CMS Pixel Data Quality Monitoring

We present the CMS Pixel Data Quality Monitoring (DQM) system. The concept and architecture are discussed. The monitored quantities are introduced, and the methods on how to ensure that the detector takes high quality data with large efficiency are explained. Finally we describe the automated data certification scheme, which is used to certify and classify the data from the Pixel detector for physics analyses

Solid-phase-assisted synthesis of targeting peptide-PEG-oligo(ethane amino)amides for receptor-mediated gene delivery.

In the forthcoming era of cancer gene therapy, efforts will be devoted to the development of new efficient and non-toxic gene delivery vectors. In this regard, the use of Fmoc/Boc-protected oligo(ethane amino)acids as building blocks for solid-phase-supported assembly represents a novel promising approach towards fully controlled syntheses of effective gene vectors. Here we report on the synthesis of defined polymers containing the following: (i) a plasmid DNA (pDNA) binding domain of eight succinoyl-tetraethylenpentamine (Stp) units and two terminal cysteine residues; (ii) a central polyethylene glycol (PEG) chain (with twenty-four oxyethylene units) for shielding; and (iii) specific peptides for targeting towards cancer cells. Peptides B6 and c(RGDfK), which bind transferrin receptor and αvβ3 integrin, respectively, were chosen because of the high expression of these receptors in many tumoral cells. This study shows the feasibility of designing these kinds of fully controlled vectors and their success for targeted pDNA-based gene transfer

The targetable kinase PIM1 drives ALK inhibitor resistance in high-risk neuroblastoma independent of MYCN status

Abstract: Resistance to anaplastic lymphoma kinase (ALK)-targeted therapy in ALK-positive non-small cell lung cancer has been reported, with the majority of acquired resistance mechanisms relying on bypass signaling. To proactively identify resistance mechanisms in ALK-positive neuroblastoma (NB), we herein employ genome-wide CRISPR activation screens of NB cell lines treated with brigatinib or ceritinib, identifying PIM1 as a putative resistance gene, whose high expression is associated with high-risk disease and poor survival. Knockdown of PIM1 sensitizes cells of differing MYCN status to ALK inhibitors, and in patient-derived xenografts of high-risk NB harboring ALK mutations, the combination of the ALK inhibitor ceritinib and PIM1 inhibitor AZD1208 shows significantly enhanced anti-tumor efficacy relative to single agents. These data confirm that PIM1 overexpression decreases sensitivity to ALK inhibitors in NB, and suggests that combined front-line inhibition of ALK and PIM1 is a viable strategy for the treatment of ALK-positive NB independent of MYCN status

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis