Design and Performance of the CMS Pixel Detector Readout Chip

The readout chip for the CMS pixel detector has to deal with an enormous data rate. On-chip zero suppression is inevitable and hit data must be buffered locally during the latency of the first level trigger. Dead-time must be kept at a minimum. It is dominated by contributions coming from the readout. To keep it low an analog readout scheme has been adopted where pixel addresses are analog coded. We present the architecture of the final CMS pixel detector readout chip with special emphasis on the analog readout chain. Measurements of its performance are discussed.Comment: 8 pages, 11 figures. Contribution to the Proceedings of the Pixel2005 Workshop, Bonn, German

Structural Simplification of Bedaquiline: the Discovery of 3-(4-(N,N-dimethylaminomethyl)phenyl)quinoline Derived Antitubercular Lead Compounds

Bedaquiline (BDQ) is a novel and highly potent last-line antituberculosis drug that was approved by the US FDA in 2013. Owing to its stereo-structural complexity, chemical synthesis and compound optimization are rather difficult and expensive. This study describes the structural simplification of bedaquiline while preserving antitubercular activity. The compound's structure was split into fragments and reassembled in various combinations while replacing the two chiral carbon atoms with an achiral linkage instead. Four series of analogues were designed; these candidates retained their potent antitubercular activity at sub-microgram per mL concentrations against both sensitive and multidrug-resistant (MDR) Mycobacterium tuberculosis strains. Six out of the top nine MIC-ranked candidates were found to inhibit mycobacterial ATP synthesis activity with IC50 values between 20 and 40 μm, one had IC50>66 μm, and two showed no inhibition, despite their antitubercular activity. These results provide a basis for the development of chemically less complex, lower-cost bedaquiline derivatives and describe the identification of two derivatives with antitubercular activity against non-ATP synthase related targets

Building CMS Pixel Barrel Detectur Modules

For the barrel part of the CMS pixel tracker about 800 silicon pixel detector modules are required. The modules are bump bonded, assembled and tested at the Paul Scherrer Institute. This article describes the experience acquired during the assembly of the first ~200 modules.Comment: 5 pages, 7 figures, Vertex200

Interpretation of Nuclear Quadrupole Resonance Spectra in Doped La2_2CuO4_4

The nuclear quadrupole resonance (NQR) spectrum of strontium doped La$_2$CuO$_4$ surprisingly resembles the NQR spectrum of La$_2$CuO$_4$ doped with excess oxygen, both spectra being dominated by a main peak and one principal satellite peak at similar frequencies. Using first-principles cluster calculations this is investigated here by calculating the electric field gradient (EFG) at the central copper site of the cluster after replacing a lanthanum atom in the cluster with a strontium atom or adding an interstitial oxygen to the cluster. In each case the EFG was increased by approximately 10 % leading unexpectedly to the explanation that the NQR spectra are only accidentally similar and the origins are quite different. Additionally the widths of the peaks in the NQR spectra are explained by the different EFG of copper centres remote from the impurity. A model, based on holes moving rapidly across the planar oxygen atoms, is proposed to explain the observed increase in frequency of both the main and satellite peaks in the NQR spectrum as the doping concentration is increased

Electronic bulk and domain wall properties in B-site doped hexagonal ErMnO3_3

Acceptor and donor doping is a standard for tailoring semiconductors. More recently, doping was adapted to optimize the behavior at ferroelectric domain walls. In contrast to more than a century of research on semiconductors, the impact of chemical substitutions on the local electronic response at domain walls is largely unexplored. Here, the hexagonal manganite ErMnO$_3$ is donor doped with Ti$^{4+}$. Density functional theory calculations show that Ti$^{4+}$ goes to the B-site, replacing Mn$^{3+}$. Scanning probe microscopy measurements confirm the robustness of the ferroelectric domain template. The electronic transport at both macro- and nanoscopic length scales is characterized. The measurements demonstrate the intrinsic nature of emergent domain wall currents and point towards Poole-Frenkel conductance as the dominant transport mechanism. Aside from the new insight into the electronic properties of hexagonal manganites, B-site doping adds an additional degree of freedom for tuning the domain wall functionality

Co-sputtered MoRe thin films for carbon nanotube growth-compatible superconducting coplanar resonators

Molybdenum rhenium alloy thin films can exhibit superconductivity up to critical temperatures of $T_c=15\mathrm{K}$. At the same time, the films are highly stable in the high-temperature methane / hydrogen atmosphere typically required to grow single wall carbon nanotubes. We characterize molybdenum rhenium alloy films deposited via simultaneous sputtering from two sources, with respect to their composition as function of sputter parameters and their electronic dc as well as GHz properties at low temperature. Specific emphasis is placed on the effect of the carbon nanotube growth conditions on the film. Superconducting coplanar waveguide resonators are defined lithographically; we demonstrate that the resonators remain functional when undergoing nanotube growth conditions, and characterize their properties as function of temperature. This paves the way for ultra-clean nanotube devices grown in situ onto superconducting coplanar waveguide circuit elements.Comment: 8 pages, 6 figure

CMS Barrel Pixel Detector Overview

The pixel detector is the innermost tracking device of the CMS experiment at the LHC. It is built from two independent sub devices, the pixel barrel and the end disks. The barrel consists of three concentric layers around the beam pipe with mean radii of 4.4, 7.3 and 10.2 cm. There are two end disks on each side of the interaction point at 34.5 cm and 46.5 cm. This article gives an overview of the pixel barrel detector, its mechanical support structure, electronics components, services and its expected performance.Comment: Proceedings of Vertex06, 15th International Workshop on Vertex Detector

A team approach to the indication for gender reassignment surgery in transsexuals resulting in long-term outcome improvement

At the University of Basel (Switzerland), a multidisciplinary team was established for pre-operative selection and treatment of patients with gender dysphoria. As a result, the indications for surgical gender reassignment could be judged with considerably greater accuracy than previously possible. In the 9-year period of this prospective study only 14 of 57 patients with gender dysphoria were selected for surgical treatment. At the time of this survey, six patients are still under psychiatric preoperative evaluation, and six further male-to-female transsexuals are under hormonal treatment awaiting surgery. Following the operation, only one of nine male-to-female patients is socially unstable and that patient's quality of life is worse than prior to gender reassignment. Of the female-to-male transsexuals, all four are stable in their professional and family relations. In conclusion, a comprehensive evaluation of patients with gender dysphoria and the conclusive indications established within the team considerably improved the postoperative outcome of gender reassignmen

Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction

Deep learning for regression tasks on medical imaging data has shown promising results. However, compared to other approaches, their power is strongly linked to the dataset size. In this study, we evaluate 3D-convolutional neural networks (CNNs) and classical regression methods with hand-crafted features for survival time regression of patients with high grade brain tumors. The tested CNNs for regression showed promising but unstable results. The best performing deep learning approach reached an accuracy of 51.5% on held-out samples of the training set. All tested deep learning experiments were outperformed by a Support Vector Classifier (SVC) using 30 radiomic features. The investigated features included intensity, shape, location and deep features. The submitted method to the BraTS 2018 survival prediction challenge is an ensemble of SVCs, which reached a cross-validated accuracy of 72.2% on the BraTS 2018 training set, 57.1% on the validation set, and 42.9% on the testing set. The results suggest that more training data is necessary for a stable performance of a CNN model for direct regression from magnetic resonance images, and that non-imaging clinical patient information is crucial along with imaging information.Comment: Contribution to The International Multimodal Brain Tumor Segmentation (BraTS) Challenge 2018, survival prediction tas