Measuring and calibrating Galactic synchrotron emission

Our position inside the Galaxy requires all-sky surveys to reveal its large-scale properties. The zero-level calibration of all-sky surveys differs from standard 'relative' measurements, where a source is measured in respect to its surroundings. All-sky surveys aim to include emission structures of all angular scales exceeding their angular resolution including isotropic emission components. Synchrotron radiation is the dominating emission process in the Galaxy up to frequencies of a few GHz, where numerous ground based surveys of the total intensity up to 1.4 GHz exist. Its polarization properties were just recently mapped for the entire sky at 1.4 GHz. All-sky total intensity and linear polarization maps from WMAP for frequencies of 23 GHz and higher became available and complement existing sky maps. Galactic plane surveys have higher angular resolution using large single-dish or synthesis telescopes. Polarized diffuse emission shows structures with no relation to total intensity emission resulting from Faraday rotation effects in the interstellar medium. The interpretation of these polarization structures critically depends on a correct setting of the absolute zero-level in Stokes U and Q.Comment: 10 pages, 8 figures. To be published in "Cosmic Magnetic Fields: From Planets, to Stars and Galaxies", K.G. Strassmeier, A.G. Kosovichev & J.E. Beckman, eds., Proc. IAU Symp. 259, CU

A model of diffuse Galactic Radio Emission from 10 MHz to 100 GHz

Understanding diffuse Galactic radio emission is interesting both in its own right and for minimizing foreground contamination of cosmological measurements. Cosmic Microwave Background experiments have focused on frequencies > 10 GHz, whereas 21 cm tomography of the high redshift universe will mainly focus on < 0.2 GHz, for which less is currently known about Galactic emission. Motivated by this, we present a global sky model derived from all publicly available total power large-area radio surveys, digitized with optical character recognition when necessary and compiled into a uniform format, as well as the new Villa Elisa data extending the 1.4 GHz map to the entire sky. We quantify statistical and systematic uncertainties in these surveys by comparing them with various global multi-frequency model fits. We find that a principal component based model with only three components can fit the 11 most accurate data sets (at 10, 22, 45 & 408 MHz and 1.4, 2.3, 23, 33, 41, 61, 94 GHz) to an accuracy around 1%-10% depending on frequency and sky region. Both our data compilation and our software returning a predicted all-sky map at any frequency from 10 MHz to 100 GHz are publicly available at http://space.mit.edu/home/angelica/gsm .Comment: Accuracy improved with 5-year WMAP data. Our data, software and new foreground-cleaned WMAP map are available at https://ascl.net/1011.01

Computing Nash Equilibrium in Wireless Ad Hoc Networks: A Simulation-Based Approach

This paper studies the problem of computing Nash equilibrium in wireless networks modeled by Weighted Timed Automata. Such formalism comes together with a logic that can be used to describe complex features such as timed energy constraints. Our contribution is a method for solving this problem using Statistical Model Checking. The method has been implemented in UPPAAL model checker and has been applied to the analysis of Aloha CSMA/CD and IEEE 802.15.4 CSMA/CA protocols.Comment: In Proceedings IWIGP 2012, arXiv:1202.422

Growing the Business Technology Management (BTM) Program: Ensuring BTM Supply is Meeting Industry Demand

The panel will present research concerning demand for ICT related occupations/skills and discuss high school level ICT career awareness initiatives. Also present information on Business Technology Management (BTM) growth initiatives related to an Employment Skills Development Canada (ESDC) grant, and explore academic community engagement and existing BTM programs

Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining

Background Worldwide, over 14% of individuals hospitalized for psychiatric reasons have readmissions to hospitals within 30 days after discharge. Predicting patients at risk and leveraging accelerated interventions can reduce the rates of early readmission, a negative clinical outcome (i.e., a treatment failure) that affects the quality of life of patient. To implement individualized interventions, it is necessary to predict those individuals at highest risk for 30-day readmission. In this study, our aim was to conduct a data-driven investigation to find the pharmacological factors influencing 30-day all-cause, intra- and interdepartmental readmissions after an index psychiatric admission, using the compendium of prescription data (prescriptome) from electronic medical records (EMR). Methods The data scientists in the project received a deidentified database from the Mount Sinai Data Warehouse, which was used to perform all analyses. Data was stored in a secured MySQL database, normalized and indexed using a unique hexadecimal identifier associated with the data for psychiatric illness visits. We used Bayesian logistic regression models to evaluate the association of prescription data with 30-day readmission risk. We constructed individual models and compiled results after adjusting for covariates, including drug exposure, age, and gender. We also performed digital comorbidity survey using EMR data combined with the estimation of shared genetic architecture using genomic annotations to disease phenotypes. Results Using an automated, data-driven approach, we identified prescription medications, side effects (primary side effects), and drug-drug interaction-induced side effects (secondary side effects) associated with readmission risk in a cohort of 1275 patients using prescriptome analytics. In our study, we identified 28 drugs associated with risk for readmission among psychiatric patients. Based on prescription data, Pravastatin had the highest risk of readmission (OR = 13.10; 95% CI (2.82, 60.8)). We also identified enrichment of primary side effects (n = 4006) and secondary side effects (n = 36) induced by prescription drugs in the subset of readmitted patients (n = 89) compared to the non-readmitted subgroup (n = 1186). Digital comorbidity analyses and shared genetic analyses further reveals that cardiovascular disease and psychiatric conditions are comorbid and share functional gene modules (cardiomyopathy and anxiety disorder: shared genes (n = 37; P = 1.06815E-06)). Conclusions Large scale prescriptome data is now available from EMRs and accessible for analytics that could improve healthcare outcomes. Such analyses could also drive hypothesis and data-driven research. In this study, we explored the utility of prescriptome data to identify factors driving readmission in a psychiatric cohort. Converging digital health data from EMRs and systems biology investigations reveal a subset of patient populations that have significant comorbidities with cardiovascular diseases are more likely to be readmitted. Further, the genetic architecture of psychiatric illness also suggests overlap with cardiovascular diseases. In summary, assessment of medications, side effects, and drug-drug interactions in a clinical setting as well as genomic information using a data mining approach could help to find factors that could help to lower readmission rates in patients with mental illness

Recent progress in marine mycological research in different countries, and prospects for future developments worldwide

Early research on marine fungi was mostly descriptive, with an emphasis on their diversity and taxonomy, especially of those collected at rocky shores on seaweeds and driftwood. Subsequently, further substrata (e.g. salt marsh grasses, marine animals, seagrasses, sea foam, seawater, sediment) and habitats (coral reefs, deep-sea, hydrothermal vents, mangroves, sandy beaches, salt marshes) were explored for marine fungi. In parallel, research areas have broadened from micro-morphology to ultrastructure, ecophysiology, molecular phylogenetics, biogeography, biodeterioration, biodegradation, bioprospecting, genomics, proteomics, transcriptomics and metabolomics. Although marine fungi only constitute a small fraction of the global mycota, new species of marine fungi continue to be described from new hosts/substrata of unexplored locations/habitats, and novel bioactive metabolites have been discovered in the last two decades, warranting a greater collaborative research effort. Marine fungi of Africa, the Americas and Australasia are under-explored, while marine Chytridiomycota and allied taxa, fungi associated with marine animals, the functional roles of fungi in the sea, and the impacts of climate change on marine fungi are some of the topics needing more attention. In this article, currently active marine mycologists from different countries have written on the history and current state of marine fungal research in individual countries highlighting their strength in the subject, and this represents a first step towards a collaborative inter- and transdisciplinary research strategy

Addressing challenges in the production and analysis of illumina sequencing data

Advances in DNA sequencing technologies have made it possible to generate large amounts of sequence data very rapidly and at substantially lower cost than capillary sequencing. These new technologies have specific characteristics and limitations that require either consideration during project design, or which must be addressed during data analysis. Specialist skills, both at the laboratory and the computational stages of project design and analysis, are crucial to the generation of high quality data from these new platforms. The Illumina sequencers (including the Genome Analyzers I/II/IIe/IIx and the new HiScan and HiSeq) represent a widely used platform providing parallel readout of several hundred million immobilized sequences using fluorescent-dye reversible-terminator chemistry. Sequencing library quality, sample handling, instrument settings and sequencing chemistry have a strong impact on sequencing run quality. The presence of adapter chimeras and adapter sequences at the end of short-insert molecules, as well as increased error rates and short read lengths complicate many computational analyses. We discuss here some of the factors that influence the frequency and severity of these problems and provide solutions for circumventing these. Further, we present a set of general principles for good analysis practice that enable problems with sequencing runs to be identified and dealt with

Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis:a multinational network cohort study

Objectives: Concern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA.Methods: We performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2 &lt;40%.Results: A total of 918 144 and 290 383 users of HCQ and SSZ, respectively, were included. No consistent risk of psychiatric events was observed with short-term HCQ (compared with SSZ) use, with meta-analytic HRs of 0.96 (95% CI 0.79, 1.16) for depression, 0.94 (95% CI 0.49, 1.77) for suicide/suicidal ideation and 1.03 (95% CI 0.66, 1.60) for psychosis. No consistent long-term risk was seen, with meta-analytic HRs of 0.94 (95% CI 0.71, 1.26) for depression, 0.77 (95% CI 0.56, 1.07) for suicide/suicidal ideation and 0.99 (95% CI 0.72, 1.35) for psychosis.Conclusion: HCQ as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation or psychosis compared with SSZ. No effects were seen in the short or long term. Use at a higher dose or for different indications needs further investigation.Trial registration: Registered with EU PAS (reference no. EUPAS34497; http://www.encepp.eu/encepp/viewResource.htm? id=34498). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine2.</p