Modelling the mechanical response of the Reed-mouthpiece-lip system of a clarinet. Part I. A one-dimensional distributed model

The motion of a clarinet reed that is clamped to a mouthpiece and supported by a lip is simulated in the time-domain using finite difference methods. The reed is modelled as a bar with non-uniform cross section, and is described using a one-dimensional, fourth-order partial differential equation. The interactions with the mouthpiece Jay and the player's lip are taken into account by incorporating conditional contact forces in the bar equation. The model is completed by clamped-free boundary conditions for the reed. An implicit finite difference method is used for discretising the system, and values for the physical parameters are chosen both from laboratory measurements and by accurate tuning of the numerical simulations. The accuracy of the numerical system is assessed through analysis of frequency warping effects and of resonance estimation. Finally, the mechanical properties of the system are studied by analysing its response to external driving forces. In particular, the effects of reed curling are investigated.

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

Testosterone levels in dominant sociable males are lower than in solitary roamers: Physiological differences between three male reproductive tactics in a sociably flexible mammal

The relative plasticity hypothesis predicts that alternative tactics are associated with changes in steroid hormone levels. In species with alternative male reproductive tactics, the highest androgen levels have usually been reported in dominant males. However, in sociable species, dominant males show amicable behaviors to gain access to females, which might conflict with high testosterone levels. We compared testosterone, corticosterone, and resting metabolic rate in male striped mice (Rhabdomys pumilio) following a conditional strategy with three different reproductive tactics: (i) philopatric group-living males, (ii) solitary-living roamers, (iii) dominant but sociable group-living territorial breeders. Philopatrics had the lowest testosterone but highest corticosterone levels, suggesting that they make the best of a bad job. Dominant territorial breeders had lower testosterone levels than roamers, which have a lower competitive status. Roamers had the highest testosterone levels, which might promote risky behavior, such as invading territories defended by territorial males. Roamers also had lower resting metabolic rates than either type of group-living males. Our results suggest that dominant males' testosterone levels reflect a trade-off between low testosterone amicable behavior and high testosterone dominance behavior.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Putting a Price on Prisoner Release: The History of Bail and the Future of Parole

In this article, we argue that the history of bail foretells the future of parole. Under a plancalled the Conditional Post-Conviction Release Bond Act (recently passed into law inthree states), US prisoners can secure early release only after posting ‘post-convictionbail’. As with pre-trial bail, the fledgling model would require prisoners to pay a percent-age of the bail amount to secure their release under the contractual responsibility of acommercial bail agency. If release conditions are breached, bounty hunters are legallyempowered to seize and return the parolee to prison. Our inquiry outlines the origins of this post-conviction bond plan and the research upon which it is based. Drawing on the‘new penology’ framework, we identify several underlying factors that make for a ripeadvocacy environment and set the stage for widespread state-level adoption of this planin the near future. Post-conviction bail fits squarely within the growing policy trendstoward privatization, managerialism, and actuarial justice. Most importantly, though,advocates have the benefit of precedent on their side, as most US states have longrelied on a system of commercial bail bonding and private bounty hunting to manageconditional pretrial release.

Pax7-expressing satellite cells are indispensable for adult skeletal muscle regeneration

Distinct cell populations with regenerative capacity have been reported to contribute to myofibres after skeletal muscle injury, including non-satellite cells as well as myogenic satellite cells. However, the relative contribution of these distinct cell types to skeletal muscle repair and homeostasis and the identity of adult muscle stem cells remain unknown. We generated a model for the conditional depletion of satellite cells by expressing a human diphtheria toxin receptor under control of the murine Pax7 locus. Intramuscular injection of diphtheria toxin during muscle homeostasis, or combined with muscle injury caused by myotoxins or exercise, led to a marked loss of muscle tissue and failure to regenerate skeletal muscle. Moreover, the muscle tissue became infiltrated by inflammatory cells and adipocytes. This localised loss of satellite cells was not compensated for endogenously by other cell types, but muscle regeneration was rescued after transplantation of adult Pax7(+) satellite cells alone. These findings indicate that other cell types with regenerative potential depend on the presence of the satellite cell population, and these observations have important implications for myopathic conditions and stem cell-based therapeutic approaches.

Are causal and intervention judgments inextricably linked? A developmental study.

The application of the formal framework of causal Bayesian Networks to children's causal learning provides the motivation to examine the link between judgments about the causal structure of a system, and the ability to make inferences about interventions on components of the system. Three experiments examined whether children are able to make correct inferences about interventions on different causal structures. The first two experiments examined whether children's causal structure and intervention judgments were consistent with one another. In Experiment 1, children aged between 4 and 8years made causal structure judgments on a three-component causal system followed by counterfactual intervention judgments. In Experiment 2, children's causal structure judgments were followed by intervention judgments phrased as future hypotheticals. In Experiment 3, we explicitly told children what the correct causal structure was and asked them to make intervention judgments. The results of the three experiments suggest that the representations that support causal structure judgments do not easily support simple judgments about interventions in children. We discuss our findings in light of strong interventionist claims that the two types of judgments should be closely linked. © 2011 Cognitive Science Society, Inc.


--------------------------------------------------------------------------------

Reaxys Database Information|

The development of regret

In two experiments, 4- to 9-year-olds played a game in which they
selected one of two boxes to win a prize. On regret trials the unchosen
box contained a better prize than the prize children actually
won, and on baseline trials the other box contained a prize of the
same value. Children rated their feelings about their prize before
and after seeing what they could have won if they had chosen
the other box and were asked to provide an explanation if their
feelings had changed. Patterns of responding suggested that regret
was experienced by 6 or 7 years of age; children of this age could
also explain why they felt worse in regret trials by referring to
the counterfactual situation in which the prize was better. No evidence
of regret was found in 4- and 5-year-olds. Additional findings
suggested that by 6 or 7 years, children’s emotions were
determined by a consideration of two different counterfactual
scenarios.

Proton pump inhibitors and histamine-2-receptor antagonists and pancreatic cancer risk: a nested case-control study

Background: The relationship between use of proton pump inhibitors (PPIs) and histamine-2-receptor antagonists (H₂RAs) and pancreatic cancer risk has yet to be examined. Data from a range of studies suggest biologically plausible mechanisms, whereby these drugs (or the conditions for which they are prescribed) may affect pancreatic cancer risk. The objective of this study was to investigate the relationship between use of PPIs/H₂RAs and pancreatic cancer risk.

Methods: A nested case – control study was conducted within the UK general practice research database (GPRD). Cases had a diagnosis of exocrine pancreatic cancer and controls were matched to cases on general practice site, sex and year of birth. Exposure to PPIs and to H₂RAs since entry into GPRD until 2 years before the diagnosis date (corresponding date in controls) and in the 5 years before the diagnosis date were separately assessed. Conditional logistic regression analyses were used to generate odds ratios (ORs) and 95% confidence intervals (CIs) associated with PPI or H₂RA use compared with nonuse.

Results: Ever use of PPIs since entry into the GPRD (excluding the 2 years prior to diagnosis) was not associated with risk of pancreatic cancer; OR (95% CI) 1.02 (0.85 – 1.22). Neither the dose nor the duration of PPI or H₂RA use was associated with pancreatic cancer risk. No consistent patterns of association were seen when cumulative exposure (dose and duration) to these drugs was examined separately or together.

Conclusion: PPI/H₂RA use, in a UK population, was not associated with pancreatic cancer risk.

Luminescent Photoinduced Electron Transfer (PET) Molecules for Sensing and Logic Operations

Chemical species can serve as inputs to supramolecular devices so that a luminescence output is created in a conditional manner. Conditionality is built into these devices by employing the classical photochemical process of photoinduced electron transfer (PET) to compete with luminescence emission. The response of these devices in the analogue regime leads to sensors that can operate in nanometric, micrometric, and millimetric spaces. Some of these devices serve in membrane science, cell physiology, and medical diagnostics. The response in the digital regime leads to Boolean logic gates. Some of these find application in improving aspects of medical diagnostics and in identifying small objects in large populations.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

A model for radiation-induced bystander effects, with allowance for spatial position and the effects of cell turnover

Bystander effects, whereby cells that are not directly exposed to ionizing radiation exhibit adverse biological effects, have been observed in a number of experimental systems. A novel stochastic model of the radiation-induced bystander effect is developed that takes account of spatial location, cell killing and repopulation. The ionizing radiation dose- and time-responses of this model are explored, and it is shown to exhibit pronounced downward curvature in the high dose-rate region, similar to that observed in many experimental systems, reviewed in the paper. It is also shown to predict the augmentation of effect after fractionated delivery of dose that has been observed in certain experimental systems. It is shown that the generally intractable solution of the full stochastic system can be considerably simplified by assumption of pairwise conditional dependence that varies exponentially over time. (C) 2004 Elsevier Ltd. All rights reserved.

Speculative Return Address Stack Management Revisited

Branch prediction feeds a speculative execution processor core with instructions. Branch mispredictions are inevitable and have negative effects on performance and energy consumption. With the advent of highly accurate conditional branch predictors, nonconditional branch instructions are gaining importance.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

Assessing length of stay and associated characteristics of geriatric patients in Northern Ireland

The effective provision of care for the elderly is becoming increasingly more difficult. This is due to the rising proportion of elderly in the population, increasing demands placed on the health services and the financial strain placed on an already stretched economy. The research presented in this paper uses three different models to represent the length of stay distribution of geriatric patients admitted to one of the six key acute hospitals in Northern Ireland and various patient characteristics associated with their respective length of stay. The accurate modelling of bed usage within wards would enable hospital managers to prepare patient discharge packages and rehabilitation services in advance. The models presented within the paper include a Cox proportional hazards model, a Bayesian network with a discrete variable to represent length of stay and a special conditional phase-type model (C-Ph) with a connecting outcome node. This research demonstrates the new efficient fitting algorithm employed for Coxian phase-type distributions while updating C-Ph models for recent elderly patient data.