Operation and performance of the ATLAS semiconductor tracker in LHC Run 2

The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules. During Run 2 (2015–2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb-1 to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector. Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2. It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%. Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules.

Characterization of Irradiated Boron, Carbon-Enriched and Gallium Si-on-Si Wafer Low Gain Avalanche Detectors

Low Gain Avalanche Detectors (LGADs) are n-on-p silicon sensors with an extra doped p-layer below the n-p junction which provides signal amplification. The moderate gain of these sensors, together with the relatively thin active region, provides excellent timing performance for Minimum Ionizing Particles (MIPs). To mitigate the effect of pile-up during the High-Luminosity Large Hadron Collider (HL-LHC) era, both ATLAS and CMS experiments will install new detectors, the High-Granularity Timing Detector (HGTD) and the End-Cap Timing Layer (ETL), that rely on the LGAD technology. A full characterization of LGAD sensors fabricated by Centro Nacional de Microelectrónica (CNM), before and after neutron irradiation up to 1015 neq/cm2, is presented. Sensors produced in 100 mm Si-on-Si wafers and doped with boron and gallium, and also enriched with carbon, are studied. The results include their electrical characterization (I-V, C-V), bias voltage stability and performance studies with the Transient Current Technique (TCT) and a Sr-90 radioactive source setup.

Symphonizing pileup and full-alignment for deep learning-based long-read variant calling

Deep learning-based variant callers are becoming the standard and have achieved superior SNP calling performance using long reads. In this paper, we present Clair3, which makes the best of two major method categories: pile-up calling handles most variant candidates with speed, and full-alignment tackles complicated candidates to maximize precision and recall. Clair3 ran faster than any of the other state-of-the-art variant callers and performed the best, especially at lower coverage.

Architecture-Level Optimization on Digital Silicon Photomultipliers for Medical Imaging

Silicon photomultipliers (SiPMs) are arrays of single-photon avalanche diodes (SPADs) connected in parallel. Analog silicon photomultipliers are built in custom technologies optimized for detection efficiency. Digital silicon photomultipliers are built in CMOS technology. Although CMOS SPADs are less sensitive, they can incorporate additional functionality at the sensor plane, which is required in some applications for an accurate detection in terms of energy, timestamp, and spatial location. This additional circuitry comprises active quenching and recharge circuits, pulse combining and counting logic, and a time-to-digital converter. This, together with the disconnection of defective SPADs, results in a reduction of the light-sensitive area. In addition, the pile-up of pulses, in space and in time, translates into additional efficiency losses that are inherent to digital SiPMs. The design of digital SiPMs must include some sort of optimization of the pixel architecture in order to maximize sensitivity. In this paper, we identify the most relevant variables that determine the influence of SPAD yield, fill factor loss, and spatial and temporal pile-up in the photon detection efficiency. An optimum of 8% is found for different pixel sizes. The potential benefits of molecular imaging of these optimized and small-sized pixels with independent timestamping capabilities are also analyzed.

Markers of Insight

Sometimes creative ideas come to mind following a step-by-step conscious reasoning, other times they rush into consciousness unexpectedly as sudden insights. Research on insight problem solving began about a century ago with a chimpanzee having an Aha! moment on how to pile up some boxes to reach a banana that was hanging from the ceiling (Köhler, 1917). Thanks to the development of neuroscientific techniques, researchers gained a better understanding of the physiology associated with insight, supplemented classic theories, and raised new questions about the cognitive processes involved in it. With the final goal of sketching a comprehensive understanding of the neurocognitive bases of insight, this chapter describes and updates the knowledge we gained about its functioning. A review of the last two decades of research on the ‘markers of insight’ revealed that: a) insights are paired with an internal attention allocation; b) the right anterior temporal lobe is a key node for insights, and if stimulated the frequency of insights increases; c) the feeling of pleasure and excitement that accompanies insights is warranted by the involvement of the reward-dopamine system; d) pupil dilation marks the switch into awareness of Aha! moments. Taken together these results indicate that insight below awareness processing might be explained by the involvement of subcortical areas responsible for learning, alertness, and emotions which are evolutionary more ancient than the cortex and it involves areas of the cortex responsible for information integration presumably together/after the switch into awareness. In conclusion, I summarize these points in terms of the defining characteristics of having an insight.

2D Ship-Like Section Slamming Pressure Numerical Analysis by Conformal Mapping

In this paper, a method to predict slamming pressures and pressure distribution at the time of water entry for 2D sections is presented. The mathematical model is based on the Schwarz-Christoffel conformal mapping method. This conformal mapping technique has been used to calculate slamming loads during water entry. The pile-up of water during motion is also considered and an alternative pile-up coefficient is assumed against Wagner’s generalized method. A simplified and accurate method is presented, which does not include non-linear terms and jet flow in the calculated pressure distribution on monotonically increasing 2D sections like wedge shapes. Comparison with real ship sections has been done to show accuracy of the results. Finally, a simple yet powerful method is obtained to aid the initial design stage of ships.

Study on dynamic mechanical properties and constitutive model description of Inconel718

In this study, the effects of strain rate and temperature on the flow stress of Inconel718 were analyzed by Split Hopkinson Pressure Bar (SHPB) experiment and quasi-static compression experiment. The classical JC constitutive model was established by combining the quasi-static compression experiment with the SHPB experiment. According to the effects of different grain sizes and [Formula: see text] phase on dislocation pile-up, the dislocation pile-up theory was introduced to modify the JC constitutive model. The modified constitutive model was compiled in FORTRAN language, and VUMAT user material subroutine was called and secondary development was carried out to establish the polycrystalline simulation model with different grain sizes. The uniaxial tensile and compression simulation process of polycrystal with different grain sizes was performed. Through comparing the simulation results with the experimental data. The correlation coefficient R, between the simulation and experimental values, is 0.97,981, and the average relative error is only 3.72%. The accuracy of the modified constitutive model was verified.