A creature that roamed the coasts of the Pacific Northwest about 20 million years ago may have had a feeding style like no other mammal, a new study suggests. Kolponomos is known only from two bearlike skulls, jawbones, and some toe bones found a few decades ago, so scientists aren’t sure where it fits on the carnivore family tree or even what it really looked like (one artist’s idea is seen above). Rather than having cheek teeth that could shear meat, as many carnivores do, Kolponomos’s molars were similar to the flattened, low-crowned teeth that otters use to crush their shelled prey—yet the creature lived long before anything similar to modern-day otters evolved. Now, a new analysis using the same sort of computer software that engineers employ to analyze bridges and aircraft parts suggests that Kolponomos may have collected its shelly prey in a unique way: They might have used their teeth and formidable neck muscles to clamp down on clams, mussels, and other mollusks and then wrench them directly off the rocks to which they were attached, the researchers report online today in the Proceedings of the Royal Society B. (Modern marine mammals that consume such prey either slurp them right out of the shell, as walruses do, or pry them from the rocks using their forelimbs and then eat them, as otters do.) Besides having a larger-than-normal chin, a deep jawbone, and massive neck muscles even larger than those of today’s bears, Kolponomos had odd grooves worn into the outer surfaces of the large canine teeth at the front of the lower jaw. With its lower canine teeth wedged firmly into place beneath a shell, Kolponomos could have braced its chin on the underlying rock, clamped down on its prey, and then popped it off the rock like a bottle opener. And although otters experience large stresses in their jawbones when crushing shelled prey, Kolponomos, whose jawbone was relatively longer and wider, likely didn’t have as much trouble.
NSF would receive $8.64 billion, $561 million above its current budget. The Trump administration had requested a cut of 12.5%, or $1 billion, to $7.1 billion. NSF’s research and related activities get an increase of 8.9%, or $586 million, to $7.1 billion. The White House had proposed a 13% cut to $5.6 billion. NASA receives an $815 million increase to $22.3 billion. The Trump administration requested a cut of 2%, or $480 million, to $21 billion. NASA’s science programs receive a $256 million boost to $7.2 billion, a 3.7% increase. The administration requested a cut of 8.7%, or $600 million, to $6.3 billion. Research programs at the National Institute of Standards and Technology get an increase of 3.7%, or $27 million, to $751 million. The administration asked for a cut of 15.5%, or $112 million, to $612 million. The budget of the National Oceanic and Atmospheric Administration would stay roughly flat at about $5.4 billion, nearly $1 billion above the president’s request of $4.5 billion. The National Science Foundation (NSF) would get a 7% budget increase, and NASA a 3.8% bump, under a 2020 spending bill approved today by an appropriations panel of the U.S. House of Representatives. The bill rejects cuts to those and other federal research agencies proposed by President Donald Trump’s administration.The bill includes $73.9 billion in funding for the departments of commerce and justice, as well as independent agencies such as NSF, for the 2020 fiscal year that begins 1 October. It includes “robust funding to address climate change and support scientific research,” said Representative José Serrano (D–NY), chair of the House appropriations subcommittee handling the bill.Some highlights: The bill now goes to the full House appropriations panel for a vote. The Senate has yet to release its version of the funding bill, and it is not clear whether Congress and the White House will be able to reach agreement on 2020 spending before the fiscal year begins this fall. If no agreement is reached, 2019 spending levels could be extended into the new fiscal year, or the government could shut down. By Science News StaffMay. 17, 2019 , 3:25 PM iStock.com/uschools NSF, NASA, NIST would get funding boosts under House spending bill
Norway has accepted a deal in which its Oslo-based Kon-Tiki Museum is due to return a trove of artifacts belonging to Easter Island, whose first inhabitants were the Rapa Nui people. The artifacts, which include human bones, ancient weapons and carved items, were claimed by one of Norway’s most esteemed explorers, Thor Heyerdahl, who visited the remote Pacific island (today under the jurisdiction of Chile) during the 1950s and 1980s.The repatriation deal was endorsed by the explorer’s son, Thor Heyerdahl Jr., on behalf of the museum and Chilean officials at a special ceremony in Chile’s capital of Santiago, the Guardian reports. The event was carried out during an official state visit by Norwegian King Harald V and his spouse Queen Sonja.King Harald V in 2013. Photo by Sámediggi Sametinget – H.M. Kong HaraldCC BY-SA 2.0Thor Heyerdahl Jr., who as a teenager joined his explorer-father in 1955 on the mission to the Pacific island, said: “This repatriation is a fulfillment of my father’s promise to the Rapa-Nui authorities, that the objects would be returned after they had been analyzed and published.”“Our common interest is that the objects are returned and, above all, delivered to a well-equipped museum,” commented Martin Biehl, director of the Kon-Tiki Museum, according to the Guardian.Thor Heyerdahl, circa 1980The repatriation process may take some time, as Mr. Biehl also noted, but no other details were provided at this point.In another statement, the Chilean culture minister, Consuelo Valdes, said: “As a ministry, we have the mission to respond to the just demand of the Rapa Nui people to recover their cultural heritage.”The ceremonial signing between Norway and Chile comes only a few months after the governor of Easter Island emotionally pleaded for the British Museum in London to return a moai statue of Hoa Hakananai’a, claimed by the British vessel HMS Topaze in 1868.The grandiose moai, which is among the greatest attractions at the British Museum, bears a name that translates to “lost or stolen friend.” Made of basalt, the hefty piece was initially gifted to Queen Victoria, after which it ended up in the British Museum.Parole list for the Kon-Tiki expedition, carved in wood by Thor Heyerdahl, and used onboard the Kon-Tiki expedition. Photo by Bjoertvedt CC BY-SA 4.0Discussions have been held between the British Museum and Easter Island officials but the British Museum has so far only given signs that it may loan the moai but not fully return.Moai sculptures are spiritually very important to the indigenous Rapa Nui community. In each moai, they see the embodiment of an important ancestor from the past. A moai is also the living incarnation of that ancestor, the belief goes.Perhaps Norway’s move to repatriation will help the Rapa Nui claim back their long sought-after “lost friend.”Rapa Nui statuesNorway obtained its deal of Easter Island artifacts in 1956 following Thor Heyerdahl’s expedition to the island. His goal was to use the trove as evidence to his theory that ancient South American populations were the first to sail and reach the remote island. Later research, however, suggested the area was first reached by migrating populations whose origin was in South East Asia.Previously, in 1947, Heyerdahl gained tremendous popularity as he managed to sail a great section of the Pacific on a balsa wood raft named the Kon-Tiki.Moai, Kon-Tiki Museum, Oslo, Norway. Photo by Николай Максимович CC BY 3.0Five more people joined his arduous adventure. The expedition members spent an astonishing 101 days on the open sea, a route encompassing 3,728 miles, before reaching Polynesia’s Raroia atoll. The effort, which commenced from Peru, was also the first of its kind to be filmed, and proved Oscar-worthy in 1951.While the raft expedition supported claims that indigenous people from South America would have been capable of reaching the remote islands of the Pacific, there was still no proof they really did so.Read another story from us: “You Have Our Soul” – Easter Island Governor Begs British Museum to Return StatueHeyerdahl conducted a number of other expeditions around the world. He would return to Easter Island once more in 1986-1988; he passed away in 2002 at the age of 87.
ShareTweetSharePinPrimary performer at the event, Mel, receives her award from Miss Dominica 2019This year, commemorative 10th anniversary awards for Jazz and Creole were presented to the primary acts at the event: The Smith Brothers, Johann Chuckaree, Mel, Boo Hinkson and Tony Chasseur.DNO interviewed some of the artists shortly after their performances. Band leader of the young and upcoming band Smith Brothers, Marxian Smith said performing with his brothers was an amazing experience.“It’s very humbling because I get to play with my family. So, it’s very moving for me… it’s emotional. I was really satisfied…looking back I can say it was good. I’m very happy for the efforts that my brothers have made individually in terms of practice and the work that they put in,” he said.He added, “I see more songs… we have a first one which is “You are my world” and the next one that we brought out recently is called “So fine”. I see more songs coming for sure and more performances on bigger stages, hopefully out of Dominica because we want to bring Dominica’s name somewhere.”Twelve-year old Micah Smith, who is the band’s youngest brother and lead singer, said that he felt “honored” to be chosen to sing at Jazz ‘n Creole. The other brothers who make up the band are Mighan the bass player and Michaj on drums.Smith Brothers perform at the eventPannist from Trinidad and Tobago, Johann Chuckaree, who played a variety of scintillating pieces from various genres, said the energy of the crowd was fantastic.“Steel pan being the only instrument invented in the 20th century…It’s the instrument of the Caribbean. It’s anonymous with Caribbean islands and I think it’s in each and every one of us.. Every Caribbean person is growing that love for the steel pan. It’s amazing to be able to move an audience just with that beautiful instrument,” Chuckaree said.“The versatility of the pan cannot be matched. You can do every genre music; that’s what I tried to demonstrate here today… to the reggae…to the R&b…to the pop…to the soca, most importantly.”He said Dominica is a beautiful island and he was happy and thrilled to be here.Johann Chukaree in action at the festivalGuitarist/Producer from Saint Lucia , Ronald Boo Hinkson gave some advice to young people who are interested in becoming artists.“What I want to tell them is to practice…I want to tell them to stay off drugs, you don’t need to do drugs even if you see people doing it…you have to figure out what’s it’s going to do to you and what’s it’s going to do to your future,” Hinkson advised. “Study the business of the music because technology keeps changing the business of the music all the time and find people who are better than you and learn from them.”He also encouraged young people to make a good investment in the money earned from music.Hinkson said his experience has been amazing and everybody has been welcoming and that crowd is so warm and embracing that they make you want to play.He said is now on tour under the name “Boo Hinkson and Friends” alongside Irvin “ACE” Loctar who was his lead vocalist at Jazz and creole.The main event of the 10th edition of Jazz ‘n Creole was held at Fort Shirley at Cabrits National Park on May 5th, 2019.Ronald ‘Boo’ HinksonBelow is a video of UMOJA performing at the event.A section of the crowd at the eventVideo Playerhttps://dominicanewsonline.com/news/wp-content/uploads/2019/05/WhatsApp-Video-2019-05-06-at-12.05.32-PM.mp400:0000:0000:26Use Up/Down Arrow keys to increase or decrease volume.
Top News Advertising After Masood Azhar blacklisting, more isolation for Pakistan By Reuters |Tunis | Published: July 6, 2019 9:47:42 am The decision follows Tuesday’s suicide bombing in Tunis by a wanted militant.It was the third such incident within a week and came as Tunisia prepares for autumn elections and at the peak of a tourist season in which the country hopes to draw record number of visitors. Islamic State has claimed all three attacks. It has been banned “for security reasons”. (File Photo)Tunisian Prime Minister Youssef Chahed has banned the wearing of the niqab face veil in public institutions “for security reasons” an official source told Reuters on Friday. Cabinet asks finance panel to consider securing funds for defence Karnataka trust vote today: Speaker’s call on resignations, says SC, but gives rebel MLAs a shield 6 Comment(s)
Robots—like people—use ‘imagination’ to learn concepts Instead of relying on a list of rules or training on a massive data set like standard computers, a new computational framework for learning lets robots come up with their own concepts by detecting abstract differences in images and then recreating them in real life. Watch the video to learn more. By Chris BurnsJan. 16, 2019 , 2:50 PM
CBI carried out searches at 18 locations in Delhi, Silchar, Jalpaiguri, Guwahati and Gwalior. (File)The CBI has arrested seven persons, including two senior officers of the National Projects Construction Corporation (NPCC) Limited, for alleged bribery in clearing bills pertaining to the construction of BSF border outposts, officials said on Monday. The agency has arrested Rakesh Mohan Kotwal, NPCC Zonal Manager and Manager Latiful Pasha, and five private persons in the case, they said.It is alleged that Kotwal and Pasha had demanded a bribe of Rs 33 lakh from Anish Baid, owner of the Shree Gautam Construction Company Ltd, for passing the bills for construction of Border Security Force (BSF) border outposts done by his firm, the officials said.The Central Bureau of Investigation (CBI) carried out searches at 18 locations in Delhi, Silchar, Jalpaiguri, Guwahati and Gwalior, they said. By PTI |New Delhi | Published: July 15, 2019 5:06:40 pm Top News 4 Comment(s) Karnataka trust vote today: Speaker’s call on resignations, says SC, but gives rebel MLAs a shield Advertising After Masood Azhar blacklisting, more isolation for Pakistan Cabinet asks finance panel to consider securing funds for defence
NRC deadline approaching, families stranded in Assam floods stay home It’s a question Democrats keep hearing: ‘Can a woman win?’ By New York Times |Washington | Published: July 9, 2019 10:55:41 am After joking tweet, comedian gets love life advice from Democratic candidate Elizabeth Warren In undecided Congress, first open call for Priyanka: She should be party chief The third quarter is a traditionally difficult fundraising period, and Warren must also overcome concerns that linger among Democrats over how she would fare against Trump in a general election. In a Washington Post/ABC News poll published last week, just 7% of Democrats and Democratic-leaning independents said Warren had the best chance to beat Trump next year. (Biden led on that question, with 45% saying he had the best shot.)Warren collected money in the second quarter from more than 384,000 donors, whose donations averaged $28, her campaign said. She finished the quarter with $19.7 million in cash on hand, less than $100,000 of which is earmarked for the general election, her campaign said. Climate change takes center stage as Biden and Warren release plans Warren’s total for the second quarter, which ran from April through June, is likely to place her third in fundraising among Democrats over that period.Two candidates have reported topping $20 million in the second quarter: Mayor Pete Buttigieg of South Bend, Indiana, raised $24.8 million, and former Vice President Joe Biden collected $21.5 million, their campaigns said last week.Sanders — who has also avoided high-dollar fundraisers — brought in $18 million in the quarter, and Sen. Kamala Harris of California raised nearly $12 million, their campaigns said.Warren’s fundraising total is the latest evidence that her policy-driven strategy is resonating with a growing segment of the Democratic base. Related News Advertising Best Of Express Advertising In this May 16, 2019, photo, Democratic presidential candidate Sen. Elizabeth Warren, D-Mass., addresses a campaign rally at George Mason University in Fairfax, Va. Warren is gaining traction with black women debating which Democratic presidential candidate to back in a historically diverse primary. (AP Photo/Cliff Owen)Written by Reid J Epstein and Astead W Herndon 1 Comment(s) Senator Elizabeth Warren of Massachusetts raised $19.1 million in the past three months, her campaign said Monday, a total that places her firmly in the top echelon of the Democratic money race and ahead of her main rival for the party’s progressive wing, Senator Bernie Sanders of Vermont.The fundraising haul represents a turnaround for Warren after she raised just $6 million in her campaign’s first three months, before her strategy of eschewing wealthy donors and inundating voters with detailed policy proposals began to pay dividends.Warren’s campaign team said her fortunes had begun to turn the last week of March, about a month after her decision to forgo closed-door fundraising events during the primary campaign. Karnataka: SC to rule today, says Speaker’s powers need relook
Reviewed by James Ives, M.Psych. (Editor)Oct 31 2018Arteriosclerosis is one of the widespread diseases. If the blood is no longer pumped properly through the veins, a heart attack or stroke may be the consequence. In most cases, the disease is only diagnosed at an advanced stage. Computer scientists from Kaiserslautern are working on software that will enable doctors to detect calcification early on and to plan surgeries more effectively. For this purpose, they use image data from computer tomographies (CT). At the Medica medical technology trade fair from 12th to 15th November in Düsseldorf, they will present the technology at the research stand (Hall 7a, Stand B06) in Rhineland Palatinate.Too little exercise, unhealthy food, smoking – these factors promote arteriosclerosis. In industrialized countries, the disease is responsible for half of all deaths. “It is usually only discovered when it has already advanced,” says Christina Gillmann from the Technische Universität Kaiserslautern (TUK). “On CT images, physicians can only recognize these deposits, if thicker layers are already present on the vessel walls.” The only therapy that can then be considered at this point is surgery.However, if arteriosclerosis is detected at an early stage, it can be treated with a healthy diet and exercise. That’s what the computer scientists around Gillmann are working on. They are developing a computer programme to help doctors make an early diagnosis. In this method, already existing CT images are used. This X-ray method provides doctors with patient images in layers, which are usually shown in grayscale. “The resolution of these images is not very high,” says the computer scientist. “To detect arteriosclerosis at an early stage, the data must be processed in a different way.”Related StoriesRepurposing a heart drug could increase survival rate of children with ependymomaAMSBIO offers new, best-in-class CAR-T cell range for research and immunotherapyOlympus Europe and Cytosurge join hands to accelerate drug development, single cell researchGillmann and her team screen the CT images for additional information with their software. For example, they are able to accurately represent the arterial bifurcations and better classify and locate the progress of the disease. In addition, the computer scientists analyze different types of catheters that can be used during the operations. In this way, the best possible solution can be found for the individual patient and the risk of potential complications during and after the surgery can be reduced. The researchers at the TUK are developing their system in collaboration with doctors from Dayton in the USA under Professor Dr Thomas Wischgoll and from Colombia under Professor Dr José Tiberio Hernández Peñaloza.However, a few more years of development work will be needed before the system can be used in hospitals. The method will also be of interest to industrial companies. They could, for example, use the technology to screen their products more specifically in order to detect possible damaged areas.At Medica, the scientists will present their method at the research stand of Rhineland-Palatinate.Gillmann is researching in the field of “Computer Graphics and Human Computer Interaction” under Professor Dr Hans Hagen. For about two decades now, the research group has been working on processing medical imaging data in such a way that they can be used easily and reliable in everyday clinical practice. For example, they have succeeded in using their methods to separate tumors from healthy tissue more clearly in images. In their projects, the computer scientists work closely with various partners, including the University Hospital Leipzig and the Premier Health Hospital in Ohio.Source: https://www.uni-kl.de/en/
Reviewed by Alina Shrourou, B.Sc. (Editor)Jul 1 2019Charity Parkinson’s UK is partnering with NRG Therapeutics Ltd to discover and develop a potential drug that could safeguard dopamine cells that are damaged by Parkinson’s and slow down the progression of the condition.Building on recent discoveries that show a direct link between mitochondrial dysfunction and the loss of dopamine cells, Parkinson’s UK will invest up to £1 million in NRG Therapeutics to develop and translate this pioneering research into a potential therapeutic.Mitochondria are the powerhouses of cells and help manage large amounts of calcium ions that continually flow into the cell when it is active, which can become toxic if not removed.When mitochondria become overloaded with calcium and stop producing energy effectively, a pore in the mitochondria – known as the mitochondrial permeability transition pore – is opened. This starts the process of cell death, leading to the loss of dopamine-producing brain cells.Related StoriesAn active brain and body associated with reduced risk of dementiaRush University Medical Center offers new FDA-approved treatment for brain aneurysmsResearch team to create new technology for tackling concussionThe initial investment in NRG Therapeutics from Parkinson’s UK will support the identification of novel, small, molecules that are likely to enter the brain and protect the mitochondria within dopamine-producing cells.If successful, these molecules will be tested in pre-clinical models of Parkinson’s disease before progressing into small-scale human clinical trials to investigate their safety and potential benefits as a treatment.Dr Arthur Roach, Director of Research at Parkinson’s UK, who recently joined NRG Therapeutics as Non-Executive Director, said: NRG Therapeutics is committed to delivering new treatments for people affected by devastating neurodegenerative diseases such as Parkinson’s and are delighted to have received this seed investment from Parkinson’s UK’s Virtual Biotech program.We welcome this endorsement of our scientific strategy and look forward to partnering with Parkinson’s UK in developing first-in-class molecules for the disease-modifying treatment of Parkinson’s.” Dr Neil Miller, CEO of NRG Therapeutics, said: We all know there is a tremendous need to find better treatments for Parkinson’s that can slow down the progression of the condition. This pioneering research could be the first step towards identifying molecules that can protect mitochondria within dopamine-producing cells. It is a privilege to be appointed to the board of NRG Therapeutics. I look forward to working with them as we strive to reach our goal of bringing forward better treatments and finding a cure for Parkinson’s.” Parkinson’s UK is the largest charitable funder of Parkinson’s research in Europe.The aim of its Virtual Biotech program, of which its partnership with NRG Therapeutics Ltd is a part, is to fast-track the most promising treatments with the potential to transform life for people with Parkinson’s. Source:Parkinson’s UK
The Sun is becoming an increasingly important source of clean electricity. Accurate sunlight forecasts being developed by A*STAR researchers could greatly improve the performance of solar energy plants, making it a viable alternative to carbon-based sources of power. New solar forecasting tool could help increase efficiency and reduce energy costs Citation: Improved forecasting of sunlight could help increase solar energy generation (2018, June 25) retrieved 18 July 2019 from https://phys.org/news/2018-06-sunlight-solar-energy.html Explore further Provided by Agency for Science, Technology and Research (A*STAR), Singapore Journal information: Solar Energy More information: Dazhi Yang et al. Reconciling solar forecasts: Temporal hierarchy, Solar Energy (2017). DOI: 10.1016/j.solener.2017.09.055 A photovoltaic power plant can cover up to 50 square kilometers of the Earth’s surface and can generate up to a billion Watts of electricity. This capacity depends on the amount of sunlight at that location, so the ability to predict solar irradiance is crucial for knowing how much power the plant will contribute to the grid on any particular day.”Forecasting is a key step in integrating renewable energy into the electricity grid,” says Dazhi Yang from A*STAR’s Singapore Institute of Manufacturing Technology (SIMTech). “It is an emerging subject that requires a wide spectrum of cross-disciplinary knowledge, such as statistics, data science, or machine learning.”Yang, together with Hao Quan from the A*STAR Experimental Power Grid Centre and colleagues from the University of Tennessee at Chattanooga and the National University of Singapore, has developed a numerical approach to weather prediction that efficiently combines multiple datasets to improve the accuracy of solar irradiation forecasts.Hourly changes in the atmosphere, annual changes in the distance between Earth and the Sun, or 10-yearly changes in the Sun’s internal cycles can all alter the amount of sunlight that reaches the Earth’s surface. These changes occur on very different time scales, and so conventional forecasting methods model variability at different timescales separately, which makes computer processing easier. However, these methods rely on a simple addition of forecasts, with no weighting that makes more use of better forecast sub-series. Moreover, the forecasts they generate are only accurate on the timescale of the original series.Yang and the team developed a framework that reconciles the different timescales by forming a temporal hierarchy that aggregates forecasts obtained at different timescales, such as high-frequency, hourly data and low-frequency, daily data. “Temporal reconciliation is a type of ensemble forecasting model that forecasts the next day’s solar generation many times, separately, using data of different temporal granularities, hourly, two-hourly, and daily,” explains Yang. “These different forecasts are then combined optimally through statistical models to produce a final forecast.”The researchers tested their numerical weather prediction method using data from 318 photovoltaic power plant sites in California over a year. Their temporal reconciliation method was shown to significantly outperform other numerical day-ahead forecasts. This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.
Apple fined millions for Australia false iPhone claims © 2018 AFP Citation: Air New Zealand fined in Australia air cargo cartel case (2018, June 27) retrieved 18 July 2019 from https://phys.org/news/2018-06-air-zealand-fined-australia-cargo.html Explore further This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. The carrier was taken to court by the Australian Competition and Consumer Commission (ACCC) over allegations it had agreements with other airlines to fix the price of fuel and insurance surcharges on freight services to and from international airports from 2002 to 2007.”These illegal price-fixing agreements unfairly reduced competition for the transport cost for goods flown into Australia,” ACCC commissioner Sarah Court said in a statement.”This decision sends a strong warning to overseas and domestic operators that the ACCC can and will continue to defend competition and the rights of Australian customers and businesses by taking action against anti-competitive conduct.”The Federal Court ordered Air New Zealand to pay Aus$11.5 million for fixing fuel surcharges for cargo from Hong Kong to Australia, and Aus$3.5 million for insurance and security surcharge fixing from Singapore to Australia.Air New Zealand, which also agreed to pay Aus$2.0 million of the ACCC’s legal costs, said in a statement it was glad the issue was resolved.”We have worked closely with the ACCC over the past year to reach this position which is in line with previous settlements reached with other international airlines,” the carrier added.So far, 14 airlines have been penalised a total of Aus$113.5 million since the Australian consumer watchdog launched its investigation into the cartel in 2006.Those hit with fines in Australia include Qantas, Dubai carrier Emirates, Singapore Airlines, British Airways and Air France KLM.A penalty hearing against another airline, Garuda Indonesia, was heard this week, with the judgement reserved.Top airlines have also been in legal battles against the European Commission for imposing large fines for their roles in an air cargo cartel from, to and within the European Economic Area between 1999 and 2006. Air New Zealand was fined over illegal price-fixing agreements with other airlines on freight services to Australia Air New Zealand was Wednesday fined Aus$15 million (US$11 million) by an Australian court for its part in a global air cargo cartel involving major international airlines.
Provided by CORDIS Customers generally frustrated with the experience of reaching out to contact centres may finally get to change their mind, thanks to a Big Data mining solution brought by the BISON project. We’re all familiar with this pre-recorded, often robotic voice that tells us how phone conversations with the likes of e-commerce businesses or after-sale services “may be recorded for quality assurance purposes.” Now if you ever wondered what these companies were actually doing with the recordings… the truth is, not as much as they could.To date, contact centres have only been able to analyse a fraction of the calls they record. They often do this manually or with rudimentary software, and undoubtedly miss out on very important trends and issues in the process. The BISON (BIg Speech data analytics for cONtact centres) project hoped to toss this problem onto the garbage heap of history with the help of innovative Big Data mining software. Their solution is already being used in several contact centres in Central Europe, and they have big plans for the rest of the continent. What would industry stand to gain from more evolved use of contact centre data mining?Mr Marek Klimes: Better efficiency and consequently lower costs. Nowadays, contact centres are able to listen to 1-3 % of calls only. With contact centre data mining, you would be able to get information from 100 % of calls to support your decisions. Who should be trained in your team, what do your customers want or what are the emerging topics? All this information is available in your calls. What are the most innovative aspects of your approach to such data mining?We have used the complete portfolio of speech technologies, including both speech analytics technologies (speech transcription and keyword spotting) and voice biometrics in multiple European languages. This enabled our teams to cover diverse use cases in contact centres. Besides its compliance with the law, our product also takes into account new challenges related to Big Data and the anonymisation of private data. What legal aspects did you focus on and why?Legal and ethical aspects were often perceived as an obstacle to the creation of a good product. The BISON consortium believed in the opportunity to create a product complying with all necessary legal requirements by design. Citation: Big Data mining for better contact centre performance (2018, June 27) retrieved 18 July 2019 from https://phys.org/news/2018-06-big-contact-centre.html Rare white bison born at Belgrade Zoo Credit: GarryKillian, Shutterstock This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. We have created the BISON societal and ethical code, which helps potential BISON users from the earliest deployment to actual usage. This code answers questions from four main pillars: How EU data protection rules can effectively protect citizens from modern technologies; how the EU regulatory framework can be exploited to develop law-abiding technologies; how to develop an ethical system respecting user privacy; and how BISON handles privacy issues.Can you provide an example of possibilities brought by your technology?There are many different ways to leverage the solution developed under the BISON project. Broadly speaking, you can unveil blind spots in contact centres that result in higher costs. To be more specific, we can tell you if contact centre agents speak too fast, interrupt customers or are having overly long monologues or even what the most common topic brought up during calls is. Another example: if you are suddenly handling more calls about a problem with internet connections, you will know it from our topic detection tool. Finally, we provide long-term statistics displaying the progress of contact centres in easy-to-understand graphic layers displayed in the BISON dashboard. What were the main outcomes of prototype testing?We confirmed the soundness of our vision for the contact centre market and gathered valuable user feedback. At the same time, we also found out about various missing details in the prototype. Direct connections with contact centres within the BISON consortium helped us improve our reporting tools and usage of the BISON recording management tool.What has been the feedback from industry so far?We have had positive reactions on how our system deals with unstructured data. The problem currently being faced by contact centres is not so much the lack of data but rather the lack of solutions to learn from. A typical contact centre produces a wealth of multilingual spoken data that is nowadays mined by humans or by rudimentary technical means. Our system automates this process.What are your plans for commercialisation?From the very start of the project, we have been striving for the commercialisation of BISON. Due to the geographical position of project participants and the 14 European languages covered in the project, we focus on Central Europe with the plan to spread our system across the rest of the continent. I am glad to announce that we have already successfully deployed our system in production environments across several call centres. Explore further
A closer look at the peopleNext we set out to measure the opinions of the people in our data set. We did this with a type of machine learning algorithm called a neural network, which in this case we set up to evaluate the content of each tweet, determining the extent to which it supported Clinton or Trump. Individuals’ opinions were calculated as the average of their tweets’ opinions. My work focuses on military and national security aspects of social networks, so naturally I was intrigued by concerns that bots might affect the outcome of the upcoming 2018 midterm elections. I began investigating what exactly bots did in 2016. There was plenty of rhetoric – but only one basic factual principle: If information warfare efforts using bots had succeeded, then voters’ opinions would have shifted. I wanted to measure how much bots were – or weren’t – responsible for changes in humans’ political views. I had to find a way to identify social media bots and evaluate their activity. Then I needed to measure the opinions of social media users. Lastly, I had to find a way to estimate what those people’s opinions would have been if the bots had never existed.Finding tweeters and botsTo narrow the research a bit, my students and I focused our analysis on the Twitter discussion around one event in the lead-up to the election: the second debate between Clinton and Trump. We collected 2.3 million tweets that contained keywords and hashtags related to the debate. Then we made a list of the roughly 78,000 Twitter users who posted those tweets and constructed the network of who followed whom among those users. To identify the bots among them, we used an algorithm based on our observation that bots often retweeted humans but were not themselves frequently retweeted.This method found 396 bots – or less than 1 percent of the active Twitter users. And just 10 percent of the accounts followed them. I felt good about that: It seemed unlikely that such a small number of relatively disconnected bots could have a major effect on people’s opinions. Numbers are a relative Clinton-support score out of 100. Credit: The Conversation, CC-BY-ND Source: Tauhid Zaman et al Provided by The Conversation Adding bots into an online discussion can definitely affect the views of real people. Credit: Tatiana Shepeleva/Shutterstock.com Once we had assigned each human Twitter user in our data a score representing how strong a Clinton or Trump backer they were, the challenge was to measure how much the bots shifted people’s opinions – which meant calculating what their opinions would have been if the bots hadn’t existed.Fortunately, a model from as far back as the 1970s had established a way to gauge people’s sentiments in a social network based on connections between them. In this network-based model, individuals’ opinions tend to align with the people connected to them. After slightly modifying the model to apply it to Twitter, we used it to calculate people’s opinions based on who followed whom on Twitter – rather than looking at their tweets. We found that the opinions we calculated from the network model matched well with opinions measured from the content of their tweets.Life without the botsSo far we had shown that the follower network structure in Twitter could accurately predict people’s opinions. This now allowed to us to ask questions such as: What would their opinions have been if the network were different? The different network we were interested in was one that contained no bots. So for our last step, we removed the bots from the network and recalculated the network model, to see what real people’s opinions would have been without bots. Sure enough, bots had shifted human users’ opinions – but in a surprising way. Given much of the news reporting, we were expecting the bots to help Trump – but they didn’t. In a network without bots, the average human user had a pro-Clinton score of 42 out of 100. With the bots, though, we had found the average human had a pro-Clinton score of 58. That shift was a far larger effect than we had anticipated, given how few and unconnected the bots were. The network structure had amplified the bots’ power.We wondered what had made the Clinton bots more effective than the Trump bots. Closer inspection showed that the 260 bots supporting Trump posted a combined 113,498 tweets, or 437 tweets per bot. However, the 150 bots supporting Clinton posted 96,298 tweets, or 708 tweets per bot. It appeared that the power of the Clinton bots came not from their numbers, but from how often they tweeted. We found that most of what the bots posted were retweets of the candidates or other influential individuals. So they were not really crafting original tweets, but sharing existing ones.It’s worth noting that our analysis looked at a relatively small number of users, especially when compared to the voting population. And it was only during a relatively short period of time around a specific event in the campaign. Therefore, they don’t suggest anything about the overall election results. But they do show the potential effect bots can have on people’s opinions.A small number of very active bots can actually significantly shift public opinion – and despite social media companies’ efforts, there are still large numbers of bots out there, constantly tweeting and retweeting, trying to influence real people who vote. It’s a reminder to be careful about what you read – and what you believe – on social media. We recommend double-checking that you are following people you know and trust – and keeping an eye on who is tweeting what on your favorite hashtags. This article is republished from The Conversation under a Creative Commons license. Read the original article. Explore further Nearly two-thirds of the social media bots with political activity on Twitter before the 2016 U.S. presidential election supported Donald Trump. But all those Trump bots were far less effective at shifting people’s opinions than the smaller proportion of bots backing Hillary Clinton. As my recent research shows, a small number of highly active bots can significantly change people’s political opinions. The main factor was not how many bots there were – but rather, how many tweets each set of bots issued. Software ‘bots’ distort Trump support on Twitter: study Citation: Even a few bots can shift public opinion in big ways (2018, November 5) retrieved 17 July 2019 from https://phys.org/news/2018-11-bots-shift-opinion-big-ways.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.
Citation: Ethiopia to send black boxes to Europe as questions mount over crash (2019, March 13) retrieved 17 July 2019 from https://phys.org/news/2019-03-ethiopia-black-europe-mount.html Ethiopia said Wednesday it would send the black boxes from last weekend’s deadly Ethiopian Airlines crash to Europe for analysis as demand grew for urgent answers over the safety of the Boeing 737 MAX 8. Updated graphic on the crash of Ethiopian Airlines ET302 on Sunday According to anonymous pilot reports on a National Aeronautics and Space Administration (NASA) database seen by AFP, several American pilots reported problems with the same system in late 2018. The second deadly crash involving the plane type in less than six months prompted governments worldwide to ban Boeing’s bestselling jet from their airspace. The move has heaped pressure on the US aerospace giant to provide proof the plane is safe.In Ethiopia, distraught families wept and lit candles as they visited the deep black crater where the plane smashed into a field, killing 157 passengers and crew, an AFP correspondent said. Ethiopian Airlines said it would decide by Thursday which country would examine the cockpit voice recorder and flight data recorder recovered from ill-fated Flight ET 302, spokesman Asrat Begashaw told AFP.”We are going to send it to Europe, but the country is not specified yet,” said Asrat.The airline said Ethiopia does not have the equipment to read the black box data that could provide crucial information about what happened.The Ethiopian Airlines 737 MAX 8 was less than four months old when it went down six minutes into a flight from Addis Ababa to Nairobi on Sunday, disintegrating on impact.Asrat said families of the victims from Kenya, China, America, and Canada, as well as diplomatic staff from embassies, were visiting the crash site.Experts have pointed out similarities with a crash in October when an Indonesian Lion Air jet went down, killing 189 passengers and crew.’Significant similarities’Both planes reportedly experienced erratic steep climbs and descents as well as fluctuating airspeeds before crashing shortly after takeoff.Questions have honed in on an automated anti-stalling system introduced on the 737 MAX 8, designed to automatically point the nose of the plane downward if it is in danger of stalling.According to the flight data recorder, the pilots of Lion Air Flight 610 struggled to control the aircraft as the automated MCAS system repeatedly pushed the plane’s nose down following takeoff.The Ethiopian Airlines pilots reported similar difficulties before their aircraft plunged into the ground.Boeing came in for criticism after the Lion Air crash for allegedly failing to adequately inform 737 pilots about the functioning of the anti-stalling system. During one incident, a co-pilot said that shortly after take-off, when autopilot was engaged, the plane suddenly began pointing downwards. The captain immediately disconnected the autopilot and straightened the plane.Biniyam Demssie, another spokesman for Ethiopian Airlines, told AFP the pilots had received the relevant training.For “every new technology, we provide training at Ethiopian Airlines,” he said. Airline CEO Tewolde GebreMariam on Sunday said captain Yared Mulugeta Getachew, 29, was an experienced aviator with more than 8,000 flight hours.Speaking to CNN on Wednesday, Tewolde told CNN Wednesday there were “significant similarities” between the Lion Air and ET 302 crashes. “There are a lot of questions to be answered on the airplane.”In a separate interview with the BBC, he called for all Boeing 737 MAX models to be grounded.Banned from the skiesA dozen airlines have grounded the plane, while Lebanon, Egypt, Serbia, Vietnam, New Zealand and Hong Kong on Wednesday became the latest countries to ban it from their airspace.All European Union countries, as well as major hubs such as the United Arab Emirates and Australia have already done so.”At this early stage of the related investigation, it cannot be excluded that similar causes may have contributed to both events,” the EU aviation agency said.Low-cost airline Norwegian Air Shuttle has said it will demand financial compensation from Boeing as the implications of the mass grounding for the airline industry remained unclear.The United States, however, is resisting calls to ground the MAX series, which is Boeing’s fastest-selling model, with more than 5,000 orders placed to date from about 100 customers.”Thus far, our review shows no systemic performance issues and provides no basis to order grounding the aircraft,” Federal Aviation Administration (FAA) chief Daniel Elwell said in a statement on Tuesday.There are about 350 MAX 8s in service around the world.Thomas Anthony, head of the Aviation Safety and Security Program at the University of Southern California, said increasing automation of planes means crews have less experience flying manually.”So it’s not just a mechanical, it is not just a software problem, but it is a problem of communication and trust,” he said. Ethiopian Airlines crash: What is the MCAS system on the Boeing 737 Max 8? © 2019 AFP Explore further Governments around the world are grounding Boeing 737 Max aircraft or barring them from their airspace This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.
Microsoft Corporate Vice President for Business AI Gurdeep Pall talks at a recent conference about autonomous systems solutions that employ machine teaching. Credit: Dan DeLong for Microsoft Mark Hammond, Microsoft general manager for Business AI and former Bonsai CEO, developed a platform that uses machine teaching to help deep reinforcement learning algorithms tackle real-world problems. Credit: Dan DeLong for Microsoft And yet, this is in some ways how we approach machine learning today—by showing machines a lot of data and expecting them to learn associations or find patterns on their own. For many of the most common applications of AI technologies today, such as simple text or image recognition, this works extremely well.But as the desire to use AI for more scenarios has grown, Microsoft scientists and product developers have pioneered a complementary approach called machine teaching. This relies on people’s expertise to break a problem into easier tasks and give machine learning models important clues about how to find a solution faster. It’s like teaching a child to hit a home run by first putting the ball on the tee, then tossing an underhand pitch and eventually moving on to fastballs. “This feels very natural and intuitive when we talk about this in human terms but when we switch to machine learning, everybody’s mindset, whether they realize it or not, is ‘let’s just throw fastballs at the system,'” said Mark Hammond, Microsoft general manager for Business AI. “Machine teaching is a set of tools that helps you stop doing that.”Machine teaching seeks to gain knowledge from people rather than extracting knowledge from data alone. A person who understands the task at hand—whether how to decide which department in a company should receive an incoming email or how to automatically position wind turbines to generate more energy—would first decompose that problem into smaller parts. Then they would provide a limited number of examples, or the equivalent of lesson plans, to help the machine learning algorithms solve it. As a first step, the system has to know how to identify a quote from a contract or an invoice. Oftentimes, no labeled training data exists for that kind of task, particularly if each salesperson in the company handles it a little differently. If the system was using traditional machine learning techniques, the company would need to outsource that process, sending thousands of sample documents and detailed instructions so an army of people can attempt to label them correctly—a process that can take months of back and forth to eliminate error and find all the relevant examples. They’ll also need a machine learning expert, who will be in high demand, to build the machine learning model. And if new salespeople start using different formats that the system wasn’t trained on, the model gets confused and stops working well.By contrast, Pelton said, Microsoft’s machine teaching approach would use a person inside the company to identify the defining features and structures commonly found in a quote: something sent from a salesperson, an external customer’s name, words like “quotation” or “delivery date,” “product,” “quantity,” or “payment terms.” It would translate that person’s expertise into language that a machine can understand and use a machine learning algorithm that’s been preselected to perform that task. That can help customers build customized AI solutions in a fraction of the time using the expertise that already exists within their organization, Pelton said. Pelton noted that there are countless people in the world “who understand their businesses and can describe the important concepts—a lawyer who says, ‘oh, I know what a contract looks like and I know what a summons looks like and I can give you the clues to tell the difference.'”Making hard problems truly solvableMore than a decade ago, Hammond was working as a systems programmer in a Yale neuroscience lab and noticed how scientists used a step-by-step approach to train animals to perform tasks for their studies. He had a similar epiphany about borrowing those lessons to teach machines.That ultimately led him to found Bonsai, which was acquired by Microsoft last year. It combines machine teaching with deep reinforcement learning and simulation to help companies develop “brains” that run autonomous systems in applications ranging from robotics and manufacturing to energy and building management. The platform uses a programming language called Inkling to help developers and even subject matter experts decompose problems and write AI programs. Deep reinforcement learning, a branch of AI in which algorithms learn by trial and error based on a system of rewards, has successfully outperformed people in video games. But those models have struggled to master more complicated real-world industrial tasks, Hammond said. Adding a machine teaching layer—or infusing an organization’s unique subject matter expertise directly into a deep reinforcement learning model—can dramatically reduce the time it takes to find solutions to these deeply complex real-world problems, Hammond said. For instance, imagine a manufacturing company wants to train an AI agent to autonomously calibrate a critical piece of equipment that can be thrown out of whack as temperature or humidity fluctuates or after it’s been in use for some time. A person would use the Inkling language to create a “lesson plan” that outlines relevant information to perform the task and to monitor whether the system is performing well. Armed with that information from its machine teaching component, the Bonsai system would select the best reinforcement learning model and create an AI “brain” to reduce expensive downtime by autonomously calibrating the equipment. It would test different actions in a simulated environment and be rewarded or penalized depending on how quickly and precisely it performs the calibration. Telling that AI brain what’s important to focus on at the outset can short circuit a lot of fruitless and time-consuming exploration as it tries to learn in simulation what does and doesn’t work, Hammond said. “The reason machine teaching proves critical is because if you just use reinforcement learning naively and don’t give it any information on how to solve the problem, it’s going to explore randomly and will maybe hopefully—but frequently not ever—hit on a solution that works,” Hammond said. “It makes problems truly solvable whereas without machine teaching they aren’t.” Today, if we are trying to teach a machine learning algorithm to learn what a table is, we could easily find a dataset with pictures of tables, chairs and lamps that have been meticulously labeled. After exposing the algorithm to countless labeled examples, it learns to recognize a table’s characteristics. But if you had to teach a person how to recognize a table, you’d probably start by explaining that it has four legs and a flat top. If you saw the person also putting chairs in that category, you’d further explain that a chair has a back and a table doesn’t. These abstractions and feedback loops are key to how people learn, and they can also augment traditional approaches to machine learning.”If you can teach something to another person, you should be able to teach it to a machine using language that is very close to how humans learn,” said Patrice Simard, Microsoft distinguished engineer who pioneered the company’s machine teaching work for Microsoft Research. This month, his team moves to the Experiences and Devices group to continue this work and further integrate machine teaching with conversational AI offerings.Millions of potential AI usersSimard first started thinking about a new paradigm for building AI systems when he noticed that nearly all the papers at machine learning conferences focused on improving the performance of algorithms on carefully curated benchmarks. But in the real world, he realized, teaching is an equally or arguably more important component to learning, especially for simple tasks where limited data is available.If you wanted to teach an AI system how to pick the best car but only had a few examples that were labeled “good” and “bad,” it might infer from that limited information that a defining characteristic of a good car is that the fourth number of its license plate is a “2.” But pointing the AI system to the same characteristics that you would tell your teenager to consider—gas mileage, safety ratings, crash test results, price—enables the algorithms to recognize good and bad cars correctly, despite the limited availability of labeled examples. In supervised learning scenarios, machine teaching improves models by identifying these high-level meaningful features. As in programming, the art of machine teaching also involves the decomposition of tasks into simpler tasks. If the necessary features do not exist, they can be created using sub-models that use lower level features and are simple enough to be learned from a few examples. If the system consistently makes the same mistake, errors can be eliminated by adding features or examples. One of the first Microsoft products to employ machine teaching concepts is Language Understanding, a tool in Azure Cognitive Services that identifies intent and key concepts from short text. It’s been used by companies ranging from UPS and Progressive Insurance to Telefonica to develop intelligent customer service bots.”To know whether a customer has a question about billing or a service plan, you don’t have to give us every example of the question. You can provide four or five, along with the features and the keywords that are important in that domain, and Language Understanding takes care of the machinery in the background,” said Riham Mansour, principal software engineering manager responsible for Language Understanding.Microsoft researchers are exploring how to apply machine teaching concepts to more complicated problems, like classifying longer documents, email and even images. They’re also working to make the teaching process more intuitive, such as suggesting to users which features might be important to solving the task.Imagine a company wants to use AI to scan through all its documents and emails from the last year to find out how many quotes were sent out and how many of those resulted in a sale, said Alicia Edelman Pelton, principal program manager for the Microsoft Machine Teaching Group. Most people wouldn’t think to teach five-year-olds how to hit a baseball by handing them a bat and ball, telling them to toss the objects into the air in a zillion different combinations and hoping they figure out how the two things connect. In supervised learning scenarios, machine teaching is particularly useful when little or no labeled training data exists for the machine learning algorithms because an industry or company’s needs are so specific. In difficult and ambiguous reinforcement learning scenarios—where algorithms have trouble figuring out which of millions of possible actions it should take to master tasks in the physical world—machine teaching can dramatically shortcut the time it takes an intelligent agent to find the solution. It’s also part of larger goal to enable a broader swath of people to use AI in more sophisticated ways. Machine teaching allows developers or subject matter experts with little AI expertise, such as lawyers, accountants, engineers, nurses or forklift operators, to impart important abstract concepts to an intelligent system, which then performs the machine learning mechanics in the background. Microsoft researchers began exploring machine teaching principles nearly a decade ago, and those concepts are now working their way into products that help companies build everything from intelligent customer service bots to autonomous systems.”Even the smartest AI will struggle by itself to learn how to do some of the deeply complex tasks that are common in the real world. So you need an approach like this, with people guiding AI systems to learn the things that we already know,” said Gurdeep Pall, Microsoft corporate vice president for Business AI. “Taking this turnkey AI and having non-experts use it to do much more complex tasks is really the sweet spot for machine teaching.” Citation: Machine teaching: How people’s expertise makes AI even more powerful (2019, April 24) retrieved 17 July 2019 from https://phys.org/news/2019-04-machine-people-expertise-ai-powerful.html Explore further A new approach for steganography among machine learning agents Microsoft Corporate Vice President for Business AI Gurdeep Pall talks at a recent conference about autonomous systems solutions that employ machine teaching. Credit: Dan DeLong for Microsoft Provided by Microsoft This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. 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Siraj Qureshi AgraJuly 17, 2019UPDATED: July 17, 2019 18:09 IST (PTI File)HIGHLIGHTSDistrict magistrates have been asked to provide adequate food for cows staying in gaushalasThe Rs 30 daily budget set by the UP government “would not even feed a goat”A single animal’s daily feed can cost at least Rs 70 per diet, according to a dairy ownerThe Uttar Pradesh government’s fascination with cows is now well known. In compliance with the UP Chief Minister Yogi Adityanath’s orders, gaushalas are being constructed in every district all over the state at a furious pace.Now another diktat from the state government has dumbfounded district magistrates in the state. The district magistrates have been ordered to arrange for adequate food for the cows and bulls being kept in these gaushalas so that they do not die from hunger.However, the budget set by the state government for this purpose “would not even feed a goat”, according to a veterinarian in Agra. The vet told IndiaToday.in on the condition of anonymity that the Yogi government has set a budget of Rs 30 per cow or bull. This meagre sum is not enough to provide adequate nutrition to a cow or bull.Mohammad Tahir who runs a dairy in Shahganj area told IndiaToday.in that a cow or buffalo eats at least 5 kg of straw per day and this straw needs to be mixed with several other ingredients before being fed to the animal. In all, a single animal’s daily feed can cost at least Rs 70 per diet and the government’s budget will only buy 4 kg of straw for the animal.Another dairy owner Shankar Yadav said that a milch cow needs a diet of more than Rs 120 per day and no animal can survive on mere dry straw.Prakash Chand, a cattle-feed dealer said that flour and other ingredients need to be added to the straw which can cost as much as Rs 1,800 per quintal.Dr AK Doneria, the chief veterinarian of Agra division, said that a budget of Rs 30 a day was not enough to feed the animals and the department will have to make additional arrangements from its own resources as well as tap social organisations to make up for the shortfall.Making fun of the Yogi government’s Rs 30 per cow budget, Samajwadi Party city president Wajid Nisar said that Yogi Adityanath himself owns dozens of cows. He should be well aware of how much it costs to feed a cow every day. If he doesn’t then he should do a market survey first, before provisioning a budget to feed the stray cows in the state.ALSO READ | Uttar Pradesh: 5 held for slaughtering stray cows in ShamliALSO WATCH | Exclusive: India Today exposes fodder scam in MaharashtraFor the latest World Cup news, live scores and fixtures for World Cup 2019, log on to indiatoday.in/sports. Like us on Facebook or follow us on Twitter for World Cup news, scores and updates.Get real-time alerts and all the news on your phone with the all-new India Today app. Download from Post your comment Do You Like This Story? Awesome! Now share the story Too bad. Tell us what you didn’t like in the comments Posted byAnupriya Thakur Tags :Follow CowsFollow GaushalaFollow Uttar Pradesh UP govt turns miserly when it comes to feeding cowsYogi government has set a daily budget of Rs 30 per cow staying in gaushalas.advertisement Next