Search for direct top-squark pair production in final states with two leptons in pp collisions at sqrts = 8TeV with the ATLAS detector

A search is presented for direct top-squark pair production in final states with two leptons (electrons or muons) of opposite charge using 20.3 fb−1 of pp collision data at ps = 8TeV, collected by the ATLAS experiment at the Large Hadron Collider in 2012. No excess over the Standard Model expectation is found. The results are interpreted under the separate assumptions (i) that the top squark decays to a b-quark in addition to an on-shell chargino whose decay occurs via a real or virtual W boson, or (ii) that the top squark decays to a t-quark and the lightest neutralino. A top squark with a mass between 150 GeV and 445 GeV decaying to a b-quark and an on-shell chargino is excluded at 95% confidence level for a top squark mass equal to the chargino mass plus 10 GeV, in the case of a 1 GeV lightest neutralino. Top squarks with masses between 215 (90) GeV and 530 (170) GeV decaying to an on-shell (off-shell) t-quark and a neutralino are excluded at 95% confidence level for a 1 GeV neutralino.

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in sqrts = 8TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three leptons and missing transverse momentum is presented. The analysis is based on 20.3 fb−1 of √s = 8TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with the Standard Model expectations and limits are set in R-parity-conserving phenomenological Minimal Supersymmetric Standard Models and in simplified supersymmetric models, significantly extending previous results. For simplified supersymmetric models of direct chargino (˜χ±1 ) and next-to-lightest neutralino (˜χ02) production with decays to lightest neutralino(˜χ01) via either all three generations of sleptons, staus only, gauge bosons, or Higgs bosons, ˜χ±1 and ˜χ02 masses are excluded up to 700GeV, 380GeV, 345GeV, or 148GeV respectively, for a massless ˜χ01.

Detecting outlying studies in meta-regression models using a forward search algorithm.

When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Spinal cerebrospinal fluid leak as the cause of chronic subdural hematomas in nongeriatric patients

OBJECT The etiology of chronic subdural hematoma (CSDH) in nongeriatric patients (≤ 60 years old) often remains unclear. The primary objective of this study was to identify spinal CSF leaks in young patients, after formulating the hypothesis that spinal CSF leaks are causally related to CSDH. METHODS All consecutive patients 60 years of age or younger who underwent operations for CSDH between September 2009 and April 2011 at Bern University Hospital were included in this prospective cohort study. The patient workup included an extended search for a spinal CSF leak using a systematic algorithm: MRI of the spinal axis with or without intrathecal contrast application, myelography/fluoroscopy, and postmyelography CT. Spinal pathologies were classified according to direct proof of CSF outflow from the intrathecal to the extrathecal space, presence of extrathecal fluid accumulation, presence of spinal meningeal cysts, or no pathological findings. The primary outcome was proof of a CSF leak. RESULTS Twenty-seven patients, with a mean age of 49.6 ± 9.2 years, underwent operations for CSDH. Hematomas were unilateral in 20 patients and bilateral in 7 patients. In 7 (25.9%) of 27 patients, spinal CSF leakage was proven, in 9 patients (33.3%) spinal meningeal cysts in the cervicothoracic region were found, and 3 patients (11.1%) had spinal cysts in the sacral region. The remaining 8 patients (29.6%) showed no pathological findings. CONCLUSIONS The direct proof of spinal CSF leakage in 25.9% of patients suggests that spinal CSF leaks may be a frequent cause of nongeriatric CSDH.

Search for long-lived, heavy particles in final states with a muon and multi-track displaced vertex in proton–proton collisions at View the MathML sources=7 TeV with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb(-1) of root s = 7 TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results.

Search for charginos nearly mass-degenerate with the lightest neutralino based on a disappearing-track signature in pp collisions at sqrts = 8 TeV with the ATLAS detector

A search is presented for direct chargino production based on a disappearing-track signature using 20.3  fb−1 of proton-proton collisions at s√=8  TeV collected with the ATLAS experiment at the LHC. In anomaly-mediated supersymmetry breaking (AMSB) models, the lightest chargino is nearly mass degenerate with the lightest neutralino and its lifetime is long enough to be detected in the tracking detectors by identifying decays that result in tracks with no associated hits in the outer region of the tracking system. Some models with supersymmetry also predict charginos with a significant lifetime. This analysis attains sensitivity for charginos with a lifetime between 0.1 and 10 ns, and significantly surpasses the reach of the LEP experiments. No significant excess above the background expectation is observed for candidate tracks with large transverse momentum, and constraints on chargino properties are obtained. In the AMSB scenarios, a chargino mass below 270 GeV is excluded at 95% confidence level.

A mixed-integer linear programming approach to the optimization of event-bus schedules: a scheduling application in the tourism sector

This paper deals with “The Enchanted Journey,” which is a daily event tour booked by Bollywood-film fans. During the tour, the participants visit original sites of famous Bollywood films at various locations in Switzerland; moreover, the tour includes stops for lunch and shopping. Each day, up to five buses operate the tour. For operational reasons, however, two or more buses cannot stay at the same location simultaneously. Further operative constraints include time windows for all activities and precedence constraints between some activities. The planning problem is how to compute a feasible schedule for each bus. We implement a two-step hierarchical approach. In the first step, we minimize the total waiting time; in the second step, we minimize the total travel time of all buses. We present a basic formulation of this problem as a mixed-integer linear program. We enhance this basic formulation by symmetry-breaking constraints, which reduces the search space without loss of generality. We report on computational results obtained with the Gurobi Solver. Our numerical results show that all relevant problem instances can be solved using the basic formulation within reasonable CPU time, and that the symmetry-breaking constraints reduce that CPU time considerably.

Search for pair-produced third-generation squarks decaying via charm quarks or in compressed supersymmetric scenarios in pp collisions at √s=8 TeV with the ATLAS detector

Results of a search for supersymmetry via direct production of third-generation squarks are reported, using 20.3  fb −1 of proton-proton collision data at √s =8  TeV recorded by the ATLAS experiment at the LHC in 2012. Two different analysis strategies based on monojetlike and c -tagged event selections are carried out to optimize the sensitivity for direct top squark-pair production in the decay channel to a charm quark and the lightest neutralino (t 1 →c+χ ˜ 0 1 ) across the top squark–neutralino mass parameter space. No excess above the Standard Model background expectation is observed. The results are interpreted in the context of direct pair production of top squarks and presented in terms of exclusion limits in the m ˜t 1, m ˜ X0 1 ) parameter space. A top squark of mass up to about 240 GeV is excluded at 95% confidence level for arbitrary neutralino masses, within the kinematic boundaries. Top squark masses up to 270 GeV are excluded for a neutralino mass of 200 GeV. In a scenario where the top squark and the lightest neutralino are nearly degenerate in mass, top squark masses up to 260 GeV are excluded. The results from the monojetlike analysis are also interpreted in terms of compressed scenarios for top squark-pair production in the decay channel t ˜ 1 →b+ff ′ +χ ˜ 0 1 and sbottom pair production with b ˜ 1 →b+χ ˜ 0 1 , leading to a similar exclusion for nearly mass-degenerate third-generation squarks and the lightest neutralino. The results in this paper significantly extend previous results at colliders.

Optimization of TRPV6 Calcium Channel Inhibitors Using a 3D Ligand-Based Virtual Screening Method

Herein, we report the discovery of the first potent and selective inhibitor of TRPV6, a calcium channel overexpressed in breast and prostate cancer, and its use to test the effect of blocking TRPV6-mediated Ca2+-influx on cell growth. The inhibitor was discovered through a computational method, xLOS, a 3D-shape and pharmacophore similarity algorithm, a type of ligand-based virtual screening (LBVS) method described briefly here. Starting with a single weakly active seed molecule, two successive rounds of LBVS followed by optimization by chemical synthesis led to a selective molecule with 0.3 μM inhibition of TRPV6. The ability of xLOS to identify different scaffolds early in LBVS was essential to success. The xLOS method may be generally useful to develop tool compounds for poorly characterized targets.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.