980 resultados para overlapping community detection


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The relationship between degree of diastolic blood pressure (DBP) reduction and mortality was examined among hypertensives, ages 30-69, in the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center community-based trial, which followed 10,940 hypertensive participants for five years. One-year survival was required for inclusion in this investigation since the one-year annual visit was the first occasion where change in blood pressure could be measured on all participants. During the subsequent four years of follow-up on 10,052 participants, 568 deaths occurred. For levels of change in DBP and for categories of variables related to mortality, the crude mortality rate was calculated. Time-dependent life tables were also calculated so as to utilize available blood pressure data over time. In addition, the Cox life table regression model, extended to take into account both time-constant and time-dependent covariates, was used to examine the relationship change in blood pressure over time and mortality.^ The results of the time-dependent life table and time-dependent Cox life table regression analyses supported the existence of a quadratic function which modeled the relationship between DBP reduction and mortality, even after adjusting for other risk factors. The minimum mortality hazard ratio, based on a particular model, occurred at a DBP reduction of 22.6 mm Hg (standard error = 10.6) in the whole population and 8.5 mm Hg (standard error = 4.6) in the baseline DBP stratum 90-104. After this reduction, there was a small increase in the risk of death. There was not evidence of the quadratic function after fitting the same model using systolic blood pressure. Methodologic issues involved in studying a particular degree of blood pressure reduction were considered. The confidence interval around the change corresponding to the minimum hazard ratio was wide and the obtained blood pressure level should not be interpreted as a goal for treatment. Blood pressure reduction was attributed, not only to pharmacologic therapy, but also to regression to the mean, and to other unknown factors unrelated to treatment. Therefore, the surprising results of this study do not provide direct implications for treatment, but strongly suggest replication in other populations. ^

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Objective. In 2009, the International Expert Committee recommended the use of HbA1c test for diagnosis of diabetes. Although it has been recommended for the diagnosis of diabetes, its precise test performance among Mexican Americans is uncertain. A strong “gold standard” would rely on repeated blood glucose measurement on different days, which is the recommended method for diagnosing diabetes in clinical practice. Our objective was to assess test performance of HbA1c in detecting diabetes and pre-diabetes against repeated fasting blood glucose measurement for the Mexican American population living in United States-Mexico border. Moreover, we wanted to find out a specific and precise threshold value of HbA1c for Diabetes Mellitus (DM) and pre-diabetes for this high-risk population which might assist in better diagnosis and better management of patient diabetes. ^ Research design and methods. We used CCHC dataset for our study. In 2004, the Cameron County Hispanic Cohort (CCHC), now numbering 2,574, was established drawn from randomly selected households on the basis of 2000 Census tract data. The CCHC study randomly selected a subset of people (aged 18-64 years) in CCHC cohort households to determine the influence of SES on diabetes and obesity. Among the participants in Cohort-2000, 67.15% are female; all are Hispanic. ^ Individuals were defined as having diabetes mellitus (Fasting plasma glucose [FPG] ≥ 126 mg/dL or pre-diabetes (100 ≤ FPG < 126 mg/dL). HbA1c test performance was evaluated using receiver operator characteristic (ROC) curves. Moreover, change-point models were used to determine HbA1c thresholds compatible with FPG thresholds for diabetes and pre-diabetes. ^ Results. When assessing Fasting Plasma Glucose (FPG) is used to detect diabetes, the sensitivity and specificity of HbA1c≥ 6.5% was 75% and 87% respectively (area under the curve 0.895). Additionally, when assessing FPG to detect pre-diabetes, the sensitivity and specificity of HbA1c≥ 6.0% (ADA recommended threshold) was 18% and 90% respectively. The sensitivity and specificity of HbA1c≥ 5.7% (International Expert Committee recommended threshold) for detecting pre-diabetes was 31% and 78% respectively. ROC analyses suggest HbA1c as a sound predictor of diabetes mellitus (area under the curve 0.895) but a poorer predictor for pre-diabetes (area under the curve 0.632). ^ Conclusions. Our data support the current recommendations for use of HbA1c in the diagnosis of diabetes for the Mexican American population as it has shown reasonable sensitivity, specificity and accuracy against repeated FPG measures. However, use of HbA1c may be premature for detecting pre-diabetes in this specific population because of the poor sensitivity with FPG. It might be the case that HbA1c is differentiating the cases more effectively who are at risk of developing diabetes. Following these pre-diabetic individuals for a longer-term for the detection of incident diabetes may lead to more confirmatory result.^

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The objective of this study was to determine shifts in the microbial community structure and potential function based on standard Integrated Ocean Drilling Program (IODP) storage procedures for sediment cores. Standard long-term storage protocols maintain sediment temperature at 4°C for mineralogy, geochemical, and/or geotechnical analysis whereas standard microbiological sampling immediately preserves sediments at -80°C. Storage at 4°C does not take into account populations may remain active over geologic time scales at temperatures similar to storage conditions. Identification of active populations within the stored core would suggest geochemical and geophysical conditions within the core change over time. To test this potential, the metabolically active fraction of the total microbial community was characterized from IODP Expedition 325 Great Barrier Reef sediment cores prior to and following a 3-month storage period. Total RNA was extracted from complementary 2, 20, and 40 m below sea floor sediment samples, reverse transcribed to complementary DNA and then sequenced using 454 FLX sequencing technology, yielding over 14,800 sequences from the six samples. Interestingly, 97.3% of the sequences detected were associated with lineages that changed in detection frequency during the storage period including key biogeochemically relevant lineages associated with nitrogen, iron, and sulfur cycling. These lineages have the potential to permanently alter the physical and chemical characteristics of the sediment promoting misleading conclusions about the in situ biogeochemical environment. In addition, the detection of new lineages after storage increases the potential for a wider range of viable lineages within the subsurface that may be underestimated during standard community characterizations.

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En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

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Diffusion controls the gaseous transport process in soils when advective transport is almost null. Knowledge of the soil structure and pore connectivity are critical issues to understand and modelling soil aeration, sequestration or emission of greenhouse gasses, volatilization of volatile organic chemicals among other phenomena. In the last decades these issues increased our attention as scientist have realize that soil is one of the most complex materials on the earth, within which many biological, physical and chemical processes that support life and affect climate change take place. A quantitative and explicit characterization of soil structure is difficult because of the complexity of the pore space. This is the main reason why most theoretical approaches to soil porosity are idealizations to simplify this system. In this work, we proposed a more realistic attempt to capture the complexity of the system developing a model that considers the size and location of pores in order to relate them into a network. In the model we interpret porous soils as heterogeneous networks where pores are represented by nodes, characterized by their size and spatial location, and the links representing flows between them. In this work we perform an analysis of the community structure of porous media of soils represented as networks. For different real soils samples, modelled as heterogeneous complex networks, spatial communities of pores have been detected depending on the values of the parameters of the porous soil model used. These types of models are named as Heterogeneous Preferential Attachment (HPA). Developing an exhaustive analysis of the model, analytical solutions are obtained for the degree densities and degree distribution of the pore networks generated by the model in the thermodynamic limit and shown that the networks exhibit similar properties to those observed in other complex networks. With the aim to study in more detail topological properties of these networks, the presence of soil pore community structures is studied. The detection of communities of pores, as groups densely connected with only sparser connections between groups, could contribute to understand the mechanisms of the diffusion phenomena in soils.

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Soil is well recognized as a highly complex system. The interaction and coupled physical, chemical, and biological processes and phenomena occurring in the soil environment at different spatial and temporal scales are the main reasons for such complexity. There is a need for appropriate methodologies to characterize soil porous systems with an interdisciplinary character. Four different real soil samples, presenting different textures, have been modeled as heterogeneous complex networks, applying a model known as the heterogeneous preferential attachment. An analytical study of the degree distributions in the soil model shows a multiscaling behavior in the connectivity degrees, leaving an empirically testable signature of heterogeneity in the topology of soil pore networks. We also show that the power-law scaling in the degree distribution is a robust trait of the soil model. Last, the detection of spatial pore communities, as densely connected groups with only sparser connections between them, has been studied for the first time in these soil networks. Our results show that the presence of these communities depends on the parameter values used to construct the network. These findings could contribute to understanding the mechanisms of the diffusion phenomena in soils, such as gas and water diffusion, development and dynamics of microorganisms, among others.

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The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until now has not reached its satisfying level. Motivated by this, I decided to devote my main research during this period into having a prototype system architecture of MapReduce framework with a new failure detection service, containing both analytical (theoretical) and implementation part. I am confident that this work should lead the way for further contributions in detecting failures to any NoSQL App frameworks, and cloud storage systems in general.

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The installers and owners show a growing interest in the follow-up of the performance of their photovoltaic (PV) systems. The owners are requesting reliable sources of information to ensure that their system is functioning properly, and the installers are actively looking for efficient ways of providing them the most useful possible information from the data available. Policy makers are becoming increasingly interested in the knowledge of the real performance of PV systems and the most frequent sources of problems that they suffer to be able to target the identified challenges properly. The scientific and industrial PV community is also requiring an access to massive operational data to pursue the technological improvements further.

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National Highway Traffic Safety Administration, Washington, D.C.

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Community responses (n = 925, response rate = 71%) of a series of eight photographs of pigmented skin lesions were compared against those of general practitioners (n = 114, response rate = 77%), considered to be the most relevant gold standard. The eight photographs included three melanomas, two potentially malignant lesions and three benign pigmented lesions. Over the pool of lesions examined, the average probability that community members thought a lesion was likely to be skin cancer (0.68 [99% CI = 0.66-0.69]) was higher (p < 0.0001) than that of the comparison general practitioners 0.58 [99% CI = 0.55-0.62]. This reflects a general (but not consistent) inflated propensity to over-diagnose among community members. The average probability that respondents indicated they would seek medical advice for a lesion was 0.71 [99% CI = 0.70-0.73]. As expected, this was strongly associated with their perceptions of the skin lesion. These results suggest that the community can play a valuable role in assessing the need for medical evaluation of pigmented skin lesions. (c) 2004 International Society for Preventive Oncology. Published by Elsevier Ltd. All rights reserved.

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Background : Within a randomized trial of population screening for melanoma, primary care physicians conducted whole-body skin examinations and referred all patients with suspect lesions to their own doctor for further treatment. Objective: Our aim was to describe characteristics of skin screening participants, clinical screening diagnoses, management following referral, and specificity and yield of screening examinations. Methods: Information collected from consent forms, referral forms, and histopathological reports of lesions that had been excised or undergone biopsy was analyzed by means of descriptive statistics. Results: A total of 16,383 whole-body skin examinations resulted in 2302 referrals (14.1% overall; 15.5% men, 18.2% >= 50 years of age) for 4129 suspect lesions (including 222 suspected melanoma, 1101 suspected basal cell carcinomas [BCCs], 265 suspected squamous cell carcinomas [SCCs]). Histopathologic results were available for 94.8% of 1417 lesions excised and confirmed 33 melanomas (23 in men; 24 in participants ? 50 years of age), 259 BCCs, and 97 SCCs. The probability of detecting skin cancer of any type within the program was 2.4%. The estimated specificity of whole-body skin examinations for melanoma was 86.1% (95% confidence interval = 85.6-86.6). The positive predictive value (number of confirmed/number of lesions excised or biopsied x 100) for melanoma was 2.5%, 19.3% for BCC, and 7.2% for SCC (overall positive predictive value for skin cancer, 28.9%). Limitations: Follow-up of participants with a negative screening examination has not been conducted for the present investigation. Conclusions: The rate of skin cancer detected per 100 patients screened was higher than previously reported and men and attendees older than 50 years more frequently received a referral and diagnosis of melanoma. The specificity for detection of melanoma through whole-body skin examination by a primary care physician was comparable to that of other screening tests, including mammography.

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Background: Early detection and treatment of mental disorders in adolescents and young adults can lead to better health outcomes. Mental health literacy is a key to early recognition and help seeking. Whilst a number of population health initiatives have attempted to improve mental health literacy, none to date have specifically targeted young people nor have they applied the rigorous standards of population health models now accepted as best practice in other health areas. This paper describes the outcomes from the application of a health promotion model to the development, implementation and evaluation of a community awareness campaign designed to improve mental health literacy and early help seeking amongst young people. Method: The Compass Strategy was implemented in the western metropolitan Melbourne and Barwon regions of Victoria, Australia. The Precede-Proceed Model guided the population assessment, campaign strategy development and evaluation. The campaign included the use of multimedia, a website, and an information telephone service. Multiple levels of evaluation were conducted. This included a cross-sectional telephone survey of mental health literacy undertaken before and after 14 months of the campaign using a quasi-experimental design. Randomly selected independent samples of 600 young people aged 12 - 25 years from the experimental region and another 600 from a comparison region were interviewed at each time point. A series of binary logistic regression analyses were used to measure the association between a range of campaign outcome variables and the predictor variables of region and time. Results: The program was judged to have an impact on the following variables, as indicated by significant region-by-time interaction effects ( p < 0.05): awareness of mental health campaigns, self-identified depression, help for depression sought in the previous year, correct estimate of prevalence of mental health problems, increased awareness of suicide risk, and a reduction in perceived barriers to help seeking. These effects may be underestimated because media distribution error resulted in a small amount of print material leaking into the comparison region. Conclusion: We believe this is the first study to apply the rigorous standards of a health promotion model including the use of a control region to a mental health population intervention. The program achieved many of its aims despite the relatively short duration and moderate intensity of the campaign.

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Survival from cutaneous melanoma is mainly dependent on the thickness of the lesion at diagnosis. Skin screening may increase detection of thin lesions and hence improve survival. Within a community-based randomized controlled trial of a population screening program for melanoma in Queensland, Australia, 9 communities were randomly assigned to the 3-year intervention and 9 communities to the control group. Skin screening prevalence was monitored by cross-sectional surveys at baseline, 1, 2 and 3 years into the intervention and 2 years later. At baseline, prevalence of whole-body clinical skin examination was similar in intervention and control communities. In intervention communities, the prevalence of whole-body skin examinations increased to 29.2%, an absolute difference of 18% from baseline, with a peak of 34.8% 2 years after baseline, and began to decline again at the end of the intervention period. The largest increases were seen in men and women ≥50 years. Uptake of screening did not differ according to melanoma risk factors; however, the decline in screening was less in participants who reported a number of melanoma risk factors. The prevalence of skin self-examination remained stable during the intervention program. No changes were observed in the control communities. These results indicate that the intervention program significantly increased the prevalence of whole-body clinical skin examinations in intervention communities. Once the intervention program ceased, and particularly after skin clinics ceased, levels of skin screening began to decline. The provision of specialized skin screening clinics may be needed to achieve sufficient screening rates should population based screening for skin cancer be considered. © 2005 Wiley-Liss, Inc.

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Aims: To elucidate whether a dominant uncultured clostridial (Clostridium thermocellum-like) species in an environmental sample (landfill leachate), possesses an autoinducing peptide (AIP) quorum-sensing (QS) gene, although it may not be functional. Methods and Results: A modified AIP accessory gene regulator (agr)C PCR protocol was performed on extracted DNA from a landfill leachate sample (also characterized by 16S rRNA gene cloning) and the PCR products were cloned, sequenced and phylogenetically analysed. It appeared that two agrC gene phylotypes existed, most closely related to the C. thermocellum agrC gene, differing by only 1 bp. Conclusions: It is possible to specifically identify and characterize the agrC AIP QS gene from uncultured Firmicutes (C. thermocellum-like) bacteria derived from environmental (landfill leachate) sample. Significance and Impact of the Study: This is the first successful attempt at identifying AIP QS genes from a cellulolytic environment (landfill). The agrC gene was identified as being most closely related to the C. thermocellum agrC gene, the same bacterium identified as being dominant, according to 16S rRNA gene cloning and subsequently fluorescence in situ hybridization analyses, in the same biomass.