Diamonds convert nuclear waste into clean batteries

Nuclear waste is normally a major environmental headache, but it could soon be a source of clean energy. Scientists have developed a method of turning that waste into batteries using diamond. If you encapsulate short-range radioactive material in a human-made diamond, you can generate a small electrical charge even as you completely block harmful radiation. While the team used a nickel isotope for its tests, it ultimately expects to do this using the carbon isotope you find in graphite blocks from nuclear power plants.

The batteries wouldn’t generate much power, but their longevity would be dictated by the life of the radiation itself. Researchers estimate that a carbon-based battery would generate 50 percent of its power in 5,730 years. Most likely, the batteries would be used in high-altitude drones, pacemakers, spacecraft and anywhere else replacing the battery is either very cumbersome or impossible. You could see interstellar probes that keep running long after they lose solar power, for example.

Any practical implementations are likely a long way off, and there are some conspicuous problems. Cost, for one. Diamond is expensive, so it might not be feasible to convert large amounts of nuclear waste into batteries. That’s assuming the technology works as well as intended, too. Still, it raises hope that the leftovers from nuclear reactors won’t just sit there posing a threat — they might actually do us some good.

Via: New Atlas

Source: University of Bristol

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Car Insurance Pricing Is Broken, But Your Phone Could Fix It

As the commercials make clear, shopping for car insurance can be frustrating. That’s in part because that auto insurance pricing is largely a black box for consumers. While the price a consumer pays for insurance is based on a risk estimate derived from demographics, past traffic violations, and claims history, each carrier uses the data in a unique, closely guarded way to calculate a price, and the number of prices for a given risk is as large as the number of insurers. Thus, it is difficult to be sure that you have the best price, or even a decent price, and many consumers are skeptical of the fairness of the entire process.

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About

David R. Martin is the chief data scientist at Root Insurance. Previously, he was a lead research and development analyst for Progressive Insurance. He holds a PhD in Applied Mathematics from Kent State University.


But today a rapidly growing share of personal auto policies in the US are being priced based on calculations using sensor data generated by the consumer’s vehicle or smartphone. Such policies are referred to as telematics, or usage-based insurance (UBI) policies. Insurance companies can use sensor data from your driving to accurately infer annualized mileage, frequency of hard brakes, and numerous other features, and correlate this information with future losses. By using this information, insurers are able to set prices for auto insurance that correlate much more directly to their cost of providing individual policies.

How does this work? Insurers provide a dongle or smartphone app to consumers, who use the technology in their cars in exchange for a possible discount. In a world where smartphones have made the casual sharing of usage data ubiquitous, it comes as no great surprise that many consumers are comfortable sharing sensor data with their insurer for a possible discount. But numerous others, distrusting of the industry in the first place, are apprehensive about the potential use of such data, fearing its existence will asymmetrically benefit the insurer.

The benefits of UBI to an insurance company are straightforward enough—increased pricing accuracy, which improves retention of the good drivers who now get better rates because they are the cheapest to insure, and it provides more adequate rates for the most dangerous of drivers. Plus, it ultimately draws in new customers who recognize the virtues of more personalized insurance.

But as crazy as it sounds, the greatest beneficiaries of UBI are not insurance companies, but consumers—even those who don’t directly participate. UBI is improving society by increasing the overall fairness of insurance pricing, reducing reliance on crude demographics, protecting everyone from fraud, and even saving lives.

Downgrading Demographics

Some consumers feel uncomfortable with the industry’s reliance on demographics such as age, gender, marital status, and credit rating to determine rates. Moreover, many of those factors are partially or completely outside a person’s control, an angle that is often exploited by consumer advocates to label their use as unfairly discriminatory.

Thankfully, as telematics risk scores become more and more powerful, we will rely less and less on demographics to approximate risk. For example, the unusually safe 16-year-old who participates in UBI can be exonerated by the sensor, saving him or her from an unfairly steep price assigned because they were lumped in with a general demographic.

Put another way, every segment of the population contains safe drivers and unsafe drivers, in varying proportions. Before UBI, the price assigned to each segment was largely determined by the ratio of unsafe drivers to safe drivers in that segment. But now, it is possible to separate drivers based on behaviors that are fundamental to actual auto risk, and thereby price more fairly, at an extremely granular and personal level.

The use of demographics in pricing may not disappear overnight, but its influence on prices will only decrease as data scientists continue to refine their models and delve deeper into understanding human behavior as it relates to risk.

Flagging Fraud

A less obvious advantage of UBI is that it allows insurers to easily identify certain types of fraud which, gone unnoticed, quietly contribute to increased rates for honest customers.

A simple example is address fraud. Pricing for insurance can vary significantly by zip code. In order to get a lower rate, some customers will provide an incorrect garaging address, in a different city or even a different state, where prices are much cheaper. As a result, the insurance company unknowingly takes on additional, underpriced risk, and inevitably, the losses end up affecting pricing and risk approximation for customers who truly do live in the stated zip code. With GPS readings from a smartphone or dongle, it is easy to flag policies that are likely to be misrepresenting their garaging address and react appropriately.

Another example of fraud that could be detected using telematics is the undisclosed business use of a personal vehicle. Driving for Lyft, for example, is generally not covered by a personal auto policy, even when a personal vehicle is being used. Before telematics, the only countermeasure available to insurers was investigation of claims circumstances, but this approach is far from optimal. By analyzing spatial and temporal driving patterns—such as frequent trips to the airport, convention centers, or major hotels—it is possible for insurers to identify customers who might be using their personal vehicle for business use. This allows them to proactively reach out to ensure legal, adequate coverage before disaster ensues, such as an uncovered accident—a better outcome for all parties involved.

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World’s Kindest Repo Man Pays Off Elderly Couple’s Buick Right Before Thanksgiving

Stanford and Patty Kipping had a hard choice to make: keep making the $95 monthly payments on their 1998 Buick, or pay for the increased costs of their prescription medicines. They couldn’t do both. So the couple, 82 and 70, were ready to lose their Buick to the bank—until one very kind repo man stepped up to save the…

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VLC media player now supports 360-degree videos

VLC, the app that lets you play basically any video format on practically any platform, is about to add support for a whole new medium. The company just unveiled a technical preview that enables its desktop app to play 360-degree videos, so folks can watch their dizzying footage on their computers. The preview is now available for Windows and Mac machines, and the full version will arrive with VLC 3.0 , which is expected at the end of the month.

VLC’s creators VideoLan teamed up with 360-degree camera maker Giroptic to develop its system, which can display photos, panoramas and videos. You can use your mouse and keyboard to control your point of view in the footage. VideoLan says it will make these features available on its mobile apps as well, and let users navigate the clips by moving their accelerometer-carrying devices around. It also said it will support VR headsets such as the Oculus Rift, Google’s Daydream and the HTC Vive in 2017. The app is also getting 360-degree audio support "including head tracking headphones," says the company, although it’s not clear when that will happen.

Since it’s still just a technical preview, those who are itching to try VLC 360 out should temper their expectations as it might be buggy. Even so, it’s clear that VLC is making a big push into enabling VR experiences across all its supported platforms, which should be good news for its large base of tech-savvy fans.

Source: VideoLan

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Anti-drone gun takes down targets from 1.2 miles away

There are numerous systems built to take down wayward or dangerous drones, but they tend to have one big catch: you need to be relatively close to the drone, which could be scary if the robotic aircraft is packing explosives. DroneShield thinks it can help. It’s introducing the DroneGun, a jammer that disables drone signals (including GPS and GLONASS positioning) from as far as 1.2 miles away. Like most rivals, it doesn’t destroy the target drone — it just forces the vehicle to land or return to its starting point. Anti-drone teams can not only disable threats from a safe distance, but potentially locate their pilots.

It’s not the lightest machine at about 13 pounds, but it’s portable enough to be usable by one person. You don’t need technical training, either, so it’s easy for security staff to use.

Whether or not you see the DroneGun in action is another matter. It’s not FCC-certified as we write this, so you can’t legally operate one in the US. Provided it’s approved, though, it could help take down drones at airports, protect soldiers against drone bombs and otherwise help in situations where it’s simply not possible to get close.

Via: Wired

Source: DroneShield

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Google Translate Solves Own Problem

translate

Google’s translate tool has created its own solution to greatly expand its automated capabilities. It can now translate between two languages even without a specific “dictionary” to do so.

The company recently switched Google Translate away from its “traditional” method of consulting a known list of phrases and their equivalent in different languages. Instead it’s now using Neural Machine Translation, which tries to simulate the way human brains learn languages, in particular taking advantage of context to produce more natural sounding translations of entire sentences.

One big problem is that it means starting over on the various combinations of languages between which the system can translate. As organizations such as the United Nations and European Union have experienced, adding new languages rapidly increases the number of possible combinations that need to be covered. For example, moving from two to three languages means adding two new combinations. Moving from 25 to 26 languages means adding 25 different combinations. Given Google currently supports 103 languages, that’s 5,253 different combinations to cover.

However, the system has effectively figured out the smart solution, namely using an intermediate language. Although Google staff haven’t specifically trained the system to do so, it’s independently figured out that if it’s learned a translation of a Japanese phrase into English and has also learned a translation of the same phrase from English to Korean, it can in turn translate from Japanese to Korean.

Even more impressively, it turns out this isn’t simply a case of cross-referencing word and phrase lists among three real-world languages. Instead, analysis of the network data shows the system is organizing its database of each language by concept. Google staff believe the system is effectively using its own interlingua, which is a basic artificial language that covers these concepts and acts as the go-between when translating a new combination of languages.

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