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Turkish university libraries during novel coronavirus (COVID-19) pandemic
No full textBu çalışmanın amacı Yeni Koronovirüs (COVID-19) nedeniyle binalarını kapatarak yüz yüze
kullanıcı hizmetlerine ara vermek ya da askıya almak durumunda kalan üniversite kütüphanelerini
tespit etmek, hizmetlerine devam edenlerin hizmetlerini hangi koşullarda, hangi sürelerle
verdiğini belirlemek ve kütüphanelerin yeniden açılması durumunda yapılması gerekenler ile
ilgili önerilerde bulunmaktır. Bu amacı bütünsel bir çerçevede yakalayabilmek için üniversite
kütüphanelerinin farklı paydaşları olan yayıncıların, meslek örgütlerinin bu dönemdeki çalışmaları
da küresel düzeyde incelenmiştir. Çalışmanın bir diğer amacı ise üniversite kütüphanelerinin
altyapı, bütçe, koleksiyon, kullanıcı eğitimi, personel açısından uzaktan hizmet vermeye ne kadar
hazır olduklarını, ani gelişen bu durum nedeniyle yaşanan sorunları tespit etmek ve sorunlar için
çözüm önerileri sunmaktır. Çalışmanın temelini oluşturan veriler 209 (129 Devlet Üniversitesi, 75
Vakıf Üniversitesi, 5 Vakıf MYO) yükseköğretim kurumunun kütüphane yöneticilerine gönderilen
anket sorularına verilen cevaplardan elde edilmiştir. Ankete 84 kurum katılmıştır. Anket sonuçları
Surveey.com ve MS Excel ile analiz edilmiş ve görselleştirilmiştir.The goal of this study is to identify how the university libraries responded to Novel Coronavirus
( COVID-19) Pandemic. While some libraries were locked down for this period, some other libraries
only limited their services as needed. To provide a full framework, the efforts pertaining this period
from the shareholders of university libraries such as publishers and professional associations have
also been studied. The second goal of this study is to find out how libraries are ready to adapt
themselves to such unexpected situations and adopt remote service models with their existing
personnel, collections, budget or infrastructure. A survey is prepared to be sent out to 209 (129 State
universities, 75 foundation universities and 5 foundation vocational schools) higher education
institutions. The survey was filled out by 84 institutions. The survey results will be analyzed using
Surveey.com and MS Excel. At the closing, since Turkey starts easing coronavirus containment
measures, recommendations on how libraries should plan their reopening will be shared
Study of excited Λ0b states decaying to Λ0b π+π−in proton-proton collisions at √s=13 TeV
No full textA study of excited Lambda(0)(b) baryons is reported, based on a data sample collected in 2016-2018 with the CMS detector at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of up to 140fb(-1). The existence of four excited Lambda(0)(b) states: Lambda(0)(b) (5912)(0), Lambda(0)(b) (5920)(0), Lambda(0)(b) (6146)(0), and Lambda(0)(b) (6152)(0) in the Lambda(0)(b)pi(+)pi(-) mass spectrum is confirmed, and their masses are measured. The Lambda(0)(b)pi(+)pi(-) mass distribution exhibits a broad excess of events in the region of 6040-6100 MeV, whose origin cannot be discerned with the present data. (C) 2020 The Author(s). Published by Elsevier B.V
Bilgisayar destekli tasarım programı "Çizen" ve tasarımcı etkileşimi ve verimlilik analizi; akıllı arayüz önerilerinin geliştirilmesi
No full textThesis (Master)--Izmir Institute of Technology, Industrial Design, Izmir, 2020Includes bibliographical references ( leaves: 169-173)Text in English; Abstract: Turkish and EnglishSoftware is not only a rapidly developing and indispensable tool today but also the most prominent driving force of digital transformation. Thanks to the innovation studies carried out in the software of these programs, the productivity growth is achieved in the design processes, and the errors arising from the design could be reduced to a minimum. In Turkey, since 2010, working on CAD development have been initiated; the domestic and national program called “ÇİZEN,” has been developed for sheet metal forming design. In this study, new techniques and innovative methods were performed in the ÇİZEN program, which was developed and personalized specifically to a particular sector and then, User Experience Survey was conducted. The study aimed to design a simple and intelligent interface by clearly determining the needs and expectations of sheet metal designers and the user's program experience. Within the scope of this objective, user experience surveys were conducted with the participation of 14 users. In this context, the users were asked pre-configured and open-ended questions, and by giving the users specific tasks, the focus points in the program were revealed with heat maps through the Eye Tracker device. As a result of the finalization of pre-test studies and obtaining eye-tracking data, the final-test phase was initiated; and after the general opinions about the program were received, System Usability and Nonverbal Pictorial Scale research was conducted. The data obtained from the research results were interpreted, evaluated, and suggestions were developed under three main headings: productivity, simplicity/functionality, and interface.Yazılım hızla gelişmekte olan ve günümüzün vazgeçilmez bir aracı olmakla birlikte dijital dönüşümün en temel itici gücüdür. Ürünler istenilen özelliklerde ve ölçülerde Bilgisayar Destekli Tasarım programları ile tasarlanmakta ve üretime hazırlanmaktadır. Bu programların yazılımlarında yapılan inovasyon çalışmaları ile tasarım süreçlerinde büyük oranda verimlilik sağlanmakta ve tasarımdan kaynaklı hatalar en aza indirilebilmektedir. Türkiye’de yerli ve milli bir programın olmayışı ve lisanslama ücretlerinin yüksek olması nedeniyle CAD programlarının kullanımı yaygınlaşamamıştır. 2010 yılından itibaren Türkiye’de de CAD geliştirme çalışmalarına başlanmış sac kalıp tasarım sektörüne özgü yerli ve milli program ÇİZEN geliştirilmiştir. Endüstri 4.0 ile birlikte ürünün tasarlanması, üretilmesi, geliştirilmesi gibi süreçlerde tamamen insan odaklı, kişiselleştirilmiş teknolojiler ortaya çıkmaya başlamıştır. Bu çalışmada, belirli sektöre özgü geliştirilen ve kişiselleştirilen ÇİZEN programında yeni teknolojiler ve inovasyon yöntemleri kullanılarak kullanıcı deneyimi araştırması yapılmıştır. Araştırma sonucunda sac kalıp tasarımcıların ihtiyaçlarının, beklentilerinin ve program deneyimlerinin net olarak belirlenerek yalın ve akıllı bir arayüz tasarlanması amaçlanmıştır. Bu amaç kapsamında 14 kullanıcı ile kullanıcı deneyim araştırması yapılmıştır. Araştırmada önceden yapılandırılmış ve açık uçlu sorular sorulmuş, kullanıcılara belirli görevler verilerek Eye Tracker cihazı ile programdaki odak noktaları ısı haritaları ile ortaya çıkarılmıştır. Ön-Test çalışmalarının sonlanması ve göz izleme verilerinin elde edilmesi sonucunda Son-Test aşamasına geçilmiş program hakkında genel görüşler alındıktan sonra Sistem Kullanılabilirlik ve Sözsöz Resim Ölçeği araştırması yapılmıştır. Araştırma sonuçlarından elde edilen veriler yorumlanarak değerlendirilmiş ve productivity, simplicity/functionality and interface olmak üzere üç ana başlık altında öneriler geliştirilmiştir
Search for top squark pair production in a final state with two tau leptons in proton-proton collisions at √s=13 TeV
No full textA search for pair production of the supersymmetric partner of the top quark, the top squark, in proton-proton collision events at s = 13 TeV is presented in a final state containing hadronically decaying tau leptons and large missing transverse momentum. This final state is highly sensitive to high-tan beta or higgsino-like scenarios in which decays of electroweak gauginos to tau leptons are dominant. The search uses a data set corresponding to an integrated luminosity of 77.2 fb(-1), which was recorded with the CMS detector during 2016 and 2017. No significant excess is observed with respect to the background prediction. Exclusion limits at 95% confidence level are presented in the top squark and lightest neutralino mass plane within the framework of simplified models, in which top squark masses up to 1100 GeV are excluded for a nearly massless neutralino
Search for direct pair production of supersymmetric partners to the τ lepton in proton–proton collisions at √s=13TeV
No full textPubMed: 32226948A search is presented for t slepton pairs produced in proton-proton collisions at a center-of-mass energy of 13 TeV. The search is carried out in events containing two t leptons in the final state, on the assumption that each t slepton decays primarily to a t lepton and a neutralino. Events are considered in which each t lepton decays to one or more hadrons and a neutrino, or in which one of the t leptons decays instead to an electron or a muon and two neutrinos. The data, collected with the CMS detector in 2016 and 2017, correspond to an integrated luminosity of 77.2 fb-1. The observed data are consistent with the standard model background expectation. The results are used to set 95% confidence level upper limits on the cross section for t slepton pair production in various models for t slepton masses between 90 and 200 GeV and neutralino masses of 1, 10, and 20 GeV. In the case of purely left-handed t slepton production and decay to a t lepton and a neutralino with a mass of 1GeV, the strongest limit is obtained for a t slepton mass of 125 GeV at a factor of 1.14 larger than the theoretical cross section
Production of Λc⁺ baryons in proton-proton and lead-lead collisions at √snn=5.02 TeV
No full textThe transverse momentum (P-T) spectra of inclusively produced A c P baryons are measured via the exclusive decay channel Lambda(+)(c) -> pK(-)pi(+) using the CMS detector at the LHC. Spectra are measured as a function of transverse momentum in proton-proton (pp) and lead-lead (PbPb) collisions at a nucleonnucleon center-of-mass energy of 5.02TeV. The measurement is performed within the Lambda(+)(c) rapidity interval vertical bar Y vertical bar < 1 in the p(T) range of 5-20GeV/c in pp and 10-20GeV/c in PbPb collisions. The observed yields of Lambda(+)(c) for p(T) of 10-20 GeV/c suggest a suppression in central PbPb collisions compared to pp collisions scaled by the number of nucleon-nucleon (NN) interactions. The Lambda(+)(c)/D-0 production ratio in pp collisions is compared to theoretical models. In PbPb collisions, this ratio is consistent with the result from pp collisions in their common p-r range. (C) 2020 The Author(s). Published by Elsevier B.V
Ethyl esters biodiesel production from Spirulina sp. and Nannochloropsis oculata microalgal lipids over alumina-calcium oxide catalyst
No full textIn this study, we present the ethyl esters biodiesel production from Nannochloropsis oculata and Spirulina sp. microalgal lipids on 60 wt% CaO on Al2O3 catalyst at 50 degrees C and 1.0 atm. The activity of the catalyst was studied as a function of ethanol:lipid molar ratios, catalyst amounts and reaction times. It was found that 6 wt% of the lipids as catalyst amount resulted in 59% biodiesel yield in 30 min at 12 of ethanol:lipid molar ratio whereas 90-99% biodiesel yield was obtained at 24 and 48 of ethanol:lipid molar ratios. In order to achieve 90-99% yields, the basic strength was found to be weak and to be in the form of bi-carbonate, whereas high basicity was not necessary. Besides, pure CaO and Al2O3 were not active under the same reaction conditions. We found that the glycerolysis of triacylglyceride occurred in series with the reverse of the transesterification of the triacylglyceride when the catalyst amount was 6 wt% of the lipids and the ethanol:lipid molar ratio was 24 and 48 and the reaction time was 60 min. (C) 2019 Elsevier Ltd. All rights reserved
Adaptive Planning: Examining Adaptation Based Urban Policies and Practices in Turkey
No full textKentlerde meydana gelen doğal ve insan kaynaklı değişiklikler, kentlerin sosyal, ekonomik ve çevresel yapılarını habitat kaybı, kirlilik, yoksulluk, toplulukların yerinden edilmesi ve işsizlik gibi sorunlar ile ciddi bir şekilde etkilemektedir. Günümüzde, bu değişimlerin etkisi kentlerin sınırlarının çok ötesinde görülebilmektedir. Kentsel planlama alanıyla ilişkili bilim insanları ve karar vericiler dış baskılar, tehlikeler, riskler oluşturan kentsel değişimler ile başa çıkmak için adaptasyon kavramına odaklanmaya başlamışlardır (Yamu ve ark., 2016; Raco ve ark., 2012; Rauws ve ark., 2016; Wendt, 2015; Jabareen, 2013; De Roo, 2015; Ahern, 2011). Planlama literatüründe “bir kentin değişen koşullara cevap verme kapasitesini destekleyen kalkınma koşullarını yaratmak” olarak tanımlanan adaptasyon planları giderek daha fazla kabul görmeye başlamıştır (Rauws ve ark., 2016: 1). Ulusal ve uluslararası platformlarda iklim değişikliğine bağlı çevre krizleri, doğal afetler veya savaş sonucu gerçekleşen uluslararası göç gibi öngörülen ve öngörülemeyen kentsel değişimlerin mevcut ya da beklenmeyen etkilerine karşılık kentsel adaptasyon planları kapsamında politikalar üretilmiş ve kentlerin adaptasyon kapasitesinin artırılması hedeflenmiştir. Kentsel adaptasyon planları sürecinde kentsel değişim türüne bağlı olarak farklı yaklaşımlar izlenmiş ve adaptasyonu sağlayan modelleme, izleme, simülasyon ve öğrenme gibi çeşitli etmenlere odaklanılmıştır. Bu çalışmada Türkiye’de kentsel adaptasyon konusunun nasıl ele alındığının ortaya koyulması ve bu kapsamda yapılan projelere yönelik bir ilk izlenim oluşturulması amaçlanmıştır. Bu amaçla Türkiye’deki kentsel adaptasyon planları araştırılarak tespit edilen 48 proje kentsel değişim türüne bağlı olarak analitik bir çerçevede incelenmiştir. Projelerin adaptasyon konuları, ilgili aktörler ve iş birlikleri, yararlandıkları hibe programları araştırılmış ve projelerin adaptasyon temelli planlama yaklaşımları, süreçleri ve odaklandıkları adaptasyon etmenleri ortaya konmuştur.Natural and manmade urban changes often have negative impacts on social, economic and environmental structure of the cities, such as habitat loss, pollution, loss of common property resources, poverty, displacement of communities and unemployment. Nowadays, the impacts of urban changes have started to be seen far beyond the borders of the cities. Within this context, many scholars and decision makers interested in urban planning have started to focus on the term of adaptability to cope with urban changes that create external stresses, dangers and risks (Yamu et al, 2015; Raco et al., 2012; Rauws et al, 2016; Wendt, 2015; Jabareen, 2013; De Roo, 2015; Ahern, 2011). In this context, adaptive planning, which is defined as “creating conditions for development which support a city’s capacity to respond to changing circumstances”, is increasingly acknowledged in the planning literature (Rauws et al., 2016: 1). At national and international platforms, in order to cope with the current or unexpected impacts of urban changes such as environmental crisis linked to climate change, natural disasters and international migration flow due to the war, policies were developed in terms of adaptive planning and the adaptative capacity of the cities was aimed to be increased. In adaptive planning process different approaches are used based on the type of urban changes and to provide urban adaptation they focused on various key elements such as modelling, monitoring, simulation, learning. In this study, how the subject of urban adaptation was approached in Turkey was explained and the projects based on adaptive planning were evaluated with the aim of providing a first impression to this field. With this aim 48 projects, which are determined through searching the urban adaptive plans in Turkey, were examined in an analytical framework. Adaptation subjects, related actors and their collaboration and funding programs of the projects were examined and their adaptive planning approaches, processes and key elements that they focused on were demonstrated
Fast texture classification of denoised SAR image patches using GLCM on Spark
No full textClassification of a synthetic aperture radar (SAR) image is an essential process for SAR image analysis and interpretation. Recent advances in imaging technologies have allowed data sizes to grow, and a large number of applications in many areas have been generated. However, analysis of high-resolution SAR images, such as classification, is a time-consuming process and high-speed algorithms are needed. In this study, classification of high-speed denoised SAR image patches by using Apache Spark clustering framework is presented. Spark is preferred due to its powerful open-source cluster-computing framework with fast, easy-to-use, and in-memory analytics. Classification of SAR images is realized on patch level by using the supervised learning algorithms embedded in the Spark machine learning library. The feature vectors used as the classifier input are obtained using gray-level cooccurrence matrix which is chosen to quantitatively evaluate textural parameters and representations. SAR image patches used to construct the feature vectors are first applied to the noise reduction algorithm to obtain a more accurate classification accuracy. Experimental studies were carried out using naive Bayes, decision tree, and random forest algorithms to provide comparative results, and significant accuracies were achieved. The results were also compared with a state-of-the-art deep learning method. TerraSAR-X images of high-resolution real-world SAR images were used as data
Measurement of the Y(1S) pair production cross section and search for resonances decaying to Y(1S)mu(+)mu(-) in proton-proton collisions at root s=13 TeV
No full textMalawski, Maciej/0000-0001-6005-0243; Stahl, Achim/0000-0002-8369-7506; Lezki, Samet/0000-0002-6909-774X; Gokbulut, Gul/0000-0002-0175-6454; Ivanchenko, Vladimir/0000-0002-1844-5433; Andreev, Vladimir F/0000-0002-5492-6920; Duarte, Javier/0000-0002-5076-7096; Meridiani, Paolo/0000-0002-8480-2259; Bartosik, Nazar/0000-0002-7196-2237; Demiroglu, Zuhal Seyma/0000-0001-7977-7127; Yzquierdo, Antonio Perez-Calero/0000-0003-3036-7965; Ivanchenko, Vladimir N/0000-0002-1844-5433; Demiroglu, Zuhal Seyma/0000-0001-7977-7127; Obertino, Maria Margherita/0000-0002-8781-8192; Galati, Giuliana/0000-0001-7348-3312; Steggemann, Jan/0000-0003-4420-5510; Ricca, Giuseppe Della/0000-0003-2831-6982; Gonzalez, Barbara Alvarez/0000-0001-7767-4810; Cuevas-Maestro, Francisco Javier/0000-0001-5080-0821; de Souza Sandro, Fonseca/0000-0001-7830-0837; Blekman, Freya/0000-0002-7366-7098; Boimska, Bozena/0000-0002-4200-1541; Tiras, Emrah/0000-0002-5628-7464; TOPAKSU, Aysel KAYIS/0000-0001-5819-6913; Guler, Y./0000-0001-7598-5252; Loukas, Dimitris/0000-0002-7431-3857; Terkulov, Adel/0000-0003-4985-3226; Tcherniaev, Evgueni/0000-0002-3685-0635; Lopez, Oscar Gonzalez/0000-0002-4532-6464; CAKIR, Altan/0000-0002-8627-7689; Wulz, Claudia-Elisabeth E/0000-0001-9226-5812; Cortezon, Jose Enrique Palencia/0000-0001-8264-0287; Ferencek, Dinko/0000-0001-9116-1202; Arneodo, Michele/0000-0002-7790-7132; Dudko, Lev/0000-0002-4462-3192; Minafra, Nicola/0000-0003-4002-1888; Bortignon, Pierluigi/0000-0002-5360-1454; Goh, Junghwan/0000-0002-1129-2083; Ligabue, Franco/0000-0002-1549-7107; Da Silveira, Gustavo Gil/0000-0003-3514-7056; Polikarpov, Sergey/0000-0001-6839-928X; Yazgan, Efe/0000-0001-5732-7950; Azarkin, Maxim/0000-0002-7448-1447; Bagliesi, Giuseppe/0000-0003-4298-1620; De Guio, Federico/0000-0001-5927-8865; Fallavollita, Francesco/0000-0003-2315-2499; Iglesias, Maria Cruz Fouz/0000-0003-2950-976X; Kim, Tae Jeong/0000-0001-8336-2434; Roskes, Jeffrey/0000-0001-8761-0490; Veckalns, Viesturs/0000-0003-3676-9711; lee, jason/0000-0002-2153-1519; Konecki, Marcin/0000-0001-9482-4841; Dewanjee, Ram Krishna/0000-0001-6645-6244; Ince Lezki, Merve/0000-0001-6907-0195; Fiorina, Davide/0000-0002-7104-257X; Schroder, Matthias/0000-0001-8058-9828; Navarro-Tobar, Alvaro/0000-0003-3606-1780; Saka, Halil/0000-0001-7616-2573; Sznajder, Andre/0000-0001-6998-1108; Redondo, Ignacio/0000-0003-3737-4121; Azzi, Patrizia/0000-0002-3129-828X; Taylor, Lucas/0000-0002-6584-2538; Petrucciani, Giovanni/0000-0003-0889-4726; Garcia, Francisco/0000-0002-4023-7964; Jafari, Abideh/0000-0001-7327-1870; Wu, Zhenbin/0000-0003-2165-9501; Reis, Thomas/0000-0003-3703-6624; Sharma, Varun/0000-0003-1287-1471; Bhowmik, Sandeep/0000-0003-1260-973X; Kayis Topaksu, Aysel/0000-0002-3169-4573; Li, Qiang/0000-0002-8290-0517; Androsov, Konstantin/0000-0003-2694-6542; Verweij, Marta/0000-0002-1504-3420; Carrillo Montoya, Camilo/0000-0002-6245-6535; Starling, Elizabeth/0000-0002-4399-7213; Shevchenko, Rostyslav/0000-0002-3236-4090; Bodek, Arie/0000-0003-0409-0341; Rolandi, Luigi (Gigi)/0000-0002-0635-274X; Palladino, Vito/0000-0002-9786-9620; Dubinin, Mikhail/0000-0002-7766-7175; Dallavalle, Gaetano Marco/0000-0002-8614-0420; Ruiz, Jose/0000-0002-3306-0363; Sanchez Navas, Sergio/0000-0001-6129-9059; Van Onsem, Gerrit/0000-0002-1664-2337; Vischia, Pietro/0000-0002-7088-8557; Chapon, Emilien/0000-0001-6968-9828; Zghiche, Amina/0000-0002-1178-1450; Nguyen, Thong Q./0000-0003-3954-5131; Golf, Frank/0000-0003-3567-9351; Piperov, Stefan/0000-0002-9266-7819; Govoni, Pietro/0000-0002-0227-1301; Lethuillier, Morgan/0000-0001-6185-2045; Kole, Gouranga/0000-0002-3285-1497; Gutsche, Oliver/0000-0002-8015-9622; Abbiendi, Giovanni/0000-0003-4499-7562; Heath, Helen/0000-0001-6576-9740; Backhaus, Malte/0000-0002-5888-2304; Vami, Tamas Almos/0000-0002-0959-9211; Forthomme, Laurent/0000-0002-3302-336X; Gozzelino, Andrea/0000-0002-6284-1126; Kothekar, Kunal/0000-0001-5102-4326; Klein, Daniel/0000-0001-9143-5162; Martinez Ruiz del Arbol, Pablo/0000-0002-7737-5121; Tully, Christopher/0000-0001-6771-2174; Dharmaraatna, Welathantri/0000-0002-6366-837X; Goy Lopez, Silvia/0000-0001-6508-5090; Waltenberger, Wolfgang/0000-0002-6215-7228; Litov, Leandar/0000-0002-8511-6883; Mousa, Jehad/0000-0002-2978-2718; Autermann, Christian/0000-0002-0057-0033; Harb, Ali/0000-0001-5750-3889; Vartak, Adish/0000-0003-1507-1365; Ivanov, Andrew/0000-0002-9270-5643; Dragicevic, Marko/0000-0003-1967-6783; Giammanco, Andrea/0000-0001-9640-8294; Tapper, Alexander/0000-0003-4543-864X; Alverson, George/0000-0001-6651-1178; Popov, Andrey/0000-0002-1207-0984; Ricci-Tam, Francesca/0000-0001-9750-7702; Mundim, Luiz/0000-0001-9964-7805; Costa, Salvatore/0000-0001-9919-0569; Adams, Todd/0000-0001-8049-5143; Lawhorn, Jay/0000-0002-8597-9259; Massironi, Andrea/0000-0002-0782-0883; Smith, Wesley/0000-0003-3195-0909; Pieri, Marco/0000-0003-3303-6301; Mrenna, Stephen/0000-0001-8731-160X; Haddad, Yacine/0000-0003-4916-7752; Beaudette, Florian/0000-0002-1194-8556; Fernandez Perez Tomei, Thiago Rafael/0000-0002-1809-5226; Moran, Dermot/0000-0002-1941-9333; YOON, INSEOK/0000-0002-3491-8026; Gerosa, Raffaele/0000-0001-8359-3734; Caputo, Claudio/0000-0001-7522-4808; Paulini, Manfred/0000-0002-6714-5787; Botta, Cristina/0000-0002-8072-795X; Cepeda, Maria/0000-0002-6076-4083; Zevi Della Porta, Giovanni/0000-0003-0495-6061; Mitra, Soureek/0000-0002-3060-2278; Delaere, Christophe/0000-0001-8707-6021; Myronenko, Volodymyr/0000-0002-3984-4732; Gonzalez Caballero, Isidro/0000-0002-8087-3199; Sagir, Sinan/0000-0002-2614-5860; Ptochos, Fotios/0000-0002-3432-3452; Klanner, Robert/0000-0002-7004-9227; Bloom, Kenneth/0000-0002-4272-8900; Bravo, Cameron/0000-0003-1102-8247; Naimuddin, Md/0000-0003-4542-386X; Ulrich, Ralf/0000-0002-2535-402X; Vilela Pereira, Antonio/0000-0003-3177-4626; Bartok, Marton/0000-0002-4440-2701; Felcini, Marta/0000-0002-2051-9331; Ozturk, Sertac/0000-0001-6533-6144; Fernandez Menendez, Javier/0000-0002-5213-3708; Brigljevic, Vuko/0000-0001-5847-0062; David, Pieter/0000-0001-9260-9371; Blumenfeld, Barry/0000-0003-1150-1735; Vormwald, Benedikt/0000-0003-2607-7287; 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Lange, Clemens/0000-0002-3632-3157; Haller, Johannes/0000-0001-9347-7657; Lo Meo, Sergio/0000-0003-3249-9208; Schonenberger, Myriam/0000-0002-6508-5776; Everaerts, Pieter/0000-0003-3848-324X; Grunewald, Martin/0000-0002-5754-0388; Kratschmer, Ilse/0000-0002-5636-9259; Lange, Johannes/0000-0001-7513-6330; Feld, Lutz/0000-0001-9813-8646; Sculac, Toni/0000-0002-9578-4105; Gomez, Gervasio/0000-0002-1077-6553; Mnich, Joachim/0000-0001-7242-8426; Joshi, Yagya/0000-0002-0651-1878; Wang, Dayong/0000-0002-9013-1199; Belyaev, Alexander/0000-0002-1733-4408; Kiminsu, Ugur/0000-0001-6940-7800; Grandi, Claudio/0000-0001-5998-3070; Zuolo, Davide/0000-0003-3072-1020; Zanetti, Marco/0000-0003-4281-4582; Zhang, Zhicai/0000-0002-1630-0986; Galli Mercadante, Pedro/0000-0001-8333-4302; Sosa Ricardo, Rafael Eduardo/0000-0002-2240-6699; Doroba, Krzysztof/0000-0002-7818-2364; Moraes, Arthur/0000-0002-5157-5686; Arcidiacono, Roberta/0000-0001-5904-142X; Ecklund, Karl/0000-0002-6976-4637; Mitselmakher, Guenakh/0000-0001-5745-3658; Landsberg, Greg/0000-0002-4184-9380; Krikler, Benjamin/0000-0001-9712-0030; Zucchetta, Alberto/0000-0003-0380-1172; Moon, Chang-Seong/0000-0001-8229-7829; Pastrone, Nadia/0000-0001-7291-1979; Goldstein, Joel/0000-0003-1591-6014; Faccioli, Pietro/0000-0003-1849-6692; Hernandez Calama, Jose Maria/0000-0001-6436-7547; Gandrajula, Reddy Pratap/0000-0001-9053-3182; Chauhan, Shubhanshu/0000-0002-6544-5794; Fernandez Ramos, Juan Pablo/0000-0002-0122-313X; Giacomelli, Paolo/0000-0002-6368-7220; Hurtado Anampa, Kenyi/0000-0002-9779-3566; Gershtein, Yuri/0000-0002-4871-5449; Hamel de Monchenault, Gautier/0000-0002-3872-3592; Barnyakov, Alexander/0000-0002-8556-6622; ALCARAZ MAESTRE, JUAN/0000-0003-0914-7474; Alves, Gilvan/0000-0002-8369-1446; Spagnolo, Paolo/0000-0001-7962-5203; Migliore, Ernesto/0000-0002-2271-5192; Garutti, Erika/0000-0003-0634-5539; Kreczko, Luke/0000-0003-2341-8330; Krammer, Manfred/0000-0003-2257-7751; Raidal, Martti/0000-0001-7040-9491; Snoeys, Walter/0000-0003-3541-9066; Padula, Sandra S./0000-0003-3071-0559; Fernandez Bedoya, Cristina/0000-0001-8057-9152; Manca, Elisabetta/0000-0001-8946-655X; Canelli, Florencia/0000-0001-6361-2117; Cadamuro, Luca/0000-0001-8789-610X; Monaco, Vincenzo/0000-0002-3617-2432; Sciacca, Crisostomo/0000-0002-8412-4072; Hall, Geoffrey/0000-0002-6299-8385; Zorbakir, Ibrahim Soner/0000-0002-5962-2221The fiducial cross section for Y(1S) pair production in proton-proton collisions at a center-of-mass energy of 13TeVin the region where both Y(1S) mesons have an absolute rapidity below 2.0 is measured to be 79 +/- 11 (stat) +/- 6 (syst) +/- 3 (B) pbassuming the mesons are produced unpolarized. The last uncertainty corresponds to the uncertainty in the Y(1S) meson dimuon branching fraction. The measurement is performed in the final state with four muons using proton-proton collision data collected in 2016 by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb(-1). This process serves as a standard model reference in a search for narrow resonances decaying to Y(1S)mu(+)mu(-) in the same final state. Such a resonance could indicate the existence of a tetraquark that is a bound state of two bquarks and two (b) over bar antiquarks. The tetraquark search is performed for masses in the vicinity of four times the bottom quark mass, between 17.5 and 19.5 GeV, while a generic search for other resonances is performed for masses between 16.5 and 27 GeV. No significant excess of events compatible with a narrow resonance is observed in the data. Limits on the production cross section times branching fraction to four muons via an intermediate Y(1S) resonance are set as a function of the resonance mass. (C) 2020 The Author(s). Published by Elsevier B.V.FWF (Austria)Austrian Science Fund (FWF); FNRS (Belgium)Fonds de la Recherche Scientifique - FNRS; FWO (Belgium)FWO; CNPq (Brazil)National Council for Scientific and Technological Development (CNPq); CAPES (Brazil)CAPES; FAPERJ (Brazil)Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ); FAPERGS (Brazil)Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS); FAPESP (Brazil)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP); MES (Bulgaria); MOST (China)Ministry of Science and Technology, China; NSFC (China)National Natural Science Foundation of China (NSFC); COLCIENCIAS (Colombia)Departamento Administrativo de Ciencia, Tecnologia e Innovacion Colciencias; CSF (Croatia); SENESCYT (Ecuador); MoER (Estonia); ERDF (Estonia)European Union (EU); Academy of Finland (Finland)Academy of Finland; MEC (Finland); CEA (Finland); CNRS/IN2P3 (France)Centre National de la Recherche Scientifique (CNRS); BMBF (Germany)Federal Ministry of Education & Research (BMBF); DFG (Germany)German Research Foundation (DFG); HGF (Germany); GSRT (Greece)Greek Ministry of Development-GSRT; NKFIA (Hungary); DAE (India)Department of Atomic Energy (DAE); DST (India)Department of Science & Technology (India); IPM (Iran); SFI (Ireland)Science Foundation Ireland; INFN (Italy)Istituto Nazionale di Fisica Nucleare (INFN); NRF (Republic of Korea); MES (Latvia); MOE (Malaysia); UM (Malaysia); BUAP (Mexico); CONACYT (Mexico)Consejo Nacional de Ciencia y Tecnologia (CONACyT); UASLP-FAI (Mexico); FCT (Portugal)Portuguese Foundation for Science and Technology; JINR (Dubna); RFBR (Russia)Russian Foundation for Basic Research (RFBR); MESTD (Serbia); SEIDI (Spain); FEDER (Spain)European Union (EU); Swiss Funding Agencies (Switzerland); NSTDA (Thailand); TUBITAK (Turkey)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK); NASU (Ukraine); DOE (USA)United States Department of Energy (DOE); NSF (USA)National Science Foundation (NSF); Marie-Curie programEuropean Union (EU); European Research CouncilEuropean Research Council (ERC); Horizon 2020 Grant [675440, 752730, 765710]; Leventis Foundation; Alfred P. Sloan FoundationAlfred P. Sloan Foundation; Alexander von Humboldt FoundationAlexander von Humboldt Foundation; Belgian Federal Science Policy OfficeBelgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium)Fonds de la Recherche Scientifique - FNRS; Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium)Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT); F.R.S. -FNRSand FWO (Belgium) under the "Excellence of Science -EOSFonds de la Recherche Scientifique - FNRS [30820817]; Beijing Municipal Science and Technology CommissionBeijing Municipal Science & Technology Commission [Z191100007219010]; Ministry of Education, Youth and Sports (MEYS) of the Czech RepublicMinistry of Education, Youth & Sports - Czech Republic; Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence StrategyGerman Research Foundation (DFG) [EXC 2121, 390833306]; Janos Bolyai Research Scholarship of the Hungarian Academy of SciencesHungarian Academy of Sciences [123842, 123959, 124845, 124850, 125105, 128713, 128786, 129058]; Council of Science and Industrial Research, IndiaCouncil of Scientific & Industrial Research (CSIR) - India; HOMING PLUS program of the Foundation for Polish Science; European Union, Regional Development FundEuropean Union (EU) [Harmonia 2014/14/M/ST2/00428, 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, 2015/19/B/ST2/02861]; Sonata-bis [2012/07/E/ST2/01406]; National Priorities Research Program by Qatar National Research Fund; Ministry of Science and Education [14, W03.31.0026]; Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu [MDM-2015-0509]; Programa Severo Ochoa del Principado de Asturias; Thalis and Aristeia programs; EU-ESFEuropean Union (EU); Greek NSRFGreek Ministry of Development-GSRT; Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch FoundationThe Welch Foundation [C-1845]; Weston Havens Foundation (USA); TAEK (Turkey)Ministry of Energy & Natural Resources - Turkey; BMBWF (Austria); CERN (China); CAS (China)Chinese Academy of Sciences; MSES (Croatia); RPF (Cyprus); ERC (Estonia); IUT (Estonia); PUT (Estonia); HIP (Finland); CEA (France)French Atomic Energy Commission; BMBF(Germany)Federal Ministry of Education & Research (BMBF)We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, PUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, ROSATOM, RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER (Spain); MoSTR(Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEP Center, IPST, STAR, and NSTDA (Thailand); TUBITAKand TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA).; Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 752730, and 765710 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S. -FNRSand FWO (Belgium) under the "Excellence of Science -EOS" -be.h project n. 30820817; the Beijing Municipal Science and Technology Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy - EXC 2121 "Quantum Universe" 390833306; the Lendulet ("Momentum") Program and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program UNKP, the NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Education, grant no. 14.W03.31.0026(Russia); the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); The Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; The Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA)