Supersymmetric top and bottom squark production at hadron colliders

The scalar partners of top and bottom quarks are expected to be the lightest squarks in supersymmetric theories, with potentially large cross sections at hadron colliders. We present predictions for the production of top and bottom squarks at the Tevatron and the LHC, including next-to-leading order corrections in supersymmetric QCD and the resummation of soft gluon emission at next-to-leading-logarithmic accuracy. We discuss the impact of the higher-order corrections on total cross sections and transverse-momentum distributions, and provide an estimate of the theoretical uncertainty due to scale variation and the parton distribution functions.Comment: 29 pages, 6 figure

The AMANDA Neutrino Telescope and the Indirect Search for Dark Matter

With an effective telescope area of order 10^4 m^2, a threshold of ~50 GeV and a pointing accuracy of 2.5 degrees, the AMANDA detector represents the first of a new generation of high energy neutrino telescopes, reaching a scale envisaged over 25 years ago. We describe its performance, focussing on the capability to detect halo dark matter particles via their annihilation into neutrinos.Comment: Latex2.09, 16 pages, uses epsf.sty to place 15 postscript figures. Talk presented at the 3rd International Symposium on Sources and Detection of Dark Matter in the Universe (DM98), Santa Monica, California, Feb. 199

The AMANDA Neutrino Telescope: Principle of Operation and First Results

AMANDA is a high-energy neutrino telescope presently under construction at the geographical South Pole. In the Antarctic summer 1995/96, an array of 80 optical modules (OMs) arranged on 4 strings (AMANDA-B4) was deployed at depths between 1.5 and 2 km. In this paper we describe the design and performance of the AMANDA-B4 prototype, based on data collected between February and November 1996. Monte Carlo simulations of the detector response to down-going atmospheric muon tracks show that the global behavior of the detector is understood. We describe the data analysis method and present first results on atmospheric muon reconstruction and separation of neutrino candidates. The AMANDA array was upgraded with 216 OMs on 6 new strings in 1996/97 (AMANDA-B10), and 122 additional OMs on 3 strings in 1997/98.Comment: 36 pages, 23 figures, submitted to Astroparticle Physic

The AMANDA Neutrino Telescope

With an effective telescope area of order $10^4$ m$^2$ for TeV neutrinos, a threshold near $\sim$50 GeV and a pointing accuracy of 2.5 degrees per muon track, the AMANDA detector represents the first of a new generation of high energy neutrino telescopes, reaching a scale envisaged over 25 years ago. We describe early results on the calibration of natural deep ice as a particle detector as well as on AMANDA's performance as a neutrino telescope.Comment: 12 pages, Latex2.09, uses espcrc2.sty and epsf.sty, 13 postscript files included. Talk presented at the 18th International Conference on Neutrino Physics and Astrophysics (Neutrino 98), Takayama, Japan, June 199

Functional Diversity and Structural Disorder in the Human Ubiquitination Pathway

The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred - E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions. © 2013 Bhowmick et al

Muon Track Reconstruction and Data Selection Techniques in AMANDA

The Antarctic Muon And Neutrino Detector Array (AMANDA) is a high-energy neutrino telescope operating at the geographic South Pole. It is a lattice of photo-multiplier tubes buried deep in the polar ice between 1500m and 2000m. The primary goal of this detector is to discover astrophysical sources of high energy neutrinos. A high-energy muon neutrino coming through the earth from the Northern Hemisphere can be identified by the secondary muon moving upward through the detector. The muon tracks are reconstructed with a maximum likelihood method. It models the arrival times and amplitudes of Cherenkov photons registered by the photo-multipliers. This paper describes the different methods of reconstruction, which have been successfully implemented within AMANDA. Strategies for optimizing the reconstruction performance and rejecting background are presented. For a typical analysis procedure the direction of tracks are reconstructed with about 2 degree accuracy.Comment: 40 pages, 16 Postscript figures, uses elsart.st

Controlled ultraviolet (UV) photoinitiated fabrication of monolithic porous layer open tubular (monoPLOT) capillary columns for chromatographic applications

An automated column fabrication technique that is based on a ultraviolet (UV) light-emitting diode (LED) array oven, and provides precisely controlled "in-capillary" ultraviolet (UV) initiated polymerization at 365 nm, is presented for the production of open tubular monolithic porous polymer layer capillary (monoPLOT) columns of varying length, inner diameter (ID), and porous layer thickness. The developed approach allows the preparation of columns of varying length, because of an automated capillary delivery approach, with precisely controlled and uniform layer thickness and monolith morphology, from controlled UV power and exposure time. The relationships between direct exposure times, intensity, and layer thickness were determined, as were the effects of capillary delivery rate (indirect exposure rate), and multiple exposures on the layer thickness and axial distribution. Layer thickness measurements were taken by scanning electron microscopy (SEM), with the longitudinal homogeneity of the stationary phase confirmed using scanning capacitively coupled contactless conductivity detection (sC(4)D). The new automated UV polymerization technique presented in this work allows the fabrication of monoPLOT columns with a very high column-to-column production reproducibility, displaying a longitudinal phase thickness variation within ±0.8% RSD (relative standard deviation)

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly characterized from brain diffusion MRI. In addition, to enable analysis of WM tracts in large datasets and in clinical practice it is essential to have methodology that is fast and easy to apply. This work therefore presents a new approach for WM tract segmentation: Neuro4Neuro, that is capable of direct extraction of WM tracts from diffusion tensor images using convolutional neural network (CNN). This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N=9752, 1.5T MRI). The proposed method showed good segmentation performance and high reproducibility, i.e., a high spatial agreement (Cohen's kappa, k = 0.72 ~ 0.83) and a low scan-rescan error in tract-specific diffusion measures (e.g., fractional anisotropy: error = 1% ~ 5%). The reproducibility of the proposed method was higher than that of a tractography-based segmentation algorithm, while being orders of magnitude faster (0.5s to segment one tract). In addition, we showed that the method successfully generalizes to diffusion scans from an external dementia dataset (N=58, 3T MRI). In two proof-of-principle experiments, we associated WM microstructure obtained using the proposed method with age in a normal elderly population, and with disease subtypes in a dementia cohort. In concordance with the literature, results showed a widespread reduction of microstructural organization with aging and substantial group-wise microstructure differences between dementia subtypes. In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice.Comment: Preprint to be published in NeuroImag

How does the social context fuel the proactive fire? A multilevel review and theoretical synthesis

© 2018 John Wiley & Sons, Ltd. The role of social context (e.g., leadership, team climate, and organizational support) in shaping employee proactive behavior has received considerable attention and has been investigated across multiple forms of proactive behavior. However, the research has not been well integrated. In this review, we adopt a multilevel approach to synthesize what is known about how social context factors influence employees' proactive behavior, as well as what mechanisms underpin these effects. Our analyses show that leader-, team-, and organization-related social context factors mainly influence employee proactivity through shaping “reason to,” “can do,” and “energized to” states (i.e., proactive motivational states) via individual-, team-, and cross-level processes. That has been most frequently investigated is the effect of the discretionary social context, particularly leadership, on proactive behavior. We also review the interaction effects between social context factors and other factors on employee proactive behavior and found inconsistent support for the motivational-fit perspective that stimuli with the same directions enhance each other's effect. We offer a research agenda to advance theoretical insights on this important topic