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The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells. Here we propose a vision of leveraging advances in AI to construct virtual cells, high-fidelity simulations of cells and cellular systems under different conditions that are directly learned from biological data across measurements and scales. We discuss desired capabilities of such AI Virtual Cells, including generating universal representations of biological entities across scales, and facilitating interpretable in silico experiments to predict and understand their behavior using virtual instruments. We further address the challenges, opportunities and requirements to realize this vision including data needs, evaluation strategies, and community standards and engagement to ensure biological accuracy and broad utility. We envision a future where AI Virtual Cells help identify new drug targets, predict cellular responses to perturbations, as well as scale hypothesis exploration. With open science collaborations across the biomedical ecosystem that includes academia, philanthropy, and the biopharma and AI industries, a comprehensive predictive understanding of cell mechanisms and interactions has come into reach.

The increase over the last years of the testing activities related to quantum systems, SRF cavities for the PIP-II and the LCLS-II projects, as well as superconducting magnets for the HL-LHC project and Fusion research activities, has required the addition of a new Helium cryogenic plant into the existing IB-1 Industrial Cryogenic Test Facility. The new cryogenic plant is composed of a cryogenic liquefier (Cold Box) able to provide up to 340 L/h, a 4 kL Dewar and two Mycom compressors providing up to 120 g/s. AL-AT (Air Liquide Advanced Technologies) has taken part of this project by designing and manufacturing the cryogenic liquefier. This new cryogenic plant is connected through a cryogenic distribution system to a 10 kL Dewar, which is part of the existing cryogenic test facility, itself composed of another Cold Box and a Sullair compressor. The new cryogenic plant has two main operating modes: one allows to transfer liquid helium at 1.7 bar between the two Dewars, the other allows to transfer supercritical Helium at 2 bar or more between the new Cold Box and the 10 kL Dewar. The entire industrial cryogenic facility is handled by a common Inventory Control System, composed of three control valves, and 9 tanks giving a total buffer volume of more than 1000 m3. This paper presents the technical features of the new Helium cryogenic plant, as well as the main results of the liquefier commissioning phase and details of the helium transfer between the two Dewars, making the connection between the cryogenic plants at the IB-1 Industrial Cryogenic Test Facility., Comment: Cryogenic Eng Conf and Intnl Cryo Materials Conf (CEC/ICMC 2023)

Employing the functional renormalization group approach at next-to-leading order of the derivative expansion, we refine our earlier findings for the location of the Yang-Lee edge singularity in classic O(N) universality classes. For the universality classes of interest to QCD, in three dimensions, we found $|z_c|/R_\chi^{1/\gamma} = 1.612(9),\ 1.597(3)$ for $N=2$, $4$ correspondingly. We also established $|z_c| = 2.04(8),\ 1.69(3)$ for $N=2$, $4$ albeit with greater systematic error., Comment: 36 pages; 6 figures; version accepted for publication

The Earth system is accumulating energy due to human-induced activities. More than 90 percent of this energy has been stored in the ocean as heat since 1970, with about 64 percent of that in the upper 700 m. Differences in upper ocean heat content anomaly (OHCA) estimates, however, exist. Here, we evaluate spread in upper OHCA estimates arising from choices in instrumental bias corrections and mapping methods, in addition to the effect of using a common ocean mask. The same dataset was mapped by six research groups for 1970 to 2008, with six instrumental bias corrections applied to expendable bathythermograph (XBT) data. We find that use of a common ocean mask may impact estimation of global OHCA by +- 13 percent. Uncertainty due to mapping method dominates over XBT bias correction at a global scale and is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Uncertainty due to XBT bias correction is largest in the Pacific Ocean within 30N to 30S. In both mapping and XBT cases, spread is higher since the 1990s. Important differences in spatial trends among mapping methods are found in the well-observed Northwest Atlantic and the poorly-observed Southern Ocean. Although our results cannot identify the best mapping or bias correction schemes, they identify where and when greater uncertainties exist, and so where further refinements may yield the largest improvements. Our results highlight the need for a future international coordination to evaluate performance of existing mapping methods., Comment: Submitted to AMS Journal of Climate (30 July 2020). Feedback welcome. Please email: abhishek.abhisheksavita@utas.edu.au

We determine a previously unknown universal quantity, the location of the Yang-Lee edge singularity for the O($N$) theories in a wide range of $N$ and various dimensions. At large $N$, we reproduce the $N\to\infty$ analytical result on the location of the singularity and, additionally, we obtain the mean-field result for the location in $d=4$ dimensions. In order to capture the nonperturbative physics for arbitrary $N$, $d$ and complex-valued external fields, we use the functional renormalization group approach., Comment: 6 pages, 2 figures; version accepted for publication in PRL

Recent lattice QCD calculations show strong indications that the crossover of QCD at zero baryon chemical potential ($\mu_B$) is a remnant of the second order chiral phase transition. The non-universal parameters needed to map temperature $T$ and $\mu_B$ to the universal properties of the second order chiral phase transition were determined by lattice QCD calculations. Motivated by these advances, first, we discuss the analytic structure of the partition function -- the so-called Yang-Lee edge singularity -- in the QCD crossover regime, solely based on universal properties. Then, utilizing the lattice calculated non-universal parameters, we map this singularity to the real $T$ and complex $\mu_B$ plane, in order to find the radius of convergence for a Taylor series expansion of QCD partition function around $\mu_B=0$ in the QCD crossover regime. Our most important findings are: (i) An universality-based estimate of the radius of convergence around $\mu_B=0$; (ii) Universality and lattice QCD based constraints on the location of the QCD critical point in the $T-\mu_B$ plane., Comment: Quark Matter 2019 Conference Proceedings; Submitted to Nuclear Physics A

In this perspective, we examine three key aspects of an end-to-end pipeline for realistic cellular simulations: reconstruction and segmentation of cellular structures; generation of cellular structures; and mesh generation, simulation, and data analysis. We highlight some of the relevant prior work in these distinct but overlapping areas, with a particular emphasis on current use of machine learning technologies, as well as on future opportunities.