Unintegrated parton distributions and inclusive jet production at HERA

We describe how unintegrated parton distributions can be calculated from conventional integrated distributions. We extend and improve the 'last-step' evolution approach, and explain why doubly-unintegrated parton distributions are necessary. We generalise k_t-factorisation to (z,k_t)-factorisation. We apply the formalism to inclusive jet production in deep-inelastic scattering, mainly at leading-order, but we also study the extension to next-to-leading order. We compare the predictions with recent HERA data.Comment: 32 pages, 11 figures. Version to appear in Eur. Phys. J.

Local Heat Transfer Coefficients Induced by Piezoelectrically Actuated Vibrating Cantilevers

Piezoelectric fans have been shown to provide substantial enhancements in heat transfer over natural convection while consuming very little power. These devices consist of a piezoelectric material attached to a flexible cantilever beam. When driven at resonance, large oscillations at the cantilever tip cause fluid motion, which in turn results in improved heat transfer rates. In this study, the local heat transfer coefficients induced by piezoelectric fans are determined experimentally for a fan vibrating close to an electrically heated stainless steel foil, and the entire temperature field is observed by means of an infrared camera. Four vibration amplitudes ranging from 6.35 to 10 mm are considered, with the distance from the heat source to the fan tip chosen to vary from 0.01 to 2.0 times the amplitude. The two-dimensional contours of the local heat transfer coefficient transition from a lobed shape at small gaps to an almost circular shape at intermediate gaps. At larger gaps, the heat transfer coefficient distribution becomes elliptical in shape. Correlations developed with appropriate Reynolds and Nusselt number definitions describe the area-averaged thermal performance with a maximum error of less than 12%

The unintegrated gluon distribution from the CCFM equation

The gluon distribution f(x, k_t^2,mu^2), unintegrated over the transverse momentum k_t of the gluon, satisfies the angular-ordered CCFM equation which interlocks the dependence on the scale k_t with the scale \mu of the probe. We show how, to leading logarithmic accuracy, the equation can be simplified to a single scale problem. In particular we demonstrate how to determine the two-scale unintegrated distribution f(x,k_t^2,mu^2) from knowledge of the integrated gluon obtained from a unified scheme embodying both BFKL and DGLAP evolution.Comment: 16 pages LaTeX, 3 eps figure

Role of angiopoietin-like protein 3 in sugar-induced dyslipidemia in rhesus macaques: suppression by fish oil or RNAi.

Angiopoietin-like protein 3 (ANGPTL3) inhibits lipid clearance and is a promising target for managing cardiovascular disease. Here we investigated the effects of a high-sugar (high-fructose) diet on circulating ANGPTL3 concentrations in rhesus macaques. Plasma ANGPTL3 concentrations increased ∼30% to 40% after 1 and 3 months of a high-fructose diet (both P < 0.001 vs. baseline). During fructose-induced metabolic dysregulation, plasma ANGPTL3 concentrations were positively correlated with circulating indices of insulin resistance [assessed with fasting insulin and the homeostatic model assessment of insulin resistance (HOMA-IR)], hypertriglyceridemia, adiposity (assessed as leptin), and systemic inflammation [C-reactive peptide (CRP)] and negatively correlated with plasma levels of the insulin-sensitizing hormone adropin. Multiple regression analyses identified a strong association between circulating APOC3 and ANGPTL3 concentrations. Higher baseline plasma levels of both ANGPTL3 and APOC3 were associated with an increased risk for fructose-induced insulin resistance. Fish oil previously shown to prevent insulin resistance and hypertriglyceridemia in this model prevented increases of ANGPTL3 without affecting systemic inflammation (increased plasma CRP and interleukin-6 concentrations). ANGPTL3 RNAi lowered plasma concentrations of ANGPTL3, triglycerides (TGs), VLDL-C, APOC3, and APOE. These decreases were consistent with a reduced risk of atherosclerosis. In summary, dietary sugar-induced increases of circulating ANGPTL3 concentrations after metabolic dysregulation correlated positively with leptin levels, HOMA-IR, and dyslipidemia. Targeting ANGPTL3 expression with RNAi inhibited dyslipidemia by lowering plasma TGs, VLDL-C, APOC3, and APOE levels in rhesus macaques

Revealing cytotoxic substructures in molecules using deep learning

In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical advances and the ever growing amount of available toxicity data enabled machine learning, especially neural networks, to impact the field of predictive toxicology. In this study, cytotoxicity prediction, one of the earliest handles in drug discovery, is investigated using a deep learning approach trained on a highly consistent in-house data set of over 34,000 compounds with a share of less than 5% of cytotoxic molecules. The model reached a balanced accuracy of over 70%, similar to previously reported studies using Random Forest. Albeit yielding good results, neural networks are often described as a black box lacking deeper mechanistic understanding of the underlying model. To overcome this absence of interpretability, a Deep Taylor Decomposition method is investigated to identify substructures that may be responsible for the cytotoxic effects, the so-called toxicophores. Furthermore, this study introduces cytotoxicity maps which provide a visual structural interpretation of the relevance of these substructures. Using this approach could be helpful in drug development to predict the potential toxicity of a compound as well as to generate new insights into the toxic mechanism. Moreover, it could also help to de-risk and optimize compounds

Load Carriage Distance Run and Pushups Tests: No Body Mass Bias and Occupationally Relevant

Recent research has demonstrated body mass (M) bias in military physical fi tness tests favoring lighter, not just leaner, service members. Mathematical modeling predicts that a distance run carrying a backpack of 30 lbs would eliminate M-bias. The purpose of this study was to empirically test this prediction for the U.S. Army push-ups and 2-mile run tests. Two tests were performed for both events for each of 56 university Reserve Offi cer Training Corps male cadets: with (loaded) and without backpack (unloaded). Results indicated signifi cant M-bias in the unloaded and no M-bias in the loaded condition for both events. Allometrically scaled scores for both events were worse in the loaded vs. unloaded conditions, supporting a hypothesis not previously tested. The loaded push-ups and 2-mile run appear to remove M-bias and are probably more occupationally relevant as military personnel are often expected to carry external loads

Cluster size distributions in particle systems with asymmetric dynamics

We present exact and asymptotic results for clusters in the one-dimensional totally asymmetric exclusion process (TASEP) with two different dynamics. The expected length of the largest cluster is shown to diverge logarithmically with increasing system size for ordinary TASEP dynamics and as a logarithm divided by a double logarithm for generalized dynamics, where the hopping probability of a particle depends on the size of the cluster it belongs to. The connection with the asymptotic theory of extreme order statistics is discussed in detail. We also consider a related model of interface growth, where the deposited particles are allowed to relax to the local gravitational minimum.Comment: 12 pages, 3 figures, RevTe