The radiation level in the containment vessel of reactor 2 at the crippledFukushima No. 1 power plant has reached a maximum of 530 sieverts per hour, the highest since the triple core meltdown in March 2011, oTokyo Electric Power Co. Holdings Inc. said Thursday. The reading means a person could die from even brief exposure, highlighting the difficulties ahead as the government and Tepco grope their way toward dismantling all three reactors that suffered core meltdowns in the March 2011 disaster. Tepco also announced that, based on image analysis, it has discovered a 2-meter hole in the metal grating beneath the pressure vessel inside reactor 2's containment vessel, and discovered a portion of it is warped. The hole could have been caused by melted fuel penetrating the vessel after the March 11, 2011 mega-quake and massive tsunami triggered a station blackout that crippled the plant's ability to keep the reactors cool. The new radiation level, described by some experts as "unimaginable," far exceeds 73 sieverts per hour, the previously highest radiation reading monitored in the interior of the reactor.

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamic filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. For quantifying the causal dependency, a mutual information based metric is presented. An energy prediction approach is subsequently proposed based on the STPN framework. For validating the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying the spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring the temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

Mechanical masterminds have spawned the Bat Bot, a soaring, sweeping and diving robot that may eventually fly circles around other drones. Because it mimics the unique and more flexible way bats fly, this 3-ounce prototype could do a better and safer job getting into disaster sites and scoping out construction zones than bulky drones with spinning rotors, said the three authors of a study released yesterday in the journal Science Robotics. For example, it would have been ideal for going inside the damaged Fukushima nuclear plant in Japan, said study co-author Seth Hutchinson, an engineering professor at the University of Illinois. The bat robot flaps its wings for better aerial maneuvers, glides to save energy and dive bombs when needed. Eventually, the researchers hope to have it perch upside down like the real thing, but that will have to wait for the robot's sequel. Like the fictional crime fighter Batman, the researchers turned to the flying mammal for inspiration.

Angling to pre-empt complaints over Japan's perennial trade surplus with the U.S., Prime Minister Shinzo Abe reportedly plans to propose a sweeping economic cooperation initiative meant to create hundreds of thousands of jobs in the U.S. when he meets with President Donald Trump later this month. Abe and Trump are expected to meet on Feb. 10. Major Japanese newspapers cited a draft of the proposal that calls for cooperation on building high-speed trains in the U.S. northeast, Texas and California. Japan would share technology on artificial intelligence, robotics, small-scale nuclear power plants, space and Internet technology. The reports Thursday said the proposed public-private initiative would create several hundred thousand jobs, reports said, and involve $450 billion in new investment.

Mechanical masterminds have spawned the Bat Bot, a soaring, sweeping and diving robot that may eventually fly circles around other drones. Because it mimics the unique and more flexible way bats fly, this 3-ounce (85-gram) prototype could do a better and safer job getting into disaster sites and scoping out construction zones than bulky drones with spinning rotors, said the three authors of a study released Wednesday in the journal Science Robotics. For example, it would have been ideal for going inside the damaged Fukushima nuclear plant in Japan, said study co-author Seth Hutchinson, an engineering professor at the University of Illinois. The bat robot flaps its wings for better aerial maneuvers, glides to save energy and dive bombs when needed. Eventually, the researchers hope to have it perch upside down like the real thing, but that will have to wait for the robot's sequel.

Abe and Trump are expected to meet on Feb. 10. Major Japanese newspapers cited a draft of the proposal that calls for cooperation on building high-speed trains in the U.S. northeast, Texas and California. Japan would share technology on artificial intelligence, robotics, small-scale nuclear power plants, space and Internet technology.

For energy generation, utilities, and oil and gas, IoT security means predictive maintenance, cyber defense, and threat remediation. In this white paper, leading Artificial Intelligence company, SparkCognition, details use cases with Fortune 500 clients addressing the gap between the vast amount of data being collected and the limited resources to analyze this important information.

Search in an environment with an uncertain distribution of resources involves a trade-off between exploitation of past discoveries and further exploration. This extends to information foraging, where a knowledge-seeker shifts between reading in depth and studying new domains. To study this decision-making process, we examine the reading choices made by one of the most celebrated scientists of the modern era: Charles Darwin. From the full-text of books listed in his chronologically-organized reading journals, we generate topic models to quantify his local (text-to-text) and global (text-to-past) reading decisions using Kullback-Liebler Divergence, a cognitively-validated, information-theoretic measure of relative surprise. Rather than a pattern of surprise-minimization, corresponding to a pure exploitation strategy, Darwin's behavior shifts from early exploitation to later exploration, seeking unusually high levels of cognitive surprise relative to previous eras. These shifts, detected by an unsupervised Bayesian model, correlate with major intellectual epochs of his career as identified both by qualitative scholarship and Darwin's own self-commentary. Our methods allow us to compare his consumption of texts with their publication order. We find Darwin's consumption more exploratory than the culture's production, suggesting that underneath gradual societal changes are the explorations of individual synthesis and discovery. Our quantitative methods advance the study of cognitive search through a framework for testing interactions between individual and collective behavior and between short- and long-term consumption choices. This novel application of topic modeling to characterize individual reading complements widespread studies of collective scientific behavior.

Mechanical masterminds have spawned the Bat Bot, a soaring, sweeping and diving robot that may eventually fly circles around other drones. Because it mimics the unique and more flexible way bats fly, this 3-ounce prototype could do a better and safer job getting into disaster sites and scoping out construction zones than bulky drones with spinning rotors, said the three authors of a study released Wednesday in the journal Science Robotics. For example, it would have been ideal for going inside the damaged Fukushima nuclear plant in Japan, said study co-author Seth Hutchinson, an engineering professor at the University of Illinois. Bat Bot, a three-ounce flying robot can be more agile at getting into treacherous places than standard drones. The flying robot weighs just three ounces, and is equipped with nine joints. It measures about 8 inches from head to tail, and has a super-thin membrane that stretches to about a foot and a half.

Probabilistic modeling is a powerful approach for analyzing empirical information. We describe Edward, a library for probabilistic modeling. Edward's design reflects an iterative process pioneered by George Box: build a model of a phenomenon, make inferences about the model given data, and criticize the model's fit to the data. Edward supports a broad class of probabilistic models, efficient algorithms for inference, and many techniques for model criticism. The library builds on top of TensorFlow to support distributed training and hardware such as GPUs. Edward enables the development of complex probabilistic models and their algorithms at a massive scale.