matrix metalloproteinase-9 (MMP-9) activity as key targets and the use of phytochemicals, or natural products, such as those from Agaricus blazei, Albatrellus confluens, Cordyceps militaris, Ganoderma lucidum, Poria cocos and Silybum marianum, together with diet derived fatty acids gamma linolenic acid (GLA) and eicosapentanoic acid (EPA) and inhibitory compounds as useful approaches to target tissue invasion and metastasis as well as other hallmark areas of cancer. Together, these strategies could represent new, inexpensive, low toxicity strategies to aid in the management of cancer metastasis as well as having holistic effects against other cancer hallmarks