Order of Magnitude Beam Current Improvement in Compact Cyclotrons

There is great need for high intensity proton beams from compact particle accelerators in particle physics, medical isotope production, and materials- and energy-research. To this end, the DAE$\delta$ALUS/IsoDAR collaboration is developing a compact isochronous cyclotron that will be able to deliver 10 mA of protons - an order of magnitude higher than on-market compact cyclotrons and a factor four higher than research machines. For the first time, vortex motion is incorporated in the design of a cyclotron, which is key to reaching high extracted beam current. We present high-fidelity simulations of the acceleration of a 5 mA H$_2^+$ beam (equivalent to 10 mA of protons) in this cyclotron, using the particle-in-cell code OPAL, demonstrating the feasibility of constructing this machine. The simulations are based on the latest cyclotron design and through them, we show that sufficient turn separation between the $(\mathrm{N}-1)^{th}$ and $\mathrm{N}^{th}$ turn can be achieved even with initially mismatched beams by careful placement of collimators to scrape away halo particles before the beam energy has reached 1.5 MeV/amu. We describe in detail the process for placement of electrostatic extraction channels. Beam losses on the septa of these channels stay below 50 W with beam quality sufficient for transport to the target. Furthermore, we present an uncertainty quantification of select beam input parameters using machine learning, showing the robustness of the design.Comment: To be submitted to PR

An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models

Understanding the interactions between natural processes and human activities poses major challenges as it requires the integration of models and data across disparate disciplines. It typically takes many months and even years to create valid end-to-end simulations as different models need to be configured in consistent ways and generate data that is usable by other models. MINT is a novel framework for model integration that captures extensive knowledge about models and data and aims to automatically compose them together. MINT guides a user to pose a well-formed modeling question, select and configure appropriate models, find and prepare appropriate datasets, compose data and models into end-to-end workflows, run the simulations, and visualize the results. MINT currently includes hydrology, agriculture, and socioeconomic models.Office of the VP for Researc

Towards Continuous Scientific Data Analysis and Hypothesis Evolution

Scientific data is continuously generated throughout the world. However, analyses of these data are typically performed exactly once and on a small fragment of recently generated data. Ideally, data analysis would be a continuous process that uses all the data available at the time, and would be automatically re-run and updated when new data appears. We present a framework for automated discovery from data repositories that tests user-provided hypotheses using expert-grade data analysis strategies, and reassesses hypotheses when more data becomes available. Novel contributions of this approach include a framework to trigger new analyses appropriate for the available data through lines of inquiry that support progressive hypothesis evolution, and a representation of hypothesis revisions with provenance records that can be used to inspect the results. We implemented our approach in the DISK framework, and evaluated it using two scenarios from cancer multi-omics: 1) data for new patients becomes available over time, 2) new types of data for the same patients are released. We show that in all scenarios DISK updates the confidence on the original hypotheses as it automatically analyzes new data

Fatty acids regulate Thy-1 antigen mRNA stability in T lymphocyte precursors.

In this study, we report the effect of fatty acids on the Thy-1 antigen mRNA decay. Low serum and synthetic medium culture conditions were used to demonstrate that fatty acids, which are important metabolites involved as second messengers in signal transduction, also influence the steady-state mRNA level. Detailed analysis demonstrated that polyunsaturated lipids attached to bovine serum albumin, such as linoleic, linolenic, and arachidonic acids, modulate gene expression specifically in the S1A T lymphoma cell line by inducing a 3-5-fold increase in the steady-state Thy-1 mRNA level, concomitant with a twofold increase in cell surface expression. A similar modulation was observed in the immature CD4-CD8- T cell precursors but not in mature thymocytes. Nuclear run-on and transfection experiments indicated that the observed Thy-1 mRNA level is post-transcriptionally regulated and that the presence of the coding region is sufficient for this adaptive response. A mechanism without a requirement for protein kinase C activation, but involving Ca2+ entry, could account for this difference in Thy-1 mRNA stability

Search for intermediate mass black hole binaries in the first observing run of Advanced LIGO

International audienceDuring their first observational run, the two Advanced LIGO detectors attained an unprecedented sensitivity, resulting in the first direct detections of gravitational-wave signals produced by stellar-mass binary black hole systems. This paper reports on an all-sky search for gravitational waves (GWs) from merging intermediate mass black hole binaries (IMBHBs). The combined results from two independent search techniques were used in this study: the first employs a matched-filter algorithm that uses a bank of filters covering the GW signal parameter space, while the second is a generic search for GW transients (bursts). No GWs from IMBHBs were detected; therefore, we constrain the rate of several classes of IMBHB mergers. The most stringent limit is obtained for black holes of individual mass 100  M⊙, with spins aligned with the binary orbital angular momentum. For such systems, the merger rate is constrained to be less than 0.93  Gpc−3 yr−1 in comoving units at the 90% confidence level, an improvement of nearly 2 orders of magnitude over previous upper limits