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Data reveals evidence of molecular absorption in the atmosphere of a hot Neptune

Data reveals evidence of molecular absorption in the atmosphere of a hot Neptune
This artist’s impression shows the LTT9779 system approximately to scale, with the hot Neptune-sized planet at left and its bright, nearby star at right. The trail of material streaming off of the planet is hypothetical but likely, based on the intense irradiation of this planet. Credit: Ethen Schmidt, Kansas University

An international team of scientists recently measured the spectrum of the atmosphere of a rare hot Neptune exoplanet, whose discovery by NASA’s Transiting Exoplanet Survey Satellite (TESS) was announced just last month.


The discovery was made with data provided from the now-retired NASA Spitzer Space Telescope, which allows a unique, infrared view of the universe to look into regions of space that are hidden from optical telescopes.

One of the main goals of NASA’s TESS mission is to find new, small planets that would be good targets for atmospheric characterization. Early in its mission, it found LTT9779b, a planet orbiting

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Syntropy Joins MITRE’s Mission to Unlock the Power of Real-World Data for Cancer Research and Treatment

Partnership on mCODE is aimed at removing barriers to standardized data, improving patient outcomes

Syntropy, a technology company specializing in healthcare data integration and collaboration solutions, today announced it is joining forces with MITRE to provide data integration support for the mCODE™ (minimal Common Oncology Data Elements) data standard. The partnership seeks to improve the overall quality and consistency of cancer data available to clinicians, patients, researchers, and other stakeholders in the fight against cancer.

Today, more than 18 million people are living with cancer globally, with thousands of additional cases diagnosed every day. While there is a vast array of data available to support oncology research and clinical care, the majority of it is contained in electronic health records (EHRs), which are not always uniform in the way they collect, analyze and store data. The lack of standardized workflows, ontologies, and integrations has significantly hindered data’s true impact and

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CACI Awarded $86.5 Million Task Order to Provide Data and Analytical Support Services to the Department of Homeland Security

CACI International Inc (NYSE: CACI) announced today that it has been awarded a five-year task order, with a ceiling value of $86.5 million, by the Department of Homeland Security (DHS) to provide mission expertise in support of the Homeland Security Investigation (HSI) division.

CACI will use its expertise in working with interagency partners, law enforcement agencies, and the Department of Defense to analyze proprietary, commercially available, and open source data to help HSI thwart criminal, fraud, risk, and terrorism activity by more precisely targeting certain investigations and transform data into actionable insights. Uncovering patterns using data analysis methodologies enables detection of criminal activities, criminal conspiracies, and criminal networks.

John Mengucci, CACI President and Chief Executive Officer, said, “CACI’s extensive experience in analyzing data to detect patterns and trends helps support our customer in identifying terrorist threats before they result in an attack against the United States or its people.”

CACI

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A new data assimilation system to improve precipitation forecast

A new data assimilation system to improve precipitation forecast
The global observing system

Data assimilation systems can provide accurate initial fields for further improving numerical weather prediction (NWP). Since 2008, Tian Xiangjun and his team at the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences have been devoted to developing the nonlinear least-squares 4-D ensemble variational data assimilation method (NLS-4DVar).


NLS-4DVar methods have been used for solving real-world applications including land data assimilation, NWP data assimilation, atmospheric-chemistry data assimilation, and targeted observations.

Recently, TIAN’s team has developed a new forecasting system—the System of Multigrid Nonlinear Least-squares Four-dimensional Variational (NLS-4DVar) Data Assimilation for Numerical Weather Prediction (SNAP). The study was published in Advances in Atmospheric Sciences on Oct. 9.

SNAP is built upon the multigrid NLS-4DVar data assimilation scheme, the operational Gridpoint Statistical Interpolation (GSI)-based data-processing and observation operators, and the widely used Weather Research and Forecasting numerical model.

The multigrid NLS-4DVar assimilation framework is used for

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Long-term data show a recent acceleration in chemical and physical changes in the ocean

Long-term data show a recent acceleration in chemical and physical changes in the ocean
From L to R: Rod Johnson (BATS Co-PI), Emily Davey (Research Technician), Dom Smith (Research Technician) and Claire Medley (Research Technician) sample the CTD for dissolved O2 and CO2 aboard the R/V Atlantic Explorer during a routine Bermuda Atlantic Time-series Study (BATS) cruise. Credit: Ella Cedarhold, Bermuda Institute of Ocean Sciences

New research published in Nature Communications Earth & Environment uses data from two sustained open-ocean hydrographic stations in the North Atlantic Ocean near Bermuda to demonstrate recent changes in ocean physics and chemistry since the 1980s. The study shows decadal variability and recent acceleration of surface warming, salinification, deoxygenation, and changes in carbon dioxide (CO2)-carbonate chemistry that drives ocean acidification.


The study utilized datasets from Hydrostation ‘S’ and the Bermuda Atlantic Time-series Study (BATS) projects at the Bermuda Institute of Ocean Sciences (BIOS). Both are led by Professor Nicholas Bates, BIOS senior scientist and the

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Sexual violence reports rise drastically at schools, Education Department data shows

The context: The data was released as part of a massive survey of information from schools, known as the Civil Rights Data Collection, which the Education Department conducts every other year.

This is the second year the civil rights data survey has asked schools to report information about sexual violence. The Education Department said it took new steps to bolster the quality of the data after errors in the last survey raised questions about the accuracy of how schools reported sexual violence.

The numbers reflect documented allegations, not necessarily confirmed incidents, the department said.

An analysis of the data by the department’s Office for Civil Rights said it was unclear what was driving the increase between the data released this year and the data released in the previous report in 2018.

“The increase in reported allegations may reflect under-reporting” in the previous survey, “an increased sensitivity to this issue” in

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Data Science | IBM

 

Data science is the process of using algorithms, methods, and systems to extract knowledge and insights from structured and unstructured data. It uses analytics and machine learning to help users make predictions, enhance optimization, and improve operations and decision making.

Today’s data science teams are expected to answer many questions. Business demands better prediction and optimization based on real-time insights backed by tools for ModelOps and cloud data science.

The data science lifecycle starts with gathering data from relevant sources, cleaning it and putting it in formats that machines can understand. In the next phase, statistical methods and other algorithms are used to find patterns and trends. Then models are programmed and built to predict and forecast; finally, results are interpreted.

Advances in AI, machine learning and automation have raised the standards of data science tools for business. The result is the formation of data science teams — expert data

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Data Science | edX

The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. The HarvardX Data Science program prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

In each course, we use motivating case studies, ask specific questions, and learn by answering these through data analysis. Case studies include: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems.

Throughout the program, we will be using the R software environment. You will learn R, statistical concepts,

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R for Data Science

Cover image This is the website for “R for Data Science”. This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.

This website is (and will

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USC Viterbi | Data Science Program

The ways we interact, how we innovate, and our national security depend on how well we can collect, manage, share, analyze, understand, present, and secure data. The breadth and depth of information available presents opportunities for creativity, entrepreneurship, and outreach that are global. The sheer quantity and our growing dependence also create grand challenges.

Our goal is to create an educational program that focuses on how information can be applied to solve real-world problems in academia, industry and government; how engineering can integrate with a multitude of diverse disciplines to enable such solutions; and how we can secure the requisite data, software and infrastructure.

Our goals are simple: to offer superior education in relevant engineering topics, combine this with outstanding offerings from across our great campus, and produce students who have world-class technical capability and immersion into a domain – whether intellectual or more applied – where it is needed.

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