On the importance of nonlinear modeling in computer performance prediction

Computers are nonlinear dynamical systems that exhibit complex and sometimes even chaotic behavior. The models used in the computer systems community, however, are linear. This paper is an exploration of that disconnect: when linear models are adequate for predicting computer performance and when they are not. Specifically, we build linear and nonlinear models of the processor load of an Intel i7-based computer as it executes a range of different programs. We then use those models to predict the processor loads forward in time and compare those forecasts to the true continuations of the time seriesComment: Appeared in "Proceedings of the 12th International Symposium on Intelligent Data Analysis

N-Acetylcysteine improves mitochondrial function and ameliorates behavioral deficits in the R6/1 mouse model of Huntington\u27s disease

Huntington\u27s disease (HD) is a neurodegenerative disorder, involving psychiatric, cognitive and motor symptoms, caused by a CAG-repeat expansion encoding an extended polyglutamine tract in the huntingtin protein. Oxidative stress and excitotoxicity have previously been implicated in the pathogenesis of HD. We hypothesized that N-acetylcysteine (NAC) may reduce both excitotoxicity and oxidative stress through its actions on glutamate reuptake and antioxidant capacity. The R6/1 transgenic mouse model of HD was used to investigate the effects of NAC on HD pathology. It was found that chronic NAC administration delayed the onset and progression of motor deficits in R6/1 mice, while having an antidepressant-like effect on both R6/1 and wild-type mice. A deficit in the astrocytic glutamate transporter protein, GLT-1, was found in R6/1 mice. However, this deficit was not ameliorated by NAC, implying that the therapeutic effect of NAC is not due to rescue of the GLT-1 deficit and associated glutamate-induced excitotoxicity. Assessment of mitochondrial function in the striatum and cortex revealed that R6/1 mice show reduced mitochondrial respiratory capacity specific to the striatum. This deficit was rescued by chronic treatment with NAC. There was a selective increase in markers of oxidative damage in mitochondria, which was rescued by NAC. In conclusion, NAC is able to delay the onset of motor deficits in the R6/1 model of Huntington\u27s disease and it may do so by ameliorating mitochondrial dysfunction. Thus, NAC shows promise as a potential therapeutic agent in HD. Furthermore, our data suggest that NAC may also have broader antidepressant efficacy

Nitrogen in ruminant nutrition: a review of measurement techniques

Nitrogen (N) is a component of essential nutrients critical for the productivity of ruminants. If excreted in excess, N is also an important environmental pollutant contributing to acid deposition, eutrophication, human respiratory problems, and climate change. The complex microbial metabolic activity in the rumen and the impact on subsequent processes in the intestines and body tissues make the study of N metabolism in ruminants challenging compared to non-ruminants. Therefore, using accurate and precise measurement techniques is imperative for obtaining reliable experimental results on N utilization by ruminants and evaluating the environmental impacts of N emission mitigation techniques. Changeover design experiments are as suitable as continuous ones for studying protein metabolism in ruminant animals, except when changes in body weight or carryover effects due to treatment are expected. Adaptation following a dietary change should be allowed for at least 2 (preferably 3) weeks, and extended adaptation periods may be required if body pools can temporarily supply the nutrients studied. Dietary protein degradability in the rumen and intestines are feed characteristics determining the primary amino acids available to the host animal. They can be estimated using in situ, in vitro, or in vivo techniques with each having inherent advantages and disadvantages. There is still a need for accurate, precise, and inexpensive laboratory assays for feed protein availability. Techniques used for direct determination of rumen microbial protein synthesis are laborious, expensive, and data variability can be unacceptably large; indirect approaches have not shown the level of accuracy required for widespread adoption. Techniques for studying postruminal digestion and absorption of nitrogenous compounds, urea recycling, and mammary amino acid metabolism are also laborious, expensive (especially the methods that utilize isotopes), and results can be variable, especially the methods based on measurements of digesta or blood flow. Volatile loss of N from feces and urine can be substantial during collection, processing, and analysis of excreta, compromising the accuracy of measurements of total tract N digestion and body N balance. In studying ruminant N metabolism, nutritionists should consider the longer-term fate of manure N as well. Various techniques used to determine the effects of animal nutrition on total N, ammonia- or nitrous oxide-emitting potentials, as well as plant fertilizer value, of manure are available. Overall, over 150 years of animal nutrition research have developed methods to study ruminant N metabolism, but many of them are laborious and impractical for application on a large number of animals. The increasing environmental concerns associated with livestock production systems necessitate a more accurate and reliable methods to determine manure N emissions in the context of feed composition and ruminant N metabolism

Genome‐wide studies of von Willebrand factor propeptide identify loci contributing to variation in propeptide levels and von Willebrand factor clearance

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134219/1/jth13401-sup-0001-FigS1-S7.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134219/2/jth13401.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134219/3/jth13401_am.pd

Covariant description of inelastic electron--deuteron scattering:predictions of the relativistic impulse approximation

Using the covariant spectator theory and the transversity formalism, the unpolarized, coincidence cross section for deuteron electrodisintegration, $d(e,e'p)n$, is studied. The relativistic kinematics are reviewed, and simple theoretical formulae for the relativistic impulse approximation (RIA) are derived and discussed. Numerical predictions for the scattering in the high $Q^2$ region obtained from the RIA and five other approximations are presented and compared. We conclude that measurements of the unpolarized coincidence cross section and the asymmetry $A_\phi$, to an accuracy that will distinguish between different theoretical models, is feasible over most of the wide kinematic range accessible at Jefferson Lab.Comment: 54 pages and 24 figure

High speed outflows driven by the 30 Doradus starburst

Echelle spectroscopy has been carried out towards a sample region of the halo of the giant HII region 30 Doradus in the Large Magellanic Cloud. This new kinematical data is the amongst the most sensitive yet obtained for this nebula and reveals a wealth of faint, complex high speed features. These are interpreted in terms of localised shells due to individual stellar winds and supernova explosions, and collections of discrete knots of emission that still retain the velocity pattern of the giant shells from which they fragmented. The high speed velocity features may trace the base of the superwind that emanates from the 30 Doradus starburst, distributed around the super star cluster R136.Comment: 8 pages, 8 figures, accepted for publication in MNRA

Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy

Methane (CH) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH. To address this limitation, we developed novel CH prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH production (g CH/animal·d, ANIM-B models) and CH yield (g CH/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin’s concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH emissions from sheep, providing valuable insights for future research and mitigation strategies.Te authors gratefully acknowledge funding for this project from the USDA National Institute of Food and Agriculture (Award number: 2014-67003-21979). Te animal and microbial data originated from a study funded by the Pastoral Greenhouse Gas Research Consortium (www.pggrc.co.nz)

Branching Fractions of tau Leptons to Three Charged Hadrons

From electron-positron collision data collected with the CLEO detector operating at CESR near \sqrt{s}=10.6 GeV, improved measurements of the branching fractions for tau decays into three explicitly identified hadrons and a neutrino are presented as {\cal B}(\tau^-\to\pi^-\pi^+\pi^-\nu_\tau)=(9.13\pm0.05\pm0.46)%, {\cal B}(\tau^-\to K^-\pi^+\pi^-\nu_\tau)=(3.84\pm0.14\pm0.38)\times10^{-3}, {\cal B}(\tau^-\to K^-K^+\pi^-\nu_\tau)=(1.55\pm0.06\pm0.09)\times10^{-3}, and {\cal B}(\tau^-\to K^-K^+K^-\nu_\tau)<3.7\times10^{-5} at 90% C.L., where the uncertainties are statistical and systematic, respectively.Comment: 10 pages postscript, also available through http://w4.lns.cornell.edu/public/CLNS, to appear in Phys. Rev. Let