Evaluation of a real time DGPS data server

The goal of the this paper is to show that the DGPS data Internet service we designed and developed provides campus-wide real time access to Differential GPS (DGPS) data and, thus, supports precise outdoor navigation. First we describe the developed distributed system in terms of architecture (a three tier client/server application), services provided (real time DGPS data transportation from remote DGPS sources and campus wide data dissemination) and transmission modes implemented (raw and frame mode over TCP and UDP). Then we present and discuss the results obtained and, finally, we draw some conclusions.

Is adolescent pregnancy a risk factor for low birth weight?

OBJECTIVE: The objective of this study was to evaluate whether adolescent pregnancy is a risk factor for low birth weight (LBW) babies. METHODS: This was a cross-sectional study of mothers and their newborns from a birth cohort in Aracaju, Northeastern Brazil. Data were collected consecutively from March to July 2005. Information collected included socioeconomic, biological and reproductive aspects of the mothers, using a standardized questionnaire. The impact of early pregnancy on birth weight was evaluated by multiple logistic regression. RESULTS: We studied 4,746 pairs of mothers and their babies. Of these, 20.6% were adolescents (< 20 years of age). Adolescent mothers had worse socioeconomic and reproductive conditions and perinatal outcomes when compared to other age groups. Having no prenatal care and smoking during pregnancy were the risk factors associated with low birth weight. Adolescent pregnancy, when linked to marital status "without partner", was associated with an increased proportion of low birth weight babies. CONCLUSIONS: Adolescence was a risk factor for LBW only for mothers without partners. Smoking during pregnancy and lack of prenatal care were considered to be independent risk factors for LBW.

Risk factors of HIV-related oral lesions in adults

OBJECTIVE: To assess the risk factors in the occurrence of oral lesions in HIV-positive adults. METHODS: A retrospective analytical-descriptive survey was conducted using the medical/dental records of 534 patients with oral lesions associated with HIV. The data were collected from five referral centers for managing HIV and associated comorbidities in the city of Porto Alegre, Southern Brazil, between 1996 and 2011. Using a standardized form, socio-demographic and clinical data were recorded. Exclusively and definitively diagnosed oral pathologies were included and classified according to ECC criteria on Oral Problems Related to HIV Infection. For data analysis cross-tabulations, Chi-squared tests and logistic regression models were used where appropriate. RESULTS: CD4+ counts lower than 350 cells/mm³ (p < 0.001), alcohol consumption (p = 0.011) and female gender (p = 0.031) were predisposing factors for oral candidiasis. The occurrence of hairy leukoplakia was independently associated with CD4+ counts below 500 cells/mm³, (p = 0.029) a viral load above 5,000 copies/mm³ (p = 0.003) and smoking (p = 0.005). CONCLUSIONS: Moderate and severe degrees of immunodeficiency and detectable viral loads were risk factors for the onset of oral lesions. Smoking and alcohol consumption also increased susceptibility to the development of opportunistic infections in HIV-positive adults from Porto Alegre, irrespective of the use of antiretroviral therapy.

Effects of irregular-shift work and physical activity on cardiovascular risk factors in truck drivers

OBJECTIVE: To analyze the putative effect of type of shift and its interaction with leisure-time physical activity on cardiovascular risk factors in truck drivers.METHODS: A cross-sectional study was undertaken on 57 male truck drivers working at a transportation company, of whom 31 worked irregular shifts and 26 worked on the day-shift. Participants recorded their physical activity using the International Physical Activity Questionnaire along with measurements of blood pressure, body mass index and waist-hip ratio. Participants also provided a fasting blood sample for analysis of lipid-related outcomes. Data were analyzed using a factorial model which was covariate-controlled for age, smoking, work demand, control at work and social support.RESULTS: Most of the irregular-shift and day-shift workers worked more than 8 hours per day (67.7% and 73.1%, respectively). The mean duration of experience working the irregular schedule was 15.7 years. Day-shift workers had never engaged in irregular-shift work and had been working as a truck driver for 10.8 years on average. The irregular-shift drivers had lower work demand but less control compared to day-shift drivers (p < 0.05). Moderately-active irregular-shift workers had higher systolic and diastolic arterial pressures (143.7 and 93.2 mmHg, respectively) than moderately-active day-shift workers (116 and 73.3 mmHg, respectively) (p < 0.05) as well as higher total cholesterol concentrations (232.1 and 145 mg/dl, respectively) (p = 0.01). Irrespective of their physical activity, irregular-shift drivers had higher total cholesterol and LDL-cholesterol concentrations (211.8 and 135.7 mg/dl, respectively) than day-shift workers (161.9 and 96.7 mg/dl, respectively (ANCOVA, p < 0.05).CONCLUSIONS: Truck drivers are exposed to cardiovascular risk factors due to the characteristics of the job, such as high work demand, long working hours and time in this profession, regardless of shift type or leisure-time physical activity.

Effect of eliminating chronic diseases among elderly individuals

OBJECTIVE: To determine whether the elimination of certain chronic diseases is capable of leading to the compression of morbidity among elderly individuals.METHODS: A population-based, cross-sectional study was carried out with official data for the city of Sao Paulo, Southeastern Brazil in 2000 and data from the SABE (Health, Wellbeing and Ageing) study. Sullivan's method was used to calculate disability-free life expectancy. Cause-deleted life tables were used to calculate the probabilities of death and disabilities with the elimination of health conditions.RESULTS: The largest gains in disability-free life expectancy, with the elimination of chronic illness, occurred in the female gender. Among individuals of a more advanced age, gains in disability-free life expectancy occurred as result of a relative compression of morbidity. Among men aged 75 years, all conditions studied, except heart disease and systemic arterial pressure, led to an absolute expansion of morbidity and, at the same time, to a relative compression of morbidity upon being eliminated.CONCLUSIONS: The elimination of chronic diseases in the elderly could lead to the compression of morbidity in elderly men and women.

Mining protein structure data

The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.

Data gathering approach in dense sensor networks

Sensor/actuator networks promised to extend automated monitoring and control into industrial processes. Avionic system is one of the prominent technologies that can highly gain from dense sensor/actuator deployments. An aircraft with smart sensing skin would fulfill the vision of affordability and environmental friendliness properties by reducing the fuel consumption. Achieving these properties is possible by providing an approximate representation of the air flow across the body of the aircraft and suppressing the detected aerodynamic drags. To the best of our knowledge, getting an accurate representation of the physical entity is one of the most significant challenges that still exists with dense sensor/actuator network. This paper offers an efficient way to acquire sensor readings from very large sensor/actuator network that are located in a small area (dense network). It presents LIA algorithm, a Linear Interpolation Algorithm that provides two important contributions. First, it demonstrates the effectiveness of employing a transformation matrix to mimic the environmental behavior. Second, it renders a smart solution for updating the previously defined matrix through a procedure called learning phase. Simulation results reveal that the average relative error in LIA algorithm can be reduced by as much as 60% by exploiting transformation matrix.

Environmental data management in the Sado Estuary

Estuaries are perhaps the most threatened environments in the coastal fringe; the coincidence of high natural value and attractiveness for human use has led to conflicts between conservation and development. These conflicts occur in the Sado Estuary since its location is near the industrialised zone of Peninsula of Setúbal and at the same time, a great part of the Estuary is classified as a Natural Reserve due to its high biodiversity. These facts led us to the need of implementing a model of environmental management and quality assessment, based on methodologies that enable the assessment of the Sado Estuary quality and evaluation of the human pressures in the estuary. These methodologies are based on indicators that can better depict the state of the environment and not necessarily all that could be measured or analysed. Sediments have always been considered as an important temporary source of some compounds or a sink for other type of materials or an interface where a great diversity of biogeochemical transformations occur. For all this they are of great importance in the formulation of coastal management system. Many authors have been using sediments to monitor aquatic contamination, showing great advantages when compared to the sampling of the traditional water column. The main objective of this thesis was to develop an estuary environmental management framework applied to Sado Estuary using the DPSIR Model (EMMSado), including data collection, data processing and data analysis. The support infrastructure of EMMSado were a set of spatially contiguous and homogeneous regions of sediment structure (management units). The environmental quality of the estuary was assessed through the sediment quality assessment and integrated in a preliminary stage with the human pressure for development. Besides the earlier explained advantages, studying the quality of the estuary mainly based on the indicators and indexes of the sediment compartment also turns this methodology easier, faster and human and financial resource saving. These are essential factors to an efficient environmental management of coastal areas. Data management, visualization, processing and analysis was obtained through the combined use of indicators and indices, sampling optimization techniques, Geographical Information Systems, remote sensing, statistics for spatial data, Global Positioning Systems and best expert judgments. As a global conclusion, from the nineteen management units delineated and analyzed three showed no ecological risk (18.5 % of the study area). The areas of more concern (5.6 % of the study area) are located in the North Channel and are under strong human pressure mainly due to industrial activities. These areas have also low hydrodynamics and are, thus associated with high levels of deposition. In particular the areas near Lisnave and Eurominas industries can also accumulate the contamination coming from Águas de Moura Channel, since particles coming from that channel can settle down in that area due to residual flow. In these areas the contaminants of concern, from those analyzed, are the heavy metals and metalloids (Cd, Cu, Zn and As exceeded the PEL guidelines) and the pesticides BHC isomers, heptachlor, isodrin, DDT and metabolits, endosulfan and endrin. In the remain management units (76 % of the study area) there is a moderate impact potential of occurrence of adverse ecological effects and in some of these areas no stress agents could be identified. This emphasizes the need for further research, since unmeasured chemicals may be causing or contributing to these adverse effects. Special attention must be taken to the units with moderate impact potential of occurrence of adverse ecological effects, located inside the natural reserve. Non-point source pollution coming from agriculture and aquaculture activities also seem to contribute with important pollution load into the estuary entering from Águas de Moura Channel. This pressure is expressed in a moderate impact potential for ecological risk existent in the areas near the entrance of this Channel. Pressures may also came from Alcácer Channel although they were not quantified in this study. The management framework presented here, including all the methodological tools may be applied and tested in other estuarine ecosystems, which will also allow a comparison between estuarine ecosystems in other parts of the globe.

Building a microscope for the data center

Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolutionof the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center andwith them, _and opportunities to optimize energy consumption. Havinga high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.