Wheat is the main agricultural crop of Pakistan and is a staple food requirement of almost every Pakistani household making it the main strategic commodity of the country whose availability and affordability is the government's main priority. Wheat food availability can be vastly affected by multiple factors included but not limited to the production, consumption, financial crisis, inflation, or volatile market. The government ensures food security by particular policy and monitory arrangements, which keeps up purchase parity for the poor. Such arrangements can be made more effective if a dynamic analysis is carried out to estimate the future yield based on certain current factors. Future planning of commodity pricing is achievable by forecasting their future price anticipated by the current circumstances. This paper presents a wheat price forecasting methodology, which uses the price, weather, production, and consumption trends for wheat prices taken over the past few years and analyzes them with the help of advance neural networks architecture Long Short Term Memory (LSTM) networks. The proposed methodology presented significantly improved results versus other conventional machine learning and statistical time series analysis methods.

We study computational aspects of a well-known single-winner voting rule called the Schulze method [Schulze, 2003] which is used broadly in practice. In this method the voters give (weak) ordinal preference ballots which are used to define the weighted majority graph (WMG) of direct comparisons between pairs of candidates. The choice of the winner comes from indirect comparisons in the graph, and more specifically from considering directed paths instead of direct comparisons between candidates. When the input is the WMG, to our knowledge, the fastest algorithm for computing all possible winners in the Schulze method uses a folklore reduction to the All-Pairs Bottleneck Paths (APBP) problem and runs in $O(m^{2.69})$ time, where $m$ is the number of candidates. It is an interesting open question whether this can be improved. Our first result is a combinatorial algorithm with a nearly quadratic running time for computing all possible winners. If the input to the possible winners problem is not the WMG but the preference profile, then constructing the WMG is a bottleneck that increases the running time significantly; in the special case when there are $O(m)$ voters and candidates, the running time becomes $O(m^{2.69})$, or $O(m^{2.5})$ if there is a nearly-linear time algorithm for multiplying dense square matrices. To address this bottleneck, we prove a formal equivalence between the well-studied Dominance Product problem and the problem of computing the WMG. We prove a similar connection between the so called Dominating Pairs problem and the problem of verifying whether a given candidate is a possible winner. Our paper is the first to bring fine-grained complexity into the field of computational social choice. Using it we can identify voting protocols that are unlikely to be practical for large numbers of candidates and/or voters, as their complexity is likely, say at least cubic.

In recent years we have witnessed an increase in cyber threats and malicious software attacks on different platforms with important consequences to persons and businesses. It has become critical to find automated machine learning techniques to proactively defend against malware. Transformers, a category of attention-based deep learning techniques, have recently shown impressive results in solving different tasks mainly related to the field of Natural Language Processing (NLP). In this paper, we propose the use of a Transformers' architecture to automatically detect malicious software. We propose a model based on BERT (Bidirectional Encoder Representations from Transformers) which performs a static analysis on the source code of Android applications using preprocessed features to characterize existing malware and classify it into different representative malware categories. The obtained results are promising and show the high performance obtained by Transformer-based models for malicious software detection.

Increased adoption of artificial intelligence (AI) systems into scientific workflows will result in an increasing technical debt as the distance between the data scientists and engineers who develop AI system components and scientists, researchers and other users grows. This could quickly become problematic, particularly where guidance or regulations change and once-acceptable best practice becomes outdated, or where data sources are later discredited as biased or inaccurate. This paper presents a novel method for deriving a quantifiable metric capable of ranking the overall transparency of the process pipelines used to generate AI systems, such that users, auditors and other stakeholders can gain confidence that they will be able to validate and trust the data sources and contributors in the AI systems that they rely on. The methodology for calculating the metric, and the type of criteria that could be used to make judgements on the visibility of contributions to systems are evaluated through models published at ModelHub and PyTorch Hub, popular archives for sharing science resources, and is found to be helpful in driving consideration of the contributions made to generating AI systems and approaches towards effective documentation and improving transparency in machine learning assets shared within scientific communities.

Artificial intelligence is becoming a true industry, with all the pluses and minuses that entails, according to a sweeping new report.Why it matters: AI is now in nearly every area of business, with the pandemic pushing even more investment in drug design and medicine. But as the technology matures, challenges around ethics and diversity grow.Stay on top of the latest market trends and economic insights with Axios Markets. Subscribe for freeDriving the news: This morning, the Stanford Institute for Human-Centered Artificial Intelligence (HAI) released its annual AI Index, a top overview of the current state of the field.A majority of North American AI Ph.D.s — 65% — now go into industry, up from 44% in 2010, a sign of the growing role that large companies are playing both in AI research and implementation."The striking thing to me is that AI is moving from a research phase to much more of an industrial practice," says Erik Brynjolfsson, a senior fellow at HAI and director of the Stanford Digital Economy Lab.By the numbers: Even with the pandemic, private AI investment grew by 9.3% in 2020, a bigger increase than in 2019.For the third year in a row, however, the number of newly funded companies decreased, a sign that "we're moving from pure research and exploratory small startups to industrial-stage companies," says Brynjolfsson.While academia remains the single-biggest source worldwide for peer-reviewed AI papers, corporate-affiliated research now represents nearly a fifth of all papers in the U.S., making it the second-biggest source.The drug and medical industries took in by far the biggest share of overall AI private investment in 2020, absorbing more than $13.8 billion — 4.5 times greater than in 2019 and nearly three times more than the next category of autonomous vehicles.The catch: While the field has experienced sudden busts in the past — the "AI winters" that vaporized funding — there's little indication such a collapse is on the horizon. But industrialization comes with its own growing pains.Cutting-edge AI increasingly requires huge amounts of computing and data, which puts more power in the hands of fewer big players.Conversely, the commoditization of AI technologies like facial recognition means more players in the field, both domestically and internationally, which makes it more difficult to regulate their use. As AI grows, the ethical challenges embedded in the field — and the fact that 45% of new AI Ph.D.s are white, compared to just about 2% who are Black — will mean "there's a new frontier of potential privacy violations and other abuses," says Brynjolfsson.The AI Index found that while the field of AI ethics is growing, the interest level of big companies is still "disappointingly small," says Brynjolfsson.Details: Those growing pains are at play in one of the most exciting applications in AI today: massive text-generating models. Systems like OpenAI's GPT-3, released last year, swallow hundreds of billions of words along the way to producing original text that can be eerily human-like in its execution.Text-generating AI models could help polish human-written resumes for job search, but could also potentially be used to spam corporate competitors with realistic computer-generated applicants, not to mention warp our shared reality."What we increasingly have with these models is a double-edged sword," says Kristin Tynski, a co-founder and senior VP at Fractl, a data-driven marketing company.What to watch: The growing geopolitical AI competition between the U.S. and China.The National Security Commission on Artificial Intelligence warned in a major report this week that "China possesses the might, talent, and ambition to surpass the United States as the world’s leader in AI in the next decade if current trends do not change.""We don’t have to go to war with China," former Google CEO Eric Schmidt, who chaired the committee that authored the report, told my Axios colleague Ina Fried. "We do need to be competitive."Yes, but: While researchers in China publish the most AI papers, the U.S. still leads on quality, according to the Stanford survey.And while a majority of AI Ph.D.s in the U.S. are from abroad, more than 80% remain in the country when they take jobs — a sign of the lasting attraction of the U.S. tech sector.The bottom line: AI still has a long way to go, but the challenges the field faces are shifting from what it can do to what it should do.Like this article? Get more from Axios and subscribe to Axios Markets for free.

Numerous studies have shown that trained dogs can detect many kinds of disease -- including lung, breast, ovarian, bladder, and prostate cancers, and possibly Covid-19 -- simply through smell. In some cases, involving prostate cancer for example, the dogs had a 99 percent success rate in detecting the disease by sniffing patients' urine samples. But it takes time to train such dogs, and their availability and time is limited. Scientists have been hunting for ways of automating the amazing olfactory capabilities of the canine nose and brain, in a compact device. Now, a team of researchers at MIT and other institutions has come up with a system that can detect the chemical and microbial content of an air sample with even greater sensitivity than a dog's nose.

SCI COMMUN### COVID-19 Johnson & Johnson (J&J) last week became the third COVID-19 vaccinemaker to receive emergency use authorization for its product from the U.S. Food and Drug Administration. In contrast to the two-dose vaccines from Moderna and Pfizer authorized earlier, the J&J vaccine—a harmless virus delivering the gene for the spike protein from SARS-CoV-2—proved safe and effective with a single dose. The company intends to deliver 20 million doses to the United States this month, 80 million more by the end of June, and more than 1 billion doses worldwide this year. A placebo-controlled trial that took place in eight countries and involved more than 43,000 participants found that the single shot had 66% efficacy against moderate to severe COVID-19 after 28 days and 85% protection against severe disease. This is below the approximately 95% efficacy against mild disease achieved by the Pfizer and Moderna vaccines, which produce the spike protein using messenger RNA (mRNA)—but the J&J trial included locations in South Africa and Brazil where SARS-CoV-2 variants that may escape vaccine-induced antibodies are now common. (The mRNA vaccine results came before their spread.) No one who received the J&J vaccine in any country was hospitalized or died from COVID-19. The White House also brokered a deal with Merck, a major vaccine producer that dropped its own COVID-19 candidates because of poor performance, to help make the J&J product. ### Archaeology A detailed excavation in what was once a Roman port city has helped archaeologists identify what may be the oldest known pet cemetery. The remains of nearly 600 cats and dogs had been laid in prepared pits and covered with pieces of pottery and textiles, and some wore collars and other adornments. Researchers discovered the graveyard in 2011 outside the ancient city of Berenice, which today lies in Egypt. Features of some skeletons indicated the animals had lived with debilitating injuries and illnesses and survived into old age, indicating the animals were cared for, the researchers reported recently in World Archaeology . ### Art and science “I'm the first author, you're just et al. ,” raps this year's winner of Science 's annual “Dance Your Ph.D.,” a contest that challenges scientists to explain their research through dance. The first place video by Jakub Kubečka, a doctoral student at the University of Helsinki, features an original rap song and choreography, performed by him and two friends (above), explaining the search for atmospheric molecular clusters—groups of atoms that stick together and encourage water vapor to condense into clouds. Kubečka beat out 39 competitors for the $2000 top prize, sponsored by the artificial intelligence firm Primer. The winning entry is at . ### COVID-19 The U.S. National Institutes of Health (NIH) last week announced a multipronged research effort to better understand and treat Long COVID, in which people suffer lingering effects after infection by the pandemic coronavirus. Symptoms include lung problems, heart abnormalities, and enduring fatigue. In December 2020, Congress gave NIH $1.15 billion over 4 years to study the perplexing condition. The agency is inviting applications for research on its natural history, prevalence, and underlying biology and plans an expansive biorepository for samples from volunteers. Last week, the World Health Organization released a policy document estimating 10% of patients remain unwell 12 weeks after being infected. Explanations for the lasting effects have been elusive ( Science , 7 August 2020, p. [614][1]). ### Climate change Countries are drastically lagging in the fossil fuel cuts needed to reach the goals of the Paris climate agreement, a new analysis suggests. Globally, emissions were up by an average of 0.21 billion tons of carbon dioxide (CO2) per year from 2016 to 2019 compared with 2011–15, the Global Carbon Project reported this week in Nature Climate Change . Although 64 countries—most of them wealthy ones that have contributed the most to climate change—cut their CO2 emissions by a collective 0.16 billion tons per year during this time, their reductions must increase 10-fold, to some 1 billion tons annually, to meet the Paris goal of limiting global warming to 2°C. Although the pandemic caused a 7% drop in emissions in 2020, the report says, evidence from previous economic crises suggests emissions will rebound to previous levels unless recovery plans aggressively push decarbonization. ### Immigration U.S. President Joe Biden last week ended a policy, imposed last year by then-President Donald Trump, that had barred most noncitizens not already in the United States from seeking permanent residency and work permits, or green cards. Trump had said issuing new green cards didn't make sense given unemployment caused by the COVID-19 pandemic. But industry groups had challenged the policy, in part because they said it prevented companies from hiring needed scientists and skilled technical workers. In revoking the ban, Biden said it had harmed U.S. businesses “that utilize talent from around the world.” A Trump ban on temporary work permits remains in place but is set to expire on 31 March. ### Climate policy U.S. President Joe Biden's administration last week raised the government's benchmark for the “social cost of carbon,” the estimate it uses in cost-benefit analyses of regulations and other policies to represent the burden that global warming places on present and future generations. The figure will rise to $51 per ton on an interim basis; former President Donald Trump's administration had set it as low as $1. The revised standard restores the level set under former President Barack Obama, adjusted for inflation. The Biden administration may further increase the figure in an update due in January 2022 to reflect increased damages from heat waves and other disasters made worse by global warming. ### Publishing A study of more than 5000 biomedical journals found a pattern of apparent favoritism: In 206 journals, a single author was responsible for between 11% and 40% of the papers published between 2015 and 2019. Of 100 of these “nepotistic” journals given closer scrutiny, the prolific author was the editor-in-chief for about one-quarter and on the editorial board for more than 60%. Prolific authors also enjoyed faster peer reviews, according to a preprint of the study posted last month on the bioRxiv server. A research team did the analysis after scrutinizing publications by microbiologist Didier Raoult of Aix-Marseilles University, who has promoted hydroxychloroquine as a COVID-19 treatment, although most other studies have found no evidence of benefit. Raoult, who now faces disciplinary action by a French medical regulator, appears as an author on one-third of the 728 papers at the journal New Microbes and New Infections , where some of his collaborators serve as editors. ### Science and art An artificial intelligence (AI) program for the first time has written a play, which was staged by actors in Prague's Švanda Theater and premiered online last week. The script, depicting a robot's journey trying to understand humans, was generated by a widely available AI system called GPT-2. Researchers at Charles University helped it start to write the play by feeding it two sentences of dialogue about human experiences, and the software generated more, using related information drawn from the internet. Dramatist David Košt'ák, who tweaked about 10% of the resulting script to ensure it followed a coherent storyline, called its style “abstract.” But AI: When a robot writes a play showcases what the evolving technology can now do, specialists say. Judge the 60-minute play for yourself at . ### Conservation The population of monarch butterflies overwintering in Mexico showed another big drop this year. Researchers counted 2.1 hectares of occupied habitat, down 26% from last year and more than 80% from 2 decades ago, the Center for Biological Diversity said. Six hectares is the minimum considered necessary to avoid a risk of extinction. DINO TRACKS IN PERIL Ongoing mining threatens to destroy China's largest site of dinosaur tracks, researchers reported online on 27 February in Geoscience Frontiers . In 1994, the first of the tracks, 145 million to 120 million years old, were uncovered in a copper mine in China's southwestern Sichuan province. Paleontologists have identified 1928 individual footprints from dozens of individuals, representing ornithopods, theropods, sauropods, and pterosaurs. By 2012, mining had led one of the track-bearing rock faces to collapse, before it was fully studied. NEW MINE HELD UP The Biden administration has delayed a huge Arizona copper mine opposed by archaeologists and Native tribes, who say it will destroy cultural treasures. In 2014 Congress approved giving 970 hectares of federal land at Oak Flat to a mining firm. But this week officials said they want to review an environmental study needed for the transfer. Mine opponents have asked Congress and the courts to kill the project. A WIN AGAINST MALARIA El Salvador last week became the first country in Central America to be certified free of malaria by the World Health Organization. The country became eligible after recording no home-grown cases of the mosquito-borne disease since 2017. Globally, 38 countries and territories have reached this milestone. BIG CANCER FUND A new foundation will provide $250 million for cancer research, one of the largest such gifts ever. Break Through Cancer was financed by a Richmond, Virginia, businessperson whose son died of cancer in 2020. The funding will support research teams drawn from five prominent U.S. university cancer centers that will study cancer types that are difficult to treat and have high mortality rates, including pancreatic and ovarian cancer, glioblastomas, and acute myelogenous leukemia. NO PLACE LIKE HOME Americans value space research aimed at protecting Earth over sending astronauts to other bodies, a survey by Morning Consult says. Sixty-three percent of respondents called monitoring Earth's climate a top or important priority. Just 33% voiced that level of backing for launching astronauts to Mars or the Moon. ### Should peer reviewers be paid? Reviewing journal articles can seem a thankless task. Scientists do the work for free, even as as journals publish ever more papers and some publishers make sizable profits. Even before the COVID-19 pandemic led to a blizzard of submissions, journal editors were reporting that “reviewer fatigue” was making it harder to find volunteers. At the Researcher to Reader conference on scholarly publishing last week, two teams debated a provocative question: Should peer reviewers be paid? Here are some of their arguments. (See a fuller version at .) YES: “There is no downward pressure on the endless use of academic labor. And the easiest way to exert that pressure is to value the task not [only] with recognition, but with the traditional way to support skilled labor in every other industry, which is money.” James Heathers, a former research scientist, now chief scientist at a technology startup NO: “A 2018 survey found that only 17% of respondents selected cash or in-kind payment as something that would make them more likely to accept review requests.” (Nearly half said more explicit recognition of reviewing work from their universities or employers would inspire them to do it.) Alison Mudditt, CEO of PLOS, a nonprofit publisher of open-access articles NO: It could cost $3960 per accepted paper to cover the cost of reviewing, if each reviewer was paid $450, each manuscript received 2.2 reviews, and the journal accepted 25% of submissions. “Surely that money would better spent on the research itself and on solving our most pressing global challenges.” Tim Vines, a publishing consultant YES: “What might very well happen is fewer papers get submitted, because the costs go up. … A contract provides much needed certainty around the time frame, the quality, and the predictability of the review received.” Brad Fenwick, senior vice president at Taylor & Francis, a for-profit publisher NO: “It's completely unrealistic to expect that anybody is going to have either the time or the expertise or the scale to be able to manage and monitor hundreds of thousands of additional new contracts across the publishing system. Just not gonna happen.” A.M. [1]: http://www.sciencemag.org/content/369/6504/614

The year 2020 saw a reusable rocket launch two astronauts into space, multiple COVID-19 vaccines developed in record time, and a robot that could write a persuasive op-ed. In the United States, the year also saw public distrust of science contribute to the worst health crisis in modern history. This contrast highlights a sharp dichotomy in the role of science in American public life: breathtaking discovery and innovation alongside growing distrust of scientific evidence and recommendations. How can the country reconcile this dissociation? The problem is that few Americans have access to scientific institutions, to the process of research and discovery, and to scientists themselves. Elite American universities lead in scientific R&D, but low-income and even middle-class students are underrepresented. Clinical trials, a core part of medical research, often do not reflect America's demographic and socioeconomic diversity. A recent poll reported that more than 80% of Americans could not name a living scientist. If most Americans are not scientifically knowledgeable or engaged, they are less likely to trust scientific evidence and rally together to tackle future pandemics, confront climate change, or adopt new technologies. To bridge this disconnect, the Biden administration could launch an “American Science Corps” (ASC) to elevate science as a central part of American culture. Such a nonpartisan agency, federally funded and administered, would employ early-career scientists in underserved urban and rural communities to fulfill the goal expressed by Alondra Nelson, the Office of Science and Technology Policy's newly appointed deputy director for science and society: “to situate [scientific] development in our values of equality, accountability, justice, and trustworthiness.” Eventually placing 20,000 full-time ASC service members across the country, each serving roughly 16,500 Americans, would create a cooperative extension service—for science. The ASC is inspired by the Agricultural Extension Service, which, for over a century, has employed county agents at land-grant universities. The agents serve as a conduit between academic researchers and farmers, designing educational programs that respond to local needs and communicating farmers' problems back to researchers. Equally ambitious, the ASC would administer civic science workshops, public events, and training programs to engage Americans on the nuances and assumptions associated with scientific research and discovery. The ASC would enable dialogue that redirects science toward problems that plague local communities but often remain blind spots for academic researchers. ASC service members would receive training from communications experts and behavioral and social scientists. Training would include learning how to listen to community needs and engage in forums that scientists have traditionally avoided, such as places of worship, state and county fairs, farmers' markets, town halls, local theaters, libraries, community colleges, and sporting events. To attract talent, the ASC needs to become a viable career option. The scientific enterprise incentivizes research careers, but full-time jobs in public engagement are often considered fringe, alternative, or second-rate choices. Potential ASC service members exist among the Ph.D. students and postdocs whose academic job prospects have been diminished by the pandemic. Elevating ASC service members to the same prestige and compensation as those of researchers would attract highly qualified scientists committed to pursuing this new career, giving them time to build trust and carry out long-term programs that can lead to lasting change. We estimate that deployment of 7000 ASC service members for a pilot year would cost $500 million—a mere 0.4% of annual federal R&D spending across the Departments of Defense and Energy, National Science Foundation, National Institutes of Health, and National Aeronautics and Space Administration. This relatively small investment would bolster the missions of these departments and agencies, ensure a stronger workforce, and encourage greater public support for their work while benefiting public health, economic justice, and national security. As the economy adapts to new technologies, ASC service members could help retrain and bring new skills to American adults. The ASC would also counter misinformation and conspiracy theories arising from gaps in trust in science. Uniting the country around the conviction that science can improve the life of every American would be one of the most important public investments of the century. Without such an effort, vast swaths of Americans may not benefit from, or participate in, “the endless frontier” of scientific progress.

This year's report shows a maturing industry, significant private investment, and rising competition between China and the U.S. The last decade was a pivotal one for the AI industry, and 2020 saw AI substantially increase its impact on the world despite the chaos brought about by the COVID pandemic: Technologists made significant strides in massive language and generative models; the United States witnessed its first drop in AI hiring ever – pointing to a maturation of the industry – while hiring around the world increased; more dollars flowed to government use of AI than ever before, while colleges and universities offered students double the AI courses from a few years ago. These are just some of the findings from the 2021 AI Index, an annual study of AI impact and progress developed by an interdisciplinary team at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) in partnership with organizations from industry, academia, and government. "The impact of AI this past year was both societal and economic, driven by the increasingly rapid progress of the technology itself," said AI Index co-chair Jack Clark. "With the AI Index, we can actually measure and evaluate the changes, enabling leaders and decision makers to take meaningful action to advance AI responsibly and ethically with humans in mind." The 2021 AI Index is one of the most comprehensive reports about AI to date, analyzing and distilling patterns about AI's impact on everything from national economies to job growth to the analysis of technical progress within AI research itself, and analysis of the diversity (or lack of) among the people who create AI systems.

Algorithms are the heartbeat of applications, but they may not be perceived as entirely benign by their intended beneficiaries. Most educated people know that an algorithm is simply any stepwise computational procedure. Most computer programs are algorithms of one sort of another. Embedded in operational applications, algorithms make decisions, take actions, and deliver results continuously, reliably, and invisibly. But on the odd occasion that an algorithm stings -- encroaching on customer privacy, refusing them a home loan, or perhaps targeting them with a barrage of objectionable solicitation -- stakeholders' understandable reaction may be to swat back in anger, and possibly with legal action.