Computational modelling and experimental characterisation of heterogeneous materials

Heterogeneous materials can exhibit behaviour under load that cannot be described by classical continuum elasticity. Beams in bending can show a relative stiffening as the beam depth tends to zero, a size effect. Size effects are recognised in higher order continuum elastic theories such as micropolar elasticity. The drawback of higher order theories is the requirement of addition constitutive relations and associated properties that are often difficult to establish experimentally. Furthermore the finite element method, of great benefit in classical elasticity, has shown limitations when applied to micropolar elasticity. The determination of additional constitutive properties and the computational modelling of micropolar elasticity will be discussed in the context of a model heterogeneous material loaded in simple 3 point bending. The model material was created by drilling holes in aluminium bar in a regular pattern, with the hole axis normal to the plane of bending. The bending tests show that a size effect is present. These results are compared against modelling the detailed beam geometries in the finite element package ANSYS, which again shows the size effect. These two bending test are used to extract the additional micropolar elastic material properties. A comparison is then made against analytical solutions,numerical solutions using a micropolar beam finite element and a micropolar plane stress control volume method.It will be shown that the need for extensive experimental testing to determine the additional constitutive properties may not be necessary with the appropriate use of numerical methods

Reassessment of the NuTeV determination of the Weinberg angle

In light of the recent discovery of the importance of the isovector EMC effect for the interpretation of the NuTeV determination of sin^2 theta_W, it seems timely to reassess the central value and the errors on this fundamental Standard Model parameter derived from the NuTeV data. We also include earlier work on charge symmetry violation and the recent limits on a possible asymmetry between s and \bar{s} quarks. With these corrections we find a revised NuTeV result of sin^2 theta_W = 0.2232 \pm 0.0013(stat) \pm 0.0024(syst), which is in excellent agreement with the running of sin^2 theta_W predicted by the Standard Model.Comment: 4 pages, one figur

Phenotypic and Functional Separation of Memory and Effector Human CD8+ T Cells

Human CD8+ memory- and effector-type T cells are poorly defined. We show here that, next to a naive compartment, two discrete primed subpopulations can be found within the circulating human CD8+ T cell subset. First, CD45RA−CD45R0+ cells are reminiscent of memory-type T cells in that they express elevated levels of CD95 (Fas) and the integrin family members CD11a, CD18, CD29, CD49d, and CD49e, compared to naive CD8+ T cells, and are able to secrete not only interleukin (IL) 2 but also interferon γ, tumor necrosis factor α, and IL-4. This subset does not exert cytolytic activity without prior in vitro stimulation but does contain virus-specific cytotoxic T lymphocyte (CTL) precursors. A second primed population is characterized by CD45RA expression with concomitant absence of expression of the costimulatory molecules CD27 and CD28. The CD8+CD45RA+CD27− population contains T cells expressing high levels of CD11a, CD11b, CD18, and CD49d, whereas CD62L (L-selectin) is not expressed. These T cells do not secrete IL-2 or -4 but can produce IFN-γ and TNF-α. In accordance with this finding, cells contained within this subpopulation depend for proliferation on exogenous growth factors such as IL-2 and -15. Interestingly, CD8+CD45RA+CD27− cells parallel effector CTLs, as they abundantly express Fas-ligand mRNA, contain perforin and granzyme B, and have high cytolytic activity without in vitro prestimulation. Based on both phenotypic and functional properties, we conclude that memory- and effector-type T cells can be separated as distinct entities within the human CD8+ T cell subset

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

The DUNE far detector vertical drift technology. Technical design report

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease