Radioactive material went missing in New Jersey earlier this month, fueling conspiracy theories that it could be linked to the mysterious drone sightings. A piece of medical equipment used for cancer scans was shipped from the Nazha Cancer Center in Newfield on December 2 for disposal, but the'shipping container arrived at its destination damaged and empty.' The device, known as a'pin source,' contained a small amount of Germanium-68 (Ge-68) that is used to calibrate a medical scanner's accuracy. If handled without proper gear, it can cause radiation poisoning. The US Nuclear Regulatory Commission (NRC) issued an alert for the missing shipment deemed'less than a Category 3,' meaning it could cause permanent injury if mishandled.

This paper aims to construct models based on economically motivated factor decompositions and shrinkage methods to forecast large-dimensional, and time-varying realized measures of daily covariance matrices of returns on financial assets. Realized measures of a covariance matrix are estimates, based on intraday returns, of the integrated covariance matrix of a multivariate diffusion process. One example of such an estimator used in this paper is the composite realized kernel method recently introduced by Lunde et al. (2016). Our proposed model is evaluated in terms of its forecasting ability and, more importantly, several performance measures in a conditional mean-variance portfolio allocation problem. Modeling and forecasting the covariance matrix of financial assets are essential for portfolio allocation and risk management.

We present a formal tasK AllocatioN and scheduling apprOAch for multi-robot missions (KANOA). KANOA supports two important types of task constraints: task ordering, which requires the execution of several tasks in a specified order; and joint tasks, which indicates tasks that must be performed by more than one robot. To mitigate the complexity of robotic mission planning, KANOA handles the allocation of the mission tasks to robots, and the scheduling of the allocated tasks separately. To that end, the task allocation problem is formalised in first-order logic and resolved using the Alloy model analyzer, and the task scheduling problem is encoded as a Markov decision process and resolved using the PRISM probabilistic model checker. We illustrate the application of KANOA through a case study in which a heterogeneous robotic team is assigned a hospital maintenance mission.

A'cyber seed' that grows'like a plant' to design structures using material from the local environment has been developed by researchers. The'seed' is composed of hundreds of pieces of information, digitally encoded, that includes data on necessary materials, properties, and other parameters such as weight, height, colour, and density. Simple seeds could have 50 lines of information, with six pieces of information per line. This seed, algorithmically, then attempts to grow into a particular design set out by researchers from Queen's University Belfast, Loughborough University and the University of York. Starting off from a single cell in a CAD (computer-aided design) program, the seed will grow in a certain direction until it reaches the limit of the parameter it has been programmed with.

Pneumonia, an acute respiratory condition which affects the lungs, kills millions of people around the world each year. This includes 16 percent of all children who die under the age of five. It's particularly devastating in parts of the world without the necessary trained doctors and required medical equipment, such as X-ray machines, to treat it effectively. Researchers from Johns Hopkins University think so. Spinning off to form the startup Sonavi Labs, they have developed an updated version of this core piece of medical equipment which has remained largely unchanged since the 1800s, boasting some smart, cutting-edge additions. This includes smart noise-filtering technology for enhancing the sound quality of chest readings.

The Japanese government is teaming up with businesses and academia to set up hospitals enhanced by artificial intelligence, seeking to allow short-handed doctors to spend more time on patient care while curbing medical spending. The government is expected to invest more than $100 million in the effort over half a decade, with a target of establishing 10 model hospitals by the end of fiscal 2022. AI will help with tasks from updating patients' charts to analyzing tests and parsing images to help with diagnoses. The effort aims to address structural challenges to health care, including the chronic lack of doctors and nurses in some areas and rising medical expenses. The initiative will also help make Japan more competitive on the world stage, giving AI development a shot in the arm and helping boost exports of medical equipment. Three ministries central to the effort -- the education, industry and health ministries -- will recruit participating companies and hospitals this month, targeting AI specialists and medical equipment makers.

We may buy new smartphones and laptops every year or two, but when it comes expensive medical computers, that's not an option. There are more than three million medical equipment installed in hospitals today, and more than 100,000 new instruments added each year -- that's according Nvidia CEO Jensen Huang said at the company's GPU Technology Conference (GTC). At this rate, it would take more than 30 years to replace all the old hospital equipment. So how do we advance medical care without adding more cost? Nvidia's technique is to leverage the cloud to provide a "virtual upgrade" to existing medical equipment.

Sectra, a medical IT and secure communications company, offered both workflow and big data modeling products and previews at the 2016 RSNA meeting, underway this week in Chicago. The company's recent initiatives are motivated by a long held practice among physicians: peer review and cross-specialty consulting. These principles provide the foundation of its Peer Review platform, now available for radiologists to gain greater increased insight into their patient diagnoses. KenQuest provides all major brands of surgical c-arms (new and refurbished) and carries a large inventory for purchase or rent. With over 20 years in the medical equipment business we can help you fulfill your equipment needs "Peer Review gives instant feedback and stats between radiologists to improve the workflow," Hans Lugnegard, product manager told HCB News.

Talking to WIRED before his speech at WIRED Health, Kyu Rhee, IBM's chief health officer, took from his pocket one of the iconic pieces of medical equipment: the stethoscope. The stethoscope is celebrating its 200th anniversary – the first, monaural version was created by the French doctor René Laennec. Despite technical advances – and the rise of other non-invasive techniques for internal examination – the stethoscope still means "doctor": according to a 2012 research paper, carrying a stethoscope makes a practitioner seem more trustworthy than any other piece of medical equipment. "It's amazing how medicine in some ways still leverages this piece of technology," said Rhee. "But I believe that in the next 200 years a cognitive system like Watson will be a part of every healthcare decision, for every stakeholder." IBM Watson's cognitive approach to computing absorbs data – structured and unstructured – and produces answers.