Risky behavior regarding drug use and HIV infection: an Internet questionnaire coupled with short education texts for Portuguese speakers

Surveys of risky behavior relating to HIV/AIDS are generally made for groups at risk of infection, for which HIV/AIDS prevalence is usually expected to be higher than in the general population. Therefore, an educational homepage in Portuguese was created on the Internet to inform/ask internauts regarding knowledge and behavior. The internauts were classified as adolescents (13 to 25 years) and adults (>25 years). The number of STDs was reported as 1. 8 ± 2. 6 infections (range: 1 to 20 infections); 43% used condoms during sexual intercourse. Alcohol consumption was reported by 63% and illicit drug use by 32% (marijuana 24% and inhalants 15%). Among the adolescents, 31% did not classified alcohol as a drug. The adults more frequently reported homosexuality, anal intercourse and STDs, although the adolescents also presented high rates of risky behavior. These results show the need to reach out to internauts through better control strategies. Different types of strategies must be encouraged, in order to reach people that use this means of communication and entertainment.

Potential use of Piper nigrum ethanol extract against pyrethroid-resistant Aedes aegypti larvae

Fractionation of Piper nigrum ethanol extract, biomonitored by assays on pyrethroid-resistant Aedes aegypti larvae yielded isolation of the larvicidal amides piperolein-A and piperine. Comparing LC50 values, the ethanol extract (0. 98 ppm) was the most toxic, followed by piperolein-A (1. 46ppm) and piperine (1. 53ppm).

Differences in ERP use and value across Iberian Manufacturing and Services SMEs

Enterprise Resource Planning (ERP) system literature reports very little research on post-adoption stages, that is, actual usage and value. Even fewer studies focus on the specificities of an industry analysis. Based on the Technology-Organizational-Environment (TOE) framework and the Resource-Based View (RBV) theory, we develop a research model to measure and examine determinants of ERP use and value and their impact in the Iberian region (Portugal and Spain) across Manufacturing and Services industries in Small and Medium Enterprises (SMEs). The empirical test was conducted through structural equation modelling, using data from 261 firms in the peninsula in the Manufacturing and Service industries. Results show that amongst ERP use determinants, Training is the most important determinant for Service firms and Compatibility for Manufacturing firms. Firm size, Analytics, and Collaboration contribute to ERP Value in both industries, with Analytics being more important for the Service industry. The paper provides insight into which determinants contribute to ERP use and ERP value in Iberian Manufacturing and Services SMEs, offering managerial and academic implications.

Acquired non-Chagas megacolon associated with the use of psychiatric medication: case report and differential diagnosis with Chagas megacolon

A case of acquired megacolon in a 62-year-old man with acute abdomen due to sigmoid volvulus is reported. The case was associated with the use of psychiatric medications. The aim in this report was to emphasize the differential diagnosis with Chagas megacolon. Anatomopathological examination did not show any evidence of denervation, ganglionitis and/or myositis, and the serological test for Chagas disease was negative.

How do companies use social media?

NSBE-UNL

Evaluation of the use of real-time PCR for human T cell lymphotropic virus 1 and 2 as a confirmatory test in screening for blood donors

INTRODUCTION: HTLV-1/2 screening among blood donors commonly utilizes an enzyme-linked immunosorbent assay (EIA), followed by a confirmatory method such as Western blot (WB) if the EIA is positive. However, this algorithm yields a high rate of inconclusive results, and is expensive. METHODS: Two qualitative real-time PCR assays were developed to detect HTLV-1 and 2, and a total of 318 samples were tested (152 blood donors, 108 asymptomatic carriers, 26 HAM/TSP patients and 30 seronegative individuals). RESULTS: The sensitivity and specificity of PCR in comparison with WB results were 99.4% and 98.5%, respectively. PCR tests were more efficient for identifying the virus type, detecting HTLV-2 infection and defining inconclusive cases. CONCLUSIONS: Because real-time PCR is sensitive and practical and costs much less than WB, this technique can be used as a confirmatory test for HTLV in blood banks, as a replacement for WB.

Antimicrobial use and incidence of multidrug-resistant Pseudomonas aeruginosa in a teaching hospital: an ecological approach

INTRODUCTION: Multidrug-resistant Pseudomonas aeruginosa is a major threat in healthcare settings. The use of antimicrobials can influence the incidence of resistant strains by direct and indirect mechanisms. The latter can be addressed by ecological studies. METHODS: Our group attempted to analyze the relation between the use of antipseudomonal drugs and the incidence of MDR-PA among 18 units from a 400-bed teaching hospital. The study had a retrospective, ecological design, comprising data from 2004 and 2005. Data on the use of four antimicrobials (amikacin, ciprofloxacin, ceftazidime and imipenem) were tested for correlation with the incidence of MDR-PA (defined as isolates resistant to the four antimicrobials of interest) in clinical cultures. Univariate and multivariate linear regression analyses were performed. RESULTS: Significant correlations were determined between use and resistance for all antimicrobials in the univariate analysis: amikacin (standardized correlation coefficient = 0.73, p = 0.001); ciprofloxacin (0.71, p = 0.001); ceftazidime (0.61, p = 0.007) and imipenem (0.87, p < 0.001). In multivariate analysis, only imipenem (0.67, p = 0.01) was independently related to the incidence of multidrug-resistant strains. CONCLUSIONS: These findings share similarities with those reported in individual-based observational studies, with possible implications for infection control.

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Use of multi-sensory marketing techniques and its influence on brand experience in retail and HORECA sector

Double degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA- School of Business and Economics and Warsaw School of Economics

O uso da força no Direito Internacional = Use of force in Public International Law

Versão online da Revista Brasileira de Estudos Políticos, Belo Horizonte, nº 107, pp. 149-200, jul./dez.2013

Comparative evaluation of adverse effects in the use of powder trivalent antivenom and liquid antivenoms in Bothrops snake bites

INTRODUCTION: Snake bite, a problem in public health, generally occurs where there is no electric power. METHODS: A comparative clinical study was conducted with 102 victims of Bothrops snake bite, from the state of Amazonas, Brazil; 58 victims were treated with liofilizated trivalent antivenom serum (SATL) and 44 victims treated with liquid bivalent and monovalent antivenom serum (SAMBL). RESULTS: 17% (10/58) of patients presented adverse effects with the SATL and 25% (11/44) with the SAMBL. CONCLUSIONS: There was no statistic difference in number of adverse effects between the two types of snake bite antivenom.