46 resultados para Two-Phase Regression


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In this paper, we study a two-phase underlay cognitive relay network, where there exists an eavesdropper who can overhear the message. The secure data transmission from the secondary source to secondary destination is assisted by two decode-and-forward (DF) relays. Although the traditional opportunistic relaying technique can choose one relay to provide the best secure performance, it needs to continuously have the channel state information (CSI) of both relays, and may result in a high relay switching rate. To overcome these limitations, a secure switch-and-stay combining (SSSC) protocol is proposed where only one out of the two relays is activated to assist the secure data transmission, and the secure relay switching occurs when the relay cannot support the secure communication any longer. This security switching is assisted by either instantaneous or statistical eavesdropping CSI. For these two cases, we study the system secure performance of SSSC protocol, by deriving the analytical secrecy outage probability as well as an asymptotic expression for the high main-to-eavesdropper ratio (MER) region. We show that SSSC can substantially reduce the system complexity while achieving or approaching the full diversity order of opportunistic relaying in the presence of the instantaneous or statistical eavesdropping CSI.

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The spouted bed was widely used due to its good mixing of particles and effective phase transferability between the gas and solid phase. In this paper, the transportation process of particles in a 3D spouted bed was studied using the Computational Particle Fluid Dynamics (CPFD) numerical method. Experiments were conducted to verify the validity of the simulation results. Distributions of the pressure, velocities and particle concentration of transportation devices were investigated. The motion state and characteristics of multiphase flows in the transportation device were demonstrated under various operating conditions. The results showed that a good consistency was obtained between the simulated results and the experimental results. The motion characteristics of the gas-solid two-phase flow in the device was effectively predicted, which could assist the optimal operating condition estimation for the spouted transportation process.

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A matrix-type silicone elastomer vaginal ring providing 28-day continuous release of dapivirine (DPV) - a lead candidate human immunodeficiency virus type 1 (HIV-1) microbicide compound - has recently demonstrated moderate levels of protection in two Phase III clinical studies. Here, next-generation matrix and reservoir-type silicone elastomer vaginal rings are reported for the first time offering simultaneous and continuous in vitro release of DPV and the contraceptive progestin levonorgestrel (LNG) over a period of between 60 and 180days. For matrix-type vaginal rings comprising initial drug loadings of 100, 150 or 200mg DPV and 0, 16 or 32mg LNG, Day 1 daily DPV release values were between 4132 and 6113μg while Day 60 values ranged from 284 to 454μg. Daily LNG release ranged from 129 to 684μg on Day 1 and 2-91μg on Day 60. Core-type rings comprising one or two drug-loaded cores provided extended duration of in vitro release out to 180days, and maintained daily drug release rates within much narrower windows (either 75-131μg/day or 37-66μg/day for DPV, and either 96-150μg/day or 37-57μg/day for LNG, depending on core ring configuration and ignoring initial lag release effect for LNG) compared with matrix-type rings. The data support the continued development of these devices as multi-purpose prevention technologies (MPTs) for HIV prevention and long-acting contraception.

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Some non-classical properties such as squeezing, sub-Poissonian photon statistics or oscillations in photon-number distributions may survive longer in a phase-sensitive environment than in a phase-insensitive environment. We examine if entanglement, which is an inter-mode non-classical feature, can also survive longer in a phase-sensitive environment. Differently from the single-mode case, we find that making the environment phase-sensitive does not aid in prolonging the inter-mode non-classical nature, i.e. entanglement.

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PURPOSE The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. PATIENTS AND METHODS Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and WBC. Two different models of prognostic scores for 90-day mortality were generated by using these factors, including or excluding PS; both achieved specificities of more than 85% and sensitivities of approximately 50% when using a score cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. CONCLUSION Patient selection using any of these prognostic scores will reduce non-drug-related 90-day mortality among patients enrolled in phase I trials by 50%. However, this can be achieved only by an overall reduction in recruitment to phase I studies of 20%, more than half of whom would in fact have survived beyond 90 days.

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Discrete Conditional Phase-type (DC-Ph) models are a family of models which represent skewed survival data conditioned on specific inter-related discrete variables. The survival data is modeled using a Coxian phase-type distribution which is associated with the inter-related variables using a range of possible data mining approaches such as Bayesian networks (BNs), the Naïve Bayes Classification method and classification regression trees. This paper utilizes the Discrete Conditional Phase-type model (DC-Ph) to explore the modeling of patient waiting times in an Accident and Emergency Department of a UK hospital. The resulting DC-Ph model takes on the form of the Coxian phase-type distribution conditioned on the outcome of a logistic regression model.

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Background: We sought to determine if a common polymorphism can influence vulnerability to LDL cholesterol, and thereby influence the clinical benefit derived from therapies that reduce LDL cholesterol.

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This article describes by means of a simple model how signal recombination effects behave under the influence of phase conjugating retrodirective array (RDA) technology. A two-ray ground reflection model is used to predict the operational advantages of RDA technology in multipath rich environments. The simulation results show that advantageous signal recombination occurs due to automatic self-phasing. As the number of elements in the RDA increases, the fading effect normally observed due to out of phase multipath signal is mitigated to the extent that the system approaches that of one operating in a free space environment. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:1987–1989, 2013

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We present a compact experimental realization of the interaction among five field modes in a chi((2)) nonlinear crystal. The classical evolution of the fields can be analytically described assuming that two of the fields play the role of nondepleted pumps. A peculiar behavior appears that has been experimentally verified. If one of the fields has a nonzero input amplitude, then the other two fields at the output are holographic replicas of the input signal. (C) 2004 Optical Society of America

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The From Boys to Men Project was funded by the Economic and Social Research
Council to explore why some boys become domestic abuse perpetrators when
others do not. In so doing, it sought to establish what more could be done to
reduce the number of young men who become perpetrators. The study
involved three phases of data collection including: Phase 1 - a survey of school
children aged 13-14, Phase 2 - focus groups with 69 young people aged 13-19,
and Phase 3 - life history interviews with 30 young men, aged 16-21, who had experienced domestic violence as victims, perpetrators or witnesses.