Subacute effects of the thiodicarb pesticide on target organs of male wistar rats: biochemical, histological, and flow cytometry studies

Thiodicarb, a carbamate pesticide widely used on crops, may pose several environmental and health concerns. This study aimed to explore its toxicological profile on male rats using hematological, biochemical, histopathological, and flow cytometry markers. Exposed animals were dosed daily at 10, 20, or 40 mg/kg/body weight (group A, B, and C, respectively) during 30 d. No significant changes were observed in hematological parameters among all groups. After 10 d, a decrease of total cholesterol levels was noted in rats exposed to 40 mg/kg. Aspartate aminotransferase (AST) activity increased (group A at 20 d; groups A and B at 30 d) and alkaline phosphatase (ALP) (group B at 30 d) activity significantly reduced. At 30 d a decrease of some of the other evaluated parameters was observed with total cholesterol and urea levels in group A as well as total protein and creatinine levels in groups A and B. Histological results demonstrated multi-organ dose-related damage in thiodicarb-exposed animals, evidenced as hemorrhagic and diffuse vacuolation in hepatic tissue; renal histology showed disorganized glomeruli and tubular cell degeneration; spleen was ruptured with white pulp and clusters of iron deposits within red pulp; significant cellular loss was noted at the cortex of thymus; and degenerative changes were observed within testis. The histopathologic alterations were most prominent in the high-dose group. Concerning flow cytometry studies, an increase of lymphocyte number, especially T lymphocytes, was seen in blood samples from animals exposed to the highest dose. Taken together, these results indicate marked systemic organ toxicity in rats after subacute exposure to thiodicarb.

Multidimensional scaling analysis of the dynamics of a country economy

This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process.

Multidimensional scaling for orthodontic root resorption

The paper investigates the risk factors for the severity of orthodontic root resorption. The multidimensional scaling (MDS) visualization method is used to investigate the experimental data from patients who received orthodontic treatment at the Department of Orthodontics and Dentofacial Orthopedics, Faculty of Dentistry, “Carol Davila” University of Medicine and Pharmacy, during a period of 4 years. The clusters emerging in the MDS plots reveal features and properties not easily captured by classical statistical tools. The results support the adoption of MDS for tackling the dentistry information and overcoming noise embedded into the data. The method introduced in this paper is rapid, efficient, and very useful for treating the risk factors for the severity of orthodontic root resorption.

Transport mechanism in ionic liquid membranes and the study of thiomersal biodegradation

The initial goal of this work was the development of a supported liquid membrane (SLM) bioreactor for the remediation of vaccine production effluents contaminated with a highly toxic organomercurial – thiomersal. Therefore, two main aspects were focused on: 1) the development of a stable supported liquid membrane – using room temperature ionic liquids (RTILs) – for the selective transport of thiomersal from the wastewater to a biological compartment, 2) study of the biodegradation kinetics of thiomersal to metallic mercury by a Pseudomonas putida strain. The first part of the work focused on the evaluation of the physicochemical properties of ionic liquids and on the SLMs’ operational stability. The results obtained showed that, although it is possible to obtain a SLM with a high stability, water possesses nonnegligible solubility in the RTILs studied. The formation of water clusters inside the hydrophobic ionic liquid was identified and found to regulate the transport of water and small ions. In practical terms, this meant that, although it was possible to transport thiomersal from the vaccine effluent to the biological compartment, complete isolation of the microbial culture could not be guaranteed and the membrane might ultimately be permeable to other species present in the aqueous vaccine wastewater. It was therefore decided not to operate the initially targeted integrated system but, instead, the biological system by itself. Additionally, attention was given to the development of a thorough understanding of the transport mechanisms involved in the solubilisation and transport of water through supported liquid membranes with RTILs as well as to the evaluation of the effect of water uptake by the SLM in the transport mechanisms of water-soluble solutes and its effect on SLM performance. The results obtained highlighted the determinant role played by water – solubilised inside the ionic liquids – on the transport mechanism. It became clear that the transport mechanism of water and water-soluble solutes through SLMs with [CnMIM][PF6] RTILs was regulated by the dynamics of water clusters inside the RTIL, rather than by molecular diffusion through the bulk of the ionic liquid. Although the stability tests vi performed showed that there were no significant losses of organic phase from the membrane pores, the formation of water clusters inside the ionic liquid, which constitute new, non-selective environments for solute transport, leads to a clear deterioration of SLM performance and selectivity. Nevertheless, electrical impedance spectroscopy characterisation of the SLMs showed that the formation of water clusters did not seem to have a detrimental effect on the SLMs’ electrical characteristics and highlighted the potential of using this type of membranes in electrochemical applications with low resistance requirements. The second part of the work studied the kinetics of thiomersal degradation by a pure culture of P. putida spi3 strain, in batch culture and using a synthe tic wastewater. A continuous ly stirred tank reactor fed with the synthetic wastewater was also operated and the bioreactor’s performance and robustness, when exposed to thiomersal shock loads, were evaluated. Finally, a bioreactor for the biological treatment of a real va ccine production effluent was set up and operated at different dilution rates. Thus it was possible to treat a real thiomersal-contaminated effluent, lowering the outlet mercury concentration to values below the European limit for mercury effluent discharges.

Preemption-light multiprocessor scheduling of sporadic tasks with high utilisation bound

Known algorithms capable of scheduling implicit-deadline sporadic tasks over identical processors at up to 100% utilisation invariably involve numerous preemptions and migrations. To the challenge of devising a scheduling scheme with as few preemptions and migrations as possible, for a given guaranteed utilisation bound, we respond with the algorithm NPS-F. It is configurable with a parameter, trading off guaranteed schedulable utilisation (up to 100%) vs preemptions. For any possible configuration, NPS-F introduces fewer preemptions than any other known algorithm matching its utilisation bound. A clustered variant of the algorithm, for systems made of multicore chips, eliminates (costly) off-chip task migrations, by dividing processors into disjoint clusters, formed by cores on the same chip (with the cluster size being a parameter). Clusters are independently scheduled (each, using non-clustered NPS-F). The utilisation bound is only moderately affected. We also formulate an important extension (applicable to both clustered and non-clustered NPS-F) which optimises the supply of processing time to executing tasks and makes it more granular. This reduces processing capacity requirements for schedulability without increasing preemptions.

Analysis of temperature time-series: embedding dynamics into the MDS method

Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.

Dynamical behaviour of multi-particle large-scale systems

Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.

Contratos de futuros sobre taxas de juro : estudo de caso sobre a Euribor a 3 meses

Mestrado em Contabilidade e Análise Financeira

Improving quality-of-service in wireless sensor networks by mitigating “Hidden-Node Collisions”

Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.

Optimal virtual cluster-based multiprocessor scheduling

Scheduling of constrained deadline sporadic task systems on multiprocessor platforms is an area which has received much attention in the recent past. It is widely believed that finding an optimal scheduler is hard, and therefore most studies have focused on developing algorithms with good processor utilization bounds. These algorithms can be broadly classified into two categories: partitioned scheduling in which tasks are statically assigned to individual processors, and global scheduling in which each task is allowed to execute on any processor in the platform. In this paper we consider a third, more general, approach called cluster-based scheduling. In this approach each task is statically assigned to a processor cluster, tasks in each cluster are globally scheduled among themselves, and clusters in turn are scheduled on the multiprocessor platform. We develop techniques to support such cluster-based scheduling algorithms, and also consider properties that minimize total processor utilization of individual clusters. In the last part of this paper, we develop new virtual cluster-based scheduling algorithms. For implicit deadline sporadic task systems, we develop an optimal scheduling algorithm that is neither Pfair nor ERfair. We also show that the processor utilization bound of us-edf{m/(2m−1)} can be improved by using virtual clustering. Since neither partitioned nor global strategies dominate over the other, cluster-based scheduling is a natural direction for research towards achieving improved processor utilization bounds.

Spectroscopic characterization of a novel 2 /[4Fe /4S] ferredoxin isolated from Desulfovibrio desulfuricans ATCC 27774

Inorganica Chimica Acta 356 (2003) 215-221

H-NAMe: specifying, implementing and testing a hidden-node avoidance mechanism for wireless sensor networks

The hidden-node problem has been shown to be a major source of Quality-of-Service (QoS) degradation in Wireless Sensor Networks (WSNs) due to factors such as the limited communication range of sensor nodes, link asymmetry and the characteristics of the physical environment. In wireless contention-based Medium Access Control protocols, if two nodes that are not visible to each other transmit to a third node that is visible to the formers, there will be a collision – usually called hidden-node or blind collision. This problem greatly affects network throughput, energy-efficiency and message transfer delays, which might be particularly dramatic in large-scale WSNs. This technical report tackles the hidden-node problem in WSNs and proposes HNAMe, a simple yet efficient distributed mechanism to overcome it. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes and then scales to multiple clusters via a cluster grouping strategy that guarantees no transmission interference between overlapping clusters. We also show that the H-NAMe mechanism can be easily applied to the IEEE 802.15.4/ZigBee protocols with only minor add-ons and ensuring backward compatibility with the standard specifications. We demonstrate the feasibility of H-NAMe via an experimental test-bed, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. We believe that the results in this technical report will be quite useful in efficiently enabling IEEE 802.15.4/ZigBee as a WSN protocol.

H-NAMe: a hidden-node avoidance mechanism for wireless sensor networks

The hidden-node problem has been shown to be a major source of Quality-of-Service (QoS) degradation in Wireless Sensor Networks (WSNs) due to factors such as the limited communication range of sensor nodes, link asymmetry and the characteristics of the physical environment. In wireless contention-based Medium Access Control protocols, if two nodes that are not visible to each other transmit to a third node that is visible to the formers, there will be a collision – usually called hidden-node or blind collision. This problem greatly affects network throughput, energy-efficiency and message transfer delays, which might be particularly dramatic in large-scale WSNs. This paper tackles the hiddennode problem in WSNs and proposes H-NAMe, a simple yet efficient distributed mechanism to overcome it. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes and then scales to multiple clusters via a cluster grouping strategy that guarantees no transmission interference between overlapping clusters. We also show that the H-NAMe mechanism can be easily applied to the IEEE 802.15.4/ZigBee protocols with only minor add-ons and ensuring backward compatibility with the standard specifications. We demonstrate the feasibility of H-NAMe via an experimental test-bed, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. We believe that the results in this paper will be quite useful in efficiently enabling IEEE 802.15.4/ZigBee as a WSN protocol

Spatial study of homicide rates in the state of Bahia, Brazil, 1996-2010

OBJECTIVE To analyze the spatial distribution of homicide mortality in the state of Bahia, Northeastern Brazil. METHODS Ecological study of the 15 to 39-year old male population in the state of Bahia in the period 1996-2010. Data from the Mortality Information System, relating to homicide (X85-Y09) and population estimates from the Brazilian Institute of Geography and Statistics were used. The existence of spatial correlation, the presence of clusters and critical areas of the event studied were analyzed using Moran’s I Global and Local indices. RESULTS A non-random spatial pattern was observed in the distribution of rates, as was the presence of three clusters, the first in the north health district, the second in the eastern region, and the third cluster included townships in the south and the far south of Bahia. CONCLUSIONS The homicide mortality in the three different critical areas requires further studies that consider the socioeconomic, cultural and environmental characteristics in order to guide specific preventive and interventionist practices.

ECG Analysis Using Consensus Clustering

Biosignals analysis has become widespread, upstaging their typical use in clinical settings. Electrocardiography (ECG) plays a central role in patient monitoring as a diagnosis tool in today's medicine and as an emerging biometric trait. In this paper we adopt a consensus clustering approach for the unsupervised analysis of an ECG-based biometric records. This type of analysis highlights natural groups within the population under investigation, which can be correlated with ground truth information in order to gain more insights about the data. Preliminary results are promising, for meaningful clusters are extracted from the population under analysis. © 2014 EURASIP.