914 resultados para time to event analysis


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As neuroscience gains social traction and entices media attention, the notion that education has much to benefit from brain research becomes increasingly popular. However, it has been argued that the fundamental bridge toward education is cognitive psychology, not neuroscience. We discuss four specific cases in which neuroscience synergizes with other disciplines to serve education, ranging from very general physiological aspects of human learning such as nutrition, exercise and sleep, to brain architectures that shape the way we acquire language and reading, and neuroscience tools that increasingly allow the early detection of cognitive deficits, especially in preverbal infants. Neuroscience methods, tools and theoretical frameworks have broadened our understanding of the mind in a way that is highly relevant to educational practice. Although the bridge’s cement is still fresh, we argue why it is prime time to march over it.

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En el presente documento se estudia el desempeño que ha tenido Perú durante la última fase expansiva del ciclo de precios de commodities, específicamente entre los años 2001 y 2015. Para esto, se desarrolla un modelo de equilibrio general estocástico y dinámico, basado en Medina y Soto (2007) y Fornero y Kichner (2014), que incorpora un sector productor de commodities con inversión del tipo time to build. El modelo es estimado de forma lineal y a partir de este se muestra la importancia que tienen los choques de precios commodities sobre el resto de la actividad económica. Asimismo, se analizan distintos tipos de políticas fiscales y monetarias, ante este tipo de choques. También se obtienen políticas monetarias óptimas a partir de la función de pérdida de la autoridad monetaria. Los resultados de la investigación apuntan a que, cuando hay un incremento en el precio de los commodities, se genera una dinámica procíclica en el valor de la producción de todos los sectores, en la inversión, el consumo y el gasto del Gobierno. Además, se encuentra que la incorporación del mecanismo de time to build permite explicar mejor la dinámica observada. Dicho mecanismo ayuda a comprender que el choque en cuestión demora en propagarse, ya que los proyectos mineros toman tiempo en construirse. Este aporte metodológico es de particular relevancia en los ejercicios de modelamiento y predicción que se quieran realizar sobre la economía peruana.

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TV Advertising is evolving quickly. This article examines how the popularity of viewing content on mobile platforms is changing the way we advertise. VOD and OTT media services have meant that advertisers can now automate and personalise their TV advertising. It's having a significant impact on the UK TV business model.

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As neuroscience gains social traction and entices media attention, the notion that education has much to benefit from brain research becomes increasingly popular. However, it has been argued that the fundamental bridge toward education is cognitive psychology, not neuroscience. We discuss four specific cases in which neuroscience synergizes with other disciplines to serve education, ranging from very general physiological aspects of human learning such as nutrition, exercise and sleep, to brain architectures that shape the way we acquire language and reading, and neuroscience tools that increasingly allow the early detection of cognitive deficits, especially in preverbal infants. Neuroscience methods, tools and theoretical frameworks have broadened our understanding of the mind in a way that is highly relevant to educational practice. Although the bridge’s cement is still fresh, we argue why it is prime time to march over it.

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The focus of this research is to explore the applications of the finite difference formulation based on the latency insertion method (LIM) to the analysis of circuit interconnects. Special attention is devoted to addressing the issues that arise in very large networks such as on-chip signal and power distribution networks. We demonstrate that the LIM has the power and flexibility to handle various types of analysis required at different stages of circuit design. The LIM is particularly suitable for simulations of very large scale linear networks and can significantly outperform conventional circuit solvers (such as SPICE).

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For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

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Background: The survival rates of preterm infants has increased over the last years, but oral feeding difficulties are the most common problems encountered by them Objectives: This study aimed at comparing the effects of non-nutritive sucking (NNS) and pre-feeding oral stimulation on feeding skills, length of hospital stay and weight gain of 26-32 weeks gestational age preterm infants in NICU, to determine the more effective intervention. Patients and Methods: Thirty-two preterm infants were assigned randomly into three groups. One intervention group received pre-feeding oral stimulation program and the other received non-nutritive sucking stimulation, while the control group received a sham intervention. Gestational age of infants was calculated during 1, 4 and 8 oral feeding and discharge time from NICU. The infants’ weights were measured weekly from birth and at discharge time. Results: Mean gestational age on 8 time oral feeding per day, in 3 groups was not significant (P = 0.282). Although NNS and pre-feeding oral stimulation groups has fulfilled this criterion 7.55 and 6.07 days sooner than the control group, respectively (a result which is of great clinical and economic importance), but the difference did not reach statistical significance. Weight gaining at discharge time in NNS group was significantly higher than control and pre-feeding oral stimulation groups (P < 0.05). Conclusions: This study revealed that pre-feeding oral stimulation and NNS programs both were effective on oral feeding skills and weight gaining of the immature newborns. Yet, it seems that NNS program was more effective than pre-feeding oral stimulation on weight gaining.

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The objective of this thesis is to explore new and improved methods for greater sample introduction efficiency and enhanced analytical performance with inductively coupled plasma optical emission spectrometry (ICP-OES). Three projects are discussed in which the capabilities and applications of ICP-OES are expanded: 1. In the first project, a conventional ultrasonic nebuliser was modified to replace the heater/condenser with an infrared heated pre-evaporation tube. In continuation from previous works with pre-evaporation, the current work investigated the effects of heating with infrared block and rope heaters on two different ICP-OES instruments. Comparisons were made between several methods and setups in which temperatures were varied. By monitoring changes to sensitivity, detection limit, precision, and robustness, and analyzing two certified reference materials, a method with improved sample introduction efficiency and comparable analytical performance to a previous method was established. 2. The second project involved improvements to a previous work in which a multimode sample introduction system (MSIS) was modified by inserting a pre-evaporation tube between the MSIS and torch. The new work focused on applying an infrared heated ceramic rope for pre-evaporation. This research was conducted in all three MSIS modes (nebulisation mode, hydride generation mode, and dual mode) and on two different ICP-OES instruments, and comparisons were made between conventional setups in terms of sensitivity, detection limit, precision, and robustness. By tracking both hydride-forming and non-hydride forming elements, the effects of heating in combination with hydride generation were probed. Finally, optimal methods were validated by analysis of two certified reference materials. 3. A final project was completed in collaboration with ZincNyx Energy Solutions. This project sought to develop a method for the overall analysis of a 12 M KOH zincate fuel, which is used in green energy backup systems. By employing various techniques including flow injection analysis and standard additions, a final procedure was formulated for the verification of K concentration, as well as the measurement of additives (Al, Fe, Mg, In, Si), corrosion products (such C from CO₃²¯), and Zn particles both in and filtered from solution. Furthermore, the effects of exposing the potassium zincate electrolyte fuel to air were assessed.

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Despite current recommendations, a high percentage of patients with severe symptomatic aortic stenosis are managed conservatively. The aim of this study was to study symptomatic patients undergoing conservative management from the IDEAS registry, describing their baseline clinical characteristics, mortality, and the causes according to the reason for conservative management. Consecutive patients with severe aortic stenosis diagnosed at 48 centers during January 2014 were included. Baseline clinical characteristics, echocardiographic data, Charlson index, and EuroSCORE-II were registered, including vital status and performance of valve intervention during one-year follow-up. For the purpose of this substudy we assessed symptomatic patients undergoing conservative management, including them in 5 groups according to the reason for performing conservative management [I: comorbidity/frailty (128, 43.8%); II: dementia 18 (6.2%); III: advanced age 34 (11.6%); IV: patients’ refusal 62 (21.2%); and V: other reasons 50 (17.1%)]. We included 292 patients aged 81.5 ± 9 years. Patients from group I had higher Charlson index (4 ± 2.3), higher EuroSCORE-II (7.5 ± 6), and a higher overall (42.2%) and non-cardiac mortality (16.4%) than the other groups. In contrast, patients from group III had fewer comorbidities, lower EuroSCORE-II (4 ± 2.5), and low overall (20.6%) and non-cardiac mortality (5.9%). Patients with severe symptomatic aortic stenosis managed conservatively have different baseline characteristics and clinical course according to the reason for performing conservative management. A prospective assessment of comorbidity and other geriatric syndromes might contribute to improve therapeutic strategy in this clinical setting.

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These statistics break down the incarceration time left for inmates of South Carolina prisons. It ranges from 3 months or less to Life/Death as of June 30, 2016.

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Survival models are being widely applied to the engineering field to model time-to-event data once censored data is here a common issue. Using parametric models or not, for the case of heterogeneous data, they may not always represent a good fit. The present study relays on critical pumps survival data where traditional parametric regression might be improved in order to obtain better approaches. Considering censored data and using an empiric method to split the data into two subgroups to give the possibility to fit separated models to our censored data, we’ve mixture two distinct distributions according a mixture-models approach. We have concluded that it is a good method to fit data that does not fit to a usual parametric distribution and achieve reliable parameters. A constant cumulative hazard rate policy was used as well to check optimum inspection times using the obtained model from the mixture-model, which could be a plus when comparing with the actual maintenance policies to check whether changes should be introduced or not.