A French and an American astronaut floated outside the International Space Station Friday on a successful spacewalk to upgrade the orbiting outpost for the arrival of future space crews. Outfitted in bulky white spacesuits, helmets and gloves, France's Thomas Pesquet, 39, and American Shane Kimbrough, 49, completed their work right on schedule, after six hours and 34 minutes in the vacuum of space. "Another great example of international collaboration and the work that we can do when we get a great team like this together," said Jessica Meir, a NASA astronaut who coordinated the spacewalk from mission control in Houston. The goal for Friday's outing was to prepare for the installation of the second of two parking spots for space taxis, known as the International Docking Adapters. New crew spaceships, being designed by SpaceX and Boeing, will use them when they begin flying astronauts to the station in the coming years, as early as 2018.

March 24, 2017 --The days when a chemist's assistant like Michael Faraday or a friar like Gregor Mendel could single-handedly revolutionize a field of science may seem long gone, but one British student is showing the world that anyone can play a role in research. This week NASA is feeling grateful to the sharp eyes of 17-year-old Miles Soloman of Sheffield, England, who was able to help uncover a faulty sensor on board the International Space Station (ISS) when he noticed some wacky readings in a data spreadsheet. His findings add to a long history of amateurs making real contributions to science, a phenomenon many researchers are eager to encourage. Miles's physics teacher, James O'Neill, had no idea what was going to happen when he enrolled his class in the TimPix project from the Institute for Research in Schools (IRIS), an initiative that provides classes with data collected from a radiation detector on board the ISS. By studying the data sets, students can learn about energy and "contribute to research that will improve our understanding of radiation in space," IRIS wrote on their website.

Interview Sure, algorithms are insanely useful, but we need to watch we don't become complacent and unable to question them, University College London's Dr Hannah Fry warned in an interview with The Register. Dr Fry is a lecturer in the mathematics of cities at the Centre for Advanced Spatial Analysis at UCL, where her research "revolves around the study of complex social and economic systems at various scales, from the individual to the urban, regional and the global, and particularly those with a spatial element." While not engaged in research, however, Dr Fry is quickly becoming one of the UK's favourite mathematicians, known for her work on BBC 4's The Joy of Data, as well as her popular TED talk, 'The Mathematics of Love', which applied statistical and data-scientific models to dating, sex and marriage. Chatting to The Register ahead of DataFest2017, the inaugural week-long data science festival in Edinburgh, Dr Fry said she thought the event was going to be "a lot of fun". It's something people really need to address, and having so many excellent people together in a room at once; it's going to be a great few days." "Data science as a field has exploded over the past five years," because there's "much more access to data now" said Dr Fry, noting that with "sensors, IoT, with us living more of our lives online" there's now "very little that is untouched by data". We "realised a few years ago how much data there was," Dr Fry said. "I think the whole thing is very exciting.

Seven million years ago, the first ancestors of mankind appeared in Africa and seven million years later, as we speak, mankind's existence is being traced by archaeologists in South Africa, where they believe they are finding several missing links in our history. A history traced back to the first hominid forms. What is a hominid, I hear you say, and when did it exist? Well, way back when scientists believe that the Eurasian and American tectonic plates collided and then settled, creating a massive flat area in Africa, after the Ice Age. This new massive field was flat for hundreds of miles, as far as the eye could see, and the apes that inhabited this land suddenly found there were no trees to climb. This meant that the apes found it hard going thundering over hundreds of miles on their hands and feet, so they started to stand up to make it easier to move over the land. This resulted in a change in the wiring of the brain, which, over thousands of years, led to the early forms of what is now recognized as human. The first link to understanding this chain was the discovery of Lucy. Lucy--named after the Beatles song "Lucy in the Sky with Diamonds"--is the first skeleton that could be pieced together to show how these early human forms appeared on the African plains in the post-Ice Age world. The skeleton was found in the early 1970s in Ethiopia by paleoanthropologist Donald Johanson and is an early example of the hominid australopithecine, dating back to about 3.2 million years ago. The skeleton presents a small skull akin to that of most apes, plus evidence of a walking gait that was bipedal and upright, similar to that of humans and other hominids. This combination supports the view of human evolution that bipedalism preceded an increase in brain size. Since Lucy was found, there have been many other astonishing discoveries in what is now called the "Cradle of Humankind" in South Africa, a Unesco World Heritage site.

FSCQ is the first file system with a machine-checkable proof that its implementation meets a specification, even in the presence of fail-stop crashes. FSCQ provably avoids bugs that have plagued previous file systems, such as performing disk writes without sufficient barriers or forgetting to zero out directory blocks. If a crash happens at an inopportune time, these bugs can lead to data loss. FSCQ's theorems prove that, under any sequence of crashes followed by reboots, FSCQ will recover its state correctly without losing data. To state FSCQ's theorems, this paper introduces the Crash Hoare logic (CHL), which extends traditional Hoare logic with a crash condition, a recovery procedure, and logical address spaces for specifying disk states at different abstraction levels. CHL also reduces the proof effort for developers through proof automation. Using CHL, we developed, specified, and proved the correctness of the FSCQ file system. Although FSCQ's design is relatively simple, experiments with FSCQ as a user-level file system show that it is sufficient to run Unix applications with usable performance. FSCQ's specifications and proofs required significantly more work than the implementation, but the work was manageable even for a small team of a few researchers. This paper describes Crash Hoare logic (CHL), which allows developers to write specifications for crash-safe storage systems and also prove them correct. "Correct" means that, if a computer crashes due to a power failure or other fail-stop fault and subsequently reboots, the storage system will recover to a state consistent with its specification (e.g., POSIX17). For example, after recovery, either all disk writes from a file-system call will be on disk, or none will be. Using CHL we write a simple specification for a subset of POSIX and build the FSCQ certified file system, which comes with a machine-checkable proof that its implementation matches the specification. Proving the correctness of a file system implementation is important, because existing file systems have a long history of bugs both in normal operation and in handling crashes.24

"As we honor the more mathematical, abstract, and scientific' parts of our subject more, and the practical parts less, we misdirect the young and brilliant minds away from a body of challenging and important problems that are our peculiar domain, depriving these problems of the powerful attacks they deserve." I have the privilege of working at the Defense Advanced Research Projects Agency (DARPA) and currently serve as the Acting Deputy Director of the Defense Sciences Office (DSO). Our goal at DARPA is to create and prevent technological surprise through investments in science and engineering, and our history and contributions are well documented. The DSO is sometimes called "DARPA's DARPA," because we strive to be at the forefront of all of science--on the constant lookout for opportunities to enhance our national security and collective well-being, and our projects are very diverse. One project uses cold atoms to measure time with 10 18th precision; another is creating amazing composite materials that can change the way in which we manufacture.

The computer systems we use today make it easy for programmers to mitigate event latencies in the nanosecond and millisecond time scales (such as DRAM accesses at tens or hundreds of nanoseconds and disk I/Os at a few milliseconds) but significantly lack support for microsecond (μs)-scale events. This oversight is quickly becoming a serious problem for programming warehouse-scale computers, where efficient handling of microsecond-scale events is becoming paramount for a new breed of low-latency I/O devices ranging from datacenter networking to emerging memories (see the first sidebar "Is the Microsecond Getting Enough Respect?"). Processor designers have developed multiple techniques to facilitate a deep memory hierarchy that works at the nanosecond scale by providing a simple synchronous programming interface to the memory system. A load operation will logically block a thread's execution, with the program appearing to resume after the load completes. A host of complex microarchitectural techniques make high performance possible while supporting this intuitive programming model. Techniques include prefetching, out-of-order execution, and branch prediction. Since nanosecond-scale devices are so fast, low-level interactions are performed primarily by hardware. At the other end of the latency-mitigating spectrum, computer scientists have worked on a number of techniques--typically software based--to deal with the millisecond time scale.

They were also discussed in 2015 in the Computing at School (CAS) framework and guide for teachers to enable teachers in the U.K. to incorporate computational thinking into their teaching work.10 CSTA/ISTE and CAS also provide pedagogical approaches to embed these capabilities across the curriculum in elementary and secondary classes. For example, CSTA/ISTE describes how the nine core computational thinking concepts and capabilities could be practiced in science classrooms by collecting and analyzing data from experiments (data collection and data analysis) and summarizing that data (data representation). Computational thinking is often mistakenly equated with using computer technology. Algorithms are central to both computer science and computational thinking.

Images produced with innovation engines were not only accepted to a selective art competition and displayed at the University of Wyoming Art Museum, but they also were among the 21% of submissions that won an award. It is not unusual to hear a student is taking an advanced placement computer science (AP CS) course these days, but eyebrows raise when Jackeline Mendez tells people about it, because Mendez is a senior at Boston Arts Academy where, as the name implies, the emphasis is on the arts. "I had a free block, and I was surprised how [computer science is] more than just systems and machines and the Internet," explains Mendez, who plans to major in physics in college. "People have a mind set that it's machines, but it's really not. It's what the world is right now. We use computer science for everything."

Real-time communication and collaboration lie at the heart of a new generation of high-definition (HD) digital maps that react quickly to changes in the real world. Autonomous vehicles and construction-site surveys are among the applications that are driving companies toward high-precision mapping performed almost in real time. James Dean, founder and director of technology applications at London, U.K.-based startup SenSat, says, "Digitizing the world is incredibly important. We can make better, faster decisions from that digitized information than is possible with traditional means" Early adopters of SenSat's mapping technology come from the road-construction industry, a sector that today mainly relies on manual surveys conducted at ground level. Surveys can take as long as six weeks and, as a result, can only be performed infrequently during a project.