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Turkey to reveal artificial intelligence strategy

#artificialintelligence

Turkey will soon release its national artificial intelligence (AI) strategy which has been prepared by a joint effort of public, private and academic bodies, the Turkish industry and technology minister said Thursday. "As Turkey, we are doing our best to frame worldwide initiatives on AI development," Mustafa Varank said at a Turkish-Hungarian conference on artificial intelligence and high technology. Policymakers' main responsibility should be to design a holistic AI policy that will promote social welfare, human values, and a fair legal framework, he said. "In our strategy, we make special emphasis on the most important aspects of AI policies such as talent development, scientific research, ethics and inclusion and digital infrastructure," he said. The government is in the process of structuring its national artificial intelligence institute and Varank stressed it will bring together researchers, private sector companies, entrepreneurs and public institutes with a co-creation based approach from the beginning.


Autoantibodies against type I IFNs in patients with life-threatening COVID-19

Science

The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. [eabd4570][1], p. [eabd4585][2]; see also p. [404][3] ### INTRODUCTION Interindividual clinical variability is vast in humans infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ranging from silent infection to rapid death. Three risk factors for life-threatening coronavirus disease 2019 (COVID-19) pneumonia have been identified—being male, being elderly, or having other medical conditions—but these risk factors cannot explain why critical disease remains relatively rare in any given epidemiological group. Given the rising toll of the COVID-19 pandemic in terms of morbidity and mortality, understanding the causes and mechanisms of life-threatening COVID-19 is crucial. ### RATIONALE B cell autoimmune infectious phenocopies of three inborn errors of cytokine immunity exist, in which neutralizing autoantibodies (auto-Abs) against interferon-γ (IFN-γ) (mycobacterial disease), interleukin-6 (IL-6) (staphylococcal disease), and IL-17A and IL-17F (mucocutaneous candidiasis) mimic the clinical phenotypes of germline mutations of the genes that encode the corresponding cytokines or receptors. Human inborn errors of type I IFNs underlie severe viral respiratory diseases. Neutralizing auto-Abs against type I IFNs, which have been found in patients with a few underlying noninfectious conditions, have not been unequivocally shown to underlie severe viral infections. While searching for inborn errors of type I IFN immunity in patients with life-threatening COVID-19 pneumonia, we also tested the hypothesis that neutralizing auto-Abs against type I IFNs may underlie critical COVID-19. We searched for auto-Abs against type I IFNs in 987 patients hospitalized for life-threatening COVID-19 pneumonia, 663 asymptomatic or mildly affected individuals infected with SARS-CoV-2, and 1227 healthy controls from whom samples were collected before the COVID-19 pandemic. ### RESULTS At least 101 of 987 patients (10.2%) with life-threatening COVID-19 pneumonia had neutralizing immunoglobulin G (IgG) auto-Abs against IFN-ω (13 patients), against the 13 types of IFN-α (36), or against both (52) at the onset of critical disease; a few also had auto-Abs against the other three individual type I IFNs. These auto-Abs neutralize high concentrations of the corresponding type I IFNs, including their ability to block SARS-CoV-2 infection in vitro. Moreover, all of the patients tested had low or undetectable serum IFN-α levels during acute disease. These auto-Abs were present before infection in the patients tested and were absent from 663 individuals with asymptomatic or mild SARS-CoV-2 infection ( P < 10−16). They were present in only 4 of 1227 (0.33%) healthy individuals ( P < 10−16) before the pandemic. The patients with auto-Abs were 25 to 87 years old (half were over 65) and of various ancestries. Notably, 95 of the 101 patients with auto-Abs were men (94%). ### CONCLUSION A B cell autoimmune phenocopy of inborn errors of type I IFN immunity accounts for life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men. In these patients, adaptive autoimmunity impairs innate and intrinsic antiviral immunity. These findings provide a first explanation for the excess of men among patients with life-threatening COVID-19 and the increase in risk with age. They also provide a means of identifying individuals at risk of developing life-threatening COVID-19 and ensuring their enrolment in vaccine trials. Finally, they pave the way for prevention and treatment, including plasmapheresis, plasmablast depletion, and recombinant type I IFNs not targeted by the auto-Abs (e.g., IFN-β). ![Figure][4] Neutralizing auto-Abs to type I IFNs underlie life-threatening COVID-19 pneumonia. We tested the hypothesis that neutralizing auto-Abs against type I IFNs may underlie critical COVID-19 by impairing the binding of type I IFNs to their receptor and the activation of the downstream responsive pathway. Neutralizing auto-Abs are represented in red, and type I IFNs are represented in blue. In these patients, adaptive autoimmunity impairs innate and intrinsic antiviral immunity. ISGs, IFN-stimulated genes; TLR, Toll-like receptor; IFNAR, IFN-α/β receptor; pSTAT, phosphorylated signal transducers and activators of transcription; IRF, interferon regulatory factor. Interindividual clinical variability in the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is vast. We report that at least 101 of 987 patients with life-threatening coronavirus disease 2019 (COVID-19) pneumonia had neutralizing immunoglobulin G (IgG) autoantibodies (auto-Abs) against interferon-ω (IFN-ω) (13 patients), against the 13 types of IFN-α (36), or against both (52) at the onset of critical disease; a few also had auto-Abs against the other three type I IFNs. The auto-Abs neutralize the ability of the corresponding type I IFNs to block SARS-CoV-2 infection in vitro. These auto-Abs were not found in 663 individuals with asymptomatic or mild SARS-CoV-2 infection and were present in only 4 of 1227 healthy individuals. Patients with auto-Abs were aged 25 to 87 years and 95 of the 101 were men. A B cell autoimmune phenocopy of inborn errors of type I IFN immunity accounts for life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men. [1]: /lookup/doi/10.1126/science.abd4570 [2]: /lookup/doi/10.1126/science.abd4585 [3]: /lookup/doi/10.1126/science.abe7591 [4]: pending:yes


Inborn errors of type I IFN immunity in patients with life-threatening COVID-19

Science

The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. [eabd4570][1], p. [eabd4585][2]; see also p. [404][3] ### INTRODUCTION Clinical outcomes of human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection range from silent infection to lethal coronavirus disease 2019 (COVID-19). Epidemiological studies have identified three risk factors for severe disease: being male, being elderly, and having other medical conditions. However, interindividual clinical variability remains huge in each demographic category. Discovering the root cause and detailed molecular, cellular, and tissue- and body-level mechanisms underlying life-threatening COVID-19 is of the utmost biological and medical importance. ### RATIONALE We established the COVID Human Genetic Effort ([www.covidhge.com][4]) to test the general hypothesis that life-threatening COVID-19 in some or most patients may be caused by monogenic inborn errors of immunity to SARS-CoV-2 with incomplete or complete penetrance. We sequenced the exome or genome of 659 patients of various ancestries with life-threatening COVID-19 pneumonia and 534 subjects with asymptomatic or benign infection. We tested the specific hypothesis that inborn errors of Toll-like receptor 3 (TLR3)– and interferon regulatory factor 7 (IRF7)–dependent type I interferon (IFN) immunity that underlie life-threatening influenza pneumonia also underlie life-threatening COVID-19 pneumonia. We considered three loci identified as mutated in patients with life-threatening influenza: TLR3 , IRF7 , and IRF9 . We also considered 10 loci mutated in patients with other viral illnesses but directly connected to the three core genes conferring influenza susceptibility: TICAM1/TRIF , UNC93B1 , TRAF3 , TBK1 , IRF3 , and NEMO/IKBKG from the TLR3-dependent type I IFN induction pathway, and IFNAR1 , IFNAR2 , STAT1 , and STAT2 from the IRF7- and IRF9-dependent type I IFN amplification pathway. Finally, we considered various modes of inheritance at these 13 loci. ### RESULTS We found an enrichment in variants predicted to be loss-of-function (pLOF), with a minor allele frequency <0.001, at the 13 candidate loci in the 659 patients with life-threatening COVID-19 pneumonia relative to the 534 subjects with asymptomatic or benign infection ( P = 0.01). Experimental tests for all 118 rare nonsynonymous variants (including both pLOF and other variants) of these 13 genes found in patients with critical disease identified 23 patients (3.5%), aged 17 to 77 years, carrying 24 deleterious variants of eight genes. These variants underlie autosomal-recessive (AR) deficiencies ( IRF7 and IFNAR1 ) and autosomal-dominant (AD) deficiencies ( TLR3 , UNC93B1 , TICAM1 , TBK1 , IRF3 , IRF7 , IFNAR1 , and IFNAR2 ) in four and 19 patients, respectively. These patients had never been hospitalized for other life-threatening viral illness. Plasmacytoid dendritic cells from IRF7-deficient patients produced no type I IFN on infection with SARS-CoV-2, and TLR3−/−, TLR3+/−, IRF7−/−, and IFNAR1−/− fibroblasts were susceptible to SARS-CoV-2 infection in vitro. ### CONCLUSION At least 3.5% of patients with life-threatening COVID-19 pneumonia had known (AR IRF7 and IFNAR1 deficiencies or AD TLR3, TICAM1, TBK1, and IRF3 deficiencies) or new (AD UNC93B1, IRF7, IFNAR1, and IFNAR2 deficiencies) genetic defects at eight of the 13 candidate loci involved in the TLR3- and IRF7-dependent induction and amplification of type I IFNs. This discovery reveals essential roles for both the double-stranded RNA sensor TLR3 and type I IFN cell-intrinsic immunity in the control of SARS-CoV-2 infection. Type I IFN administration may be of therapeutic benefit in selected patients, at least early in the course of SARS-CoV-2 infection. ![Figure][5] Inborn errors of TLR3- and IRF7-dependent type I IFN production and amplification underlie life-threatening COVID-19 pneumonia. Molecules in red are encoded by core genes, deleterious variants of which underlie critical influenza pneumonia with incomplete penetrance, and deleterious variants of genes encoding biochemically related molecules in blue underlie other viral illnesses. Molecules represented in bold are encoded by genes with variants that also underlie critical COVID-19 pneumonia. Clinical outcome upon infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ranges from silent infection to lethal coronavirus disease 2019 (COVID-19). We have found an enrichment in rare variants predicted to be loss-of-function (LOF) at the 13 human loci known to govern Toll-like receptor 3 (TLR3)– and interferon regulatory factor 7 (IRF7)–dependent type I interferon (IFN) immunity to influenza virus in 659 patients with life-threatening COVID-19 pneumonia relative to 534 subjects with asymptomatic or benign infection. By testing these and other rare variants at these 13 loci, we experimentally defined LOF variants underlying autosomal-recessive or autosomal-dominant deficiencies in 23 patients (3.5%) 17 to 77 years of age. We show that human fibroblasts with mutations affecting this circuit are vulnerable to SARS-CoV-2. Inborn errors of TLR3- and IRF7-dependent type I IFN immunity can underlie life-threatening COVID-19 pneumonia in patients with no prior severe infection. [1]: /lookup/doi/10.1126/science.abd4570 [2]: /lookup/doi/10.1126/science.abd4585 [3]: /lookup/doi/10.1126/science.abe7591 [4]: https://www.covidhge.com [5]: pending:yes


Text to speech, automation and AI: How Google is backing Middle East news providers

ZDNet

Google has awarded just under $2m to 21 projects in the Middle East, Turkey and Africa, following the first Google News Initiative (GNI) Innovation Challenge in the region. The move is part of a wider series of regional innovation challenges, and a global commitment from Google News to give $300m "to help journalism thrive in the digital age". A key focus for funding is "to support projects that drive digital innovation and develop new business models". Specifically in the Middle East, proposals were asked to focus on projects that "increase reader engagement and/or explore new business models to build a stronger future for journalism". Engagement was defined as a key metric, given that "engaged users are … more likely to convert to paid subscribers", while the focus on business models sought to encourage "moves which go beyond the traditional means to generate revenues".


Financial Time Series Forecasting with Deep Learning

#artificialintelligence

In this episode of the Data Exchange I speak with Murat Özbayoğlu, Chair of Artificial Intelligence Engineering at TOBB University of Economics and Technology in Ankara, Turkey. I've long been fascinated with finance and trading. My first job after I left academia was as the lead quant in a hedge fund, and ever since, I've tried to stay abreast of what tools and techniques quants and data scientists in finance are using. Forecasting in this setting usually means price prediction or price movement (trend) prediction. Output of forecasting models are used to inform investment decisions.


Can artificial intelligence transform higher education?

#artificialintelligence

Readers are recommended to start with Zawacki-Richter et al.'s'Systematic review of research on artificial intelligence applications in higher education.' The authors reduced an initial trawl of 2656 articles published between 2007 and 2018 in peer reviewed journals down to 146 articles that met their selection criteria. The Zawacki-Richter at al. paper gives readers a good overview of the various areas where AI is being applied in higher education, as well as an indication of which areas researchers have tended to focus on. One of the areas identified by Zawacki-Richter et al. was the use of AI to predict final academic performance based on test results earlier in a course (profiling and prediction). The second paper in this issue by Akçapinar, Altun and Askar observed that 74% of the students who were unsuccessful at the end of term in an online computer science course in Turkey could be accurately predicted through the use of a specific algorithm (kNN) in as short as 3 weeks from the beginning of the course.


Demand Prediction Using Machine Learning Methods and Stacked Generalization

arXiv.org Artificial Intelligence

Supply and demand are two fundamental concepts of sellers and customers. Predicting demand accurately is critical for organizations in order to be able to make plans. In this paper, we propose a new approach for demand prediction on an e-commerce web site. The proposed model differs from earlier models in several ways. The business model used in the e-commerce web site, for which the model is implemented, includes many sellers that sell the same product at the same time at different prices where the company operates a market place model. The demand prediction for such a model should consider the price of the same product sold by competing sellers along the features of these sellers. In this study we first applied different regression algorithms for specific set of products of one department of a company that is one of the most popular online e-commerce companies in Turkey. Then we used stacked generalization or also known as stacking ensemble learning to predict demand. Finally, all the approaches are evaluated on a real world data set obtained from the e-commerce company. The experimental results show that some of the machine learning methods do produce almost as good results as the stacked generalization method.


Scientists Created AI to Analyze People's Dreams on a Massive Scale

#artificialintelligence

Aiello and his collaborators applied their AI tool to dream reports collected in the DreamBank, a massive database put together by Adam Schneider and UC Santa Cruz professor emeritus G. William Domhoff. The dream reports are more thorough than my brief dream journal entries. One, from a blind person, reads: "I was at a religious retreat. We were sitting in a dining room, eating dinner. There were roses on the table, I smelled their fragrance. We had a Thanksgiving-type dinner with my favorite things (turkey, stuffing, cranberries) and my favorite kind of dessert, pumpkin pie. And it was in the middle of spring, which was most ironic."


'Gotham Knights' is a Batman game without the Caped Crusader

Engadget

DC's Fandome event was intended as a replacement for the company's usual big presence at this year's cancelled San Diego Comic-Con, and within minutes the company came out swinging with its first big announcement: Gotham Knights, a video game about a city without Batman, where his various proteges have to step up to defend their home. In the action-adventure title the player will get to play as one of four prominent members of the Bat-Family: Nightwing, Robin, Batgirl and Red Hood. Bruce Wayne is dead, and it won't take long for the villains of Gotham City to figure out that Batman is gone too. Luckily, he's left behind plenty for his associates to work with, including a well-equipped headquarters and of course, the ever-faithful Alfred. The mechanics lie in the vein of games like Marvel's Spider-Man for PS4 and the Assassin's Creed series, with plenty of stealth and brawling, though we also get to see Batgirl drive a pretty sweet bike through the streets of Gotham. The one standout is that this game will be a co-op title, with players able to work together to clear areas and defeat villains -- in the gameplay footage shown, we got to see Batgirl and Robin make their way through a building taken over by perennial Batman villain Mr. Freeze.


Iraq fumes against Turkey over deadly drone attack

Al Jazeera

Iraq cancelled a ministerial visit and summoned Turkey's ambassador on Wednesday as it blamed Ankara for a drone attack that killed two high-ranking Iraqi military officers. Iraqi officials called the attack a "blatant Turkish drone attack" in the autonomous Kurdish region in northern Iraq, where Turkey's military has for weeks raided positions of fighters it considers "terrorists". Two border guard battalion commanders and the driver of their vehicle were killed on Tuesday, the army said in a statement, marking the first Iraqi troop deaths since Turkey launched the cross-border operation in mid-June against Kurdistan Workers' Party (PKK) rebels. Iraq's foreign ministry - which already summoned the Turkish envoy twice over the military action on its soil - said the ambassador would this time be given "a letter of protest with strong words" rejecting the offensive. The ministry also confirmed the Turkish defence minister would no longer be welcomed for a planned visit on Thursday.