Leishmania, Babesia and Ehrlichia in urban pet dogs: co-infection or cross-reaction in serological methods?

INTRODUCTION: The present study was designed to assess the occurrence of co-infection or cross-reaction in the serological techniques used for detecting the anti-Leishmania spp., -Babesia canis vogeli and -Ehrlichia canis antibodies in urban dogs from an area endemic to these parasites. METHODS: The serum samples from dogs were tested for the Babesia canis vogeli strain Belo Horizonte antigen and Ehrlichia canis strain São Paulo by immunofluorescence antibody test (IFAT) and by anti-Leishmania immunoglobulin G (IgG) antibody detection to assess Leishmania infection. We used the following four commercial kits for canine visceral leishmaniasis: ELISA, IFAT, Dual Path Platform (DPP) (Bio Manguinhos(r)/FIOCRUZ/MS) and a rK39 RDT (Kalazar Detect Canine Rapid Test; Inbios). RESULTS : Of 96 serum samples submitted to serological assays, 4 (4.2%) were positive for Leishmania as determined by ELISA; 12 (12.5%), by IFAT; 14 (14.6%) by rK39 RDT; and 20 (20.8%), by DPP. Antibodies against Ehrlichia and Babesia were detected in 23/96 (23.9%) and 30/96 (31.2%) samples, respectively. No significant association was identified between the results of tests for detecting Babesia or Ehrlichia and those for detecting Leishmania (p-value>0.05). CONCLUSIONS: In the present study, we demonstrated co-infection with Ehrlichia or Babesia and Leishmania in dogs from Minas Gerais (Brazil); we also found that the serological tests that were used did not cross-react.

Comparison of recombinant A2-ELISA with rKE16 dipstick and direct agglutination tests for diagnosis of visceral leishmaniasis in dogs in Northwestern Iran

INTRODUCTION: Various methods are used for the diagnosis of visceral leishmaniasis (VL), such as microscopic examination, culture and inoculation of laboratory animals; however, serological assays are commonly used for the detection of antibodies in serum samples with a wide range of specificity and sensitivity. METHODS: The purpose of this study was to compare three serological methods, including rA2-ELISA, the recombinant KE16 (rKE16) dipstick test and the direct agglutination test (DAT), for the detection of antibodies against VL antigens. The assays utilized 350 statistically based random serum samples from domestic dogs with clinical symptoms as well as samples from asymptomatic and healthy dogs from rural and urban areas of the Meshkinshahr district, northwestern Iran. RESULTS: Samples were assessed, and the following positive rates were obtained: 11.5% by rKE16, 26.9% by DAT and 49.8% by ELISA. The sensitivity among symptomatic dogs was 32.4% with rKE16, 100% with DAT and 52.9% with ELISA. Conversely, rA2-ELISA was less specific for asymptomatic dogs, at 46.5%, compared with DAT, at 88.9%. CONCLUSIONS : This study recommends rA2-ELISA as a parallel assay combined with DAT to detect VL infection among dogs. Further evaluations should be performed to develop an inexpensive and reliable serologic test for the detection of Leishmania infantum among infected dogs.

Electrohysterogram signal component cataloging with spectral and time-frequency methods

The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

Single-tube nested PCR assay with in-house DNA extraction for Mycobacterium tuberculosis detection in blood and urine

Abstract: INTRODUCTION : Molecular analyses are auxiliary tools for detecting Koch's bacilli in clinical specimens from patients with suspected tuberculosis (TB). However, there are still no efficient diagnostic tests that combine high sensitivity and specificity and yield rapid results in the detection of TB. This study evaluated single-tube nested polymerase chain reaction (STNPCR) as a molecular diagnostic test with low risk of cross contamination for detecting Mycobacterium tuberculosis in clinical samples. METHODS: Mycobacterium tuberculosis deoxyribonucleic acid (DNA) was detected in blood and urine samples by STNPCR followed by agarose gel electrophoresis. In this system, reaction tubes were not opened between the two stages of PCR (simple and nested). RESULTS: STNPCR demonstrated good accuracy in clinical samples with no cross contamination between microtubes. Sensitivity in blood and urine, analyzed in parallel, was 35%-62% for pulmonary and 41%-72% for extrapulmonary TB. The specificity of STNPCR was 100% in most analyses, depending on the type of clinical sample (blood or urine) and clinical form of disease (pulmonary or extrapulmonary). CONCLUSIONS: STNPCR was effective in detecting TB, especially the extrapulmonary form for which sensitivity was higher, and had the advantage of less invasive sample collection from patients for whom a spontaneous sputum sample was unavailable. With low risk of cross contamination, the STNPCR can be used as an adjunct to conventional methods for diagnosing TB.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Development of benchmarks for operating costs and resources consumption to be used in healthcare building sustainability assessment methods

Since the last decade of the twentieth century, the healthcare industry is paying attention to the environmental impact of their buildings and therefore new regulations, policy goals and Buildings Sustainability Assessment (HBSA) methods are being developed and implemented. At the present, healthcare is one of the most regulated industries and it is also one of the largest consumers of energy per net floor area. To assess the sustainability of healthcare buildings it is necessary to establish a set of benchmarks related with their life-cycle performance. They are both essential to rate the sustainability of a project and to support designers and other stakeholders in the process of designing and operating a sustainable building, by allowing the comparison to be made between a project and the conventional and best market practices. This research is focused on the methodology to set the benchmarks for resources consumption, waste production, operation costs and potential environmental impacts related to the operational phase of healthcare buildings. It aims at contributing to the reduction of the subjectivity found in the definition of the benchmarks used in Building Sustainability Assessment (BSA) methods, and it is applied in the Portuguese context. These benchmarks will be used in the development of a Portuguese HBSA method.

Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal

As a renewable energy source, the use of forest biomass for electricity generation is advantageous in comparison with fossil fuels, however the activity of forest biomass power plants causes adverse impacts, affecting particularly neighbouring communities. The main objective of this study is to estimate the effects of the activity of forest biomass power plants on the welfare of two groups of stakeholders, namely local residents and the general population and we apply two stated preference methods: contingent valuation and discrete choice experiments, respectively. The former method was applied to estimate the minimum compensation residents of neighbouring communities of two forest biomass power plants in Portugal would be willing to accept. The latter method was applied among the general population to estimate their willingness to pay to avoid specific environmental impacts. The results show that the presence of the selected facilities affects individuals’ well-being. On the other hand, in the discrete choice experiments conducted among the general population all impacts considered were significant determinants of respondents’ welfare levels. The results of this study stress the importance of performing an equity analysis of the welfare effects on different groups of stakeholders from the installation of forest biomass power plants, as their effects on welfare are location and impact specific. Policy makers should take into account the views of all stakeholders either directly or indirectly involved when deciding crucial issues regarding the sitting of new forest biomass power plants, in order to achieve an efficient and equitable outcome.

Decision methods applied to solve a safety problem on a waste treatment facility

To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

Qualitative risk assessment during polymer mortar test specimens preparation - methods comparison

Polymer binder modification with inorganic nanomaterials (NM) could be a potential and efficient solution to control matrix flammability of polymer concrete (PC) materials without sacrificing other important properties. Occupational exposures can occur all along the life cycle of a NM and “nanoproducts” from research through scale-up, product development, manufacturing, and end of life. The main objective of the present study is to analyse and compare different qualitative risk assessment methods during the production of polymer mortars (PM) with NM. The laboratory scale production process was divided in 3 main phases (pre-production, production and post-production), which allow testing the assessment methods in different situations. The risk assessment involved in the manufacturing process of PM was made by using the qualitative analyses based on: French Agency for Food, Environmental and Occupational Health & Safety method (ANSES); Control Banding Nanotool (CB Nanotool); Ecole Polytechnique Fédérale de Lausanne method (EPFL); Guidance working safely with nanomaterials and nanoproducts (GWSNN); Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro, Italy method (ISPESL); Precautionary Matrix for Synthetic Nanomaterials (PMSN); and Stoffenmanager Nano. It was verified that the different methods applied also produce different final results. In phases 1 and 3 the risk assessment tends to be classified as medium-high risk, while for phase 2 the more common result is medium level. It is necessary to improve the use of qualitative methods by defining narrow criteria for the methods selection for each assessed situation, bearing in mind that the uncertainties are also a relevant factor when dealing with the risk related to nanotechnologies field.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Comparison of different numerical methods for the solution of the time-fractional reaction-diffusion equation with variable diffusion coefficient

In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Improvement of in silico strain engineering methods in Saccharomyces cerevisiae

PhD thesis in Bioengineering