Single-inclusive production of large-pT charged particles in hadronic collisions at TeV energies and perturbative QCD predictions

The single inclusive spectrum of charged particles with transverse momenta pT=3-150 GeV/c measured at midrapidity by the CDF experiment in proton-antiproton (p-pbar) collisions at sqrt(s)=1.96 TeV is compared to next-to-leading order (NLO) perturbative QCD calculations using the most recent parametrizations of the parton distributions and parton-to-hadron fragmentation functions. Above pT~20 GeV/c, there is a very sizeable disagreement of the Tevatron data compared to the NLO predictions and to xT-scaling expectations, suggesting a problem in the experimental data. We also present the predictions for the pT-differential charged hadron spectra and the associated theoretical uncertainties for proton-proton (p-p) collisions at LHC energies (sqrt(s)=0.9-14 TeV). Two procedures to estimate the charged hadron spectra at LHC heavy-ion collision energies (sqrt(s)=2.76,5.5 TeV) from p-p measurements are suggested.Comment: 23 pages, 9 figures. A few text additions. Accepted for publication in JHE

Video-tracking and On-plant Tests Show Cry1Ab Resistance Influences Behavior and Survival of Neonate Ostrinia nubilalis Following Exposure to Bt Maize

To examine how resistance to Bacillus thuringiensis (Bt) toxins influences movement and survival of European corn borer (Ostrinia nubilalis [Hübner]) neonates, the responses of Cry1Ab-resistant , -susceptible, and hybrid (F1) larvae were examined using two different techniques. First, using an automated video-tracking system, aspects of O. nubilalis movement were quantified in the presence of artificial diet incorporating 50% non-Bt or insect-resistant Cry1Ab maize tissue. Second, O. nubilalis dispersal and survival were measured 48–72 h after hatching on a Cry1Ab maize plant surrounded by two non-Bt maize plants. Video tracking indicated the presence of Cry1Ab tissue increased the total distance moved (m), time moving (%), and time away from the diet (%) for O. nubilalis while decreasing meander (degrees/cm). However, resistant larvae showed reduced movement and increased meander (≈localized searching) relative to susceptible or hybrid larvae on diet incorporating Cry1Ab tissue. Conversely, when placed onto Cry1Ab maize plants, resistant larvae were more likely than susceptible O. nubilalis to disperse onto adjacent non-Bt plants. The difference in on-plant dispersal seems to reflect greater survival after toxin exposure for resistant larvae rather than increased activity. These results suggest that simplified ‘Petri dish’ tests may not be predictive of larval movement among non-Bt and insect-resistant Bt maize plants. Because models of O. nubilalis resistance evolution incorporate various movement and survival parameters, improved data for on-plant behavior and survival of Bt- resistant , -susceptible, and hybrid larvae should help preserve the efficacy of transgenic insect-resistant maize

Quantum Computing

Quantum mechanics---the theory describing the fundamental workings of nature---is famously counterintuitive: it predicts that a particle can be in two places at the same time, and that two remote particles can be inextricably and instantaneously linked. These predictions have been the topic of intense metaphysical debate ever since the theory's inception early last century. However, supreme predictive power combined with direct experimental observation of some of these unusual phenomena leave little doubt as to its fundamental correctness. In fact, without quantum mechanics we could not explain the workings of a laser, nor indeed how a fridge magnet operates. Over the last several decades quantum information science has emerged to seek answers to the question: can we gain some advantage by storing, transmitting and processing information encoded in systems that exhibit these unique quantum properties? Today it is understood that the answer is yes. Many research groups around the world are working towards one of the most ambitious goals humankind has ever embarked upon: a quantum computer that promises to exponentially improve computational power for particular tasks. A number of physical systems, spanning much of modern physics, are being developed for this task---ranging from single particles of light to superconducting circuits---and it is not yet clear which, if any, will ultimately prove successful. Here we describe the latest developments for each of the leading approaches and explain what the major challenges are for the future.Comment: 26 pages, 7 figures, 291 references. Early draft of Nature 464, 45-53 (4 March 2010). Published version is more up-to-date and has several corrections, but is half the length with far fewer reference

An experimental investigation into resonance dry grinding of hardened steel and nickel alloys with element of MQL

Current policies on environmental issues put extra pressures on manufacturing processes to be resource efficient and eco-friendly. However, in grinding processes, large amounts of cutting fluids are used. These fluids are not environmental friendly thus require proper management before disposal with associated cost. Hence, this work sets to explore low-frequency vibration in grinding in order to improve coolant application in conventional grinding at the first stage with the aim to introduce this into high efficiency deep grinding (HEDG) at latter stage. An attempt is made to grind nickel alloys with minimum quantity lubricant (MQL) as oppose to flood cooling. To achieve this with minimum alterations to the machine tool, a piezo-driven workpiece holder was developed for surface grinding. This simple innovative workpiece holder allowed oscillating during actual grinding process. However, this paper presents the results of low-frequency oscillatory grinding in dry and near-dry conditions. The response of the machine tool spindle unit is presented alongside with the workpiece holder response. In this investigation, hardened steels and nickel alloys were ground with vibration assistance. The grinding forces are illustrated together with the surface finish. The wheel performance is given in terms of grinding ratio

HER2-family signalling mechanisms, clinical implications and targeting in breast cancer.

Approximately 20 % of human breast cancers (BC) overexpress HER2 protein, and HER2-positivity is associated with a worse prognosis. Although HER2-targeted therapies have significantly improved outcomes for HER2-positive BC patients, resistance to trastuzumab-based therapy remains a clinical problem. In order to better understand resistance to HER2-targeted therapies in HER2-positive BC, it is necessary to examine HER family signalling as a whole. An extensive literature search was carried out to critically assess the current knowledge of HER family signalling in HER2-positive BC and response to HER2-targeted therapy. Known mechanisms of trastuzumab resistance include reduced receptor-antibody binding (MUC4, p95HER2), increased signalling through alternative HER family receptor tyrosine kinases (RTK), altered intracellular signalling involving loss of PTEN, reduced p27kip1, or increased PI3K/AKT activity and altered signalling via non-HER family RTKs such as IGF1R. Emerging strategies to circumvent resistance to HER2-targeted therapies in HER2-positive BC include co-targeting HER2/PI3K, pan-HER family inhibition, and novel therapies such as T-DM1. There is evidence that immunity plays a key role in the efficacy of HER-targeted therapy, and efforts are being made to exploit the immune system in order to improve the efficacy of current anti-HER therapies. With our rapidly expanding understanding of HER2 signalling mechanisms along with the repertoire of HER family and other targeted therapies, it is likely that the near future holds further dramatic improvements to the prognosis of women with HER2-positive BC

Predicting survival of de novo metastatic breast cancer in Asian women: Systematic review and validation study

10.1371/journal.pone.0093755PLoS ONE94-POLN

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Societal-level versus individual-level predictions of ethical behavior: a 48-society study of collectivism and individualism

Is the societal-level of analysis sufficient today to understand the values of those in the global workforce? Or are individual-level analyses more appropriate for assessing the influence of values on ethical behaviors across country workforces? Using multi-level analyses for a 48-society sample, we test the utility of both the societal-level and individual-level dimensions of collectivism and individualism values for predicting ethical behaviors of business professionals. Our values-based behavioral analysis indicates that values at the individual-level make a more significant contribution to explaining variance in ethical behaviors than do values at the societal-level. Implicitly, our findings question the soundness of using societal-level values measures. Implications for international business research are discussed

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or  ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention

Method for evaluating prediction models that apply the results of randomized trials to individual patients

<p>Abstract</p> <p>Introduction</p> <p>The clinical significance of a treatment effect demonstrated in a randomized trial is typically assessed by reference to differences in event rates at the group level. An alternative is to make individualized predictions for each patient based on a prediction model. This approach is growing in popularity, particularly for cancer. Despite its intuitive advantages, it remains plausible that some prediction models may do more harm than good. Here we present a novel method for determining whether predictions from a model should be used to apply the results of a randomized trial to individual patients, as opposed to using group level results.</p> <p>Methods</p> <p>We propose applying the prediction model to a data set from a randomized trial and examining the results of patients for whom the treatment arm recommended by a prediction model is congruent with allocation. These results are compared with the strategy of treating all patients through use of a net benefit function that incorporates both the number of patients treated and the outcome. We examined models developed using data sets regarding adjuvant chemotherapy for colorectal cancer and Dutasteride for benign prostatic hypertrophy.</p> <p>Results</p> <p>For adjuvant chemotherapy, we found that patients who would opt for chemotherapy even for small risk reductions, and, conversely, those who would require a very large risk reduction, would on average be harmed by using a prediction model; those with intermediate preferences would on average benefit by allowing such information to help their decision making. Use of prediction could, at worst, lead to the equivalent of an additional death or recurrence per 143 patients; at best it could lead to the equivalent of a reduction in the number of treatments of 25% without an increase in event rates. In the Dutasteride case, where the average benefit of treatment is more modest, there is a small benefit of prediction modelling, equivalent to a reduction of one event for every 100 patients given an individualized prediction.</p> <p>Conclusion</p> <p>The size of the benefit associated with appropriate clinical implementation of a good prediction model is sufficient to warrant development of further models. However, care is advised in the implementation of prediction modelling, especially for patients who would opt for treatment even if it was of relatively little benefit.</p