Chirality transfer & chiral turbulence in gauge theories

Chirality transfer between fermions and gauge fields plays a crucial role for understanding the dynamics of anomalous transport phenomena such as the Chiral Magnetic Effect. In this proceeding we present a first principles study of these processes based on classical-statistical real-time lattice simulations of strongly coupled QED $(e^2N_f=64)$. Our simulations demonstrate that a chirality imbalance in the fermion sector triggers chiral plasma instabilities in the gauge field sector, which ultimately lead to the generation of long range helical magnetic fields via a self-similar turbulent cascade of the magnetic helicity.Comment: Quark Matter 2019 conference proceedin

Spectral function of fermions in a highly occupied non-Abelian plasma

We develop a method to obtain fermion spectral functions non-perturbatively in a non-Abelian gauge theory with high occupation numbers of gauge fields. After recovering the free field case, we extract the spectral function of fermions in a highly occupied non-Abelian plasma close to its non-thermal fixed point, i.e., in a self-similar regime of the non-equilibrium dynamics. We find good agreement with hard loop perturbation theory for medium-induced masses, dispersion relations and quasiparticle residues. We also extract the full momentum dependence of the damping rate of the collective excitations. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP(3).Peer reviewe

No DNN Left Behind: Improving Inference in the Cloud with Multi-Tenancy

With the rise of machine learning, inference on deep neural networks (DNNs) has become a core building block on the critical path for many cloud applications. Applications today rely on isolated ad-hoc deployments that force users to compromise on consistent latency, elasticity, or cost-efficiency, depending on workload characteristics. We propose to elevate DNN inference to be a first class cloud primitive provided by a shared multi-tenant system, akin to cloud storage, and cloud databases. A shared system enables cost-efficient operation with consistent performance across the full spectrum of workloads. We argue that DNN inference is an ideal candidate for a multi-tenant system because of its narrow and well-defined interface and predictable resource requirements

Ectopic Sequestered Thyroid Tissue: An Unusual Cause of a Mediastinal Mass

An 80-year-old female presented with an incidental finding of a retrosternal mass on magnetic resonance imaging. Ultrasound demonstrated a mediastinal lesion adjacent to but separate from the inferior pole of the right thyroid lobe. Fine needle aspiration cytology demonstrated colloid and follicular cells. At surgery, the right thyroid lobe was found to be normal. A discrete 5 cm nodule was found in the anterior mediastinum separate from the thyroid and just anterior and to the right of the trachea and thymus. The nodule had a vascular pedicle arising from the mediastinum. The differential diagnosis included metastatic thyroid carcinoma. Histology was consistent with a benign ectopic sequestered thyroid nodule. Extensive investigations demonstrated no sign of a thyroid malignancy

Biomaterials and Fabrication to Optimise Scaffold Properties for Musculoskeletal Tissue Engineering.

Tissue engineering has emerged as a promising scientific field potentially yielding in vitro developed tissue to replace degenerative or injured tissues in vivo, thus avoiding the donor site morbidity associated with reconstructive surgery. Integral to the process is the role of scaffolds and the biomaterials used to form them. This review explores the concept of scaffold based tissue engineering and design considerations. The scaffold needs to have certain mechanical and architectural properties, it needs to be biocompatible and biodegradable, and allow combination with bioactive molecules. We also discuss scaffolding techniques, different biomaterial options and fabrication technologies, and future areas of development.This is the author accepted manuscript. The final version is available from Bentham Science via http://dx.doi.org/10.2174/1574888X1166616061410103