RADYNVERSION: Learning to Invert a Solar Flare Atmosphere with Invertible Neural Networks

During a solar flare, it is believed that reconnection takes place in the corona followed by fast energy transport to the chromosphere. The resulting intense heating strongly disturbs the chromospheric structure, and induces complex radiation hydrodynamic effects. Interpreting the physics of the flaring solar atmosphere is one of the most challenging tasks in solar physics. Here we present a novel deep learning approach, an invertible neural network, to understanding the chromospheric physics of a flaring solar atmosphere via the inversion of observed solar line profiles in H{\alpha} and Ca II {\lambda}8542. Our network is trained using flare simulations from the 1D radiation hydrodynamics code RADYN as the expected atmosphere and line profile. This model is then applied to single pixels from an observation of an M1.1 solar flare taken with SST/CRISP instrument just after the flare onset. The inverted atmospheres obtained from observations provide physical information on the electron number density, temperature and bulk velocity flow of the plasma throughout the solar atmosphere ranging from 0-10 Mm in height. The density and temperature profiles appear consistent with the expected atmospheric response, and the bulk plasma velocity provides the gradients needed to produce the broad spectral lines whilst also predicting the expected chromospheric evaporation from flare heating. We conclude that we have taught our novel algorithm the physics of a solar flare according to RADYN and that this can be confidently used for the analysis of flare data taken in these two wavelengths. This algorithm can also be adapted for a menagerie of inverse problems providing extremely fast ($\sim$10 {\mu}s) inversion samples.Comment: Published in Ap

Market-to-Revenue Multiples in Public and Private Capital Markets

The behavior and determinants of market-to-revenue ratios in public and private capital markets is examined. Three samples are analysed: (1) all publicly traded stocks listed at some time on the New York Stock Exchange/American Stock Exchange/National Association of Securities Dealers Automated Quotation System in the 1980—2004 period; (2) sample of over 300 so-called ‘internet companies’ in the 1996—2004 period; and (3) over 5500 privately held venture capital-backed companies in the 1992—2004 period. Both company size and the most recent revenue growth rate are found to explain significant variation across companies in their market-to-revenue multiples — smaller companies and companies with higher recent revenue growth rates have higher multiples. We also document how the capital market appears to use a broad-based information set when setting market-to-revenue multiples for companies with negative revenue growth rates — transitory revenue growth components appear to be identified (in a probabilistic sense) by the capital market. Contrary to much anecdotal comment, we present evidence that the capital market behaved directionally along the lines predicted by capital market theory in the pricing of internet stocks in the 1996—2004 period

Biases in Multi-Year Management Financial Forecasts: Evidence From Private Venture-Backed U.S. Companies

This paper studies the properties and determinants of managers’ multi-year financial forecasts. Using one- to five-year-ahead forecasts reported by private venture-backed firms, we ask whether, by how much, and why biases in managers’ forecasts of revenues, expenses and profits depend on the forecasting horizon and the verifiability of assets. We find that profitability forecasts contain a strategic component, in that [1] one-year-ahead revenue (expense) forecasts are slightly and asymmetrically pessimistic (optimistic), while five-year-ahead forecasts are hugely and asymmetrically optimistic (pessimistic); and [2] biases in revenue and expense forecasts are larger, the harder to verify or more intangible-intensive are firms’ assets

Generating analysis topology using virtual topology operators

AbstractVirtual topology operations have been utilized to generate an analysis topology definition suitable for downstream mesh generation. Detailed descriptions are provided for virtual topology merge and split operations for all topological entities, where virtual decompositions are robustly linked to the underlying geometry. Current virtual topology technology is extended to allow the virtual partitioning of volume cells. A valid description of the topology, including relative orientations, is maintained which enables downstream interrogations to be performed on the analysis topology description, such as determining if a specific meshing strategy can be applied to the virtual volume cells. As the virtual representation is a true non-manifold description of the sub-divided domain the interfaces between cells are recorded automatically. Therefore, the advantages of non-manifold modelling are exploited within the manifold modelling environment of a major commercial CAD system without any adaptation of the underlying CAD model. A hierarchical virtual structure is maintained where virtual entities are merged or partitioned. This has a major benefit over existing solutions as the virtual dependencies here are stored in an open and accessible manner, providing the analyst with the freedom to create, modify and edit the analysis topology in any preferred sequence

Novel multi-marker proteomics in phenotypically matched patients with ST-segment myocardial infarction:association with clinical outcomes

Early prediction of significant morbidity or mortality in patients with acute ST-segment elevation myocardial infarction (STEMI) represents an unmet clinical need. In phenotypically matched population of 139 STEMI patients (72 cases, 67 controls) treated with primary percutaneous coronary intervention, we explored associations between a 24-h relative change from baseline in the concentration of 91 novel biomarkers and the composite outcome of death, heart failure, or shock within 90 days. Additionally, we used random forest models to predict the 90-day outcomes. After adjustment for false discovery rate, the 90-day composite was significantly associated with concentration changes in 14 biomarkers involved in various pathophysiologic processes including: myocardial fibrosis/remodeling (collagen alpha-1, cathepsin Z, metalloproteinase inhibitor 4, protein tyrosine phosphatase subunits), inflammation, angiogenesis and signaling (interleukin 1 and 2 subunits, growth differentiation factor 15, galectin 4, trefoil factor 3), bone/mineral metabolism (osteoprotegerin, matrix extracellular phosphoglycoprotein and tartrate-resistant acid phosphatase), thrombosis (tissue factor pathway inhibitor) and cholesterol metabolism (LDL-receptor). Random forest models suggested an independent association when inflammatory markers are included in models predicting the outcomes within 90 days. Substantial heterogeneity is apparent in the early proteomic responses among patients with acutely reperfused STEMI patients who develop death, heart failure or shock within 90 days. These findings suggest the need to consider synergistic multi-biomarker strategies for risk stratification and to inform future development of novel post-myocardial infarction therapies

Imaging Coral I: Imaging Coral Habitats with the SeaBED AUV

The SeaBED autonomous underwater vehicle (AUV) is a new imaging platform designed for high resolution optical and acoustic sensing. This low cost vehicle has been specifically designed for use in waters up to 2000 m to carry out video transects, bathymetric and side-scan sonar surveys. In this paper we detail the systems issues associated with navigation, control, and imaging that led us to our particular hardware and software design choices so as to allow us to operate in shallow, shelf and ocean basin environments. We illustrate the strengths of our design with data obtained during two research cruises associated with mapping coral reefs off Puerto Rico and Bermuda. In both these cases, SeaBED was deployed in extremely challenging terrain associated off the shelf edge and was successful in returning high quality color imagery of deep coral habitats.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86034/1/hsingh-34.pd

Resistance to the antimicrobial agent fosmidomycin and an FR900098 prodrug through mutations in the deoxyxylulose phosphate reductoisomerase gene (dxr)

There is a pressing need for new antimicrobial therapies to combat globally important drug-resistant human pathogens, including Plasmodium falciparum malarial parasites, Mycobacterium tuberculosis, and Gram-negative bacteria, including Escherichia coli. These organisms all possess the essential methylerythritol phosphate (MEP) pathway of isoprenoid biosynthesis, which is not found in humans. The first dedicated enzyme of the MEP pathway, 1-deoxy-d-xylulose 5-phosphate reductoisomerase (Dxr), is inhibited by the phosphonic acid antibiotic fosmidomycin and its analogs, including the N-acetyl analog FR900098 and the phosphoryl analog fosfoxacin. In order to identify mutations in dxr that confer resistance to these drugs, a library of E. coli dxr mutants was screened at lethal fosmidomycin doses. The most resistant allele (with the S222T mutation) alters the fosmidomycin-binding site of Dxr. The expression of this resistant allele increases bacterial resistance to fosmidomycin and other fosmidomycin analogs by 10-fold. These observations confirm that the primary cellular target of fosmidomycin is Dxr. Furthermore, cell lines expressing Dxr-S222T will be a powerful tool to confirm the mechanisms of action of future fosmidomycin analogs

Proteostasis by STUB1/HSP70 complex controls sensitivity to androgen receptor targeted therapy in advanced prostate cancer.

Protein homeostasis (proteostasis) is a potential mechanism that contributes to cancer cell survival and drug resistance. Constitutively active androgen receptor (AR) variants confer anti-androgen resistance in advanced prostate cancer. However, the role of proteostasis involved in next generation anti-androgen resistance and the mechanisms of AR variant regulation are poorly defined. Here we show that the ubiquitin-proteasome-system (UPS) is suppressed in enzalutamide/abiraterone resistant prostate cancer. AR/AR-V7 proteostasis requires the interaction of E3 ubiquitin ligase STUB1 and HSP70 complex. STUB1 disassociates AR/AR-V7 from HSP70, leading to AR/AR-V7 ubiquitination and degradation. Inhibition of HSP70 significantly inhibits prostate tumor growth and improves enzalutamide/abiraterone treatments through AR/AR-V7 suppression. Clinically, HSP70 expression is upregulated and correlated with AR/AR-V7 levels in high Gleason score prostate tumors. Our results reveal a novel mechanism of anti-androgen resistance via UPS alteration which could be targeted through inhibition of HSP70 to reduce AR-V7 expression and overcome resistance to AR-targeted therapies

Extending the Ehresmann-Schein-Nambooripad Theorem

We extend the `join-premorphisms' part of the Ehresmann-Schein-Nambooripad Theorem to the case of two-sided restriction semigroups and inductive categories, following on from a result of Lawson (1991) for the `morphisms' part. However, it is so-called `meet-premorphisms' which have proved useful in recent years in the study of partial actions. We therefore obtain an Ehresmann-Schein-Nambooripad-type theorem for meet-premorphisms in the case of two-sided restriction semigroups and inductive categories. As a corollary, we obtain such a theorem in the inverse case.Comment: 23 pages; final section on Szendrei expansions removed; further reordering of materia