On the impact of overlapping access points in detecting node encounters

Data traces, consisting of logs about the use of mobile and wireless networks, have been used to study the statistics of encounters between mobile nodes, in an attempt to predict the performance of opportunistic networks. Understanding the role and potential of mobile devices as relaying nodes in message dissemination and delivery depends on the knowledge about patterns and number of encounters among nodes. Data traces about the use of WiFi networks are widely available and can be used to extract large datasets of encounters between nodes. However, these logs only capture indirect encounters between nodes, and the resulting encounters datasets might not realistically represent the spatial and temporal behaviour of nodes. This paper addresses the impact of overlapping between the coverage areas of different Access Points of WiFi networks in extracting encounters datasets from the usage logs. Simulation and real-world experimental results show that indirect encounter traces extracted directly from these logs strongly underestimate the opportunities for direct node-to- node message exchange in opportunistic networks.

Detection of dangerous situations using a smart internet of things system

The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

Structure and composition of the ground-herb community in a terra-firme Central Amazonian forest

The herb community of tropical forests is very little known, with few studies addressing its structure quantitatively. Even with this scarce body of information, it is clear that the ground herbs are a rich group, comprising 14 to 40% of the species found in total species counts in tropical forests. The present study had the objective of increasing the knowledge about the structure and composition of the ground-herb community and to compare the sites for which there are similar studies. The study was conducted in a tropical non-inundated and evergreen forest 90 km north of Manaus, AM. Ground herbs were surveyed in 22 transects of 40 m², distributed in five plots of 4 ha. The inventoried community was composed of 35 species, distributed in 24 genera and 18 families. Angiosperms were represented by 8 families and Pteridophytes by 10 families. Marantaceae (12 sp) and Cyperaceae (4 sp) were the richest families. Marantaceae and Poaceae were the families with greatest abundance and cover. Marantaceae, Poaceae, Heliconiaceae and Pteridophytes summed 96% of total herb cover, and therefore were responsible for almost all the cover of the community. The 10 most important species had 83.7% of the individuals. In general, the most abundant species were also the most frequent. Richness per transect varied from 7 to 19 species, and abundance varied from 30 to 114 individuals. The community structure was quite similar to 3 other sites in South America and one site in Asia.

Seasonality, parity rates and transmission indices of Mansonella ozzardi (Manson) (Nematoda: Onchocercidae) by Cerqueirellum argentiscutum (Shelley & Luna Dias) (Diptera: Simulidae) in a lower Solimões River community, Amazonas, Brazil

Mansonella ozzardi is transmitted by two dipterian families, Ceratopogonidae (midges) and Simuliidae (black flies). In Brazil, black flies are vectors for this filariasis until now. In this paper, we determined the seasonality, parity capacity and parasitic infection rate of Cerqueirellum argentiscutum. The work was carried out in the Porto Japão community, Lower Solimões River, Amazonas, Brazil. Results show that the black flies were more abundant during the rainy season (from December to May). The number of parous flies was higher in every sampling during the course of year. Monthly Biting Rate (MBR1 123742.00, MBR2 86701.50) was high, although Parasitic Infection Rate (PIR1 0.06, PIR2 0.08) and Annual Transmission Potential (ATP 7.25) were low in numbers.

Planeamento fiscal e reestruturação empresarial: análise dos ordenamentos jurídicos português e brasileiro

Dissertação de mestrado em Direito Tributário e Fiscal

Gd2O3: Eu Nanoparticle-Based Poly(vinylidene fluoride) Composites for Indirect X-ray Detection

Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

On line pre-concentration for simultaneous determination of low molecular weight organic acids and inorganic anions in Amazonian river water samples employing ion chromatography with conductivity detection

An ion chromatography procedure, employing an IonPac AC15 concentrator column was used to investigate on line preconcentration for the simultaneous determination of inorganic anions and organic acids in river water. Twelve organic acids and nine inorganic anions were separated without any interference from other compounds and carry-over problems between samples. The injection loop was replaced by a Dionex AC15 concentrator column. The proposed procedure employed an auto-sampler that injected 1.5 ml of sample into a KOH mobile phase, generated by an Eluent Generator, at 1.5 mL min-1, which carried the sample to the chromatographic columns (one guard column, model AG-15, and one analytical column, model AS15, with 250 x 4mm i.d.). The gradient elution concentrations consisted of a 10.0 mmol l-1 KOH solution from 0 to 6.5 min, gradually increased to 45.0 mmol l-1 KOH at 21 min., and immediatelly returned and maintained at the initial concentrations until 24 min. of total run. The compounds were eluted and transported to an electro-conductivity detection cell that was attached to an electrochemical detector. The advantage of using concentrator column was the capability of performing routine simultaneous determinations for ions from 0.01 to 1.0 mg l-1 organic acids (acetate, propionic acid, formic acid, butyric acid, glycolic acid, pyruvate, tartaric acid, phthalic acid, methanesulfonic acid, valeric acid, maleic acid, oxalic acid, chlorate and citric acid) and 0.01 to 5.0 mg l-1 inorganic anions (fluoride, chloride, nitrite, nitrate, bromide, sulfate and phosphate), without extensive sample pretreatment and with an analysis time of only 24 minutes.

Concurrency detection on finish-to-start activity precedence networks

We explore the finish-to-start precedence relations of project activities used in scheduling problems. From these relations, we devise a method to identify groups of activities that could execute concurrently, i.e. activities in the same group can all execute in parallel. The method derives a new set of relations to describe the concurrency. Then, it is represented by an undirected graph and the maximal cliques problem identifies the groups. We provide a running example with a project from our previous studies in resource constrained project cost minimization together with an example application on the concurrency detection method: the evaluation of the resource stress.

Structural and successional variability of periphytic algal community in a Amazonian lake during the dry and rainy season (Rio Branco, Acre)

The colonization process and successional patterns of a periphytic algal community were evaluated in a Amazonian Viveiro Lake (Rio Branco, Acre, Brazil). Sampling was performed over a period of 35 days; at four-day intervals for 20 days, and then at five-day intervals. Water sampling for physical, chemical and biological analyses was done during the dry and rainy season. Glass slides were used as artificial substrates for periphyton colonization. The structural community was evaluated through population density, algae class, diversity indices and descriptive species. Species richness, diversity and evenness increased as succession progressed. While density of Bacillariophyceae, Euglenophyceae and Zygnemaphyceae increased with succession, Cyanobacteria remained dominant. Synechocystis aquatilis, Synechocystis diplococcus and Navicula pseudolanceolata were the main descriptive species in both the dry and rainy season. Cymbela tumida, Frustulia rhomboides, Trachelomonas lacustris and Closterium acicularis was correlated with an increase in hydrologic level during the rainy season. Conversely, the density of Chlamydomonas sp., Chroomonas nordstedtii, Trachelomonas volvocinopsis, Trachelomonas volvocina and Synechococcus linearis was correlated with an increase in water transparency during the dry season. In general, the periphytic algal community showed high diversity and species richness independent of season. Season also had little influence on representation of algae class and main descriptive species. However, successional patterns varied by season, and changes in hydrologic levels acted directly on the succession path of periphytic algae. More research on periphyton dynamics is needed to improve our understanding of tropical lake ecosystems, especially in Amazonian.

Widespread environmental contamination with Mycobacterium tuberculosis complex revealed by a molecular detection protocol

Environmental contamination with Mycobacterium tuberculosis complex (MTC) has been considered crucial for bovine tuberculosis persistence in multi-host-pathogen systems. However, MTC contamination has been difficult to detect due to methodological issues. In an attempt to overcome this limitation we developed an improved protocol for the detection of MTC DNA. MTC DNA concentration was estimated by the Most Probable Number (MPN) method. Making use of this protocol we showed that MTC contamination is widespread in different types of environmental samples from the Iberian Peninsula, which supports indirect transmission as a contributing mechanism for the maintenance of bovine tuberculosis in this multi-host-pathogen system. The proportion of MTC DNA positive samples was higher in the bovine tuberculosis-infected than in presumed negative area (0.32 and 0.18, respectively). Detection varied with the type of environmental sample and was more frequent in sediment from dams and less frequent in water also from dams (0.22 and 0.05, respectively). The proportion of MTC-positive samples was significantly higher in spring (p<0.001), but MTC DNA concentration per sample was higher in autumn and lower in summer. The average MTC DNA concentration in positive samples was 0.82 MPN/g (CI95 0.70-0.98 MPN/g). We were further able to amplify a DNA sequence specific of Mycobacterium bovis/caprae in 4 environmental samples from the bTB-infected area.

Getting Listeners Involved: Rádio Ás, a Community Web Project

[Excerpt] The idea of community is usually associated with radio today in the context of what Bart Cammaerts (2009,635) classifies as a "third type of broadcast, namely participatory radio, complementary to both commercial and public media". Following Ellie Rennie (2006, 3), community radio corresponds, as all other forms of community media, to non-profit media that provide "community members with an opportunity to participate in the production process". For the International Association for Media and Communication Research, which supports a research group on Community Communication, this area includes media that originate from, circulate and resonate with the sphere of civil society.

Palm community transitions along a topographic gradient from floodplain to terra firme in the eastern Amazon

Palms show clear niche segregation patterns along topographic gradients in tropical forests, with some species associated to terra firme and others to seasonally flooded areas. The aim of this study was to quantitatively describe the fine-scale spatial variation within a palm community, tracking the changes in species' abundance along environmental gradients associated with a perennial stream the eastern Amazon. The study of palm communities was based on 60 forest plots in which all adult palms were counted. We found a total of 566 palms in a community containing 11 species. Furthermore, we found a significant separation in the palm community between seasonally-flooded and terra firme forests. We found a gradient with various densities of the three most abundant palm species within the first 100 m away from the flooded area. Other species were located exclusively in the terra firme forest. The abundance of the six most common species were distributed in relation to humidity gradients from floodplains to terra firme, with palm distribution from the most flood-tolerant to the least flood-tolerant palm species as follows: Euterpe oleracea, Attalea phalerata and Socratea exorrhiza (species with floodplain affinity), Astrocaryum gynacanthum, Astrocaryum aculeatum, Attalea maripa (species with terra firme affinity)