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Valdai Discussion Club The Valdai Discussion Club was established in 2004. It was named after Lake Valdai, which is located close to Veliky Novgorod, where the club’s first meeting took place. The club’s goal is to promote dialogue between Russian and international intellectual elite, and to make an independent, unbiased scientific analysis of political, economic and social events in Russia and the rest of the world.
Energy Investing News | Investing News Network Energy surrounds us in our everyday lives from the moment we flick on our lights in the morning to the time we settle into bed. We use it to warm our homes, drive to work, communicate and much, much more. Different tasks require different types of energy. For example, oil and gas are often used to create heat, while nuclear reactors use uranium to generate electricity. Because energy is so necessary to all aspects of life today, investing in energy is becoming an increasingly popular choice for investors. But what kind of energy is the best to invest in? Different investors have different needs, and it’s important for those interested in the energy space to do their due diligence. To help investors make the right decision, we’ve put together a brief overview of the oil, gas and uranium markets — all are popular sources of energy today, and may be good investment choices. Investing in energy: Oil and gas Crude oil and natural gas have been key sources of energy for years, and today they are ubiquitous sources of energy throughout the world. Both occur naturally, and are in a class of chemicals called hydrocarbons. The two are generally found in close proximity to each other deep underground in rock formations; exploration companies drill wells to find the fuels, then extract them. Those watching the oil space know that oil prices are often volatile. Indeed, in just the past decade oil prices have seen an incredible range — prices soared past $140 per barrel in 2008, then crashed steeply from the end of 2014 to the beginning of 2016. At their lowest, prices were below $30, though since then they’ve recovered to trade between about $45 and $50. Such price swings are the result of a variety of factors, and in this article Forbes contributor Michael Lynch does a good job of outlining some of them. For example, he notes that oil consumption data is often not reported in a timely manner, and comments that the Organization of the Petroleum Exporting Companies, better known as OPEC, can influence prices. Even the weather can have an impact. Gas prices have also been volatile in the last decade. Like oil prices, gas prices reached their highest point in the last 10 years in 2008, when they were above $13 per MMBtu. Their lowest point of below $2 came at the beginning of 2016; currently gas prices are around $3. As with oil prices, gas prices are affected by a number of factors. However, weather has more of an effect on gas prices than it does on oil prices. Given that volatility, investing in oil and gas can be daunting. But for some investors it’s an exciting prospect — after all, while both spaces have seen incredible lows in the last 10 years, they have also seen incredible highs. Click here to learn more about how to invest in oil and click here to learn more about gas investing. Investing in energy: Uranium Uranium is a heavy metal that occurs in most rocks in concentrations of 2 to 4 parts per million, meaning that it is as common in the Earth’s crust as tin, tungsten and molybdenum. It is a cleaner and more efficient source of energy than oil and coal, and as noted is used to power nuclear reactors. Despite having advantages over other more polluting fuel sources, uranium has some downsides. Most notably, nuclear reactor accidents can be devastating. For evidence, investors need look no further than the 2011 Fukushima disaster in Japan — a major earthquake in the area caused a tsunami that ultimately led to meltdowns at three reactors and to the release of radioactive materials. After that incident concern about nuclear power increased, with Germany even announcing plans to phase out nuclear power. However, uranium is by no means out of the picture as a source of energy. Japan is slowly bringing its reactors back online, and has added further safety mechanisms to reduce the likelihood of future disasters. Overall, more and more reactors are being built worldwide — as of February 2017, there were 440 reactors operating globally, and over 60 being constructed. Even so, uranium prices are currently in a slump; in fact, 2016 was one of the toughest years for uranium in recent memory. The uranium spot price hit a 12-year low of $18.75 per pound that year, an unexpected turn of events for many in the sector. Fortunately, many experts believe that the bottom is now in, meaning that the uranium price will rise moving forward. While it may still be awhile before uranium reaches its high point of close to $140, investors who believe in the future of nuclear energy may want to consider investing in uranium. For more information on how to invest in uranium, click here.
Neon John''s Home on the Web Neon John''s own little pothole on the information superhighway. I deal with science, engineering, neon sign making, RV camping, high performance cars, things that go boom, good food, power generation and many other things
Sancerres at Sunset | Travel. Home. Repeat. Solo travel is daring, liberating, rejuvenating. It feels a little bit naughty, like getting away with something. You go when you want to go, where you want to go. You eat when you want to eat, what you want to eat. You can sleep when you want, and get up when you want, and you get the whole bed. You can stay at a luxury hotel or a campground; it's your choice. You get to indulge your own interests, no matter how nerdy, or boring, or eclectic someone else might think them. If you want to plan your trip around seeing a historic museum, a national park, and a baseball game, you can. You don't have to convince anyone why they matter, and you don't have to compromise. You can't live this way all time, and it wouldn't be good for you anyway. It's better to have people in your life, people you want to put first. But every once in a while, it's good to get away from others, so you can restore yourself. It's rare, and that's what makes it special. This post contains affiliate links. For more information, click here. Road trips are adventurous, raw, and so intriguing they've inspired movies from It Happened One Night to Thelma & Louise. You have flexibility. You stop when there's something interesting to see or do, or when you just want a break. You stay in one place as long as you want, and you move on to the next one whenever you want. You don't have a plane to catch, and you don't have to be molested to get on board. Your car is your cocoon; you can load it with whatever you're going to want. But the trip isn't about the car; it's about you and the road and where the road takes you and where you choose to follow it, eyes wide and mind open and heart full of excitement. And when you put solo travel and road trip together, it's magic. It's a rare and nurturing oasis of freedom in our over-regulated, over-scheduled, over-intrusive, over-judgmental modern world. It's life on your terms. And good magic needs a lot of behind-the-scenes planning and preparation. After five fabulous weeks alone on the road, here's my comprehensive list of Solo Road-Trip Essentials 1) A Loose Plan Freedom and flexibility are the glory of the solo road trip. You don't want to over-plan. But you have to have some idea of where you want to go and what you want to do. Make a short list of your top things to do. Mine included: Southfork Ranch in Texas and a Salem Red Sox game in Virginia, as well as the Everything Food Conference in Utah. I also wanted to go to all five of the contiguous states I hadn't already visited (North Dakota, South Dakota, Wyoming, Idaho, and Oregon). Rough draft your route. You can do this online or on a paper map or both. Plot your to-see points, and trace a route that covers them. Use it to gauge how long it should take to drive from point to point and to plan stops on the way. But remember: it's just a rough plan; adjust it continually as you go along. At the end of every driving day, after I checked in to my hotel room and cleaned out the car, I got online to figure out where to stop next and what I'd like to see on the way--a small museum, a historic site, a local park. I made reservations if it looked like rooms were filling up, but the best driving days were the ones when I knew I could go until I wanted to stop. Decide how much you want to drive daily and weekly. I settled on roughly six hours per day, five days per week. I thought this would be a fairly light schedule, especially after years of driving from northern Virginia to my parents' home outside Boston. I've seen some travel bloggers write about driving 12 hours in a day, and great for them if that's what they like. But for me, the point of the journey was the journey, and I wanted to spend more time exploring out of the car than in it. I also knew that I'd have daily and weekly blogging responsibilities, that I like wearing frequently washed clothes, and that God gave us a weekly day of rest for a reason. As it turned out, even this light and flexible schedule became pretty tiring after five weeks, and I started slowing down by the time I made it back to the southeast. Write up a nightly to-do list. When you're road tired, and possibly hungry, you don't want to keep asking yourself, "What do I need to remember to do next?" Make a fool-proof list. Mine included: Unload and tidy up car. Charge electronics.Research next stop; make reservations. Jot down notes for upcoming blog posts. Edit photographs.Check in on social media: Instagram, facebook, twitter, PinterestRespond to email. Outline a basic daily schedule. You can make day to day changes when they're called for, but having a schedule will help you stay on track. Mine looked like this: A Day in the Life of a Travel Blogger on the Road 5:15am: Alarm goes off. Hit snooze. Visualize day ahead.5:24: Alarm goes off again. Get up. Make coffee. Do crunches.5:30ish: Over coffee, go online and make sure nothing catastrophic happened overnight, e.g. the blog didn't get hacked, Trump didn't tweet the nuclear codes, etc.5:55: Don exercise clothes and go outside or to hotel gym to work out.7ish: Shower and dress for the day. Comfy casual clothes for driving. No make-up, just eye cream with sunscreen, tinted moisturizer with sunscreen, lip balm with sunscreen, curled lashes, and body lotion with sunscreen. Keep concealer, powder foundation, red lipstick, and 3-in-1 blush, highlighter, and lip tint at the ready just in case.7:45ish: Protein breakfast, no simple carbs. Grab an apple for lunch.8:15ish: Pack, load car, swap out CDs. Check out of hotel. (Even though most hotels email a receipt, I always ask for a print-out at the desk and look it over before I leave, just in case.) 8:45ish: Hit the road. Stop along the way at an interesting site or two. Eat the apple for lunch.4-5pm: Check in at next hotel. Complete task list.6ish: Dinner. Usually a low-carb charcuterie plate in the room, occasionally a juicy burger from room service, out to a local Mexican place if in the southwest.7ish: Play at casino, read, watch TV.9: Skin care: oil-based cleanser, creamy cleanser, toner, serum, eye cream, neck cream, moisturizer, body lotion. Bed. Prepare for departure. An organized approach to a few simple tasks will help make your departure much smoother. Set up a packing station a few days ahead of time. The earlier you can gather up the things you'll be taking, the less stressed you'll be as departure day nears. I used my small den for this, so that the growing piles wouldn't drive me crazy. Pay your bills. Set up automatic payments. Don't forget: housing--mortgage, rent, condo feesinsurance--health, home, autocredit cardsutilities (Suspend your cable unless you'll want to access it from the road.) Clean thoroughly. You don't want to return to an untidy home (and you don't want any multi-legged squatters moving in while you're away). I set aside a full day for this. Plan for a short first day of driving. Leaving can be the most stressful part of a trip. Give your extra self time to double-check that you've packed the prescriptions and turned off all the appliances (you can even snap pictures of them if you'll want the reassurance). Make a one-night reservation at an inexpensive highway hotel; just make sure it's far enough away that you won't be tempted to turn home to get that one last thing you wish you'd packed. Prepare to come home. This is part of preparing to leave, so that it won't haunt you near the end of the journey. I brought along a re-entry folder, for some paperwork regarding things I'd need to handle upon my return. Toward the end of the trip, I also planned for a short last day of driving, so that if there were any problems at home, I'd have time and energy to cope with them. I reserved what I hoped would be a luxury hotel room for my last few days on the road, so that I'd be coming home feeling rested and so that the last stretch of the trip wouldn't seem like more of a downer than necessary. Be flexible. You know that plan I had to see five new states? I only got to three of them before I decided that the last two would just be too much for this trip. On the other hand, I visited lots of places that I would never have planned ahead, just because they looked intriguing, from the Museum of Space History in New Mexico to the Grand Ole Opry in Nashville. Go with the road and go with your gut. 2) A Priority on Safety You matter. Your safety matters. Take it seriously. Have your car checked out before you leave. I did this a few weeks early so there'd be time for any necessary repairs. Bring: A navigation system. Make sure your maps are updated.A road atlas. Electronics fail. Books don't. Have a back-up.Coolant, oil, and jumper cables. A road safety kit.A First-Aid kit.A Swiss Army knife. Membership in an auto club.A spare key.Any needed medications. I always travel with Extra-Strength Tylenol for headaches, Advil for muscle aches, and Claritin for allergies. (I'm happy to report that I didn't need the Tylenol.)Your Passport and of course your driver's license, registration, and proof of insurance. Establish your safety rules. It's easy to make wrong decisions in the moment when you don't have firm rules in place. Mine were: Never let the gas tank go below 1/2 west of the Mississippi or 1/4 east.No hiking alone in large parks. Marked trails in small parks were okay. No alcohol until the car is parked for the night. I also had a soft rule of only one glass of wine per night, which I bent twice for craft cocktails. But most nights, the only thing I drank was water. No stopping on the shoulder for photographs, no matter how beautiful the scenery. Stop only at designated overlooks and turn-outs. You might notice a few places in my narratives with metaphoric descriptions of landscapes and no pictures to match; that's why. 3) Lodging that Suits Your Style Lots of travellers are comfortable at hostels and campgrounds. If you're one of them, you might want to skip this part. I prefer luxury hotels, but they're not practical for one-night stops along the road. For road trips, I like a combination of casino, casual-convenient, and extended-stay hotels. Casino Hotels Casino hotels are a great option for women travelling alone, because: They're safe. There are cameras and security personnel everywhere. In casino towns, you can even walk alone at night, because they're all lit up, and there are lots of cops around. They're inexpensive. They're not in business to make money on the rooms, so you can usually stay for cheap or even for free. They usually have reasonably priced or even complementary valet parking. The big ones have rewards credit cards without annual fees, making them a better bet than most travel credit cards, and you also earn points redeemable as cash with their player's cards. There's always something to do. There are restaurants and bars, spas and pools, and of course table games and slot machines. These casino brands have hotels in multiple locations: Caesars Caesars has properties all over the country. Along with its namesake, its brands include Horseshoe, Harrah's, Bally's, and others. Its properties range from luxury to well-at-least-it's-comped. The two nicest hotels where I stayed on my recent road trip were Caesars properties. Its rewards program is Caesars Rewards. MGM MGM is another large network, with properties concentrated in Las Vegas and then scattered primarily through the South and the mid-Atlantic. Most have unique names. They range from luxury to mid-scale. Its rewards program is MLife. Boyd Boyd Gaming has 18 midscale properties in Nevada, the South, and the midwest. Most have unique names. Its rewards program is B Connected. El Dorado El Dorado has 26 midscale properties in the South, the West, and the midwest. Along with its namesake, its affiliated brands include Tropicana, Isle, Lady Luck, and others, with independent rewards programs. As of this writing, El Dorado has announced plans to acquire Caesars next year. Casual-Convenient Hotels These properties tend to be easily accessible from the road. They're often called limited-service hotels, because they lack upscale amenities like spas and bars, valet service, and shopping esplanades. But they do have what long-term road trippers want: big open parking lots, gyms, breakfast in the morning and cookies at night and coffee and tea all day, and usually microwaves and refrigerators in the rooms. My go-to brand has long been Hampton by Hilton, because they're ubiquitous and reliably clean and comfortable and reasonably priced. Hilton's rewards program is HHonors. I did have one nice stay at the Country Inn & Suites by Radisson in Northwood, Iowa. Two big plusses for this brand are cookies all day and a wonderful lending library system whereby road trippers can take a book at one property and return it at the next. Radisson's frequent-travel program is Radisson Rewards. Extended-Stay Hotels For longer stops, I prefer extended-stay hotels. Like their casual-convenient counterparts, they offer complimentary breakfast in the morning and sometimes receptions in the evening. The rooms have fully equipped kitchens with real dishes and glassware, things you miss after weeks on the road. My favorite brand is Residence Inn by Marriott. They're reliably clean and reasonably priced. The gyms and laundry rooms are large and well equipped. The televisions are Netflix-ready for use with your own account. They have a complimentary same-day grocery-shopping service. And there's microwave popcorn in the kitchen, which I never have at home, but can't resist when I'm curling up with a Netflix flick after a long day of driving or writing or laundry or all three. Marriott's rewards program is Bonvoy. 4) Food In my vision for the trip, I thought I'd be alternately dining at local haunts and having happy-hour bites with my single glass of wine at hotel bars. In reality, more often than not, I made myself a small charcuterie board in the hotel room, washed down with water, after I'd finished the tasks on my to-do list. Here's my list of groceries to pack: bottled water half-and-halfcured meats tunacheesesdips cruditesberriesplastic platesplastic cutlerypaper napkinsZiploc bags (more than you think you'll need)a small bottle of dish detergentcold packs 5) A Wardrobe for All Seasons Be prepared for all kinds of weather. After five weeks ranging from hot sun to wet snow (including both in Salt Lake City), here's what I wish I'd packed: Footwear comfortable pumpsversatile, comfy sandalsslip-on sneakershiking bootsrunning shoes flip-flopsslippers8 pr cushy gym socks4 pr ankle socks4 pr thick slouch socks2 pr hose/tights Basics I love Talbots for inexpensive basics that are easy to notch up with the right accessories. 1 comfortable skirt1 pr comfortable cotton pants1 pr designer jeans1 pr mom jeans2 pr cropped pants or Capris3 pr modest shorts4 long-sleeved tops8 short-sleeved tops Dresses 2 day-to-evening dresses3 casual dresses, including at least one that can double as a swim cover-up Outerwear 2 cardigans1 blazer1 windbreaker1 pr winter gloves Hats 3-4 wide-brimmed hats2-3 baseball caps1 warm knit hat Accessories 3 scarves3 belts: wide, medium, thin Activewear 2 pr gym shorts1 pr sweats1 modest bathing suit1 bikini Sleepwear 1 comfy cotton nightgown1 pr cozy pajamas 1 modest silk robe Jewelry I hate worrying about losing my jewelry when I travel, so I bring only a few good pieces that I can wear together: 1 pr comfortable earrings1 simple necklace3 rings3 bracelets1 brooch Laundry Supplies lg mesh laundry bagdetergentbleach podsdryer sheets 6) Bags and Baggage 1 sm. crossbody1 med. crossbody1 lg tote1 duffel bag, for 2-3 days worth of clothes1 lg suitcase, for clothes not presently needed1 picnic basket1 sm. soft-sided cooler that fits inside the picnic basket1 laptop bag1 camera bag packing cubes: Not only do they keep your suitcase organized, but they also help you keep tidy in hotel rooms that inexplicably don't have dressers with drawers. a collapsible wagon: If you take one piece of advice from this whole long post, take this one. I bought my little blue wagon to carry wine-and-cheese picnics to outdoor concerts and the beach. I use it more to lug groceries up to my 11th-storey condo. But it was a lifesaver not only for loading and unloading the car but also for carting the wash to and from hotel laundry rooms. 7) A Fitness Plan You have to be intentional about fitness or it will be too easy to blow off. I resolved before I left to spend an hour exercising every morning before I hit the road, unless I knew I'd be doing significant movement during the day. Most days I either used a treadmill in the hotel gym or went for a long walk in the fresh air. I also did ten crunches every morning while the coffee was brewing and lifted weights once or twice each week. I brought along my favorite work-out DVDs, yoga mat, hand weights, ankle weights, and resistance bands--and didn't take them out of the car once. The good news: I hit my 10,000-step goal every day, and usually far exceeded it, according to my fitbit, and I lost eight pounds. The bad news: It wasn't enough; I lost muscle tone because I didn't do enough strength training. If I'd known then what I know now, here's what I'd do: every morning: 10 crunches and five burpees5-6 times/week: 3-4 miles jogging or brisk walking3-4 times/week: strength training when possible: climb stairs 8) Money Rewards Credit Cards There are a lot of rewards credit cards out there, and it's worth selecting a few that will help maximize what you can reap back from your travels (and put toward your next journey!). Here's the balance that worked for me: 2 cards that pay an unlimited blanket rate of at least 1.5 percent (a go-to card and a back-up). Citibank's Double Cash card pays 1 percent back when you make purchases and 1 percent when you pay your bill; it has no annual fee. 1-2 casino branded cards. Caesars offers a Visa with benefits that include Caesars Rewards Platinum status (the lowest elite tier) for $5,000 in annual spending. It has no annual fee, and even low rollers can get nice rooms comped with it. If your credit is good enough, you may qualify for a Visa Signature, with its additional travel perks, like room upgrades and late check-out. 2-3 cards that pay at least 4 percent cash back for some of your major road-trip expenses. The Discover it Card offers a blanket 1 percent cash back on most items, and 5 percent on quarterly categories, like restaurants and gas stations, on up to $1,500 in purchases. It has no annual fee and will double all the cash back you earn during your first year. Cash Some people don't feel comfortable with a lot of cash; some people only feel comfortable with a lot of cash. Bring the amount you feel comfortable with. Just make sure to carry enough $5s and $1s for tips. And bring quarters for laundry; most hotels can sell you a roll, but I wouldn't count on it. Don't forget your ATM card(s). 9) Electronics and Entertainment Your list will depend somewhat on your personal preferences, but here are my road-trip must-haves: phone and chargers: I like my iPhone SE because it's small but has a good camera.earbuds: I save the ones they give out on planes and use them to catch up with the morning news while I exercise. laptop and charger: The only laptop I want to take on the road is my MacBook Air, because it's thin and light.cameras, chargers, cables, tripod: My big camera is a Nikon D3100 DSLR, which I often use with this tripod. I use my Sony DSC-W70 when lugging a DSLR is impractical; it's lightweight and takes good videos. a variety of things to listen to: I brought around 100 CDs, from classical to Christian (which was great for singing along in praise of God's creation), and swapped them out in the mornings before I hit the road, and I still got bored with them. I would add educational CDs from the Teaching Company and some Rosetta Stone to polish up one of my rusty languages. There are also podcasts and audio books, if you enjoy them. reading material: I like to bring a lot of magazines when I travel, because I can leave them for someone else to enjoy and lighten my load as I go. On the other hand, I usually limit myself to one book, because they're heavy. journal(s)/notebook(s): It's easy to forget things on the road, whether it's how your heart soared seeing a family of deer scamper through the Black Hills or the tour hours at Southfork Ranch. Write them down. I love these notebooks. 10) The Right Mind-Set A solo road trip is a wonderful opportunity, but it can be physically and emotionally grueling. Driving hours a day for weeks is tiring, and there's no one to take the wheel when you want a break. Things will go wrong. You may get lost. I took an hour-long detour through the Mojave Desert in California because I overshot my turn to Laughlin, Nevada. You may get scared. I've developed a weird phobia of overpasses that are so high I can't see the ground. You may get lonely. I missed my late mother, with whom I took my previous cross-country road trips, and I cried from Arizona to New Mexico. You have to set your mind to accept these kinds of things before you go. You have to allow yourself to feel emotional swings without being overwhelmed by them. You have to believe that the rewards are worth the risks. (And if you can't, that's okay, and it's better to realize it; long-term solo road tripping is not for everybody, and there are lots of other ways to travel.) I never questioned. No matter how sad or scared I became, I loved being on the road, and being on my own. And I slept better than I have in years.
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| Follow us on Our Journey To Smile ! Join us to say #Enough! | Follow us on Our Journey To Smile ! Join us to say #Enough! Love Letter 1: Having Communal Fun in the Afghan Mountains so as to Stay Strong Love Letter 2: Bringing the Sun Home to Prevent Mom's Death Love Letter 3: Embracing Our Equal Place and Work on Mother Earth Love Letter 4: Humans can Help One Another, Now, and for a While More Love Letter 5: Afghan Street Kids Survive Amidst a Selfish Economy Love Letter 6: Are Unemployed Afghans Interested in Work? Love Letter 7: Nonviolent Versus Violent Peace in Afghanistan and the World Love Letter 8: In Afghanistan, Nursing Our Anger to Health Love Letter 9: From Afghanistan, the Outrageous Abolition of War Love Letter 10: Revolutionary Relationships Inaam (left), Habib (right) and I (photographer) sharing a good laugh at the Borderfree Nonviolence Community Centre in Kabul I decided to write this ninth love letter specially to Inaam, the 21st century generations of the world and the people of Okinawa because of three personal reasons. I miss having the wonderful energies of 15-year-old Inaam at the Borderfree Nonviolence Community Centre. Inaam has to polish boots in the streets of Kabul to supplement his family's income and to survive today's terrible economic system. I also wish that the vision and work of abolishing war had been "attractive" enough to keep Inaam in the Abolish War Team beyond three weeks. Inaam, born at the turn of the 21st century, deserves to live in world without war. I write to the courageous and kind Okinawans because though Japanese soldiers killed my grandfather in World War II, the people of Okinawa and Japan are healing my father through their nonviolent resistance. By Dr Hakim 20th March 2019 Dear Inaam, the 21st century generations of the world and the people of Okinawa, You're only fifteen, and I'm almost fifty. I wish I didn't hear you say to me, "Hakim, I think that war will never be abolished." Have we greedy adults made it so very difficult for you to picture a humanity without war? I know that deep down inside, you want war to disappear forever. I can see this wish on your face in the photo I took in 2015, for the Afghan Peace Volunteer's #Enough! War campaign. Inaam in 2015 (second from left) saying no to war In 1945, the UN Charter had committed "to save succeeding generations from the scourge of war, which twice in our lifetime has brought untold sorrow to mankind". I'm sorry that the UN and our human family have continued to inflict on you "untold sorrow". But I believe in you and your generation! 16-year-old Swedish student Greta Thurnberg is your peer, and she demonstrated the same wisdom you have when she said, "Today we use 100 million barrels of oil every day. There are no politics to change that. There are no rules to keep that oil in the ground, so we can't save the world by playing by the rules because the rules have to change. Everything needs to change and it has to start today." I wish Greta had said this about the obsolete and ineffective method of war too, but she didn't. There is no politician currently in office who has proposed laws to ban war. I had hoped that Bernie Sanders in the US and Jeremy Corbyn in the UK would, but they haven't. With your reason and compassion, you see through all the current peace negotiators of the Afghan conflict: beneath their emperor's clothes, you see that they are naked war executioners. When the world imagines that these peace negotiators/war executioners will negotiate for genuine peace, the world is fantasizing that the US military-christened Hellfire missiles, costing about US$58,000 each, or the extremists' opposing suicide bombing vests, costing much less, can usher heaven into Afghanistan. Even if you could cast an under-age vote in this July's scheduled Afghan Presidential elections, none of the 18 candidates will abolish war. Yes, to gain votes, they will all parrot the rhetoric that they wish to end the Afghan war, but none of them will abolish the method of war. It was only years after his political career, in 2017, that former President of USSR Mikhail Gorbachev wrote, "In modern world, wars must be outlawed, because none of the global problems we are facing can be resolved by war — not poverty, nor the environment, migration, population growth, or shortages of resources." Gorbachev understands the real political risk of humankind annihilating herself through nuclear warfare. Inaam, as a war child, you understand by experience that there are also no politics today to abolish war. Together with the Gretas and youth of the world, build the necessary new politics. You've seen how the Afghan Peace Volunteers are organized without a Director, so if the new politics needs to be one without a President, a CEO or a Prime Minister, go for it! And, don't worry about all the various mis-used and bombastic political terms. Go for nonviolent liberty, equality and fraternity. As the late French diplomat Stephane Hessel wrote about nonviolent resistance when he was 93, "Indignez vous. Time for Outrage!" Also, to practice magnanimity through life, you and I must exercise timeless patience while working our butts off. I mean, it was way back in the 1930s that British engineer Guy Stewart Callendar calculated that a doubling of CO2 in the Earth's atmosphere could warm the Earth by 2 degrees Celsius. It has taken 90 years to reach today's level of climate activism, and despite this, we still have people like Trump who denies climate change. Or like with the abolition of slavery. The Qin Dynasty of China abolished slavery in 221 BC and Pope Paul III forbade slavery of the indigenous peoples of the Americas in 1537. Niger made slavery a crime only in 2003! So, the human family's struggle against slavery took more than 2000 years, and even today, modern slavery still exists, like with the child brick-layers of Afghanistan. History's gradual but seismic changes happened when different individuals and societies took decisive actions at different times and ages. We can each be those channels of change: get the scientific results of war out there, use your shrill and growing voice, demand for laws to ban war, divest from the military industrial complex, don't join the military corporations, persuade your soldier-brother to be a conscientious objector, prohibit all weapons, make military generals very unpopular just as the CUNY undergraduates did, refuse to cooperate for war like some Google and Microsoft staff did, replace every war method with a thousand nonviolent methods, turn soldiers into pacifist mediators… All these are revolutionary acts of love; you're already familiar with the Dari phrase, "Dar kaar khair pesh dasti kardan", which means "For charitable work, set your hands to work quickly!" Am I asking too much of the 15-year-old you? You see, I want so much for you to have a meaningful and gorgeous life, and to have enough friends, even with those considered "enemies". My father had considered my Japanese friend Eitaro Oka an "enemy", because Japanese soldiers who had occupied Singapore in 1942 killed his father. It was World War II. But, when Eitaro visited me in Singapore years ago, my father and mother hosted him. The first thing Eitaro said to my father was, "I want to ask you for forgiveness, for the killing of your father." My father inspired me with his reply, "You were not the one who killed my father. Please enjoy the meal, a special Singaporean dish called Hainanese Chicken Rice prepared by my wife." Eitaro (centre) with my parents in Singapore When I joined a group of Japanese peace activists in Okinawa three years ago, an elderly Japanese monk stood before officials in the local office of Japan's Ministry of Defense, and asked me for forgiveness! He pleaded against the presence of US military bases in Okinawa. This kind monk had covered his bald head with the Borderfree Blue Scarf of the Afghan Peace Volunteers! The kind monk (left, standing) and Yuichi ( centre, standing ) with other Japanese activists in an office of Okinawa's Ministry of Defense. Many young Japanese like Yuchi, Sara and Kamoshita are resisting the re-militarization of Japan. Their current Prime Minister, Shinzo Abe, is regrettably addicted to military prowess, and wants to amend the Japanese constitution to enable the re-establishment of a Japanese army. Shinzo is a human being who is sold-out to money and power, and not very sound, as he has even nominated US President Trump for the Nobel Peace Prize! Yuchi (rear) and Sara (front) block a US military convoy in Okinawa Kamoshita protests in a boat ( inserted photo ) and stands in front of US military base's gate in Okinawa. Sara, Yuichi and Kamoshita ( first, second and third from right) with other activists Kamoshita and Sara had wanted to visit us in Kabul this winter, but Kamoshita emailed me, "I am sorry to late reply. I can't travel to Afghanistan this time. I couldn't persuade my family…They worry me to go." Not only are Japanese activists working to abolish war. Many ordinary Japanese are resisting the heavy killer machinery too. In fact, in a February 2019 Okinawa referendum, 72% of Okinawan voters opposed the construction of a new US military base to replace an existing one. Most Okinawans don't want US military bases on their peaceful and beautiful island. You'll also be encouraged to know that Masoma, Habib and new members of the Afghan Peace Volunteers had sent Kamoshita, Sara and Okinawans a video message of solidarity. Ordinary Japanese link hands in protest, at the gate of a US military base in Okinawa New Afghan Peace Volunteers link hands in solidarity with Okinawans, saying, "No to US military bases in Okinawa and Afghanistan!" So, dear Inaam, remember how you told me that the current education system is not teaching you anything useful? You're right. I'm sure that you can educate yourself better than the schools, especially in the knowledge, values and skills needed to build a better world. We have on many occasions talked about true education: thinking and feeling deeply, freeing ourselves from the control of money, questioning all power, changing the culture of war within us. In relational learning, we connect all the dots and love like everyone and everything in the world is related. Our lives are brief, but as long as I have opportunity, I'll walk with you. Inaam saying "#Bas! #Enough!" in 2015 Inaam ( right ) with Habib, studying for his school exam in November 2018 The courageous and kind people of Okinawa Baa mihr ( With love ) ! Hakim
Vanadium Investing News | Investing News Network Vanadium is a silvery-gray transition metal that was first discovered in 1801. It is named after Vanadis, the Norse god of beauty, and occurs in about 65 different minerals, including vanadinite, carnotite and patronite. The metal is mined as a by-product of other metals, and exists in deposits of phosphate rock, titaniferous magnetite, uraniferous sandstone and siltstone. It is also present in bauxite and in carboniferous materials such as coal, crude oil, oil shale and tar sands. Many investors believe the vanadium industry is compelling and are interested in getting involved in the market. Read on for a brief overview of the metal, from supply and demand to how to invest in this compelling industrial metal. Vanadium investing: Supply and demand China was the world’s largest producer of vanadium in 2016 by far, contributing 42,000 MT to the vanadium industry. It was followed by Russia at 16,000 MT and South Africa at 12,000 MT. China also has the highest vanadium reserves globally. Most vanadium in South Africa is mined from a formation known as the Bushveld Igneous Complex, and until 2014 the country was the second-largest vanadium producer, accounting for 14 percent of the market. However, in 2015, Evraz Highveld Steel and Vanadium’s Mapochs mine closed, leaving only two vanadium-producing mines operating in South Africa. In terms of demand, Roskill’s latest vanadium market report says that 91 percent of vanadium is used as an additive in steel to make it lighter, stronger and more resistant to shock and corrosion. The metal is often used to make parts for airplanes, as well as crankshafts, axles and gears. Less than 0.1 percent of vanadium is needed to double the strength of steel, and although other metals — including manganese, molybdenum, niobium, titanium and tungsten — can be interchanged with vanadium for alloying with steel, there is no substitute for vanadium in aerospace titanium alloys. Vanadium alloys are also used in nuclear reactors because they have low neutron-absorbing properties. Vanadium oxide is used as a pigment for ceramics and glass, and also acts as a catalyst in the production of superconducting magnets. Vanadium redox batteries are generating excitement because they are reusable over semi-infinite cycles, and do not degrade for at least 20 years. However, these batteries are quite large and are better suited for industrial or commercial use than for use in electric vehicles. Roskill expects the market for stationary energy storage to increase from less than 2 GWh today to 16 GWh by 2026. The firm notes that vanadium redox batteries currently account for just a fraction of the energy storage market, but even slight growth in market share could potentially add tens of kilotonnes of demand to the market. Roskill predicts that vanadium prices will recover from their current level and peak around 2019 or 2020. The current price of ferrovanadium, an alloy of iron and vanadium, is about $21 per kilogram. Vanadium investing: How get started Vanadium bullion is available from private individuals, but the metal is not publicly traded and so most experts do not advise investing in physical vanadium. Instead, many investors interested in the vanadium industry choose to invest in companies that are focused on the metal. Largo Resources (TSX:LGO) continues to ramp up vanadium production in South America. The company owns and operates the Maracas Menchen mine in Brazil, and its goal is to reach annual vanadium output of 9,600 tonnes. The mine started producing vanadium in August 2014, and Largo says it is the highest-grade vanadium deposit yet discovered. Aside from Largo, few other publicly traded companies are currently mining vanadium. However, many companies are exploring for the metal or developing vanadium projects. You can read more about them by clicking here. This description was last updated in July 2017.
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Prototype | Prototyping Your Future / HCI IxD Any large organisation, be it public or private, monitors the media for information to keep abreast of developments in their field of interest, and usually also to become aware of positive or negative opinions expressed towards them. At least for the written media, computer programs have become very efficient at helping the human analysts significantly in their monitoring task by gathering media reports, analysing them, detecting trends and – in some cases – even to issue early warnings. We present here trend recognition-related functionality of the Europe Media Monitor (EMM) system, which was developed by the European Commission's Joint Research Centre (JRC) for public administrations in the European Union (EU) and beyond. EMM performs large-scale media analysis in up to seventy languages and recognises various types of trends, some of them combining information from news articles written in different languages. EMM also lets users explore the huge amount of multilingual media data through interactive maps and graphs, allowing them to examine the data from various view points and according to multiple criteria. A lot of EMM's functionality is accessibly freely over the internet or via apps for hand-held devices. Introduction Automated Content Analysis (ACA) is likely to be more limited than human intelligence for tasks such as evaluating the relevance of information for a certain purpose, or such as drawing high-level conclusions. Computer programs are also error-prone because human language is inherently ambiguous and text often only makes sense when the meaning of words and sentences is combined with the fundamental world knowledge only people have. However, computers have the advantage that they can easily process more data in a day than a person can read in a life time. Computer programs are particular useful in application areas with a time component, such as monitoring the live printed online media, because they can ingest the latest news articles as soon as they get published and they can detect changes and recognise and visualise trends. Due to the amount of textual information they can process, computer programs can be used to gain a wider view based on more empirical evidence. These features make ACA applications powerful tools to complement human intelligence. At least for the written media, the manual paper clipping process of the past – cutting out newspaper articles and combining them into a customised in-house news digest – has to a large extent been replaced by automatic systems. Computers can take over repetitive work such as gathering media reports automatically, categorising them according to multiple categories, grouping related documents, recognising references to persons, organisations and locations in them, etc. Using this filtered and pre-processed data, human analysts can then focus on the more demanding tasks of evaluating the data, selecting the most relevant information and drawing conclusions. The work of analysts will be more efficient if the computer programs can extract more information and the more high-level information they can recognise. Trend recognition is deemed particularly useful as it partially summarises events and it may help users detect hidden developments that can only be seen from a bird's perspective, i.e. by viewing very large amounts of data. Trend visualisations may serve as early warning tools, e.g. when certain keywords are suddenly found frequently or when any combination of other text features suddenly changes, compared to the usual average background. Trend prediction would then be the next logical step: based on regular historical observations specifically co-occurring with certain trends, it should be possible to predict certain trends when the same feature combinations occur again. Such an effort was described by O'Brien (2002) for the challenging domain of conflict and instability. A major challenge for complex subject domains such as societal conflict or war is that the data needed for making a reliable prediction may simply not exist and/or that some specific factors may decide on whether or not a conflict arises, factors that lie outside the realm of statistical analysis (e.g. the sudden sickness or death of a political leader). In any case, features for predictions should probably include data that can only be found outside the document corpus, such as statistical indicators on the economy and on the society (More REFS). The main disciplines contributing to ACA are called computational linguistics, natural language processing, language engineering or text mining. In recent years, this field has made a leap forward due to insights and methods developed in statistics and in machine learning, and of course due to the strong increase of computer power, the availability of large collections of machine-readable documents and the existence of the internet. In Section 2, we will give an overview of EMM, its functionality and its users. We will particularly point out the usefulness of aggregating information derived from the news in many different languages, which has the advantage of reducing any national bias and of benefitting from information complementarity observed in media sources written in different languages. In Section 3, we will then present a variety of trend presentations and data visualisation techniques used in EMM. These include time series graphs using numbers of articles on a certain subject, the usage of automatically extracted information on named entities mentioned in any selection of news, map representations combining geographical and subject domain information, opinion trends, graphs comparing information derived from the social media with that from the online version of printed media, and more. In Section 4, we summarise the benefits of automatic media monitoring, not without pointing out limitations of ACA and the potential dangers of relying on automatically derived information based on large volumes of textual data. Europe Media Monitor (EMM) A brief Overview 2.1 Overview Europe Media Monitor (EMM) stands for a whole family of media gathering and analysis applications, including NewsBrief, NewsExplorer, the Medical Information System MedISys, BlogBrief, NewsDesk and more (Steinberger et al. 2009). EMM was entirely developed at the JRC. While the main users are the EU institutions and the national authorities of the 28 EU member states, EMM was also made accessible to international organisations (e.g. various United Nations sub-organisations, the African Union and the Organisation of American States) and to the national authorities of selected partner countries of the EU. The first version of NewsBrief came online in 2002 while NewsExplorer came in 2004, but both systems processed smaller volumes of news and they had less functionality. EMM currently gathers a daily average of about 220,000 online news articles per day in seventy languages from approximately 4,000 different web sources (status May 2015). The news sources were manually selected with the purpose to represent the major newspapers of all countries in the world and to include European-language news (especially English) from around the world. For reasons of balance, it was decided not to include all easily accessible news sources, but to monitor a comparable number of news sources per country, with a focus on Europe. EMM additionally processes news feeds from over twenty press agencies. It visits news-like websites such as governmental and non-governmental web pages and it monitors social media such as Twitter, FaceBook and selected blog sites. The public versions of EMM do not show commercially acquired documents and usually have less functionality than the EC-internal versions. Separately for each language, the news articles then undergo a series of processing steps, including language recognition, document duplicate detection, Named Entity Recognition (NER) for persons, organisations and locations, quotation extraction, sentiment/tonality analysis, categorisation into one or more of the over 1,000 different subject domain classes. EMM then clusters related articles into groups, which allows users to examine the load of articles in an organised fashion. The different EMM applications provide different functionality, described in the next section. Family of EMM news monitoring applications NewsBrief (Figure 1) is the most widely used system. It provides users with near-real-time information on their field of interest in all seventy languages. Separately for each language, news gathered within a sliding four-hour window (8 hours for some languages) are clustered, but older articles remain linked to the cluster as long as new articles arrive. For each cluster, automatically extracted meta-information such as named entities and quotations are displayed. Continuously updated graphs show the ten currently largest clusters and their development over time. By clicking on any of the clusters, users can see the list of all articles and click on each article to read the entire text on the website where it was originally found. For fourteen languages, an automatically pre-generated translation into English is available. For event types with relevance to health, safety and security, NewsBrief also displays automatically extracted event information (eight languages only), including the event type, location and time of the event, number and type of victims (dead, injured, infected), and – where this was mentioned – the perpetrator (the person or group inflicting the damage). The limitation of the event types is due to the user groups, which are mostly concerned with providing support in case of disasters, epidemics, etc. NewsBrief offers subscriptions for automatic updates per category by email, for institutional users also via SMS. BlogBrief provides the same functionality as NewsBrief, but instead of news, it processes English language blogs by bloggers who have been hand-selected due to their importance or impact (e.g. politicians and journalists). MedISys is rather similar to NewsBrief, except that all its content categories are related to issues that are relevant for Public Health monitoring. Its news categories include all major communicable diseases and other Chemical, Biological, Radiological or Nuclear (CBRN) dangers, symptoms, as well as subjects of scientific or societal value such as vaccinations and genetically modified organisms. NewsExplorer provides a more long-term view of the news (in 21 languages only) and it provides a cross-lingual functionality. Rather than displaying and grouping the current news, NewsExplorer clusters the news of a whole calendar day and displays the clusters ordered by size. For each cluster, hyperlinks lead users to the equivalent news clusters in any of the other twenty languages (where applicable) and to historically related news. NewsExplorer also includes hundreds of thousands of entity pages (persons, organisations and more), where historically gathered information on each entity is aggregated and displayed, including name variants, titles, clusters and quotes where the entity was mentioned, quotes issued by that person, other entities frequently mentioned together with this entity, and more (see Figure 2). NewsDesk is a tool for human moderation. It allows media monitoring professionals to view and select the automatically pre-processed news data and to easily create readily formatted in-house newsletters. EMM Apps for mobile devices such as iOS and Android phones and tablets first became publicly and freely available in 2013 (See Figure 3). Due to the personal nature of such devices, it became first possible to display customised starting pages for each user. For the iOS EMM App alone, about 26,000 downloads were recorded up to May 2015. This customisable version of EMM became very popular so that this functionality was implemented in a new web version of EMM, called MyNews (see below). The EMM App uses a whole new concept and way to interact with EMM Metadata, referred to as Channels. A channel is a stream of EMM articles that all share the same metadata: Channels can be (a) any News Category, (b) the Top 20 Stories in a particular language, (c) a Country/Category combination, (d) an entity recognised by EMM or (e) a search in the full-text index. Users can create such channels for themselves and they can group channels into sets, allowing them to browse freely between channels in any of these sets. When users open a channel, they get access to all the articles that are present in the channel at the time, plus the other metadata that EMM has identified and associated to that channel. Users can of course also browse the attached meta-data, turn them into new channels and pin them to the current set. Crisis management tools and products have been found to be challenging to design and produce due to the complexity of dynamic customisable data-sets defined by each individual user. The main problems in designing such tools are ambiguity, multi-platform support, data representation and other pitfalls commonly seen in mobile technology development. We adhere to a model-based methodology focusing on core functionality and logical interactions with the data-set, user-centric design and data visualisation while supporting other development activities including a requirement analysis for a wide set of devices and operating systems, verification and validation. The result of the development cycle is a layout structure in which a wide scale of EMM crisis management tools has been developed. There are many digital solutions aiming to support humanitarian and emergency response tools by means of open source information gathering and text analysis. A strong trend among those tools is the ability to detect and analyse vast amounts of data, highlighting important developments relevant to each user and use. Many solutions are already operational today, the majority of these solutions requires the user to open a webpage a few times every day to get updated. Other solutions are relying on communicating with external servers, which is expensive and demanding in maintenance. They additionally usually require user authentication, which can compromise privacy and security. Our own solution allows custom notifications based on changes in the specific data set the user has defined. When a logical threshold is activated the system displays a notification directly on the user's mobile device. By merging our notifications with the core system notification system of the mobile device, we alert the user only when it is appropriate. For example, notification will wait silently when the user is asleep and will schedule the notifications to be presented a few minutes after the user has started using the device. This is being done without any user intervention or pre-settings. This novel solution differentiates itself from most notification solutions in the fact that it does not rely on any server side technology. The application itself calculates when and how notifications are presented to the user based on an internal logic crossed with background fetching of the current total data set. MyNews is the first customisable web interface to the news items supplied by the EMM engine designed for desktop browsers. It only became available in 2015. It requires logging in and is only available in-house, i.e. it is not accessible to the wider public. MyNews is highly customisable, since it allows users to define their own specific view by selecting the topics they are most interested in. This is achieved – similarly to the EMM mobile apps – by allowing users to tune news channels focused on very specific topics. They can create as many channels as they like, and they can organise them into sets (see Figure 4). There are many different ways to create new channels, which increases greatly the flexibility of the tool, combining as a union or as an intersection of article selections based on (a) text language, (b) news categories, (c) entities, (d) news from a certain country or (e) news about a certain country, (f) top stories (i.e. the biggest clusters of news talking about the same event) or (g) freely chosen search words. When visualising the contents of any of the channels, the meta-data relating specifically to this selection of news is displayed visually (see Figure 5). The Big Screen App, available since 2014, offers a view of EMM that is visible on large screens in central locations at user organisations. It shows a revolving and continuously updated view of what is happening around the world, targeted to the respective user communities, using text, maps and graphs. Citizens and Science (CAS) is a project that aims to gauge the relative importance of reporting on Science & Technology (S&T) in traditional and social media. It does this by comparing the reporting volume from a number of European Nations and the USA of items that correspond to a number of predefined S&T categories. The sources of these items are taken from the traditional online news media, public posts from FaceBook and tweets from Twitter. CAS allows investigating the relative dominance of certain themes across different media (traditional vs. social), languages and countries and it can help find empirical evidence of biased reporting (see Figure 6; more detail in Section 3.2). Details on ingested news, sources, numbers, geographical distribution Event extraction Multilinguality in EMM Multilinguality is an extremely important feature in this news monitoring application. Covering so many languages is not only important because the European Union consists of 28 Member States with 24 official EU languages. The coverage of news in 70 different languages is also due to the insight that news reporting is complementary across different countries and languages, both regarding the contents and the opinions expressed in the media. By gathering and analysing different languages, EMM reduces any national or regional bias and it increases the coverage of events and of opinions. While major world events such as large-scale disasters, major sports events, wars and meetings of world leaders are usually also reported in English, there is ample evidence that only a minority of the smaller events is reported on in the press outside the country where the event happens. Many EMM users have specialised interests such as the monitoring of events that may have negative effects on Public Health (e.g. disease outbreaks, reports on food poisoning, lack of access to medicines) or on the stability or welfare of a country (e.g. clashes between ethnic groups, accidents, crime). An analysis has shown that the vast majority of such events is not translated or reported abroad (Piskorski et al. 2011 – PROVIDE DETAILED NUMBERS). The links between related clusters across different languages in NewsExplorer show that only some of the news items in each country or language have an equivalent in other languages while the majority of news clusters talk about subjects of national interest. Figure 7, taken from the live EMM news cluster world map, also gives evidence of the uneven distribution of language reporting for locations on the globe: News mentioning locations in Latin America are mostly reported in Spanish and Portuguese; there is little news on Russia and China that is not written in Russian or Chinese, respectively, etc. Only by combining the world news in all different languages do we get a fuller picture of what is happening . Trend observation and distribution statistics in EMM In this section, we want to give some concrete examples of trend monitoring, as well as of bird's views of large amounts of media data giving insights in the relative distribution of news contents. The selection of examples shown here is based on wanting to present different visualisation principles or types, but it is naturally also driven by the interests of EMM users. Since EMM monitors in near-real time (time stamp) large amounts of media reports from around the world and it keeps track of the information (e.g. news provenance, news source, publication language, URL, media type, time of publication, etc.) and it additionally extracts categories and features (e.g. subject domain; number of related articles; names of persons, organisations and locations; sentiment; combinations of features; average values, etc.), it is in principle possible to produce and visualise statistics on any feature or feature combination. This can be done for a specific point in time (most EMM users are interested in now), it can be done for any moment back in time, it is possible to compare current values to average values, and it is possible to perform a time series analysis, i.e. it is possible to show any change over time. Note, however, that, while all such meta-data extracted by EMM can be stored, the original full text of the news has to be deleted after the analysis, for copyright reasons. Users will thus be able to see the meta data and a snippet of the news text (title and the first few words), but if they want to see the full text, they have to follow the hyperlink provided. Whether or not the full text is still accessible then depends on the news source. In the following sub-sections, we will present some types of trend observations and visual presentations of distribution statistics. Bar graphs and pie charts The simplest and probably clearest way of presenting static data is achieved using bar graphs and pie charts. Figure 5 shows three different bar charts to visualise different aspects for the same selection of news documents (provenance of the news, countries mentioned in the articles, and subject domains/entities referred to). These charts give the reader an overview of the whole collection of documents and it thus helps them evaluate and categorise the contents before reading them in detail. Figure 7b shows the language distribution of a multilingual set of European news articles talking on the subject of Science & Technology and comparing it with the language distribution in all articles covering the same time period. It is immediately visible that English and Polish language articles (left) are over-proportionally talking about S&T, while German and French S&T articles are under-represented, compared to the average. Maps visualising geographical distributions Map views are rather popular and intuitive. Figure 5 shows an aggregated map view (number of articles per continent/country/region, depending on the zoom level) while Figure 7 shows all news clusters (or those in a selection of languages). Many types of map data are available, allowing to combine any EMM information with third-party information, as seen in Figure 8 . Any map data in EMM is hyperlinked to the underlying news articles together with the extracted meta-information so that users can verify the contents and read the underlying news sources. Trend graphs Trend graphs show a simple correlation between at least two variables, of which one is time. Typically, they take the shape of line graphs or bar graphs where one axis represents time. Figure 1 shows the size (number of news articles) of the ten largest English language news clusters and their development over the past 12 hours, with a ten-minute resolution (update frequency). The interactive graph clearly shows which stories are most discussed. By hovering with the mouse over any of the points, the most typical news article header of that moment in time is shown so that users can get informed of the development of that story. The system decides on the most typical article header statistically by selecting the medoid, i.e. the document that is closest to the centroid of the vector. By clicking on any of the curves, a new page will open showing the articles that are part of that cluster plus all meta-information available to the system. This graph thus shows ten trend lines in one graph, for the sake of comparison. Similarly, Figure 6 visualises the numbers of news articles and of Social Media postings over time on four science areas. The graph shows longer-term developments. The chosen resolution is one day. For each of the four science areas, two trend curves are displayed to facilitate the visual understanding of the relative long-term development. Such graphs can be rather revealing. For instance, Figure 9 compares Science & Technology reporting in Europe and in the US. For better comparison, the numbers have been normalised: the x-axis shows the percentage of S&T articles compared to all articles, instead of absolute numbers. This graph reveals that the intensity of reporting on S&T in Europe lags behind that observed in US-American media (0.5% of all articles in all languages in the EU vs. 2.8% in the USA report about S&T). Comparing only English language articles in predominantly English-speaking countries (UK and Ireland in Europe; graph not shown here) with the English language articles in the USA, the difference is smaller, but it still notable (1.5% of articles in the UK and in Ireland vs. 3.2% in the USA). To put these numbers into perspective: the reporting on the reference categories Conflict, Ecology, Society and Sports, considering only the English language, was respectively 2.56%, 0.14%, 0.59% and 5.46% for the USA and 1.93%, 0.09%, 0.45% and 6.63% for the EU. This means that the reporting on S&T issues does not fall far behind the reporting on Sports in the USA, but in Europe reporting on Sports is 4 times more than on S&T issues. Note that, in EMM, sports articles are additionally only taken from general news streams because EMM does not scan sports pages of news sites. Looking in detail at a specific topic such as Space, we observe that there is a very strong correlation between the peaks, but the volumes are much smaller in the UK and Ireland, compared to the USA (See Figure 9). Other than a weak correlation between product announcements in the media and on twitter, we have not observed a clear media-driven discussion on the social media, i.e. we have not been able to establish any correlation between media reports and the user-driven content. Such data is a good starting point for the work of social scientists, who can then search for an interpretation and for explanations. Economists and politicians may then think of possible remedies (if needed and wanted). Figure 10 shows the interactive long-term news story timeline produced in EMM-NewsExplorer. The graph shows the number of news articles per day in the daily news clusters about the same event or subject. By hovering over any of the bars, the news cluster title is displayed so that users can explore what happened that day. By clicking on that day, the users are taken to the page with information on that day's news cluster in order to read the articles, see the related meta-information and follow hyperlinks to related reports in other languages. The graph allows exploring developments over longer periods of time and refreshing one's memory on what happened when. Figure 11 shows the development of positive or negative tonality (or sentiment) measured in English and French news articles, using a one-week resolution. Early warning graphs Figure 8 visualises results on the most recent events of a certain type, allowing stakeholders to become aware of the latest developments, to deepen their understanding of what happened (by reading the related news articles) and to take action, if needed. Another type of early warning is achieved with statistical means, as shown at the top of Figure 10, taken from EMM's Medical Information System MedISys. The graph called daily alert statistics shows the currently biggest threats world-wide, with decreasing relevance from left to right (the red threats are the ones with the highest alert levels). MedISys counts the number of articles in the last 24 hours for any country-threat combination (e.g. tuberculosis and Poland) and compares it to the two-week average count for this same combination. This ratio is then normalised by the number of articles for different days of the week (there are less articles on the weekend). The alert statistics graph then shows the results of all calculations, ranked by the value of this ratio . Note that the ratio is entirely independent of the absolute numbers as it rather measures the unexpectedness. Each country-threat combination is shown in two columns: the left one (light blue) shows the observed number of articles while the right one (red, yellow or blue) shows the expected two-week average. An important feature of this graph and of MedISys/EMM as a whole is that this alert is language-independent. The same categories for countries and for threats exist for (almost) all EMM languages, meaning that the articles may be found in one language only (e.g. Polish or Arabic), which often is different from the languages spoken by the MedISys user. The graph is interactive: Users can click on any of the bars to jump to a new page where all relevant articles for this country-threat combination are displayed, together with a heat map and a trend line showing the development over the past 14 days. The Spain-legionellosis threat combination in Figure 10 no longer is a top threat as it had already been reported on for four days. Further graph types used in EMM Figure 11 shows a node graph visualising co-occurrence relations between people. For each person, the 100 most associated entities (persons or organisations) are displayed. The subset of common entities is highlighted in red. The graph is interactive: by clicking on any of the entity nodes, they jump to a page with the news mentioning that entity and displaying all automatically extracted meta-information (e.g. Figure 2), or to the Wikipedia page for that entity. Further entities can be added to the same graph. EMM-NewsExplorer produces the correlation data by counting which entities are mentioned together with which other entities in the same news items. In order to suppress media VIPs such as the US president from the purely frequency-based correlation lists (called 'related entities' in NewsExplorer), a weighting formula is used that brings those entities to the top that are mostly mentioned together with this person and not so much with other persons. The data, referred to in NewsExplorer as 'associated entities', is produced on the basis of mention co-occurrence in the news in 21 different languages, i.e. it is less biased by the reporting language than data produced by a monolingual media monitoring system. EMM recognises direct speech quotations in the news in about twenty different languages and keeps track of who issued the quotation and who is mentioned inside the quotation. Figure 12 shows a quotation network indicating who mentions whom (arrows). Persons most referred to are automatically placed closer to the centre of the graph. During the 2007 presidential elections in France, it was observed that Nicolas Sarkozy, who was the winner of the elections, was consistently more central than his opponent Ségolène Royal. Quotation networks are no longer used in EMM. The same applies to topic maps, which display the most prominent subject matters referred to in a document collection. The topics are grouped into islands of relatedness (using a method known as Kohonen Maps). The more prominent a group of topics is in the collection, the higher the mountains on the island, with peaks being snow-covered. Summary and conclusions, pitfalls Computers have the ability to sieve through large volumes of data in little time and the technologies required for Automated Content Analysis (ACA) have matured to a level where automatically produced results can be useful for the human analyst. We have argued that a man-machine collaboration for the analysis of large volumes of media reports will produce best results because people and computers have complementary strengths. We have presented the main functionality of the European Commission's family of Europe Media Monitor (EMM) applications, which currently gathers an average of 220,000 online news articles per day from about 5,000 online news sources in seventy languages (and also from social media postings about certain themes), categorises the news into about 2,000 different categories, groups related articles, extracts various types of information from them, links related articles over time and across languages and presents the analysis results in a variety of ways to the human end user. Moderation tools support the users in viewing the data, in selecting and amending it and in producing in-house newsletters for the information-seeking decision takers. Monitoring not only English or some widely spoken languages is important in order to avoid bias and also because the news is complementary across languages, both for contents and for the sentiment contained therein. Automatic tools that process and analyse documents turn unstructured information into a structured format that can easily be processed by machines and that also provides useful data for the human user. This results in a data collection, where for each article, we know the news source, the country of origin, the language, the timestamp of the publication, the news categories, the persons, organisations and locations mentioned therein, related articles within the same and across different languages, quotations by and about persons. Additionally, we have data about trends, i.e. whether news related to the same event or subject are increasing or decreasing in numbers over time, and there is some information on sentiment/tonality. This structured collection makes it in principle possible to produce any statistics and to establish any trends related to these types of information. For selected subjects and feature combinations, the JRC regularly publishes its analysis, allowing EMM users to have a deeper insight into the publications on subject areas of their interest. In this article, we presented a range of different types of analyses and visualisations in order to give an overview of distributions and trends observed during large-scale media analysis. Such an extraction and aggregation of data is not usually the final objective, but it normally is the starting point for an intellectual human analysis. Analysts can get inspired by the data, questions may arise, suspicions may get confirmed or contradicted. Used carefully, we believe that the analyses produced by EMM or similar systems can be very useful because they may be used as an inspiration and as empirical evidence for any argument human analysts may want to make. However, we find it extremely important that users be aware of the limitations and of possible pitfalls when using such data, be it from EMM or from other automatic systems: First of all, media monitoring is not reality monitoring. What the media say is not necessarily factually true and media attention towards certain subjects usually differs from the real-life distribution of facts or events, giving media consumers a biased view. Media reporting is heavily influenced by the political or geographical viewpoint of the news source. It is therefore useful to analyse a large, well-balanced set of media sources coming from many different countries world-wide. EMM aims to reach such a balance, but sources are also added on request of users, it is not always known what political standpoints newspapers have, and not all news sources are freely accessible. For this reason, EMM displays the list of media sources so that users can form their own opinion. Any analysis, be it automatic or man-made, is error-prone. This is even true for basic functionalities such as the recognition of person names in documents and the categorisation of texts according to subject domains. Machines might make simple mistakes easily spottable by human analysts, such as categorising an article as being about the outbreak of communicable diseases when category-defining words such as tuberculosis are found in articles discussing a new song produced by a famous music producer, which is easily spottable by a person. On the other hand, machines are better at going through very large document collections and they are very consistent in their categorisation while people suffer from inconsistency and they tend to generalise on the basis of the small document collection they have read. For these reasons, it is crucial that any summaries, trend visualisations or other analyses can be verified by the human analysts. Users should be able to verify the data by drilling down, e.g. viewing the original text data in the case of peaks or unexpected developments, and especially to get an intuitive confidence measure by viewing a number of cases that lead to conclusions. Most of EMM's graphs are interactive and allow viewing the underlying data. It would be useful if system providers additionally offered confidence values regarding the accuracy of their analyses. For EMM, most specialised applications on individual information extraction tools include such tool evaluation results and an error analysis (e.g. XXX-REF). However, the tools can behave very differently depending on the text type and the language, making the availability of drill-down functionality indispensable. End users should be careful with accuracy statistics given by system providers. Especially commercial vendors (but not only) are good at presenting their systems in a very positive light. For instance, our experience has shown that, especially in the field of sentiment analysis (opinion mining, tonality), high accuracy is difficult to achieve even when the statistical accuracy measurement Precision and Recall are high. Overall Precision (accuracy for the system's predictions) may for instance indeed be high when considering predictions for positive, negative and neutral sentiment, but this might simply be because the majority class (e.g. neutral) is very large and the system is good at spotting this. Accuracy statistics may also have been produced on an easy-to-analyse dataset while the data at hand may be harder to analyse. Sentiment, for instance, may be easier to detect on product review pages on vending sites such as Amazon than on the news because journalists tend to want to give the impression of neutrality. Machine learning approaches to text analysis are particularly promising because computers are good at optimising evidence and because machine learning tools are cheap to produce, compared to man-made rules. However, the danger is that the automatically learnt rules are applied to texts that are different from the training data as comparable data rarely exists. Manually produced rules might be easier to tune and to adapt. Again, statistics on the performance of automatic tools should be considered with care. Within EMM, machine learning is used to learn vocabulary and recognition patterns, but these are then usually manually verified and generalised (e.g. Zavarella et al. 2010; Tanev & Magnini 2008). To summarise: we firmly believe that Automated Content Analysis works when it is used with care and when its strengths and limits are known. Computers and people have different strengths which – in combination – can be very powerful as they combine large-scale evidence gathering with the intelligence of human judgement. References Atkinson M, Keim D, Schaefer M, Franz W, Leitner-Fischer F, Zintgraf F. (2010). DYNEVI - DYnamic News Entity VIsualization. In: J.Kohlhammer, D.Keim (eds). Proceedings of the International Symposium on Visual Analytics Science and Technology. Golsar (Germany): The Eurographics Association. pp. 69-74 . Atkinson Martin, Jakub Piskorski, Erik van der Goot & Roman Yangarber (2011). Multilingual Real-Time Event Extraction for Border Security Intelligence Gathering. In: U. Kock Wiil (ed.) Counterterrorism and Open Source Intelligence. Springer Lecture Notes in Social Networks, Vol. 2, 1st Edition, 2011, ISBN: 978-3-7091-0387-6, pp 355-390. Atkinson Martin, Jakub Piskorski, Hristo Tanev, Roman Yangarber & Vanni Zavarella. Techniques for Multilingual Security-related Event Extraction from Online News. In: Przepiórkowski Adam et al. Computational Linguistics Applications, pp. 163-186. Springer-Verlag, Berlin, 2013. Atkinson Martin, Jenya Belayeva, Vanni Zavarella, Jakub Piskorski, S. Huttunen, A. Vihavainen, Roman Yangarber (2010). News Mining for Border Security Intelligence. In IEEE ISI-2010: Intelligence and Security Informatics, Vancouver, BC, Canada. Balahur Alexandra & Hristo Tanev (2013). Detecting event-related links and sentiments from social media texts. Proceedings of the Conference of the Association for Computational Linguistics (ACL'2013). Balahur Alexandra, Ralf Steinberger, Erik van der Goot, Bruno Pouliquen & Mijail Kabadjov (2009). Opinion Mining on Newspaper Quotations. Proceedings of the workshop 'Intelligent Analysis and Processing of Web News Content' (IAPWNC), held at the 2009 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, pp. 523-526. Milano, Italy, 15.09.2009. Balahur Alexandra, Ralf Steinberger, Mijail Kabadjov, Vanni Zavarella, Erik van der Goot, Matina Halkia, Bruno Pouliquen & Jenya Belyaeva (2010). Sentiment Analysis in the News. In: Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC'2010), pp. 2216-2220. Valletta, Malta, 19-21 May 2010. Barboza P, Vaillant L, Mawudeku A, Nelson NP, Hartley DM, Madoff LC, Linge JP, Collier N, Brownstein JS, Yangarber R, Astagneau P (2013). Early Alerting Reporting Project Of The Global Health Security Initiative. Evaluation of epidemic intelligence systems integrated in the early alerting and reporting project for the detection of A/H5N1 influenza events. PLoS One. 2013;8(3):e57252. doi: 10.1371/journal.pone.0057252. Epub 2013 Mar 5. Jakub Piskorski, Hristo Tanev, Martin Atkinson, Erik van der Goot & Vanni Zavarella (2011). Online News Event Extraction for Global Crisis Surveillance. Transactions on Computational Collective Intelligence. Springer Lecture Notes in Computer Science LNCS 6910/2011, pp. 182-212. Krstajic, M.; Bak, P.; Oelke, D..; Atkinson, M.; Keim, D.A. (2010). Applied Visual Exploration on Real-Time News Feeds Using Polarity and Geo-Spatial Analysis. Web Information Systems and Technologies WEBIST 2010, Valencia, 7-10 April 2010. Krstajic, M.; Mansmann, F.; Stoffel, A.; Atkinson, M.; Keim, D.A. (2010). Processing online news streams for large-scale semantic analysis. 26th International Conference on Data Engineering (ICDE) Workshops, pp.215-220, 1-6 March 2010. Linge Jens, Ralf Steinberger, Thomas Weber, Roman Yangarber, Erik van der Goot, Delilah Al Khudhairy & Nikolaos Stilianakis (2009). Internet Surveillance Systems for Early Alerting of Health Threats. EuroSurveillance Vol. 14, Issue 13. Stockholm, 2 April 2009. Linge, J.P., Mantero, J. Fuart, F., Belyaeva, J., Atkinson, M., van der Goot, E. (2011). Tracking Media Reports on the Shiga toxin-producing Escherichia coli O104:H4 outbreak in Germany. In: Malaga. P. Kostkova, M. Szomszor, and D. Fowler (eds.), Proceedings of eHealth conference (eHealth 2011), LNICST 91, pp. 178–185, 2012. PUBSY JRC65929. Piskorski Jakub, Jenya Belyaeva & Martin Atkinson (2011). Exploring the usefulness of cross-lingual information fusion for refining real-time news event extraction. Proceedings of the 8th International Conference Recent Advances in Natural Language Processing (RANLP'2011), pp. 210-217. Hissar, Bulgaria, 12-14 September 2011 Pouliquen Bruno, Hristo Tanev & Martin Atkinson (2008). Extracting and Learning Social Networks out of Multilingual News. Proceedings of the social networks and application tools workshop (SocNet-08) pp. 13-16. Skalica, Slovakia, 19-21 September 2008. Pouliquen Bruno, Marco Kimler, Ralf Steinberger, Camelia Ignat, Tamara Oellinger, Ken Blackler, Flavio Fuart, Wajdi Zaghouani, Anna Widiger, Ann-Charlotte Forslund, Clive Best (2006). Geocoding multilingual texts: Recognition, Disambiguation and Visualisation. Proceedings of the 5th International Conference on Language Resources and Evaluation (LREC'2006), pp. 53-58. Genoa, Italy, 24-26 May 2006. Pouliquen Bruno, Ralf Steinberger & Clive Best (2007). Automatic Detection of Quotations in Multilingual News. In: Proceedings of the International Conference Recent Advances in Natural Language Processing (RANLP'2007), pp. 487-492. Borovets, Bulgaria, 27-29.09.2007. Pouliquen Bruno, Ralf Steinberger & Olivier Deguernel (2008). Story tracking: linking similar news over time and across languages. In Proceedings of the 2nd workshop Multi-source Multilingual Information Extraction and Summarization (MMIES'2008) held at CoLing'2008. Manchester, UK, 23 August 2008. Pouliquen Bruno, Ralf Steinberger, Camelia Ignat & Tamara Oellinger (2006). Building and displaying name relations using automatic unsupervised analysis of newspaper articles. Proceedings of the 8th International Conference on the Statistical Analysis of Textual Data (JADT'2006). Besançon, 19-21 April 2006. Pouliquen Bruno, Ralf Steinberger, Jenya Belyaeva (2007). Multilingual multi-document continuously updated social networks. Proceedings of the Workshop Multi-source Multilingual Information Extraction and Summarization (MMIES'2007) held at RANLP'2007, pp. 25-32. Borovets, Bulgaria, 26 September 2007. Sean P. O'Brien (2002). Anticipating the Good, the Bad, and the Ugly. An Early Warning Approach to Conflict and Instability Analysis. Journal of Conflict Resolution, Vol. 46 No. 6, December 2002, pp. 791-811 Steinberger Ralf & Bruno Pouliquen (2009). Cross-lingual Named Entity Recognition. In: Satoshi Sekine & Elisabete Ranchhod (eds.): Named Entities - Recognition, Classification and Use, Benjamins Current Topics, Volume 19, pp. 137-164. John Benjamins Publishing Company. ISBN 978-90-272-8922 3. ( Steinberger Ralf (2012). A survey of methods to ease the development of highly multilingual Text Mining applications. Language Resources and Evaluation Journal, Springer, Volume 46, Issue 2, pp. 155-176 (DOI 10.1007/s10579-011-9165-9). Steinberger Ralf, Bruno Pouliquen & Erik van der Goot (2009). An Introduction to the Europe Media Monitor Family of Applications. In: Fredric Gey, Noriko Kando & Jussi Karlgren (eds.): Information Access in a Multilingual World - Proceedings of the SIGIR 2009 Workshop (SIGIR-CLIR'2009), pp. 1-8. Boston, USA. 23 July 2009. Steinberger Ralf, Flavio Fuart, Erik van der Goot, Clive Best, Peter von Etter & Roman Yangarber (2008). Text Mining from the Web for Medical Intelligence. In: Fogelman-Soulié Françoise, Domenico Perrotta, Jakub Piskorski & Ralf Steinberger (eds.): Mining Massive Data Sets for Security. pp. 295-310. IOS Press, Amsterdam, The Netherlands Tanev Hristo & Bernardo Magnini (2008). Weakly supervised approaches for ontology population. In: Paul Buitelaar & Philipp Cimiano (eds.): Ontology learning and population: Bridging the Gap between Text and Knowledge. IOS Press, Amsterdam, The Netherlands. Frontiers in Artificial Intelligence and Applications, Volume 167. Tanev Hristo & Josef Steinberger (2013). Semi-automatic acquisition of lexical resources and grammars for event extraction in Bulgarian and Czech. Proceedings of the 4th Biennial International Workshop on Balto-Slavic Natural Language Processing, held at ACL'2013, pp. 110-118. Tanev Hristo (2007). Unsupervised Learning of Social Networks from a Multiple-Source News Corpus. Proceedings of the Workshop Multi-source Multilingual Information Extraction and Summarization (MMIES'2007) held at RANLP'2007, pp. 33-40. Borovets, Bulgaria, 26 September 2007. Tanev Hristo, Bruno Pouliquen, Vanni Zavarella & Ralf Steinberger (2010). Automatic Expansion of a Social Network Using Sentiment Analysis. In: Nasrullah Memon, Jennifer Jie Xu, David Hicks & Hsinchun Chen (eds). Annals of Information Systems, Volume 12. Special Issue on Data Mining for Social Network Data, pp. 9-29. Springer Science and Business Media (DOI 10.1007/978-1-4419-6287-4_2). Tanev Hristo, Jakub Piskorski & Martin Atkinson (2008). Real-time News Event Extraction for Global Crisis Monitoring. In V. Sugumaran, M. Spiliopoulou, E. Kapetanios (editors) Proceedings of 13th International Conference on Applications of Natural Language to Information Systems (NLDB 2008 ), Lecture Notes in Computer Science, Cool. 5039, 24-27 June, London, UK. Tanev Hristo, Maud Ehrmann, Jakub Piskorski & Vanni Zavarella (2012). Enhancing Event Descriptions through Twitter Mining. In: AAAI Publications, Sixth International AAAI Conference on Weblogs and Social Media, pp 587-590. Dublin, June 2012. Tanev Hristo, Vanni Zavarella, Jens Linge, Mijail Kabadjov, Jakub Piskorski, Martin Atkinson & Ralf Steinberger (2009). Exploiting Machine Learning Techniques to Build an Event Extraction System for Portuguese and Spanish. In: linguaMÁTICA Journal:2, pp. 55-66. Available at: . Turchi Marco, Martin Atkinson, Alastair Wilcox, Brett Crawley, Stefano Bucci, Ralf Steinberger & Erik van der Goot (2012). ONTS: "OPTIMA" News Translation System. Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL), pp. 25–30, Avignon, France, April 23 - 27 2012. Van der Goot Erik, Hristo Tanev & Jens Linge (2013). Combining twitter and media reports on public health events in MedISys. Proceedings of the 22nd international conference on World Wide Web companion, pp. 703-718. International World Wide Web Conferences Steering Committee, 2013. Zavarella Vanni, Hristo Tanev, Jens Linge, Jakub Piskorski, Martin Atkinson & Ralf Steinberger (2010). Exploiting Multilingual Grammars and Machine Learning Techniques to Build an Event Extraction System for Portuguese. In: Proceedings of the International Conference on Computational Processing of Portuguese Language (PROPOR'2010), Porto Alegre, Brazil, 27-30 April 2010. Springer Lecture Notes for Artificial Intelligence, Vol. 6001, pp. 21-24. Springer. Observing Trends in Automated Multilingual Media Analysis Authors: Ralf, Aldo, Alexandra, Guillaume, Hristo, Martin, Michele, Yaniv, Erik European Commission – Joint Research Centre (JRC), Ispra (VA), Italy e-mail: Ralf.Steinberger@jrc.ec.europa.eu ( corresponding author )
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