Gene duplication and hierarchical modularity in intracellular interaction networks

Networks of interactions evolve in many different domains. They tend to have topological characteristics in common, possibly due to common factors in the way the networks grow and develop. It has been recently suggested that one such common characteristic is the presence of a hierarchically modular organization. In this paper, we describe a new algorithm for the detection and quantification of hierarchical modularity, and demonstrate that the yeast protein-protein interaction network does have a hierarchically modular organization. We further show that such organization is evident in artificial networks produced by computational evolution using a gene duplication operator, but not in those developing via preferential attachment of new nodes to highly connected existing nodes. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Successful use of recombinant factor VII in massive hemoptysis due to community-acquired pneumonia

Recombinant activated factor VII (rFVIIa) is a powerful hemostatic agent developed for use in hemophilia. It has been used increasingly in life-threatening hemorrhage in a variety of other settings in which conventional medical or surgical therapy is unsuccessful. This report describes the successful use of rFVIIa for pulmonary hemorrhage due to a focal bleeding source in a regional hospital where bronchial artery embolization or surgery were not available. rFVIIa may be a useful temporizing measure in the unstable patient with pulmonary hemorrhage without coagulopathic bleeding when conventional treatment. is not immediately available.

The contribution of modularity to green operations practices

This paper discusses the possible contributions from modularity and industrial condominiums towards enhancing environmental performance in the automotive industry. The research described in this study is underpinned by a review of journal articles and books on the topics of: modularity of production systems; green operations practices, and the automotive industry and sustainability. The methodology is based on theoretical analysis of the contribution of the modular production system characteristics used in the automotive industry for Green Operations Practices (GOP). The following GOPs were considered: green buildings, eco-design, green supply chains, greener manufacturing, and reverse logistics. The results are theoretical in nature; however, due to the small number of studies that investigate the relationship between modularity and sustainability, this work is relevant to increase knowledge in academic circles and among practitioners in order to understand the possible environmental benefits from modular production systems. For instance, based upon our analysis, we could deduce that the existing modular production systems in the automotive industry may contribute in different ways to the implementation of GOPs. In all types of modularity, product simplification through the use of modules can enhance environmental performance and facilitate further activities such as maintenance and repair contributing to a longer life of cars on the road. Moreover, modules will make automobiles easier to disassembly, so increasing the chances of reuse of valuable components and a better final disposal of scrap. Regarding the potential benefits of each type of modularity, it is expected that modular consortia will have a better integration of environmental practices with suppliers and seize on high efficiency during manufacturing and logistics compared with conventional production systems.

Modularity and industrial complexes:perspectives for green operations in the automotive industry

This paper discusses the possible contributions from modularity and industrial condominiums towards enhancing environmental performance in the automotive industry. The research described in this study is underpinned by a review of journal articles and books on the topics of: modularity of production systems; green operations practices, and the automotive industry and sustainability. The methodology is based on theoretical analysis of the contribution of the modular production system characteristics used in the automotive industry for Green Operations Practices (GOP). The following GOPs were considered: green buildings, eco design, green supply chains, greener manufacturing, and reverse logistics. The results are theoretical in nature; however, due to the small number of studies that investigate the relationship between modularity and sustainability, this work is relevant to increase knowledge in academic circles and among practitioners in order to understand the possible environmental benefits from modular production systems.

A Circuit Implementing Massive Parallelism in Transition P Systems

ransition P-systems are based on biological membranes and try to emulate cell behavior and its evolution due to the presence of chemical elements. These systems perform computation through transition between two consecutive configurations, which consist in a m-tuple of multisets present at any moment in the existing m regions of the system. Transition between two configurations is performed by using evolution rules also present in each region. Among main Transition P-systems characteristics are massive parallelism and non determinism. This work is part of a very large project and tries to determine the design of a hardware circuit that can improve remarkably the process involved in the evolution of a membrane. Process in biological cells has two different levels of parallelism: the first one, obviously, is the evolution of each cell inside the whole set, and the second one is the application of the rules inside one membrane. This paper presents an evolution of the work done previously and includes an improvement that uses massive parallelism to do transition between two states. To achieve this, the initial set of rules is transformed into a new set that consists in all their possible combinations, and each of them is treated like a new rule (participant antecedents are added to generate a new multiset), converting an unique rule application in a way of parallelism in the means that several rules are applied at the same time. In this paper, we present a circuit that is able to process this kind of rules and to decode the result, taking advantage of all the potential that hardware has to implement P Systems versus previously proposed sequential solutions.

Adaptive agents in changing environments, the role of modularity

We explored the role of modularity as a means to improve evolvability in populations of adaptive agents. We performed two sets of artificial life experiments. In the first, the adaptive agents were neural networks controlling the behavior of simulated garbage collecting robots, where modularity referred to the networks architectural organization and evolvability to the capacity of the population to adapt to environmental changes measured by the agents performance. In the second, the agents were programs that control the changes in network's synaptic weights (learning algorithms), the modules were emerged clusters of symbols with a well defined function and evolvability was measured through the level of symbol diversity across programs. We found that the presence of modularity (either imposed by construction or as an emergent property in a favorable environment) is strongly correlated to the presence of very fit agents adapting effectively to environmental changes. In the case of learning algorithms we also observed that character diversity and modularity are also strongly correlated quantities. © 2014 Springer Science+Business Media New York.

Mineralogy, mineral chemistry, and genesis of precious metal-bearing volcanogenic massive sulfide deposits in the Newfoundland Appalachians, Canada: the Ming deposit as example

The Ming deposit, Newfoundland Appalachians, is a metamorphosed (upper greenschist to lower amphibolite facies), Cambro-Ordovician, bimodalmafic volcanogenic massive sulfide (VMS) deposit that consists of several, spatially-associated, elongated orebodies composed of stratabound semimassive to massive sulfides and/or discordant sulfide stringers in a rhyodacitic footwall. Copper is the main commodity; however, the deposit contains precious metal-bearing zones with elevated Au grades. In this study, field observations, microscopy, and micro-analytical tools including electron microprobe, laser ablation inductively coupled plasma mass spectrometry, and secondary ion mass spectrometry were used to constrain the relative timing of precious metal emplacement, the physico-chemical conditions of hydrothermal fluid precipitation, and the sources of sulfur, precious metals, semi-metals and metals. The ore mineral assemblage is complex and indicates an intermediate sulfidation state. Pyrite and chalcopyrite are the dominant ore minerals with minor sphalerite and pyrrhotite, and trace galena, arsenopyrite and cubanite. Additional trace phases include tellurides, NiSb phases, sulfosalts, electrum, AgHg±Au alloys, and oxides. Silver phases and precious metals occur predominantly in semi-massive and massive sulfides as free grains, and as grains spatially associated with arsenopyrite and/or sulfosalts. Precious metal phases occurring between recrystallized pyrite and within cataclastic pyrite are rare. Hence, the complex ore assemblage and textures strongly suggest syngenetic precious metal emplacement, whereas metamorphism and deformation only internally and locally remobilized precious metal phases. The ore assemblage formed from reduced, acidic hydrothermal fluids over a range of temperatures (≈350 to below 260ºC). The abundance of telluride and Ag-bearing tetrahedrite, however, varies strongly between the different orebodies indicating variable ƒTe₂, ƒSe₂, mBi, and mSb within the hydrothermal fluids. The variations in the concentrations of semi-metals and metals (As, Bi, Hg, Sb, Se, Te), as well as Au and Ag, were due to variations in temperature but also to a likely contribution of magmatic fluids into the VMS hydrothermal system from presumably different geothermal reservoirs. Sulfur isotope studies indicate at least two sulfur sources: sulfur from thermochemically-reduced seawater sulfate and igneous sulfur. The source of igneous sulfur is the igneous footwall, direct magmatic fluid/volatiles, or both. Upper greenschist to lower amphibolite metamorphic conditions and deformation had no significant effect on the sulfur isotope composition of the sulfides at the Ming deposit.

Guia didático-metodológico para aprendizagem e memorização dos conhecimentos disseminados nos moocs – Massive Open Online Courses

The present research has character exploratory, bibliographic and qualitative. It is based in consolidated scientific arguments in cognitive theories inspired in constructivist method and, under this perspective proposes to develop a didactic guide oriented to students of courses MOOCs - Massive Open Online Courses that will make it possible to maximize the utilization and the assimilation of the knowledge available in these courses. Intends also prepare these students in practice of a methodology of storage that enables the knowledge acquired are not lost nor be forgotten over the course of time. The theoretical framework, based on the theories of Meaningful Learning (Ausubel), the Genetic Epistemology (Piaget), Socioconstructivist (Vigotsky) and the Multimedia Learning (Mayer), subsidizes the understanding of important concepts such as meaningful learning, previous knowledge, and conceptual maps. Supported by fundamental contribution of the Theory of Categories, which are inter-related to concepts applicable to teaching methodology supported by use of structured knowledge maps in the establishment of the binomial teaching-learning; and with valuable study performed by teachers Luciano Lima (UFU) and Rubens Barbosa Filho (UEMS) that culminated with the development of Exponential Effective Memorization Method in Binary Base (Double MEB).

Satellites around massive galaxies since z∼ 2

The accretion of minor satellites has been postulated as the most likely mechanism to explain the significant size evolution of massive galaxies over cosmic time. Using a sample of 629 massive (M_star~ 10^11 M_⊙) galaxies from the near-infrared Palomar/DEEP-2 survey, we explore what fraction of these objects have satellites with 0.01 < M_sat/M_central < 1 (1:100) up to z= 1 and what fraction have satellites with 0.1 < M_sat/M_central < 1 (1:10) up to z= 2 within a projected radial distance of 100 kpc. We find that the fraction of massive galaxies with satellites, after background correction, remains basically constant and close to 30 per cent for satellites with a mass ratio down to 1:100 up to z= 1, and close to 15 per cent for satellites with a 1:10 mass ratio up to z= 2. The family of spheroid-like massive galaxies presents a 2–3 times larger fraction of objects with satellites than the group of disc-like massive galaxies. A crude estimation of the number of 1:3 mergers a massive spheroid-like galaxy has experienced since z~2 is around 2. For a disc-like galaxy this number decreases to ~1.

Measuring star formation in high-z massive galaxies: a mid-infrared to submillimetre study of the GOODS NICMOS Survey sample

We present measurements of the mean mid-infrared to submillimetre flux densities of massive (M_*≳ 10^11 M_⊙) galaxies at redshifts 1.7 < z < 2.9, obtained by stacking positions of known objects taken from the GOODS NICMOS Survey (GNS) catalogue on maps at 24 μm (Spitzer/MIPS); 70, 100 and 160 μm (Herschel/PACS); 250, 350 and 500 μm (BLAST); and 870 μm (LABOCA). A modified blackbody spectrum fit to the stacked flux densities indicates a median [interquartile] star formation rate (SFR) of SFR = 63[48, 81] M_⊙ yr^−1. We note that not properly accounting for correlations between bands when fitting stacked data can significantly bias the result. The galaxies are divided into two groups, disc-like and spheroid-like, according to their Sérsic indices, n. We find evidence that most of the star formation is occurring in n≤ 2 (disc-like) galaxies, with median [interquartile] SFR = 122[100, 150] M_⊙ yr^−1, while there are indications that the n > 2 (spheroid-like) population may be forming stars at a median [interquartile] SFR = 14[9, 20] M_⊙ yr^−1, if at all. Finally, we show that star formation is a plausible mechanism for size evolution in this population as a whole, but find only marginal evidence that it is what drives the expansion of the spheroid-like galaxies.

System to predict bipolar disorder crises analysing massive data

Durante el desarrollo del proyecto he aprendido sobre Big Data, Android y MongoDB mientras que ayudaba a desarrollar un sistema para la predicción de las crisis del trastorno bipolar mediante el análisis masivo de información de diversas fuentes. En concreto hice una parte teórica sobre bases de datos NoSQL, Streaming Spark y Redes Neuronales y después diseñé y configuré una base de datos MongoDB para el proyecto del trastorno bipolar. También aprendí sobre Android y diseñé y desarrollé una aplicación de móvil en Android para recoger datos para usarlos como entrada en el sistema de predicción de crisis. Una vez terminado el desarrollo de la aplicación también llevé a cabo una evaluación con usuarios.