The Formation of Rapidly Rotating Black Holes in High Mass X-ray Binaries

High mass X-ray binaries (HMXRBs) like Cygnus X-1, host some of the most rapidly spinning black holes (BHs) known to date, reaching spin parameters $a \gtrsim 0.84$. However, there are several effects that can severely limit the maximum BH spin parameter that could be obtained from direct collapse, such as tidal synchronization, magnetic core-envelope coupling and mass loss. Here we propose an alternative scenario where the BH is produced by a {\it failed} supernova (SN) explosion that is unable to unbind the stellar progenitor. A large amount of fallback material ensues, whose interaction with the secondary naturally increases its overall angular momentum content, and therefore, the spin of the BH when accreted. Through SPH hydrodynamic simulations, we studied the unsuccessful explosion of a $8M_{\odot }$ pre-SN star in a close binary with a $12M_{\odot}$ companion with an orbital period of $\approx1.2$ days, finding that it is possible to obtain a BH with a high spin parameter $a\gtrsim0.8$ even when the expected spin parameter from direct collapse is $a \lesssim 0.3$. This scenario also naturally explains the atmospheric metal pollution observed in HMXRB stellar companions.Comment: 6 pages, 4 figure

Pulay forces from localized orbitals optimized in situ using a psinc basis set

In situoptimization of a set of localized orbitals with respect to a systematically improvable basis set independent of the position of the atoms, such as psinc functions, would theoretically eliminate the correction due to Pulay forces from the total ionic forces. We demonstrate that for strict localization constraints, especially with small localization regions, there can be non-negligible Pulay forces that must be calculated as a correction to the Hellmann-Feynman forces in the ground state. Geometry optimization calculations, which rely heavily upon accurate evaluation of the total ionic forces, show much better convergence when Pulay forces are included. The more conventional case, where the local orbitals remain fixed to pseudo-atomic orbital multiple-ζ basis sets, also benefits from this implementation. We have validated the method on several test cases, including a DNA fragment with 1045 atoms

Entrepreneurial Responses to the COVID Era: A Qualitative Study of Five ProfessionalMusic Entrepreneurs

The impact of COVID-19 has affected not only private citizens, but also arts entrepreneurship professionalsand their respective business models. To explore both the problems experienced by professional musicentrepreneurs and their solutions for navigating company survivability, growth and impact, a multiple-case qualitative research study using intensity sampling and grounded theory was conducted to uncoverhow professional music entrepreneurs (N = 5) succeeded in not only surviving the pandemic’s effects on their personal businesses, but also in augmenting their companies’ finances, resources and impact withinthe constructs of a post-COVID multimodal creative economy. The results present various themes andsuggestions for implementation within music (and arts) entrepreneurship practice and education

A desorption model for the code SOLIDUSS and its experimental benchmarking

Acknowledgements The experiments reported in this document could be carried out thanks to the assistance of numerous colleagues at CERN. In particular, the authors would like to express their gratitude to Guilherme Correia, Karl Johnston, Juliana Schell, Sebastian Rothe, Jochen Ballof, Thierry Stora, Joachim Vollaire, Reiner Geyer, Yann Pira, Lucie Vitkova, Alexandre Dorsival, Nabil Menaa, Aurore Boscher, Giuseppe Prete, Renaud Charousset and Miranda Van Stenis.The code SOLIDUSS is a Monte Carlo based solid-state diffusion software for radiation protection. It was developed to accurately estimate the amount of radionuclides that could escape activated material affected by an accidental fire. A desorption model based on the computation of the desorption probability of those radionuclides reaching the surface of an object was introduced to upgrade the software, proven to be a significant improvement with respect to earlier stages of the code. A set of experiments was performed at CERN to estimate the out-diffusion of radionuclides from activated materials typically used in accelerator environments when exposed to high temperatures. In particular, a 49.3 µm thick Cu foil containing 60Co and a 94 µm thick Al foil with 22Na were exposed to approximately 1000 °C and 600 °C respectively for different time periods. Out-diffusion fractions of 1.5 5.5% for 60Co after 5 h and 22.5 3.1% for 22Na after 4 h were obtained. A set of SOLIDUSS simulations was carried out replicating the experimental setup and using literature diffusion and desorption activation parameters. The results obtained are in good agreement with the experimental data within error bars. A high sensitivity of the simulation results to changes in the input parameters was observed

Towards self-attention based visual navigation in the real world

Vision guided navigation requires processing complex visual information to inform task-orientated decisions. Applications include autonomous robots, self-driving cars, and assistive vision for humans. A key element is the extraction and selection of relevant features in pixel space upon which to base action choices, for which Machine Learning techniques are well suited. However, Deep Reinforcement Learning agents trained in simulation often exhibit unsatisfactory results when deployed in the real-world due to perceptual differences known as the $\textit{reality gap}$. An approach that is yet to be explored to bridge this gap is self-attention. In this paper we (1) perform a systematic exploration of the hyperparameter space for self-attention based navigation of 3D environments and qualitatively appraise behaviour observed from different hyperparameter sets, including their ability to generalise; (2) present strategies to improve the agents' generalisation abilities and navigation behaviour; and (3) show how models trained in simulation are capable of processing real world images meaningfully in real time. To our knowledge, this is the first demonstration of a self-attention based agent successfully trained in navigating a 3D action space, using less than 4000 parameters.Comment: Submitted to The 2022 Australian Conference on Robotics and Automation (ACRA 2022

Design of a Soil Cutting Resistance Sensor for Application in Site-Specific Tillage

One objective of precision agriculture is to provide accurate information about soil and crop properties to optimize the management of agricultural inputs to meet site-specific needs. This paper describes the development of a sensor equipped with RTK-GPS technology that continuously and efficiently measures soil cutting resistance at various depths while traversing the field. Laboratory and preliminary field tests verified the accuracy of this prototype soil strength sensor. The data obtained using a hand-operated soil cone penetrometer was used to evaluate this field soil compaction depth profile sensor. To date, this sensor has only been tested in one field under one gravimetric water content condition. This field test revealed that the relationships between the soil strength profile sensor (SSPS) cutting force and soil cone index values are assumed to be quadratic for the various depths considered: 0–10, 10–20 and 20–30 cm (r2 = 0.58, 0.45 and 0.54, respectively). Soil resistance contour maps illustrated its practical value. The developed sensor provides accurate, timely and affordable information on soil properties to optimize resources and improve agricultural economyMinistry of Science and Innovation RTA2006-00058-C03-0