Centuries-old genetic material can solve historical mysteries, from lost species to what killed Napoleon's army. A glowing, digital double helix represents the billions of base pairs scientists analyze when sequencing ancient DNA. Breakthroughs, discoveries, and DIY tips sent every weekday. In 1976, workers excavating a tunnel for the Toronto subway system came across some very old bones. Using radiocarbon dating, researchers determined the partial cranium and fragments of antlers were roughly 12,000 years old.

If you've never heard colours, you can now do so. Researchers planted tiny electrodes on the surface of the brain of a man paralysed from the neck down. As he imagined writing letters with his hand, the researchers analysed the neural patterns for each letter. They created an algorithm that transformed these neural patterns into words on a screen [Anushree Dave, ScienceNews]. From his brain activity alone, the participant produced 90 characters, or 15 words, per minute, Krishna Shenoy, a Howard Hughes Medical Institute investigator at Stanford University, and colleagues report May 12 in Nature.

The quest for new and better actuation technologies and'soft' robotics is often based on principles of biomimetics, in which machine components are designed to mimic the movement of human muscles -- and ideally, to outperform them. Despite the performance of actuators like electric motors and hydraulic pistons, their rigid form limits how they can be deployed. As robots transition to more biological forms and as people ask for more biomimetic prostheses, actuators need to evolve. Associate professor (and alum) Michael Shafer and professor Heidi Feigenbaum of Northern Arizona University's Department of Mechanical Engineering, along with graduate student researcher Diego Higueras-Ruiz, published a paper in Science Robotics presenting a new, high-performance artificial muscle technology they developed in NAU's Dynamic Active Systems Laboratory. The paper, titled "Cavatappi artificial muscles from drawing, twisting, and coiling polymer tubes," details how the new technology enables more human-like motion due to its flexibility and adaptability, but outperforms human skeletal muscle in several metrics.

The main goal of this paper is to describe an axiomatic utility theory for Dempster-Shafer belief function lotteries. The axiomatic framework used is analogous to von Neumann-Morgenstern's utility theory for probabilistic lotteries as described by Luce and Raiffa. Unlike the probabilistic case, our axiomatic framework leads to interval-valued utilities, and therefore, to a partial (incomplete) preference order on the set of all belief function lotteries. If the belief function reference lotteries we use are Bayesian belief functions, then our representation theorem coincides with Jaffray's representation theorem for his linear utility theory for belief functions. We illustrate our framework using some examples discussed in the literature, and we propose a simple model based on an interval-valued pessimism index representing a decision-maker's attitude to ambiguity and indeterminacy. Finally, we compare our decision theory with those proposed by Jaffray, Smets, Dubois et al., Giang and Shenoy, and Shafer.

In an expansion of their ongoing collaboration, Cerner has chosen Amazon Web Services as its preferred artificial intelligence and machine learning provider – and will continue to use AWS technologies to improve patient and provider experience, boost population health efforts and tackle healthcare costs. WHY IT MATTERS Cerner will work to migrate core applications to AWS as part of the collaborative agreement, officials said. In addition, the company is standardizing its AI and machine learning workloads on AWS to develop new predictive technology. One focus of this new initiative is the Cerner Machine Learning Ecosystem – a platform built using Amazon SageMaker, Amazon Simple Storage Service, AWS Lambda, Amazon Simple Queue Service, AWS Step Functions and Amazon CloudWatch. The companies say the platform will help healthcare data scientists building, deploy, monitor and manage machine models at scale – and help Cerner find more predictive and digital diagnostic insights for earlier health interventions.

Health IT company Cerner is leveraging its partnership with Amazon Web Services to launch a new cloud-based health platform to incorporate artificial intelligence to improve usability and provide predictive insights for patient care. The new platform, called Project Apollo, brings a more cognitive approach to practicing medicine, Cerner Chairman and CEO Brent Shafer said during his keynote address at Cerner Health Conference, according to a company press release. Shafer said the new platform will leverage Cerner's health care technology and the AWS infrastructure to accelerate the speed that innovations are integrated by removing manual steps for clients that slow the pace of adoption. Cerner also is creating an "intelligence ecosystem" to innovate next-generation user experiences and care delivery algorithms, the company said. We're looking to return the joy of delivering medicine, and we're focused on innovating for the future and delivering better usability today," Shafer said. The Kanas City-based company also announced new predictive modeling tools to help reduce opioid abuse, improved dashboards and analytics, and a new capability aimed at enhancing interoperability in the healthcare industry. In July, Cerner announced a collaboration with cloud giant AWS, which is part of Amazon, with the aim of accelerating healthcare innovation. As part of the agreement, Cerner named AWS its preferred cloud provider. During his keynote speech, Shafer said Cerner will focus on several key areas in its broader strategy to innovate with Amazon, including turning data into insights, increasing interoperability and usability, and rapid development and deployment, according to the Kansas City Business Journal. Matt Wood, vice president of artificial intelligence for AWS, also spoke at the conference on the partnership with Cerner and the possibilities that arise when companies can access "infrastructure as if it was a utility, according to the Kansas City Business Journal.

They were given six weeks to accomplish the task, and that is what they did. A couple of weeks ago, members of the Red River Rage, which is what the students from Fargo North, Fargo South and Davies High School call themselves, were among the winners of a regional tournament held in Grand Forks. Now, they are heading to the 2019 FIRST Robotics Championship tournament in Detroit, which will be held April 24-27. FIRST Robotics is an international high school robotics competition that gives students real-world engineering experience. There are about 4,800 teams around the world and about 600 will compete in Detroit, according to Ellen Shafer, one of several mentors of the local high school team, which includes her son, Ethan Shafer, a junior at North High.

Cerner is joining forces with Amazon as the EHR giant positions itself to deal with the rapidly changing healthcare environment, including the rise of consumerism. Partnering with a brand predominantly known for speed, convenience and affordability could be a good move for Cerner, especially now that Amazon's done more than just dip its toe in the market. "AWS's global infrastructure and breadth and depth of services, coupled with Cerner's health care technology acumen and source for data, can bring significant benefits to Cerner clients." the companies said in a Tuesday blog post. Amazon's foray into healthcare stretches across at-home diagnoses with Alexa's voice recognition technology, pharmaceutical distribution with subsidiary PillPack, a venture to lower healthcare costs in tandem with industry heavyweights J.P. Morgan and Berkshire-Hathaway, and machine learning, AI and data hosting through its cloud services arm. "If you look even just at Amazon Web Services, everything that we do is because customers are asking us to help," Taha Kass-Hout, Amazon's senior leader of healthcare and artificial intelligence, told Healthcare Dive earlier this year.

Mathematical Theory of Evidence (MTE), a foundation for reasoning under partial ignorance, is blamed to leave frequencies outside (or aside of) its framework. The seriousness of this accusation is obvious: no experiment may be run to compare the performance of MTE-based models of real world processes against real world data. In this paper we consider this problem from the point of view of conditioning in the MTE. We describe the class of belief functions for which marginal consistency with observed frequencies may be achieved and conditional belief functions are proper belief functions,%\ and deal with implications for (marginal) approximation of general belief functions by this class of belief functions and for inference models in MTE.

This paper is concerned with the apparent greatest weakness of the Mathematical Theory of Evidence (MTE) of Shafer \cite{Shafer:76}, which has been strongly criticized by Wasserman \cite{Wasserman:92ijar}. Weaknesses of Shafer's proposal \cite{Shafer:90b} of probabilistic interpretation of MTE belief functions is demonstrated. Thereafter a new probabilistic interpretation of MTE conforming both to definition of belief function and to Dempster's rule of combination of independent evidence. It is shown that shaferian conditioning of belief functions on observations \cite{Shafer:90b} may be treated as selection combined with modification of data, that is data is not viewed as it is but it is casted into one's beliefs in what it should be like.