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Forecasting the Evolutionary Pathways of the SARS-CoV-2 Spike Protein via the Calculation of Mutability Landscapes
No full textThe 3rd BEYOND 2023: Computational Science, Mathematical Modeling and Engineering Conference TOBB University of Economics and Technology, Ankara-Turkey, 19-20 October 2023Viruses, known as infectious agents, cause diseases and deaths in humans. Although vaccines and drugs have been developed to prevent these effects, through mutations in the genetics of viruses, the virus acquires features such as escaping the immune system and binding better to the host cell, thus becoming resistant to the treatments offered. The global COVID-19 pandemic has highlighted the need for rapid, reliable, and efficient tracking and forecasting of the changes in genetic material as new SARS-CoV-2 variants arise. Developing appropriate drugs and vaccines for the new genetic content of the virus is costly and takes a long time. For this reason, it is of great importance to be able to predict the mutations that may occur in the genetics of SARS-CoV-2 and the effects of these mutations before they occur and take the necessary precautions. Here we studied the evolution process of SARS-CoV-2 and predicted the key mutations that may occur in the future. To this end, first, the gene sequences of the spike region are obtained from GISAID database, and then the sequences are aligned with various multiple alignment methods (Clustal Omega, MAFFT, TCoffee, etc.). Then these alignments are used to calculate the mutability scores for each amino acid using scoring functions (Karlin, Sander, Valder, etc.). By examining the correlation between the scores obtained, regions that are protected and prone to change have been obtained. Future mutations have been predicted by examining using the calculated mutability scores and the experimental mutation rate (8x10− 4 mutation/nucleotide/year) obtained, using random walk method
Derin Spektroskopi: Derin Öğrenme Yöntemleri ile Karmaşık Numunelerin Ftir Spektrumlarının Incelenmesi
No full textBu proje karmaşık ve değişken numunelerin analizi için, kızılötesi emilim spektrometrisi (FTIR) kullanarak numunenin üst katman gazlarından kimyasal parmak izi üretilmesi ve çıkan spektral parmak izlerinin bir bütün olarak istatistiksel öğrenme yöntemleri ve özel olarak modern sinir ağları mimarileri kullanılarak sınıflandırılması, nitel ve nicel olarak belirlenmesi hakkındadır. Karmaşıklıkla kastedilen, spektroskopik incelemelerde numuneyi belirleyen çok sayıda bileşenin mevcut oluşu ve her bir bileşenin çok detaylı bir spektral parmak izi deseni ile belirleniyor olması; değişkenlikle kastedilen ise, söz konusu numunelerin doğada veya teknolojik uygulamalarda karşılaşılan örneklerinin, kendi aralarında analitik farklılıklar göstermekle beraber, algısal/bütünsel sınıflandırmaya da imkân veren ortak değişmez, arketipsel öz nitelikleri barındırmasıdır. Örneğin pek çok bileşenden oluşan parfüm ve esanslar, motorin ve jet yakıtları, kömür çeşitleri, hava kirliliği tayini için toplanılan numuneler, jeoloji ve astro-jeolojide karşılaşılan kaya parçaları hem karmaşık hem de değişken numunelerdir. Canlılar âleminde her türlü bitkisel ve hayvansal kokular, taze/çürük gıda kokuları, canlılardan çıkan biyolojik sıvı ve gazlar, insan nefesi, ter/ten kokusu, idrar ve idrar üst katman gazları, bileşenleri yönünden karmaşık ve bileşenlerin bağıl oran/konsantrasyon değerleri açısından istatistiki yüksek değişkenlik gösteren malzemelerdir. Proje araştırmaları sonucunda spektroskopik veri kümeleri etiketli, etiketsiz makine öğrenmesi yöntemleri kullanılarak yüksek başarımla tanımlanmasının mümkün olduğu gösterilmiştir. Kullanılan yöntemler arasında PCA, t-SNE gibi boyut düşürme yöntemleri, etiketli istatistiksel analiz yöntemlerinden Naive Bayes, Random Forest ve Support Vector Machines gibi yöntemler ve bu yöntemlerle karşılaştırılan ileri beslemeli ağlar, convolutional sinir ağları, Kohonen haritaları ve atımlı sinir ağları yöntemleridir. Derin spektroskopi projesi, FTIR spektroskopisi ile elektronik burun araştırmalarını birleştirmeyi amaçlayarak, spektroskopik büyük verinin modern makine öğrenmesi yöntemleri ile işlenerek biyomimetik bir elektronik burun mimarisinin mümkün olduğunu göstermiştir. Bu proje, spektroskopik teknikler ve yapay zeka entegrasyonunun karmaşık ve çeşitli numuneleri tanımlamada nasıl etkili bir araç olabileceğini göstermektedir
Blockchain-Based Privacy Preserving Linear Regression
No full textIn this study we propose a blockchain-based architecture that uses smart contracts and homomorphic encryption to allow statistical computations on confidential data by third parties. The use of blockchain provides the much-desiredsecurity properties of integrity and fault tolerance and homomorphic encryption preserves the privacy of the data. We present the design, implementation, and testing of our system. Our results show that a blockchain-based data sharing mechanism with homomorphic calculations via a smart contract is feasible and provides improvements in protecting the data from unauthorized users. Even though our work focused on linear regression, the architecture can be used for other statistical analysis and machine learning algorithms
Measurement of the Top-Quark Mass Using a Leptonic Invariant Mass in Pp Collisions at ?s = 13 Tev With the Atlas Detector
No full textA measurement of the top-quark mass (mt) in the tt¯ ? lepton + jets channel is presented, with an experimental technique which exploits semileptonic decays of b-hadrons produced in the top-quark decay chain. The distribution of the invariant mass m?? of the lepton, ? (with ? = e, ?), from the W-boson decay and the muon, ?, originating from the b-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract mt. The measurement is based on data corresponding to an integrated luminosity of 36.1 fb?1 of s = 13 TeV pp collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. The measured value of the top-quark mass is mt = 174.41 ± 0.39 (stat.) ± 0.66 (syst.) ± 0.25 (recoil) GeV, where the third uncertainty arises from changing the Pythia8 parton shower gluon-recoil scheme, used in top-quark decays, to a recently developed setup. [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 Sk?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; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.21/SCI/017; IN2P3-CNRS; SCI/01
Foreign Body Reaction To Polyacrylamide Filler (aquafilling (r)) Injected Nine Years Previously: a Complication of Sars-Cov Infection or Merely a Coincidence?
No full textTools for Estimating Fake/Non-prompt Lepton Backgrounds With the Atlas Detector at the Lhc
No full textMeasurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to 'fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW, Austria; FWF, Austria; ANAS, Azerbaijan; CNPq, Brazil; FAPESP, Brazil; NSERC, Canada; NRC, Canada; CFI, Canada; CERN; ANID, Chile; CAS, China; MOST, China; NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF, Denmark; DNSRC, Denmark; IN2P3-CNRS, France; CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, Germany; HGF, Germany; MPG, Germany; GSRI, Greece; RGC, China; Hong Kong SAR, China; ISF, Israel; Benoziyo Center, Israel; INFN, Italy; MEXT, Japan; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS, Slovenia; MIZS, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC, Sweden; Wallenberg Foundation, Sweden; SERI, Switzerland; SNSF, Switzerland; Canton of Bern, Switzerland; Canton of Geneva, Switzerland; MOST, Taiwan; TENMAK, Turkiye; STFC, United Kingdom; DOE, United States of America; NSF, United States of America; BCKDF, Canada; CANARIE, Canada; Compute Canada, Canada; CRC, Canada; PRIMUS, Czech Republic; UNCE, Czech Republic; COST, European Union; ERC, European Union; ERDF, European Union; Horizon 2020, European Union; Marie Sklodowska-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; Goeran Gustafssons Stiftelse, Sweden; Royal Society, United Kingdom; Leverhulme Trust, United Kingdom; [21/SCI/017]; [SCI/013]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 Sklodowska-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
Fuzûli'den Şeyh Galib'e Aşkın Uzun Hikâyesi: Klasik Edebiyatımızda Hikâye, Mesnevi, Roman
No full text[No Abstract Available
Fibonomial and Lucanomial Sums Through Well-Poised Q-Series
No full textBy making use of known identities of terminating well-poised q-series, we shall demonstrate several remarkable summation formulae involving products of two Fibonomial/Lucanomial coefficients or quotients of two such coefficients over a third one. © 2023, Hacettepe University. All rights reserved
Electronic and Structural Modification of Three-Dimensional Porous Nico@nf as a Robust Electrocatalyst for Co2 Emission-Free Methanol Upgradation To Boost Hydrogen Co-Production
No full textElectrochemical hydrogen evolution reaction (HER) coupled with methanol oxidation reaction (MOR) is an innovative process to attain energy-efficient hydrogen generation with more valuable formate product co-generation. Herein, we present 3D porous bimetallic NiCo nanostructures with oxygen vacancies grown on a nickel foam surface (O-v-NiCo@NF) as efficient electrocatalysts that show integrated highly selective methanol oxidation along with hydrogen evolution. The electronic structure of O-v-NiCo@NF is tuned by surface oxygen vacancies that provide a high active surface area and optimum chemisorption energy for selective methanol upgradation to formate. The metallic porous nanostructures and interconnected dendritic growth of nanoparticles ensure electrolyte penetration, with faster gas release ability, that enhances charge transfer kinetics and suppresses support passivation during MOR and HER. The 3D porous Ov-NiCo@NF exhibits improved methanol conversion activity, requiring 1.30 and 1.42 V (vs RHE) to achieve 50 and 100 mA cm(-2) current densities for MOR, respectively. Furthermore, an integrated two electrode setup (Ov-NiCo@NF//Ov-NiCo@NF) requires a cell voltage of 1.41 V to attain 25 mA cm(-2) current density for methanol-upgrading-assisted water electrolysis, while a higher cell voltage (1.62 V) is required in the electrolyte without methanol (overall water splitting).Lahore University of Management Sciences (LUMS), Pakistan (FIF grant)F.A. and F.S. appreciate the financial support providedby the Lahore University of Management Sciences (LUMS), Pakistan (FIFgrant)