Watching the Super Blood Wolf Moon? What to Know About This Lunar Phenomenon

Our in-house Know-It-Alls answer questions about your interactions with technology and science. Today, we weigh in on the January 20, 2019, total lunar eclipse and the wild nomenclature surrounding it.

Q: What does it mean to be a super blood wolf moon?

A: Like presidential elections and celebrity drama, the beauty and intrigue of lunar events lies in their regularity. Supermoon! Blood moon! Harvest moon! Wolf harvest sturgeon blue blood pink worm supermoon!

Alright, maybe that last one isn’t a thing (a pink moon being the full moon in April, a sturgeon being the one in August). There are literally dozens of nicknames for the moons at various times of the year—January’s full moon is known as wolf but also the ice moon or old moon, and, hell, you may as well make up your own at this point.

But here’s the thing: It’s the damn moon. It turns reddish in a blood moon because we’re dealing with a total lunar eclipse: The sun sends light through our atmosphere, scattering short wavelengths like blue while longer wavelengths like red continue to the moon. Our trusty satellite waxes and wanes, moves slightly closer and farther from Earth due to its elliptical orbit, and gives us lunar and solar eclipses with predictable regularity. The moon is kinda clingy, and we love it for that.

Say you have a super blood wolf moon, which is super because it’s closer to Earth in its elliptical orbit and a wolf because it’s a January full moon. Now, I’m not going to sit here and put on a clinic about the origin of every moon nickname, but they drive astronomers crazy. “When I see all these headlines about the wolf blood super moon, I go nuts,” says Fred Espenak, scientist emeritus at NASA’s Goddard Space Flight Center. “Because it’s a total eclipse of the moon—that’s what’s not in the headline. It’s all these other terms to try to engage the public and get them to click stuff, but it kind of hides what the message is: It’s a total eclipse of the moon, which is a great term right there.” That, though, just isn’t good enough for some folks.

Another honorific that particularly irks astronomers: the supermoon. It’s a moon that appears bigger to us, because again, the moon follows an elliptical orbit. But really, it’s only 14 percent bigger, which is imperceptible to the human eye.

“I think the use of that term baits the public into thinking something great is going to go on outside,” says Espenak, “and they run out to see it and they’re disappointed because it just looks like a full moon. You can’t see the several percent that it’s larger or smaller.”

Oh, also. It wasn’t an astronomer who thought up the term supermoon, but an astrologer, who claimed the event is linked to seismic events and the weather. And astrology is about as far from science as a wolf on Earth is from a wolf moon. “Supermoon is a brand new term,” Espenak says. “It wasn’t anything that astronomers paid any attention to. Yeah, it was a closer moon, but it was sort of like, ‘Yeah, so what?’”

So OK, meh on supermoon. But that’s not to say that the human obsession with the moon—and naming full moons in particular—is altogether unreasonable, historically speaking. “If anyone has taken a walk under a full moon, it’s very bright,” says research scientist Noah Petro, also of NASA’s Goddard Space Flight Center. “You can understand why hunters might want to hunt by a full moon. It makes sense that it would mean something.”

Indeed, other nicknames for the moon are grounded in genuine utility. The full moon closest to the autumn equinox is known as the harvest moon, because before electricity, the glow afforded farmers the opportunity to work at night. Having a good grasp of the moon’s behavior would also help seagoing peoples divine changes in tides. A solid understanding of the moon’s phases has been pivotal for warmongering too, if that’s what you’re into: It’d be less than wise to launch a surprise night attack with a full moon over your head.

The utility of moon nicknames, though, has largely disappeared in this modern world. Except, that is, for using the moon as a grand educational platform. “It’s marketing,” says Petro. “Because everyone can go out and with their own naked eyes look at them and see the light and dark areas and make the most basic of observations. It’s unifying in that regard.”

The caveat being: If you build up a supermoon as something that’s actually super, you’ll sow disappointment. But the moon does offer a uniquely accessible platform for getting nerdy about science—you don’t need a lab full of equipment or even a telescope to enjoy it.

“One of the biggest practical values of total lunar eclipses in this day and age is simply to spark the interest of kids and students to go out and look at something,” says Espenak. “Especially when 90 or 95 percent of people live in metropolitan areas and you can’t see the Milky Way. A total lunar eclipse is something you can see from downtown in any big city.”

So yes, do go look at the moon, the fickle moon, the inconstant moon, that monthly changes in her circle orb. It’s a poetical, astronomical object; no need to gussy it up with fish and blood.

Matt Simon is a science writer at WIRED who, to be clear, loves the moon. But he also gets picky with semantics, as you might have noticed.

What can we tell you? No, really, what do you want one of our in-house experts to tell you? Post your question in the comments or email the Know-It-Alls.

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An App Built for Hurricane Harvey Is Now Saving Lives in Florida

Last Wednesday, Hurricane Michael slammed into the Florida Panhandle at 155 miles per hour, flattening neighborhoods, turning subdivisions into rubble, and plunging the coast into darkness. On Friday, Trevor Lewis packed up two trucks with crowbars, chainsaws, sledgehammers, ropes, walkie talkies, and five other guys from Cocoa Beach, where he lives on the east side of the state. As night fell they began the drive up into the worst of the wreckage. By 4 am on Saturday they were responding to their first call for help.

Lewis leads a self-funded search-and-rescue unit made up of off-duty police officers, firefighters, and EMTs. They call themselves Salty Water Rescue Services, and most of them have special emergency training on the high-speed powerboat racing circuit off Cocoa Beach. They’re one of hundreds of volunteer crews that showed up post-Michael to help first responders overwhelmed by 911 calls.

They used as their guide a service called Crowdsource Rescue, or CSR, which showed on a map individuals who might need help. On one of Salty Water’s visits, the crew met a woman whose house had a gas leak, so Lewis called local authorities. “It’s an eerie feeling to dial that number thinking someone’s going to come and it goes straight to a busy signal,” he says. The woman’s family had used CSR to request a wellness check on their relative.

The idea behind CSR started out simple: collect calls for help posted on social media, geolocate them, and route volunteers to the distressed parties. Basically, Uber for emergencies. It was a simple enough concept that a pair of developers named Matthew Marchetti and Nate Larson hacked it together in about six soggy hours in Houston last August while Hurricane Harvey howled outside. They expected it to help out a few families in their rapidly flooding neighborhood. By the time the storm was over, Marchetti says at least 25,000 people had been reached using the web service.

Turns out, armies of spontaneous samaritans can get a lot more done if technology tells them where to go. “The volunteers are going to show up no matter what,” says Marchetti. “We’re just trying to empower them to find more people safely and more effectively.”

What began as a one-off charitable coding sprint has since evolved into a five-person emergency volunteer mission control center. In their day jobs at a real estate company, Marchetti and Larson built maps. And that’s basically what the first version of CSR was. But as more hurricanes rocked the US in quick succession in late 2017—first Irma, then Maria—the pair piled on new features as problems arose in real-time. “We would change something on the site while there were 60,000 people using it, and if they didn’t like it, they’d let us know,” says Marchetti. “We had no master plan. It was all just reactionary.”

In January, when the hurricane season had ended, they found time for a more thoughtful redesign. The latest version, released two weeks before Florence hit, includes a mobile app and new safeguards. It allows users to tag hazards such as downed power lines, washed-out roads, and fast-moving water. It also gives CSR the flexibility to block off any areas that emergency management officials have declared dangerous for civilians, so that volunteers without proper training can’t see aid requests in those areas. Those precautions are to prevent volunteers from winding up needing rescuing themselves.

That’s less of a concern for volunteers like Lewis’s Salty Water crew, who used CSR for the first time during Florence, but who are no strangers to treacherous waters. After that September storm swept through, seven of their guys drove to North Carolina with a flat-bottom boat and two tuned-up jet skis with rescue sleds on the back. Over the course of a few sleepless days they checked in on nearly 100 people, delivering supplies, relaying messages to loved ones, and helping the unluckiest few to safety, including about a dozen shivering pets.

On the long drive back to Cocoa Beach they decided to formally partner up with the crowdsource platform. But when Michael arrived two months later with its powerful Category 4 winds, Lewis and his teammates had used up most of their vacation time responding to Florence, so they could only stay four days. While in the Panhandle they found they had service through AT&T, which Lewis says was the only carrier with coverage, and they switched to walkie-talkies when they hit areas with outages. If they couldn’t relay their findings back to worried families directly, they’d take pictures or video to share using their phones later. He says that his team reached more than 300 people using the app on this trip.

Yet the rescue that sticks in his mind most vividly wasn’t coordinated by CSR. It came about just by chance. She was the neighbor of someone whose family had filed a wellness request; Lewis spotted her as they were preparing to move on to the next ticket, and he asked if she was alright. It soon became clear she wasn’t. A widow in her 80s and frail, she lived alone. There was almost no food or water in her house. A section of her roof had been ripped clear of its frame. An immigrant from Thailand, she had no family in the US. No one was looking for her. She had one friend in the city, but with no phone service she couldn’t call her. “It was heart wrenching,” says Lewis.

His team reached the friend and waited until she came to pick the old woman up. Then they patched her roof and ripped out her wet carpet, collected her valuables and put them in a safe place to dry. They filed a new CSR ticket so that there was a record. And so that someone follows up. But the incident showed one of the app’s biggest limitations—on its own it can’t locate missing people. Being homeless, phoneless, family-less, or Facebook-less can make dangerous storms even more deadly in the days and weeks after the worst weather has passed.

That’s one of the reasons Marchetti’s team has started to layer social vulnerability indices and flood zones onto its maps of areas where hurricanes are expected to hit. As landfall predictions firm up, CSR places Facebook ads for its app targeted at people living in the path of the storm. They start making calls to churches and local community organizations, trying to raise awareness of the resource. “We want to play this role of equalizer, to come in and serve as a stopgap,” he says. “Not having the ability or the funds to evacuate doesn’t mean you don’t deserve to be helped.”

Early Wednesday morning, CSR had more than 1,200 open tickets for people not yet verified as “safe.” But as more people got cell service and volunteers cleared a backlog of requests, that number dropped to 548 by the end of the day. Marchetti says that doesn’t necessarily mean that all of those people really are missing and presumed dead. They could be staying with other friends or relatives and unable to communicate. “But we are starting to hit that point in every disaster where that number becomes more and more representative of the real thing,” he says.

A more official number could emerge as soon as Thursday evening, when the Federal Emergency Management Agency expects to complete its search and rescue operations. The agency has 10 crews and a dozen cadaver-sniffing dogs scouring the destruction scattered across Bay, Gulf, and Jackson counties, according to FEMA spokesperson Ruben Brown, reached Wednesday at the agency’s interim operating facility in Tallahassee.

State officials have not provided a count of the people currently considered to be missing. The state’s division of emergency management has an online system where people can report missing individuals as well as the locations of people who are trapped or running out of medications and other supplies. But Florida officials did not respond to questions about how those lists are used to coordinate searches. The state’s website also links to a searchable American Red Cross registry where people can list themselves as “safe and well” for their loved ones to find.

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This Robot Hand Taught Itself How to Grab Stuff Like a Human

Elon Musk is kinda worried about AI. (“AI is a fundamental existential risk for human civilization and I don’t think people fully appreciate that,” as he put it in 2017.) So he helped found a research nonprofit, OpenAI, to help cut a path to “safe” artificial general intelligence, as opposed to machines that pop our civilization like a pimple. Yes, Musk’s very public fears may distract from other more real problems in AI. But OpenAI just took a big step toward robots that better integrate into our world by not, well, breaking everything they pick up.

OpenAI researchers have built a system in which a simulated robotic hand learns to manipulate a block through trial and error, then seamlessly transfers that knowledge to a robotic hand in the real world. Incredibly, the system ends up “inventing” characteristic grasps that humans already commonly use to handle objects. Not in a quest to pop us like pimples—to be clear.

Video by OpenAI

The researchers’ trick is a technique called reinforcement learning. In a simulation, a hand, powered by a neural network, is free to experiment with different ways to grasp and fiddle with a block. “It’s just doing random things and failing miserably all the time,” says OpenAI engineer Matthias Plappert. “Then what we do is we give it a reward whenever it does something that slightly moves it toward the goal it actually wants to achieve, which is rotating the block.” The idea is to spin the block to show certain sides, each marked with an uppercase letter, without dropping it.

If the system does something random that brings the block slightly closer to the right position, a reward tells the hand to keep doing that sort of thing. Conversely, if it does something dumb, it’s punished, and learns to not do that sort of thing. (Think of it like a score: -20 for something very bad like dropping the object.) “Over time with a lot of experience it gradually becomes more and more versatile at rotating the block in hand,” says Plappert.

The trick with this new system is that the researchers have essentially built many different worlds within the digital world. “So for each simulation we randomize certain aspects,” says Plappert. Maybe the mass of the block is a bit different, for example, or gravity is slightly different. “Maybe it can’t move its fingers as quickly as it normally could.” As if it’s living in a simulated multiverse, the robot finds itself practicing in lots of different “realities” that are slightly different from one another.

This prepares it for the leap into the real world. “Because it sees so many of these simulated worlds during its training, what we were able to show here is that the actual physical world is just yet one more randomization from the perspective of the learning system,” says Plappert. If it only trains in a single simulated world, once it transfers to the real world, random variables will confuse the hell out of it.

For instance: Typically in the lab these researchers would position the robot hand palm-up, completely flat. Sitting in the hand, a block wouldn’t slide off. (Cameras positioned around the hand track LEDs at the tip of each finger, and also the position of the block itself.) But if the researchers tilted the hand slightly, gravity could potentially pull the block off the hand.

The system could compensate for this, though, because of “gravity randomization,” which comes in the form of not just tweaking the strength of gravity in simulation, but the direction it’s pulling. “Our model that is trained with lots of randomizations, including the gravity randomization, adapted to this environment pretty well,” says OpenAI engineer Lilian Weng. “Another one without this gravity randomization just dropped the cube all the time because the angle was different.” The tilted palm was confused because in the real world, the gravitational force wasn’t perpendicular to the plane of the palm. But the hand that trained with gravity randomization could learn how to correct for this anomaly.

To keep its grip on the block, the robot has five fingers and 24 degrees of freedom, making it very dexterous. (Hence its name, the Shadow Dexterous Hand. It’s actually made by a company in the UK.) Keep in mind that it’s learning to use those fingers from scratch, through trial and error in simulation. And it actually learns to grip the block like we would with our own fingers, essentially inventing human grasps.

Interestingly, the robot goes about something called a finger pivot a bit differently. Humans would typically pinch the block with the thumb and either the middle or ring finger, and pivot the block with flicks of the index finger. The robot hand, though, learns to grip with the thumb and little finger instead. “We believe the reason for this is simply in the Shadow Hand, the little finger is actually more dextrous because it has an extra degree of freedom” in the palm, says Plappert. “In effect this means that the little finger has a much bigger area it can easily reach.” For a robot learning to manipulate objects, this is simply the more efficient way to go about things.

It’s an aritificial intelligence figuring out how to do a complex task that would take ungodly amounts of time for a human to precisely program piece by piece. “In some sense, that’s what reinforcement learning is about, AI on its own discovering things that normally would take an enormous amount of human expertise to design controllers for,” says Pieter Abbeel, a roboticist at UC Berkeley. “This is a wonderful example of that happening.”

Now, this isn’t the first time researchers have trained a robot in simulation so a physical robot could adopt that knowledge. The challenge is, there’s a massive disconnect between simulation and the real world. There are just too many variables to account for in this great big complicated physical universe. “In the past, when people built simulators, they tried to build very accurate simulators and rely on the accuracy to make it work,” says Abbeel. “And if they can’t make it accurate enough, then the system wouldn’t work. This idea gets around that.”

Sure, you could try to apply this kind of reinforcement learning on a robot in the real world and skip the simulation. But because this robot first trains in a purely digital world, it can pack in a lot of practice—the equivalent of 100 years of experience when you consider all the parallel “realities” the researchers factored in, all running quickly on very powerful computers. That kind of learning will grow all the more important as robots assume more responsibilities.

Responsibilities that don’t including exterminating the human race. OpenAI will make sure of that.

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What sort of Team of professionals Quelled Colorado’s Enormous Spring Fire

I first heard about Colorado’s Spring Fire on July 1, when I was driving right back from the camping journey. My mom texted me from the woman home in Florida: “How close are these fires?” We pulled over to a sleep end, called up the federal catastrophe internet site Inciweb, and delivered her back a screenshot for the wildfire’s perimeter. It seemed far from my house on the Huerfano County line, enjoy it would need to get across impossible acres to come close. “Looks like we’re good,” I published back.

The Spring Fire may be the 3rd biggest into the state’s history. By the time I discovered it, the fire had already burned through significantly more than 40,000 acres. A plume of smoke unfurled right into a constantly replenished mushroom cloud. It absolutely was 0 % “contained,” and thus no human-made or natural barrier had been stopping the fire’s advantage from expanding. Costilla and Huerfano counties had evacuated around 2,000 households by July 2.

The fire had, by then, grown to above 56,000 acres, simply 5 per cent included.

We arrived at my cabin on the 3rd, hose at hand, knowing I couldn’t really assist the home yet not once you understand what else to do. The Spring Fire had bloomed to nearly 80,000 acres. The Department of Transportation closed the highway right on turnoff to my destination. Big-bellied planes filled with retardant crossed the sky overhead, their trip course traversing area of the bullishly-named Wet Valley.

That evening, the sunset, showing off the smoke particles, was spectacular. The hills all appeared to be these people were on fire—even those that weren’t.

Forty kilometers south, from their base into the Huerfano county seat of Walsenburg, friends called Rocky Mountain Incident Management Blue Team had taken fee of taming and containing the north element of the blaze; another team, Rocky Mountain region Incident Management Team Black, had been assigned to cope with the southern part. To direct the crisis response personnel—nearly 1,800 people worked the fire at its peak—the team needed plenty of data, a tightly wound plan, plus weirdly Office Space organizational structure.

Fire behavior analyst Shelly Crook, Blue Team, is paramount to that endeavor. She’s in control of figuring out just what the north percentage of the fire is performing and what it will do. Each morning during the Spring Fire, she has woken up in the sleep she keeps in the rear of her vehicle. By 5 am, she turns up on ad hoc event demand post—at John Mall High School—to see if an infrared plane sought out immediately. “we take stock of that information, and see where the fire relocated through the past border, to observe much it’s grown,” she states.

This is Crook’s fourth fire this present year, so when we spoke, it absolutely was her 60th day into the industry (she is “retired”). “each time a fire starts, you type of drop every thing,” she states. So did others Western-based people of her group, whom converged quickly on Spring Fire following the call went from Geographic Area Coordination Center, which assists mobilize emergency resources.

At their short-term demand post in Walsenburg, they will have all the divisions a small business might, including finance kinds, HR reps, and PortaPotty procurers. Every day, a planning team writes out a 30-page packet of data about every thing a firefighter might need, from where frequencies to make use of for communications to what the current weather is likely to be like.

For that second component, there’s a separate meteorologist. He sits next to Crook included in a product that prints more than 150 maps every day—county roads and structures, topography from United States Geological Survey, GPS places from the ground. After Crook checks regarding infrared journey, she gets information from the woman officemate towards general humidity recovery—she’s hoping so it increased significantly immediately. “If it’s good, the fire will not be active as early,” she says. They dig into data from weather stations—permanent ones and seven RAWS, remote automated climate systems, specially set up at critical Spring Fire locations—informing a forecast Crook can have during early morning meetings.

That’s just the beginning of Crook’s time, which she dedicates to predicting—as most readily useful she can—the north fire’s next techniques.

That sort of information fundamentally makes its option to the community—via in-person meetings and day-to-day one-sheets. The public document released in the Fourth of July waffled in its optimism. “Overnight, calmer winds and lighter fuels slowed fire development over the south and eastern flanks for the North Spring Fire,” it said. “Fire task increased along the northwest flank near Sheep hill because it moved into dry, mixed timber.”

By the afternoon, information from an infrared flight unveiled the fire’s total extent to be 95,739 acres. The preevacuation zone, shown for a Google map, now extended to two miles from my house. South, the view through the porch had morphed as a wall surface of smoke. I did so what exactly on a preevacuation checklist, in the event: defeat curtains, close and unlock windows, switch off the gas, turn on the lights, bring everything in from the porch. We utilized the hose to fill buckets with water and place them around the house. I did son’t need to (pre-pre-evacuation is non-evacuation), but my nerves had history: once I was 12, a Florida wildfire destroyed 30 structures within my rural area, and my children didn’t escape with time: On our course down the highway, the trail was blocked by fire, and we spent hours in a landfill entryway, surrounded by flames.

You will find concrete steps specific citizens can take to be much more firewise generally speaking: have the gunk from gutters, clear defensible no-brush room around home, keep lumber heaps and propane several dozen foot away, display screen all spaces so embers don’t sneak in. But sometimes, despite most useful efforts, nature wields an top hand. By this aspect inside fire, in the 4th, a lot more than 100 domiciles have been lost.

At six p.m., I tuned in the community briefing, streamed via Facebook Live from the tiny city of Los Angeles Veta.

“Happy Fourth of July, everybody,” stated David Detray, fire chief of this La Veta area. “i wish to supply this picture of your La Veta Fire Protection District personnel.” On screen behind him, eight firefighters, two keeping US flags plus one holding a giant teddy bear, endured in a V, apparently paused in a march via an otherwise empty road.

This image had been from the primary road in Cuchara, an 8,500-foot-high village that had been evacuated. Citizens couldn’t hold their annual Independence Day parade, which they’ve done for a few 50 years. Therefore the firefighters took a moment to stage a miniature, type of morbid one for them.

“These are your individuals,” Detray said.

Inside Blue Team’s enhance, operations area chief Chris Zoller noted where in actuality the fire was “pushing,” expanding its side by 6,000 to 7,000 acres. He moved on to a place, high in woods, where the fire would quickly strike a road and transfer to a region called “Paradise Acres.” “This will probably be our trouble area for the following twenty four hours,” he states.

After presenting the woman initial forecast at Rocky hill Incident Management Blue Team morning meetings, Crook goes back into prediction mode. She feeds information into models that forecast the fire’s behavior, an element of the Wildland Fire choice Support System—a powerful tool that gobbles up information from numerous sources to support wildfire strategy-making. A number of the information it sucks in originates from a federal program called Landfire, which can help firefighters inform what exactly is growing regarding affected ground, exactly how it burns off, and exactly how topography flows beneath it.

Although the help system itself is significantly newer, these federal prediction models will be in development for about 30 years. “They’ve morphed and start to become better made,” states Crook. Crook has two favorites: the three-day perimeter projection, as well as the fire spread probability prediction. “It informs me throughout the next seven to fortnight what is the probability of the fire impacting any point on the landscape,” she claims.

But simulations can only just simulate. Therefore in the afternoon, Crook heads out using the firefighters and returns with ground truth. She can feed certain information back in the models—essentially calibrating them to the North Spring Fire. Nevertheless, it is not really a perfect system. “There’s a mystery on every fire,” she says.

There’s also a bit of logistical challenge: not merely where you should place the PortaPotties but additionally how to get the people and heavy gear you’ll need. Once the Spring Fire began and Rocky hill Incident Management Blue Team arrived regarding the scene, the fire had been going fast. They needed seriously to work. Nevertheless the remaining portion of the state additionally was burning. “It took like four days before I happened to be in a position to have the resources to even come near what we needed seriously to assist begin suppressing the fire,” states Jay Esperance, the Blue Team’s event commander.

But that, he states, is life. “There’s only countless firefighters and equipment, so we were the newest show in town.”

After the heavy machinery did arrive, it was significant: At one point, there were 17 bulldozers to clear out lines of land to retain the blaze; two “masticators” to chew up brush along with other small-diameter material; and skidders to move logs.

In addition to ground-bound resources, the Spring Fire fighters also took toward sky. They used planes and helicopters, although Zoller calls them “fixed-wing” and “rotor-wing” aircraft. The planes that combated this blaze—stashed in fire-prone areas across the country during the volatile season—included single-engine leaflets and VLATs: Very Large Air Tankers. Both carried fire retardant that spilled from their bellies like paintball powder. The helicopters took care associated with the H2O. “Water is for the instant have to cool things down,” says Zoller. Retardant, meanwhile, slows the fire down.

Over the winged art flies an “eye in the sky”: an in-the-air air-traffic controller. “He directs all the traffic, and keeps the rotor-wing out of the way associated with the fixed-wing,” states Zoller.

Since the last thing anyone requires during a wildfire is really a plane crash.

At a July 11 evacuee conference in Fort Garland, which as soon as hosted a functional armed forces fort, a southern-section public information officer took the stage. “We’re going to start off with some good news,” she said. The whole fire ended up being 83 % included, and also the southern border had been entirely in order. Team Ebony ended up being going house.

Crook’s Blue Team took over the entire procedure, which, two times later on, had been 91 % contained. The north edge of the fire stayed far sufficient from the house that we never ever had to evacuate, and the Blue Team soon packed up, leaving operations to regional groups on July 16. On the way to avoid it of city, they decontaminated their gear, to avoid transporting invasive species, “weed-washing” the outside with high-pressure hoses and burning the insides of tanks with 140-degree water.

The path to recovery is long and difficult, just like the roads that climb up through the high hill passes here. Based on the Denver Post, the area has taken inside tragedy cleanup nonprofit Team Rubicon to aid, and a team called the Voluntary businesses Active in Disaster will help, too. More than 225 structures had been destroyed, in accordance with a July 18 report through the nationwide Interagency Coordination Center. The thing that was forest is charred trunks, scorched earth.

No matter simply how much information anybody or any satellites just take, it’s impractical to anticipate what will take place next the communities. However if one of Crook’s models could offer imperfect post-fire forecasts, it might most likely say that life will slowly develop right back toward normal.

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The Hairy Problem With Drug Testing and Chemical Analysis

Keri Hogan was about to become a police officer when she submitted a sample of her hair to the city of Boston for testing. The city, in turn, gave it to a company called Psychemedics, which washed the hair, dissolved it, and used gas chromatography and mass spectrometry—chemical analysis techniques—to check it twice over for evidence of cocaine. Hogan’s hair tested positive.

Boston police officers whose hair tests positive for drugs usually have two options: admit their substance abuse problems and agree to a stint in rehabilitation, or relinquish their position. But Hogan, who finished her police training prior to 2005, says that she has never used cocaine; when she sent her hair to a private company for more testing, it came back negative. Now, she and nine other black police officers are suing the city of Boston, saying that the practice of testing hair for drugs is discriminatory. Because of the chemistry behind the test, they say, it unfairly targets dark hair. The bench trial for the case began on March 12, and may have long-lasting consequences for the future of drug testing.

The hair test was developed in the late ‘60s, when an Austrian chemist named Werner Baumgartner decided to piggyback on the work of his wife. Annette Baumgartner was working at the Aerospace Corporation, trying to figure out what toxins might be ingested by onlookers during a shuttle launch, and Werner realized that he could look for drug exposure with the strategies she developed. Substances floating around the blood eventually get incorporated into the hair as it grows—either through tiny blood vessels or the oil and sweat glands that surround the hair follicle—and drugs found inside the hair itself, he realized, would be harder to cheat on than urine or saliva tests. They’d linger longer in the sample, too.

Baumgartner demonstrated the full force of the procedure when he used it to identify opiate painkillers in the poet John Keats’ hair, which the lab received from a rare book collection at the University of Texas at Austin. After a Time Magazine story about the Keats test, several businessmen approached Baumgartner with the intent to start a company, and Psychemedics was born.

In 1985, a navy chemist named David Kidwell was tasked with studying the test’s effectiveness—and soon, he began to have reservations. In 1993, he published the results of an experiment in which he soaked the hair in a mix of cocaine derivative and water, then washed it repeatedly before performing the drug test. Despite his attempts to remove the external contamination, the tests came back positive.

Baumgartner argued that Kidwell had used the wrong wash procedure; the test was still reliable. But Kidwell and his research partner lashed back: “At the current level of understanding, the presence of drugs in an individual’s hair indicates exposure to that compound,” they wrote. “Attempting to expand this observation into the suggestion of use or long-term abuse of a drug would seem unwarranted at this time.”

Thus began a scientific back-and-forth that has continued to this day. Scientists like Kidwell argue that both external and ingested cocaine binds to melanin in the hair. People with black hair have more melanin in general, but especially more of the subtype eumelanin, which studies have shown binds particularly well with cocaine and amphetamines. (Gray hair doesn’t have much of any type of melanin, so if you want to get away with using cocaine, aging may be your best bet.) And researchers disagree over whether hair can ever be washed clean of any and all drugs it could have come into contact with from the outside.

Despite those questions, both the Boston and New York police departments, 10 to 15 percent of Fortune 500 companies, court systems, federal reserve banks, and numerous high schools still use the hair test. The FBI phased it out in 2009, then re-implemented it in 2014. About 200,000 drug tests are run on hair in the US every year.

Meanwhile, research from Kidwell and other scientists has shown that both the amount of melanin in the hair and some chemical treatment involved in styling makes a difference in how much contamination the hair can absorb. Kidwell has appeared as an expert witness in many lawsuits about the validity of the tests over the last 20 years.

“I am not sure there will ever be absolute settlement,” says Bruce Goldberger, the chief of forensic medicine and a professor of toxicology at University of Florida Health. He was the first person to find a way to identify the difference between heroin and morphine in a drug hair test.

The law has generally sided with Pyschemedics. But in 2012, the state of Massachusetts ruled that the hair test alone is not enough to terminate employment. Six police officers were reinstated in their jobs, and Hogan finally graduated from the police academy. She and the other plaintiffs are now in a federal court, asserting that the test is specifically discriminatory.

The stakes are high. Everyone wants police officers and other public servants to be as alert as possible, especially in dangerous situations. The FDA has approved Psychemedic’s hair tests for eight drugs, not just cocaine. Raymond C. Kubacki, now CEO of Psychemedics, says that scientific accuracy is the company’s top priority. “Psychemedics is a pioneer in the washing technique,” he says. “It’s important that we don’t have anyone falsely accused because of outside contamination.”

But the hair test puts an undue burden on African Americans, and especially African American women. Common hair styles mean that simply cutting a chunk of hair for the test can be harder for these women. And adding extra hurdles for this group to join and stay in law enforcement could cost the city: Male police officers cost the government between two to five times more in legal fees than female police officers—and only about 13 percent of policy officers identify as women.

Though Hogan has already been reinstated, the risk of future false positives still looms over her peers, both in and out of law enforcement. The result of her discrimination case, which is still ongoing, should inform the use of a potentially flawed test—and hopefully spur the development of others.