Changes of a mutualistic network over time: reanalysis over a 10-year period

We analyzed the structure of a multispecific network or interacting ants and plants bearing extrafloral nectaries recorded in 1990 and again in 2000 in La Mancha, Veracruz, Mexico. We assessed the replicability of the number of interactions found among species and also whether there had been changes in the network structure associated with appearance of new ant and plant species during. that 10-year period. Our results show that the nested topology of the network was similar between sampling dates, group dissimilarity increased, mean number of interactions for ant species increased, the frequency distribution of standardized degrees reached higher values for plant species, more ant species and fewer plant species constituted the core of the more recent network, and the presence of new ant and plant species increased while their contribution to nestedness remained the same. Generalist species (i.e., those with the most links or interactions) appeared to maintain the stability of the network because the new species incorporated into the communities were linked to this core of generalists. Camponotus planatus was the most extreme generalist ant species (the one with the most links) in both networks, followed by four other ant species; but other species changed either their position along the continuum of generalists relative to specialists or their presence or absence within the network. Even though new species moved into the area during the decade between the surveys, the overall network structure remained unmodified.

Simulations under Ideal and Nonideal Conditions for Characterization of a Passive Doppler Geographical Location System Using Extension of Data Reception Network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of heterogeneous node network using microcontroller with protocols CAN and Zigbee

In this paper was proposed the development of an heterogeneous system using the microcontroller (AT90CANI28) where the protocol model CAN and the standard IEEE 802.15.4 are connected. This module is able to manage and monitor sensors and actuators using CAN and, through the wireless standard 802.15.4, communicate with the other network modules. © 2011 IEEE.

Report of the workshop in Caribbean small and medium-sized enterprises and trade liberalization: challenges of clusters and network initiatives

Includes bibliography

Severity of Brazilian sickle cell disease patients: severity scores and feasibility of the Bayesian network model use

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Frugivores at higher risk of extinction are the key elements of a mutualistic network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Homophobic discourse in blogs: Weaving of violence and network

This article aims at analyzing the effects of meaning installed in the discursive space of a blog, especially a formulation of discriminatory nature which was posted in November, 2011 and considerably discussed in other discursive spaces on the Internet. By means of French Discourse Analysis, we sought to track the memory networks and the ideological effects that are at play in the discourse on homosexuals posted by browsers-subjects and how they update the meanings already there in order to install effects of prejudice and hatred. Our interest is also to catch the meanings of violence inscribed in the electronic network and analyze the functioning of the language in motion in this space bordered by the imaginary in which it is possible to say anything. Hence, by means of the analyses performed in this study, we observed these effects of the subject's full freedom when he/she subscribes to the electronic network without fear of any punishment of any order. The discourses of intolerance and hatred posted on the blog by the subject give voice to a discursive confrontation observed by marks of agreement or indignation, supported by the discursive memory. Thus, we observed the interruption of regularities that break up with a supposed linearity in the discourse, putting the contradiction and the heterogeneous nature of the sayings on the net in motion.

Identification and characterization of the sRNA network in Neisseria meningitidis

Bacterial small regulatory RNAs (sRNAs) are posttranscriptional regulators involved in stress responses. These short non-coding transcripts are synthesised in response to a signal, and control gene expression of their regulons by modulating the translation or stability of the target mRNAs, often in concert with the RNA chaperone Hfq. Characterization of a Hfq knock out mutant in Neisseria meningitidis revealed that it has a pleiotropic phenotype, suggesting a major role for Hfq in adaptation to stresses and virulence and the presence of Hfq-dependent sRNA activity. Global gene expression analysis of regulated transcripts in the Hfq mutant revealed the presence of a regulated sRNA, incorrectly annotated as an open reading frame, which we renamed AniS. The synthesis of this novel sRNA is anaerobically induced through activation of its promoter by the FNR global regulator and through global gene expression analyses we identified at least two predicted mRNA targets of AniS. We also performed a detailed molecular analysis of the action of the sRNA NrrF,. We demonstrated that NrrF regulates succinate dehydrogenase by forming a duplex with a region of complementarity within the sdhDA region of the succinate dehydrogenase transcript, and Hfq enhances the binding of this sRNA to the identified target in the sdhCDAB mRNA; this is likely to result in rapid turnover of the transcript in vivo. In addition, in order to globally investigate other possible sRNAs of N. meningitdis we Deep-sequenced the transcriptome of this bacterium under both standard in vitro and iron-depleted conditions. This analysis revealed genes that were actively transcribed under the two conditions. We focused our attention on the transcribed non-coding regions of the genome and, along with 5’ and 3’ untranslated regions, 19 novel candidate sRNAs were identified. Further studies will be focused on the identification of the regulatory networks of these sRNAs, and their targets.

On the Design of a Boolean-network Robot Swarm: Collective Recognition of Ground Patterns.

Uno dei principali ambiti di ricerca dell’intelligenza artificiale concerne la realizzazione di agenti (in particolare, robot) in grado di aiutare o sostituire l’uomo nell’esecuzione di determinate attività. A tal fine, è possibile procedere seguendo due diversi metodi di progettazione: la progettazione manuale e la progettazione automatica. Quest’ultima può essere preferita alla prima nei contesti in cui occorra tenere in considerazione requisiti quali flessibilità e adattamento, spesso essenziali per lo svolgimento di compiti non banali in contesti reali. La progettazione automatica prende in considerazione un modello col quale rappresentare il comportamento dell’agente e una tecnica di ricerca (oppure di apprendimento) che iterativamente modifica il modello al fine di renderlo il più adatto possibile al compito in esame. In questo lavoro, il modello utilizzato per la rappresentazione del comportamento del robot è una rete booleana (Boolean network o Kauffman network). La scelta di tale modello deriva dal fatto che possiede una semplice struttura che rende agevolmente studiabili le dinamiche tuttavia complesse che si manifestano al suo interno. Inoltre, la letteratura recente mostra che i modelli a rete, quali ad esempio le reti neuronali artificiali, si sono dimostrati efficaci nella programmazione di robot. La metodologia per l’evoluzione di tale modello riguarda l’uso di tecniche di ricerca meta-euristiche in grado di trovare buone soluzioni in tempi contenuti, nonostante i grandi spazi di ricerca. Lavori precedenti hanno gia dimostrato l’applicabilità e investigato la metodologia su un singolo robot. Lo scopo di questo lavoro è quello di fornire prova di principio relativa a un insieme di robot, aprendo nuove strade per la progettazione in swarm robotics. In questo scenario, semplici agenti autonomi, interagendo fra loro, portano all’emergere di un comportamento coordinato adempiendo a task impossibili per la singola unità. Questo lavoro fornisce utili ed interessanti opportunità anche per lo studio delle interazioni fra reti booleane. Infatti, ogni robot è controllato da una rete booleana che determina l’output in funzione della propria configurazione interna ma anche dagli input ricevuti dai robot vicini. In questo lavoro definiamo un task in cui lo swarm deve discriminare due diversi pattern sul pavimento dell’arena utilizzando solo informazioni scambiate localmente. Dopo una prima serie di esperimenti preliminari che hanno permesso di identificare i parametri e il migliore algoritmo di ricerca, abbiamo semplificato l’istanza del problema per meglio investigare i criteri che possono influire sulle prestazioni. E’ stata così identificata una particolare combinazione di informazione che, scambiata localmente fra robot, porta al miglioramento delle prestazioni. L’ipotesi è stata confermata applicando successivamente questo risultato ad un’istanza più difficile del problema. Il lavoro si conclude suggerendo nuovi strumenti per lo studio dei fenomeni emergenti in contesti in cui le reti booleane interagiscono fra loro.

Numerical coupling of thermal-electric network models and energy-transport equations including optoelectronic semiconductor devices

In this work the numerical coupling of thermal and electric network models with model equations for optoelectronic semiconductor devices is presented. Modified nodal analysis (MNA) is applied to model electric networks. Thermal effects are modeled by an accompanying thermal network. Semiconductor devices are modeled by the energy-transport model, that allows for thermal effects. The energy-transport model is expandend to a model for optoelectronic semiconductor devices. The temperature of the crystal lattice of the semiconductor devices is modeled by the heat flow eqaution. The corresponding heat source term is derived under thermodynamical and phenomenological considerations of energy fluxes. The energy-transport model is coupled directly into the network equations and the heat flow equation for the lattice temperature is coupled directly into the accompanying thermal network. The coupled thermal-electric network-device model results in a system of partial differential-algebraic equations (PDAE). Numerical examples are presented for the coupling of network- and one-dimensional semiconductor equations. Hybridized mixed finite elements are applied for the space discretization of the semiconductor equations. Backward difference formluas are applied for time discretization. Thus, positivity of charge carrier densities and continuity of the current density is guaranteed even for the coupled model.

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.