Discrete Conditional Phase-type model (DC_Ph) for patient waiting time with a logistic regression component to predict patient admission to hospital

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.

A Randomized Controlled Trial Evaluation of Time to Read, a Volunteer Tutoring Program for 8-9 Year Olds

Tutoring is commonly employed to prevent early reading failure, and evidence suggests that it can have a positive effect. This article presents findings from a large-scale (n = 734) randomized controlled trial evaluation of the effect of Time to Read—a volunteer tutoring program aimed at children aged 8 to 9 years—on reading comprehension, self-esteem, locus of control, enjoyment of learning, and future aspirations. The study found that the program had only a relatively small effect on children’s aspirations (effect size +0.17, 95% confidence interval [0.015, 0.328]) and no other outcomes. It is suggested that this lack of evidence found may be due to misspecification of the program logic model and outcomes identified and program-related factors, particularly the low dosage of the program.

A progressive failure model for composite laminates subjected to low velocity impact damage

This paper presents a 3-D failure model for predicting the dynamic material response of composite laminates under impact loading. The formulation is based on the Continuum Damage Mechanics (CDM) approach and enables the control of the energy dissipation associated with each failure mode regardless of mesh refinement and fracture plane orientation. Internal thermodynamically irreversible damage variables were defined in order to quantify damage concentration associated with each possible failure mode and predict the gradual stiffness reduction during the impact damage process. The material model has been implemented into LS-DYNA explicit finite element code within solid elements and it has proven to be capable of reproducing experimental results with good accuracy in terms of static/dynamic responses, absorbed energy and extent of damage.

Macroscopic limit of time-dependent density-functional theory for adiabatic local approximations of the exchange-correlation kernel

Time-dependent density-functional theory is a rather accurate and efficient way to compute electronic excitations for finite systems. However, in the macroscopic limit (systems of increasing size), for the usual adiabatic random-phase, local-density, or generalized-gradient approximations, one recovers the Kohn-Sham independent-particle picture, and thus the incorrect band gap. To clarify this trend, we investigate the macroscopic limit of the exchange-correlation kernel in such approximations by means of an algebraical analysis complemented with numerical studies of a one-dimensional tight-binding model. We link the failure to shift the Kohn-Sham spectrum of these approximate kernels to the fact that the corresponding operators in the transition space act only on a finite subspace.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

Shortening design time through multiplatform simulations with a portable OpenCL golden-model: the LDPC decoder case

Hardware designers and engineers typically need to explore a multi-parametric design space in order to find the best configuration for their designs using simulations that can take weeks to months to complete. For example, designers of special purpose chips need to explore parameters such as the optimal bitwidth and data representation. This is the case for the development of complex algorithms such as Low-Density Parity-Check (LDPC) decoders used in modern communication systems. Currently, high-performance computing offers a wide set of acceleration options, that range from multicore CPUs to graphics processing units (GPUs) and FPGAs. Depending on the simulation requirements, the ideal architecture to use can vary. In this paper we propose a new design flow based on OpenCL, a unified multiplatform programming model, which accelerates LDPC decoding simulations, thereby significantly reducing architectural exploration and design time. OpenCL-based parallel kernels are used without modifications or code tuning on multicore CPUs, GPUs and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL for mapping the simulations into FPGAs. To the best of our knowledge, this is the first time that a single, unmodified OpenCL code is used to target those three different platforms. We show that, depending on the design parameters to be explored in the simulation, on the dimension and phase of the design, the GPU or the FPGA may suit different purposes more conveniently, providing different acceleration factors. For example, although simulations can typically execute more than 3x faster on FPGAs than on GPUs, the overhead of circuit synthesis often outweighs the benefits of FPGA-accelerated execution.

Beyond the standard work model? Varieties of flexible working time in European economies

Working time has been among the first aspect of the employment relation to be the object of intense regulation at the national and supra-national level. This standard regulation of working time comprised a number of elements: full-time hours, rigid working schedules, strong employers’ control and clear boundaries around working time In spite of general claims about the erosion of this model, few studies have investigated this process in a comparative and empirical perspective. The aim of this paper is to investigate the diversity of working time arrangements in European economies by applying latent class analysis to data
from the European Working Conditions Survey (EWCS). This analysis shows the existence of six different types of working time organization highlighting five cross-national patterns: multiple flexibilities, extended flexibility, standard, rigid and fragmented time.

An ultra-short-term wind power prediction method using “offline classification and optimization, online model matching” based on time series features

The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS), and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application, the pattern of the last short WPTS is recognized, then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations.

Strength model for end cover separation failure in RC beams strengthened with near-surface mounted (NSM) FRP strips

As an alternative to externally bonded FRP reinforcement, near-surface mounted (NSM) FRP reinforcement can be used to effectively improve the flexural performance of RC beams. In such FRP strengthened RC beams, end cover separation failure is one of the common failure modes. This failuremode involves the detachment of the NSM FRP reinforcement together with the concrete cover along the level of the tension steel reinforcement. This paper presents a new strength model for end cover separation failure in RC beams strengthened in flexure with NSM FRP strips (i.e. rectangular FRP bars with asectional height-to-thickness ratio not less than 5), which was formulated on the basis of extensive numerical results from a parametric study undertaken using an efficient finite element approach. The proposed strength model consists of an approximate equation for the debonding strain of the FRP reinforcement at the critical cracked section and a conventional section analysis to relate this debondingstrain to the moment acting on the same section (i.e. the debonding strain). Once the debonding strain is known, the load level at end cover separation of an FRP-strengthened RC beam can be easily determined for a given load distribution. Predictions from the proposed strength model are compared with those of two existing strength models of the same type and available test results, which shows that the proposed strength model is in close agreement with test results and is far more accurate than the existing strength models.

Analytical model for bar-end cover separation failure in RC beams strengthened with near-surface mounted FRP

The flexural performance of RC beams can be improved using the near-surface mounted (NSM) FRP strengthening technique. A likely failure mode of such FRP-strengthened RC beams is bar-end cover separation which involves the detachment of the NSM FRP reinforcement together with the concrete cover along the level of the steel tension reinforcement. This paper presents a new analytical strength model for this failure mode. The proposed strength model and two existing strength models for this failure mode are compared with test results to demonstrate the superior performance of the new analytical model.

On Infinite Time Performance of Nonlinear Model Predictive Controllers

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

Investigation of tanpura string vibrations using a two-dimensional time-domain model incorporating coupling and bridge friction

Tanpura string vibrations have been investigated previously using numerical models based on energy conserving schemes derived from a Hamiltonian description in one-dimensional form. Such time-domain models have the property that, for the lossless case, the numerical Hamiltonian (representing total energy of the system) can be proven to be constant from one time step
to the next, irrespective of any of the system parameters; in practice the Hamiltonian can be shown to be conserved within machine precision. Models of this kind can reproduce a jvari effect, which results from the bridge-string interaction. However the one-dimensional formulation has recently been shown to fail to replicate the jvaris strong dependence on the thread placement. As a first step towards simulations which accurately emulate this sensitivity to the thread placement, a twodimensional model is proposed, incorporating coupling of controllable level between the two string polarisations at the string termination opposite from the barrier. In addition, a friction force acting when the string slides across the bridge in horizontal direction is introduced, thus effecting a further damping mechanism. In this preliminary study, the string is terminated at the position of the thread. As in the one-dimensional model, an implicit scheme has to be used to solve the system, employing Newton's method to calculate the updated positions and momentums of each string segment. The two-dimensional model is proven to be energy conserving when the loss parameters are set to zero, irrespective of the coupling constant. Both frequency-dependent and independent losses are then added to the string, so that the model can be compared to analogous instruments. The influence of coupling and the bridge friction are investigated.