Flexible incorporation of both geographical patterning and risk effects in cancer survival models is becoming increasingly important, due in part to the recent availability of large cancer registries. Most spatial survival models stochastically order survival curves from different subpopulations. However, it is common for survival curves from two subpopulations to cross in epidemiological cancer studies and thus interpretable standard survival models can not be used without some modification. Common fixes are the inclusion of time-varying regression effects in the proportional hazards model or fully non-parametric modeling, either of which destroys any easy interpretability from the fitted model. To address this issue, we develop a generalized accelerated failure time model which allows stratification on continuous or categorical covariates, as well as providing per-variable tests for whether stratification is necessary via novel approximate Bayes factors. The model is interpretable in terms of how median survival changes and is able to capture crossing survival curves in the presence of spatial correlation. A detailed Markov chain Monte Carlo algorithm is presented for posterior inference and a freely available function frailtyGAFT is provided to fit the model in the R package spBayesSurv. We apply our approach to a subset of the prostate cancer data gathered for Louisiana by the Surveillance, Epidemiology, and End Results program of the National Cancer Institute. PMID:26993982
This paper aims to both identify the factors affecting driver drowsiness and to develop a real-time drowsy driving probability model based on virtual Location-Based Services (LBS) data obtained using a driving simulator. A driving simulation experiment was designed and conducted using 32 participant drivers. Collected data included the continuous driving time before detection of drowsiness and virtual LBS data related to temperature, time of day, lane width, average travel speed, driving time in heavy traffic, and driving time on different roadway types. Demographic information, such as nap habit, age, gender, and driving experience was also collected through questionnaires distributed to the participants. An Accelerated Failure Time (AFT) model was developed to estimate the driving time before detection of drowsiness. The results of the AFT model showed driving time before drowsiness was longer during the day than at night, and was longer at lower temperatures. Additionally, drivers who identified as having a nap habit were more vulnerable to drowsiness. Generally, higher average travel speeds were correlated to a higher risk of drowsy driving, as were longer periods of low-speed driving in traffic jam conditions. Considering different road types, drivers felt drowsy more quickly on freeways compared to other facilities. The proposed model provides a better understanding of how driver drowsiness is influenced by different environmental and demographic factors. The model can be used to provide real-time data for the LBS-based drowsy driving warning system, improving past methods based only on a fixed driving. Copyright 2016 Elsevier Ltd. All rights reserved.
Positive.Grid.BIAS.Pedal.v2.3.1.Incl.Keygen setup free
The analysis of time profiles of particles accelerated at interplanetary shocks allows particle transport properties to be inferred. The frequently observed power-law decay upstream, indeed, implies a superdiffusive particle transport when the level of magnetic field variance does not change as the time interval from the shock front increases. In this context, a superdiffusive shock acceleration (SSA) theory has been developed, allowing us to make predictions of the acceleration times. In this work we estimate for a number of interplanetary shocks, including the solar wind termination shock, the acceleration times for energetic protons in the framework of SSA and wemore compare the results with the acceleration times predicted by standard diffusive shock acceleration. The acceleration times due to SSA are found to be much shorter than in the classical model, and also shorter than the interplanetary shock lifetimes. This decrease of the acceleration times is due to the scale-free nature of the particle displacements in the framework of superdiffusion. Indeed, very long displacements are possible, increasing the probability for particles far from the front of the shock to return, and short displacements have a high probability of occurrence, increasing the chances for particles close to the front to cross the shock many times. less
Purpose: To determine the failure rate as a function of neutron dose of the range modulator's servo motor controller system (SMCS) while shielded with Borated Polyethylene (BPE) and unshielded in a single room proton accelerator. Methods: Two experimental setups were constructed using two servo motor controllers and two motors. Each SMCS was then placed 30 cm from the end of the plugged proton accelerator applicator. The motor was then turned on and observed from outside of the vault while being irradiated to known neutron doses determined from bubble detector measurements. Anytime the motor deviated from the programmed motion a failuremore was recorded along with the delivered dose. The experiment was repeated using 9 cm of BPE shielding surrounding the SMCS. Results: Ten SMCS failures were recorded in each experiment. The dose per monitor unit for the unshielded SMCS was 0.0211 mSv/MU and 0.0144 mSv/MU for the shielded SMCS. The mean dose to produce a failure for the unshielded SMCS was 63.5 58.3 mSv versus 17.0 12.2 mSv for the shielded. The mean number of MUs between failures were 2297 1891 MU for the unshielded SMCS and 2122 1523 MU for the shielded. A Wilcoxon Signed Ranked test showed the dose between failures were significantly different (P value = 0.044) while the number of MUs between failures were not (P value = 1.000). Statistical analysis determined a SMCS neutron dose of 5.3 mSv produces a 5% chance of failure. Depending on the workload and location of the SMCS, this failure rate could impede clinical workflow. Conclusion: BPE shielding was shown to not reduce the average failure of the SMCS and relocation of the system outside of the accelerator vault was required to lower the failure rate enough to avoid impeding clinical work flow. less
This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.
It is shown how the availability and MTBF (Mean Time Between Failures) of a redundant system with subsystems maintenanced at the points of so-called stationary renewal processes can be determined from the distributions of the intervals between maintenance actions and of the failure-free operating intervals of the subsystems. The results make it possible, for example, to determine the frequency and duration of hidden failure states in computers which are incidentally corrected during the repair of observed failures.
The hyperdynamics method (HD) developed by Voter (J. Chem. Phys. 1996, 106, 4665) sets the theoretical basis to construct an accelerated simulation scheme that holds the time scale information. Since HD is based on transition state theory, pseudoequilibrium conditions (PEC) must be satisfied before any system in a trapped state may be accelerated. As the system evolves, many trapped states may appear, and the PEC must be assumed in each one to accelerate the escape. However, since the system evolution is a priori unknown, the PEC cannot be permanently assumed to be true. Furthermore, the different parameters of the bias function used may need drastic recalibration during this evolution. To overcome these problems, we present a general scheme to switch between HD and conventional molecular dynamics (MD) in an automatic fashion during the simulation. To decide when HD should start and finish, criteria based on the energetic properties of the system are introduced. On the other hand, a very simple bias function is proposed, leading to a straightforward on-the-fly set up of the required parameters. A way to measure the quality of the simulation is suggested. The efficiency of the present hybrid HD-MD method is tested for a two-dimensional model potential and for the coalescence process of two nanoparticles. In spite of the important complexity of the latter system (165 degrees of freedoms), some relevant mechanistic properties were recovered within the present method.
A self-adaptive accelerated molecular dynamics method is developed to model infrequent atomic- scale events, especially those events that occur on a rugged free-energy surface. Key in the new development is the use of the total displacement of the system at a given temperature to construct a boost-potential, which is slowly increased to accelerate the dynamics. The temperature is slowly increased to accelerate the dynamics. By allowing the system to evolve from one steady-state con guration to another by overcoming the transition state, this self-evolving approach makes it possible to explore the coupled motion of species that migrate on vastly differentmore time scales. The migrations of single vacancy (V) and small He-V clusters, and the growth of nano-sized He-V clusters in Fe for times in the order of seconds are studied by this new method. An interstitial- assisted mechanism is rst explored for the migration of a helium-rich He-V cluster, while a new two-component Ostwald ripening mechanism is suggested for He-V cluster growth. less
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