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Author Correction: Photo-Supercapacitors Based on Nanoscaled Zno (scientific Reports, (2022), 12, 1, (11487), 10.1038/S41598-022-15180-z)
No full textCorrection to: Scientific Reports, published online 07 July 2022 The original version of this Article contained an error in the Acknowledgements section. “I.I. acknowledges the partial financial support from the SONATA BIS project 2020/38/E/ST5/00176.” now reads: “I.I. was partly funded by the NCN SONATA-BIS Program (UMO-2020/38/E/ST5/00176).” The original Article has been corrected. © 2023, The Author(s).Narodowe Centrum Nauki, NCN: UMO-2020/38/E/ST5/00176“I.I. was partly funded by the NCN SONATA-BIS Program (UMO-2020/38/E/ST5/00176).
Comparison of Inclusive and Photon-Tagged Jet Suppression in 5.02 Tev Pb+pb Collisions With Atlas
No full textParton energy loss in the quark–gluon plasma (QGP) is studied with a measurement of photon-tagged jet production in 1.7 nb−1 of Pb+Pb data and 260 pb−1 of pp data, both at sNN=5.02 TeV, with the ATLAS detector. The process pp →γ+jet+X and its analogue in Pb+Pb collisions is measured in events containing an isolated photon with transverse momentum (pT) above 50 GeV and reported as a function of jet pT. This selection results in a sample of jets with a steeply falling pT distribution that are mostly initiated by the showering of quarks. The pp and Pb+Pb measurements are used to report the nuclear modification factor, RAA, and the fractional energy loss, Sloss, for photon-tagged jets. In addition, the results are compared with the analogous ones for inclusive jets, which have a significantly smaller quark-initiated fraction. The RAA and Sloss values are found to be significantly different between those for photon-tagged jets and inclusive jets, demonstrating that energy loss in the QGP is sensitive to the colour-charge of the initiating parton. The results are also compared with a variety of theoretical models of colour-charge-dependent energy loss. © 2023 The Author(s)We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Canton of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelser, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [79].IN2P3-CNRS; CC-IN2P3; 2014-2021; SCI/013; U.S. Department of Energy, USDOE; Alexander von Humboldt-Stiftung, AvH; Alabama Space Grant Consortium, ASGC; Brookhaven National Laboratory, BNL; CRC Health Group, CRC: 21/SCI/017; Canarie; Karlsruhe Institute of Technology, KIT; H2020 Marie Skłodowska-Curie Actions, MSCA; Multiple Sclerosis Scientific Research Foundation, MSSRF; CERN; Compute Canada; Göran Gustafssons Stiftelser; Natural Sciences and Engineering Research Council of Canada, NSERC; National Research Council Canada, NRC; Canada Foundation for Innovation, CFI; Science and Technology Facilities Council, STFC; Leverhulme Trust; European Research Council, ERC; European Cooperation in Science and Technology, COST; Australian Research Council, ARC; National Stroke Foundation, NSF; Neurosurgical Research Foundation, NRF; Helmholtz-Gemeinschaft, HGF; Minerva Foundation; Deutsche Forschungsgemeinschaft, DFG; Agence Nationale de la Recherche, ANR; Japan Society for the Promotion of Science, KAKEN; Ministry of Education, Culture, Sports, Science and Technology, MEXT; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF; Danmarks Grundforskningsfond, DNRF; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP; National Natural Science Foundation of China, NSFC; Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT; Fundação para a Ciência e a Tecnologia, FCT; Bundesministerium für Bildung und Forschung, BMBF; Chinese Academy of Sciences, CAS; Austrian Science Fund, FWF; Generalitat de Catalunya; Ministry of Science and Technology of the People's Republic of China, MOST; Agencia Nacional de Promoción Científica y Tecnológica, ANPCyT; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Bundesministerium für Wissenschaft, Forschung und Wirtschaft, BMWFW; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Nella and Leon Benoziyo Center for Neurological Diseases, Weizmann Institute of Science; Israel Science Foundation, ISF; Instituto Nazionale di Fisica Nucleare, INFN; Narodowe Centrum Nauki, NCN; Javna Agencija za Raziskovalno Dejavnost RS, ARRS; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, MPNTR; Ministerio de Ciencia e Innovación, MICINN; Centre National pour la Recherche Scientifique et Technique, CNRST; Staatssekretariat für Bildung, Forschung und Innovation, SBFI; Horizon 2020; British Columbia Knowledge Development Fund, BCKDF; European Regional Development Fund, ERDF; Defence Science Institute, DSI; Narodowa Agencja Wymiany Akademickiej, NAWA; Institutul de Fizică Atomică, IFA; Agencia Nacional de Investigación y Desarrollo, ANID; Royal Society of South Australia, RSSA; Irish Rugby Football Union, IRFUWe acknowledge the support of ANPCyT , Argentina; YerPhI , Armenia; ARC , Australia; BMWFW and FWF , Austria; ANAS , Azerbaijan; CNPq and FAPESP , Brazil; NSERC , NRC and CFI , Canada; CERN ; ANID , Chile; CAS , MOST and NSFC , China; Minciencias , Colombia; MEYS CR , Czech Republic; DNRF and DNSRC , Denmark; IN2P3-CNRS and CEA-DRF/IRFU , France; SRNSFG , Georgia; BMBF , HGF and MPG , Germany; GSRI , Greece; RGC and Hong Kong SAR , China; ISF and Benoziyo Center , Israel; INFN , Italy; MEXT and JSPS , Japan; CNRST , Morocco; NWO , Netherlands; RCN , Norway; MEiN , Poland; FCT , Portugal; MNE/IFA , Romania; MESTD , Serbia; MSSR , Slovakia; ARRS and MIZŠ , Slovenia; DSI/NRF , South Africa; MICINN , Spain; SRC and Wallenberg Foundation , Sweden; SERI , SNSF and Canton of Bern and Geneva, Switzerland; MOST , Taiwan; TENMAK , Türkiye; STFC , United Kingdom; DOE and NSF , United States of America. In addition, individual groups and members have received support from BCKDF , CANARIE , Compute Canada and CRC , Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST , ERC , ERDF , Horizon 2020 and Marie Skłodowska-Curie Actions , European Union; Investissements d'Avenir Labex , Investissements d'Avenir Idex and ANR , France; DFG and AvH Foundation, Germany; Herakleitos , Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF , Greece; BSF-NSF and MINERVA , Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA , Poland; La Caixa Banking Foundation , CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana , Spain; Göran Gustafssons Stiftelser , Sweden; The Royal Society and Leverhulme Trust , United Kingdom
Measurement of the Cp Properties of Higgs Boson Interactions With Τ-Leptons With the Atlas Detector
No full textA study of the charge conjugation and parity (CP) properties of the interaction between the Higgs boson and tau -leptons is presented. The study is based on a measurement of CP-sensitive angular observables defined by the visible decay products of t -leptons produced in Higgs boson decays. The analysis uses 139 fb(-1) of proton-proton collision data recorded at a centre-of-mass energy of root s = 13 TeV with the ATLAS detector at the Large Hadron Collider. Contributions from CP-violating interactions between the Higgs boson and t -leptons are described by a single mixing angle parameter phi(tau) in the generalised Yukawa interaction. Without constraining the H -> tau tau signal strength to its expected value under the Standard Model hypothesis, the mixing angle ft is measured to be 9 degrees +/- 16 degrees, with an expected value of 0 degrees +/- 28 degrees at the 68% confidence level. The pure CPodd hypothesis is disfavoured at a level of 3.4 standard deviations. The results are compatible with the predictions for the Higgs boson in the Standard Model.ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW, Austria; FWF, Austria; ANAS, Azerbaijan; CNPq, Brazil; FAPESP, Brazil; NSERC, Canada; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF, Denmark; DNSRC, Denmark; IN2P3-CNRS, France; CEA-DRF/IRFU, France; BMBF, Germany; MPG, Germany; Hong Kong SAR, China; ISF, Israel; INFN, Italy; MEXT, Japan; JSPS, Japan; CNRST, Morocco; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS, Slovenia; MIZS, Slovenia; MICINN, Spain; Wallenberg Foundation, Sweden; SERI, Switzerland; MOST, Taiwan; DOE, United States of America; NSF, United States of America; BCKDF, Canada; CANARIE, Canada; Compute Canada, Canada; Czech Republic [PRIMUS 21/SCI/017, UNCE SCI/013]; COST, European Union; ERC, European Union; ERDF, European Union; Horizon 2020, European Union; Marie Skodowska-Curie Actions, European Union; Investissements d'Avenir Labex, France; Investissements d'Avenir Idex , France; ANR, France; DFG , Germany; AvH Foundation, Germany; Herakleitos programme - EU-ESF, Greece; Thales programme - EU-ESF, Greece; Aristeia programme - EU-ESF, Greece; Greek NSRF, Greece; BSF-NSF, Israel; MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN, Poland; NAWA, Poland; La Caixa Banking Foundation, Spain; CERCA Programme Generalitat de Catalunya, Spain; PROMETEO Programme Generalitat Valenciana, Spain; GenT Programme Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society, United Kingdom; Leverhulme Trust, United Kingdom; STFC, United Kingdom; TENMAK, Turkiye; Canton of Geneva, Switzerland; Canton of Bern, Switzerland; SNSF, Switzerland; SRC, Sweden; DSI/NRF, South Africa; NWO, Netherlands; Benoziyo Center, Israel; RGC, China; GSRI, Greece; HGF, Germany; SRNSFG, Georgia; Minciencias, Colombia; MOST, China; CAS, China; ANID, Chile; CERN; NRC, CanadaWe thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Turkiye; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Skodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [79]
El Sıkma Hareketinin İşlevsel Yakın Kızılaltı Spektroskopisi ve Elektromiyografi Sinyalleri Kullanılarak Sınıflandırılması
No full textEl hareketinin sınıflandırılması, özellikle inme rahatsızlığı geçiren kişilerde nörorehabilitasyon amaçlı beyin bilgisayar arayüzü (BBA) modellerinin geliştirilmesinde büyük önem arz etmektedir. Ancak, el hareketi odaklı BBA modellerinin geliştirilmesinde kullanılan kas ve beyin aktivitesi ölçüm modalitelerinin tek başlarına kullanılmasında, nörolojik adaptasyon ve bazı hasta gruplarının nöromusküler hastalık barındırması gibi çeşitli problemler bulunmaktadır. Bu çalışmada bir kavrama kuvveti görevi aracılığı ile gerçekleştirilen el hareketinin sonucu elde edilen işlevsel yakın kızılaltı spektroskopisi (iYKAS) ve elektromiyografi (EMG) sinyalleri kullanılarak el hareketinin sınıflandırılması gerçekleştirilmiştir. Bu sinyallerden çıkartılan öznitelikler, L1 norm tabanlı bir destek vektör makinesi (DVM) ile seçildikten sonra, K-en yakın komşuluk, doğrusal ve radyal temelli DVM, Gradyan Artırma, Adaboost, Naive Bayes, Doğrusal Diskriminant, Kuadratik Diskriminant ve Lojistik regresyon sınıflandırıcılarına verilmiştir. Sınıflandırıcıların başarımı, bir katılımcıyı dışarıda bırak (leave-one-subject-out) çapraz geçerliliği uygulanarak gerçekleştirilmiştir. Sınıflandırıcılar arasında en yüksek doğruluk yüzdesi, iYKAS ve EMG odaklı özniteliklerden faydalanılarak, Doğrusal Diskriminant metodu ile %84 olarak bulunmuştur. Sonuçlarımız bize işlevsel yakın kızılaltı spektroskopisi ve elektromiyografi verilerinin el hareketinin sınıflandırılmasında kullanılabileceğini ve bunun BBA sistemlerine de entegre edilebileceğini ortaya koymaktadır.Classification of hand movement is of great importance in the development of brain-computer interface (BCI) models for neurorehabilitation, particularly in stroke patients. However, there are various problems in the application of muscle and brain activity measurement modalities used in the performance of hand movement-oriented BCI systems, such as neurological adaptation and neuromuscular disease in some patient groups. In this study, classification of hand movement was performed using functional near infrared spectroscopy (fNIRS) and electromyography (EMG) signals obtained as a result of hand movement performed through a grip strength task. Features extracted from these signals are given to K-nearest neighbor, linear and radial basis SVM, Gradient Boost, Adaboost, Naive Bayes, Linear Discriminant, Quadratic Discriminant and Logistic regression classifiers after they are selected with an L1 norm-based support vector machine (SVM). The performance of the classifiers was achieved by applying the leaveone-subject-out cross-validation. Among the classifiers, the highest percentage of accuracy was found to be 84% with the Linear Discriminant method, using iYKAS and EMG focused features. Our results reveal that functional near-infrared spectroscopy and electromyography data can be used to classify hand movement and can be integrated into BCI systems
Electrocatalytic Determination of Uric Acid With the Poly(tartrazine)-Modified Pencil Graphite Electrode in Human Serum and Artificial Urine
No full textA novel electrocatalytic sensing strategy was built for uric acid (UA) determination with an exceptionally developed poly(tartrazine)-modified activated pencil graphite electrode (pTRT/aPGE) in human serum and artificial urine. The oxidation signal of UA at 275 mV in pH 7.5 phosphate buffer solution served as the analytical response. Cyclic voltammetry, electrochemical impedance spectroscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy were used to characterize the sensing platform, which was able to detect 0.10 μM of UA in the ranges of 0.34-60 and 70-140 μM. The samples of human serum and artificial urine were analyzed by both the pTRT/aPGE and the uricase-modified screen-printed electrode. The results were statistically evaluated and compared with each other within the confidence level of 95%, and no significant difference between the results was found. © 2023 The Authors. Published by American Chemical Society
Search for an Axion-Like Particle With Forward Proton Scattering in Association With Photon Pairs at Atlas
No full textA search for forward proton scattering in association with light-by-light scattering mediated by an axion-like particle is presented, using the ATLAS Forward Proton spectrometer to detect scattered protons and the central ATLAS detector to detect pairs of outgoing photons. Proton-proton collision data recorded in 2017 at a centre-of-mass energy of s = 13 TeV were analysed, corresponding to an integrated luminosity of 14.6 fb−1. A total of 441 candidate events were selected. A search was made for a narrow resonance in the diphoton mass distribution, corresponding to an axion-like particle (ALP) with mass in the range 150–1600 GeV. No excess is observed above a smooth background. Upper limits on the production cross section of a narrow resonance are set as a function of the mass, and are interpreted as upper limits on the ALP production coupling constant, assuming 100% decay branching ratio into a photon pair. The inferred upper limit on the coupling constant is in the range 0.04–0.09 TeV−1 at 95% confidence level. [Figure not available: see fulltext.] © 2023, The Author(s).We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.IN2P3-CNRS; 2014-2021; SCI/013; U.S. Department of Energy, USDOE; Alexander von Humboldt-Stiftung, AvH; CRC Health Group, CRC: 21/SCI/017; Canarie; H2020 Marie Skłodowska-Curie Actions, MSCA; Multiple Sclerosis Scientific Research Foundation, MSSRF; CERN; Compute Canada; Göran Gustafssons Stiftelser; Natural Sciences and Engineering Research Council of Canada, NSERC; National Research Council Canada, NRC; Canada Foundation for Innovation, CFI; Science and Technology Facilities Council, STFC; Leverhulme Trust; European Research Council, ERC; European Cooperation in Science and Technology, COST; Australian Research Council, ARC; National Stroke Foundation, NSF; Neurosurgical Research Foundation, NRF; Helmholtz-Gemeinschaft, HGF; Minerva Foundation; Deutsche Forschungsgemeinschaft, DFG; Agence Nationale de la Recherche, ANR; Japan Society for the Promotion of Science, KAKEN; Ministry of Education, Culture, Sports, Science and Technology, MEXT; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF; Danmarks Grundforskningsfond, DNRF; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP; National Natural Science Foundation of China, NSFC; Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT; Fundação para a Ciência e a Tecnologia, FCT; Bundesministerium für Bildung und Forschung, BMBF; Chinese Academy of Sciences, CAS; Austrian Science Fund, FWF; Generalitat de Catalunya; Ministry of Science and Technology of the People's Republic of China, MOST; Agencia Nacional de Promoción Científica y Tecnológica, ANPCyT; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Bundesministerium für Wissenschaft, Forschung und Wirtschaft, BMWFW; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Nella and Leon Benoziyo Center for Neurological Diseases, Weizmann Institute of Science; Israel Science Foundation, ISF; Instituto Nazionale di Fisica Nucleare, INFN; Narodowe Centrum Nauki, NCN; Javna Agencija za Raziskovalno Dejavnost RS, ARRS; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, MPNTR; Ministerio de Ciencia e Innovación, MICINN; Centre National pour la Recherche Scientifique et Technique, CNRST; Staatssekretariat für Bildung, Forschung und Innovation, SBFI; Horizon 2020; British Columbia Knowledge Development Fund, BCKDF; European Regional Development Fund, ERDF; Defence Science Institute, DSI; Narodowa Agencja Wymiany Akademickiej, NAWA; Institutul de Fizică Atomică, IFA; Agencia Nacional de Investigación y Desarrollo, ANID; Royal Society of South Australia, RSSA; Irish Rugby Football Union, IRF
A Historical Overview of Vaccine Hesitancy and Anti-Vaccination Concepts: What Has the Covid-19 Pandemicchanged?
No full textHistorically, contagious and epidemic diseases, haveplayed an important role in the development of public healthpolicy, causing the deaths of millions of people, particularlyduring the plague, cholera, and influenza epidemics in the MiddleAges.The eradication of smallpox virus by vaccination and thesignificant decrease of child mortality rates following the use ofpolio, diphtheria-tetanus-pertussis vaccines are two examples ofthe positive impacts of vaccines on public health. The StrategicAdvisory Group of Experts on Immunization (SAGE), the maincounseling unit about vaccines and immunization of the WorldHealth Organization, endorses vaccination as one of the greatestachievements in 2 0th century public health. Despite the inarguablesuccess of vaccination worldwide, anti-vaccination movementsappeared historically almost simultaneously with the emergenceof vaccines themselves. Most recently, during the Covid-19pandemic, the first such pandemic of the 21St century, the conceptof vaccine hesitancy emerged once again, not only among thegeneral population but also in healthcare workers.The availability of the Internet and particularly social mediakindled in some, a lack of trust, along with the huge volume of these echo chambers and dividing people ideologically as toCovid vaccination, despite the many lives obviously spared andthe wide availability of this simple, cost-effective preventativemeasure.The aim of this article is to examine the brief history of theanti-vaccination movement and the scope of the concepts ofvaccination and vaccine hesitancy; and to discuss the impacts ofinfodemics and the lack of trust in these two concepts during theCovid-19 pandemi
Search in Diphoton and Dielectron Final States for Displaced Production of Higgs or Z Bosons With the Atlas Detector in P S=13 Tev Pp Collisions
No full textA search is presented for displaced production of Higgs bosons or Z bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes H -; gammagamma; and Z -ee. The analysis uses the full Run 2 dataset of proton-proton collisions delivered by the LHC at an energy of p1/4 13 TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an ffiffi s integrated luminosity of 139 fb-1. Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced Higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a Z boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for Higgsino pair production, up to a ; chiSIM;01 mass of 369 (704) GeV for decays with 100% branching ratio of ; chi; ; SIM;01 to Higgs (Z) bosons for a ; chiSIM;01 lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW; FWF, Austria; ANAS; CNPq; FAPESP, Brazil; NSERC; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF; DNSRC, Denmark; IN2P3-CNRS; CEA-DRF/IRFU, France; BMBF; MPG, Germany; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS; MICINN, Spain; SRC; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; DOE; NSF; BCKDF; CANARIE; CRC, Canada [UNCE SCI/013]; Czech Republic; ERC; ERDF; Marie Sk l odowska-Curie Actions; European Union; Investissements d ' Avenir Labex, Investissements d ' Avenir Idex; ANR, France; DFG; AvH Foundation, Germany - EU-ESF; Greek NSRF, Greece; BSF-NSF; NCN; La Caixa Banking Foundation; CERCA Programme Generalitat de Catalunya; PROMETEO; Generalitat Valenciana, Spain; Gran Gustafssons Stiftelse, Sweden; Royal Society; Leverhulme Trust, United Kingdom; NDGF (Denmark, Norway, Sweden); KIT/GridKA (Germany); INFN-CNAF (Italy); NL-T1 (Netherlands) , PIC (Spain); ASGC (Taiwan); BNL (USA); [PRIMUS 21/SCI/017]We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZ S , Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Tuerkiye; STFC, United Kingdom; DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Sk l odowska-Curie Actions, European Union; Investissements d ' Avenir Labex, Investissements d ' Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goeran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada) , NDGF (Denmark, Norway, Sweden) , CC-IN2P3 (France) , KIT/GridKA (Germany) , INFN-CNAF (Italy) , NL-T1 (Netherlands) , PIC (Spain) , ASGC (Taiwan) , RAL (UK) and BNL (USA) , the Tier-2 facilities worldwide and large non-WLCG resource pro-viders. Major contributors of computing resources are listed in Ref. [63]
Plazma Destekli Kimyasal Buhardan Çöktürme Metodu ile Grafen Kapsüle Edilmiş Metalik Tozların Sentezi ve Karakterizasyonu
No full textGraphene-Cu composites have potential applications in various industries due to their improved properties compared to copper. The commonly used methods for synthesizing Graphene-Cu composites involve mixing graphene nanoplatelets with Cu powders using the Hummer method and its derivatives, followed by pressing and sintering processes. However, controlling the morphology of graphene nanoplatelets and achieving homogeneous distribution poses challenges in these methods. Recently, studies have been conducted on coating copper powders with graphene using various techniques. Among these studies, the Chemical Vapor Deposition (CVD) method is suitable for industrial applications. However, coating Cu powders with graphene using the CVD method faces difficulties due to the high-temperature requirement for hydrocarbon decomposition. This thesis work focuses on the development of graphene-coated copper (Graphene-Cu) powders using a low-temperature plasma-enhanced CVD (PECVD) method. Using these coated powders, Graphene-Cu composites were produced, and their mechanical and thermal properties were investigated. The structural, mechanical, and thermal properties of the fabricated Graphene-Cu composites were determined using various characterization methods, aimed at evaluating the microstructure and graphene distribution of the composites. The obtained results demonstrate the successful production of homogeneous Graphene-Cu composites using the low-temperature PECVD method. The effect of graphene presence on the microstructure of the formed composites was investigated, and structures with smaller grain sizes and reduced porosity were observed in the presence of graphene. Mechanical tests showed that the presence of graphene increased the yield strength and elastic properties of the composites. Thermal tests revealed that the graphene coating enhanced the thermal diffusivity of the composites. The obtained results were analyzed in relation to the microstructure of the composites, and the improvement mechanisms were investigated. This study contributes to the development of production methods for graphene-reinforced copper composites and enables their potential use in various applications.Grafen-Cu kompozitler, bakıra göre geliştirilmiş özelliklere sahip olmaları nedeniyle çeşitli endüstrilerde potansiyel uygulamalara sahiptir. Grafen-Cu kompozitlerin sentezlenmesi için yaygın olarak kullanılan yöntemler, Hummer metodu ve türevleriyle grafen yaprakçıklarının Cu tozlarıyla karıştırılması, presleme ve sinterleme işlemleridir. Ancak, bu yöntemlerde grafen yaprakçıklarının morfolojisinin kontrolü ve homojen dağılımın sağlanması zorluklar oluşturabilmektedir. Son zamanlarda, bakır tozlarının çeşitli yöntemlerle grafen ile kaplanması üzerine çalışmalar yapılmıştır. Bu çalışmalar arasında, endüstriyel uygulamalara uygun bir yöntem olarak Kimyasal Buhar Biriktirme (KBÇ) yöntemi öne çıkmaktadır. Ancak, KBÇ yöntemiyle Cu tozlarının grafen ile kaplanması, yüksek sıcaklık gerektiren hidrokarbon parçalanması nedeniyle zorluklar içermektedir. Bu tez çalışması, düşük sıcaklıkta plazma destekli KBÇ (PDKBÇ) yöntemi kullanılarak grafen ile kaplanmış bakır (Grafen-Cu) tozlarının geliştirilmesi üzerine odaklanmaktadır. Bu kaplanmış tozlar kullanılarak Grafen-Cu kompozitlerin üretimi gerçekleştirilmiş ve bu kompozitlerin mekanik ve termal özellikleri araştırılmıştır. Oluşturulan Grafen-Cu kompozitlerin yapısal, mekanik ve termal özellikleri karakterizasyon yöntemleri kullanılarak belirlenmiştir. Bu yöntemler, kompozitlerin mikroyapısını ve grafen dağılımını değerlendirmek amacıyla kullanılmıştır. Elde edilen sonuçlar, düşük sıcaklıkta PDKBÇ yönteminin başarılı bir şekilde kullanılarak homojen Grafen-Cu kompozitlerinin üretilebildiğini göstermektedir. Grafen varlığının oluşan kompozit mikroyapısı üzerinde etkisi araştırılmış ve grafen varlığında elde edilen yapılarında daha küçük tane boyutları ve azalmış gözenek miktarı gözlemlenmiştir. Mekanik testler, grafen varlığının kompozitin akma dayanımını ve elastik özelliklerini artırdığını göstermiştir. Termal testlerde ise grafen kaplamasının kompozitin termal difüzivite değerlerini artırdığı tespit edilmiştir. Elde edilen sonuçlar, kompozitlerin mikroyapısıyla ilişkilendirilerek iyileşme mekanizmaları incelenmiştir. Bu çalışma, grafen takviyeli bakır kompozitlerin üretim yöntemlerinin geliştirilmesine ve bu kompozitlerin potansiyel uygulamalarda kullanılabilmesine katkı sağlamaktadır
