The Abacus Cosmos: A Suite of Cosmological N-body Simulations

We present a public data release of halo catalogs from a suite of 125 cosmological $N$-body simulations from the Abacus project. The simulations span 40 $w$CDM cosmologies centered on the Planck 2015 cosmology at two mass resolutions, $4\times 10^{10}\;h^{-1}M_\odot$ and $1\times 10^{10}\;h^{-1}M_\odot$, in $1.1\;h^{-1}\mathrm{Gpc}$ and $720\;h^{-1}\mathrm{Mpc}$ boxes, respectively. The boxes are phase-matched to suppress sample variance and isolate cosmology dependence. Additional volume is available via 16 boxes of fixed cosmology and varied phase; a few boxes of single-parameter excursions from Planck 2015 are also provided. Catalogs spanning $z=1.5$ to $0.1$ are available for friends-of-friends and Rockstar halo finders and include particle subsamples. All data products are available at https://lgarrison.github.io/AbacusCosmosComment: 13 pages, 9 figures, 3 tables. Additional figures added for mass resolution convergence tests, and additional redshifts added for existing tests. Matches ApJS accepted versio

Energy Management of Hybrid Electric Urban Bus by Off-Line Dynamic Programming Optimization and One-Step Look-Ahead Rollout

[EN] Due to the growing air quality concern in urban areas and rising fuel prices, urban bus fleets are progressively turning to hybrid electric vehicles (HEVs) which show higher efficiency and lower emissions in comparison with conventional vehicles. HEVs can reduce fuel consumption and emissions by combining different energy sources (i.e., fuel and batteries). In this sense, the performance of HEVs is strongly dependent on the energy management strategy (EMS) which coordinates the energy sources available to exploit their potential. While most EMSs are calibrated for general driving conditions, this paper proposes to adapt the EMS to the specific driving conditions on a particular bus route. The proposed algorithm relies on the fact that partial information on the driving cycle can be assumed since, in the case of a urban bus, the considered route is periodically covered. According to this hypothesis, the strategy presented in this paper is based on estimating the driving cycle from a previous trip of the bus in the considered route. This initial driving cycle is used to compute the theoretical optimal solution by dynamic programming. The obtained control policy (particularly the cost-to-go matrix) is stored and used in the subsequent driving cycles by applying one-step look-ahead roll out, then, adapting the EMS to the actual driving conditions but exploiting the similarities with previous cycles in the same route. To justify the proposed strategy, the paper discusses the common patterns in different driving cycles of the same bus route, pointing out several metrics that show how a single cycle captures most of the key parameters for EMS optimization. Then, the proposed algorithm (off-line dynamic programming optimization and one-step look-ahead rollout) is described. Results obtained by simulation show that the proposed method is able to keep the battery charge within the required range and achieve near-optimal performance, with only a 1.9% increase in fuel consumption with regards to the theoretical optimum. As a reference for comparison, the equivalent consumption minimization strategy (ECMS), which is the most widespread algorithm for HEV energy management, produces an increase in fuel consumption with respect to the optimal solution of 11%.This research was funded by Ministerio de Ciencia e Innovacion, through the Proyectos I+D+i 2020 Program, grant number PID2020-119691RB-I00.Tormos, B.; Pla Moreno, B.; Bares-Moreno, P.; Pinto, D. (2022). Energy Management of Hybrid Electric Urban Bus by Off-Line Dynamic Programming Optimization and One-Step Look-Ahead Rollout. Applied Sciences. 12(9):1-19. https://doi.org/10.3390/app1209447411912

Multi-Wavelength Photobiomodulation Therapy Combined with Static Magnetic Field on Long-Term Pulmonary Complication after COVID-19: A Case Report

Introduction: Photobiomodulation therapy, alone (PBMT) or combined with a static magnetic field (PBMT-sMF), has been demonstrated to be effective in the regeneration of tissues, modulation of inflammatory processes, and improvement in functional capacity. However, the effects of PBMT-sMF on the pulmonary system and COVID-19 patients remain scarce. Therefore, in this case report, we demonstrated the use of PBMT-sMF for peripheral oxygen saturation, pulmonary function, massive lung damage, and fibrosis as a pulmonary complication after COVID-19. Case report: A 53-year-old Mexican man who presented with decreased peripheral oxygen saturation, massive lung damage, and fibrosis after COVID-19 received PBMT-sMF treatment once a day for 45 days. The treatment was irradiated at six sites in the lower thorax and upper abdominal cavity and two sites in the neck area. We observed that the patient was able to leave the oxygen support during the treatment, and increase his peripheral oxygen saturation. In addition, the patient showed improvements in pulmonary severity scores and radiological findings. Finally, the patient presented with normal respiratory mechanics parameters in the medium-term, indicating total pulmonary recovery. Conclusions: The use of PBMT-sMF may potentially lead to safe treatment of and recovery from pulmonary complications after COVID-19, with regard to the structural and functional aspects.publishedVersio

Simulating noisy quantum channels via quantum state preparation algorithms

In Refs. [Phys. Rev. A 96, 062303 (2017)] and [Sci. China Phys. Mech. Astron. 61, 70311 (2018)], the authors reported an algorithm to simulate, in a circuit-based quantum computer, a general quantum channel (QC). However, the application of their algorithm involves the solution of intricate non-linear systems of equations in order to obtain the quantum circuit to be implemented for the simulation. In this work, we identify and discuss a simple way to implement the simulation of QCs on any $d$-level quantum system through quantum state preparation algorithms. We exemplify the simplicity and versatility of our protocol considering most well known qubit QCs, some qudit QCs, and the effect of Lorentz transformations on spin states. We also deal with the application of our protocol for initial mixed states. Most of the given application examples are verified experimentally using IBM's quantum processors

Continuous bioprocessing and process analytical technologies: A path towards quality by design

Recent success in monoclonal antibody based immuno-oncology therapeutics such as Keytruda® has initiated a revolution within the Biopharmaceutical Industry. Development efforts to support this class of molecules include single-use technology, continuous production, process analytical technology (PAT), information technology (IT), multivariate data analysis (MVDA), and efforts towards real time release testing (RTRT). Merck’s vision for a next-generation large molecule production facility aligns with these six key principles, as demonstrated by the construction of a continuous monoclonal antibody (mAb) production pilot plant named the Protein Refinery Operations lab (PROLab) within Merck Bioprocess Development. Quality-by-Design (QbD) principles are maturing for the development of standard batch-based therapeutic protein manufacturing processes. Outside of the insight gained through similar techniques applied to unit operations run in a continuous mode, similar approaches for the dependencies created by connected and continuous processes are still in their infancy. Previously, a methodology for characterizing holistic downstream process performance through real time perturbation analysis, where the response to an upstream stimulus is monitored at several unit operations simultaneously was presented to start applying QbD principles to continuous bioprocessing. Here, the authors build upon the concept of perturbation analysis by presenting case studies where advanced PAT tools have been embedded in PROLab operation. At-line and off-line process and product quality data from continuous upstream and downstream production will be presented over the course of long term perfusion cell culture with variable production rates. Specific emphasis will be placed on the performance of bioreactor cell retention and clarification trains, and post-chromatographic ultrafiltration unit operations. This process understanding can then be utilized to place PAT tools at the appropriate locations in the process to achieve product attribute control and ultimately to assure uninterrupted supply of therapeutic proteins to patient