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Makine Ögrenmesi ile Gelismis Polarizasyon Kestirim Yöntemi
No full textNowadays, the importance of electronic warfare systems is increasing. Electronic support systems, which are one of the elements of Electronic Warfare systems, passively use the electromagnetic spectrum. These systems, which analyze the emitted signals, are able to detect the directions, positions, identities, and content of communication between the enemy and friendly elements. In this way, electronic support systems play a major role in extracting intelligence data. With the development of technology, systems that analyze radar or communication signals are expanding their capabilities. Electronic warfare and radar applications try to increase target direction and position finding performance by using signal polarization information as well as increasing reconnaissance capability. These factors have led to the incorporation of polarization information of the signal into existing systems. Depending on the location or direction of the platform where the receiver or transmitter is located, polarization mismatch between the transmitter and receiver may occur. In order for target signals to be received at high power, for successful direction finding performance, or for an effective countermeasure against electronic warfare systems, polarization mismatch in the receiver and transmitter must be prevented. Therefore, detection of the polarization of the emitted signal in electronic support systems plays a critical role in identification, direction and position finding systems. In this study, an approach that estimate the polarization of the incoming signal through deep learning is proposed. In the proposed approach, first of all, the covariance matrix is calculated, such as algorithms that perform classical angle of arrival and polarization estimation. The input images of the algorithm were obtained from the real, imaginer and phase values of the calculated covariance matrix. Thanks to convolutional neural networks, features are extracted from the input images and polarization estimation is performed thanks to fully connected layers. In the study, linear polarization was considered at certain resolutions. Linear polarization is divided into ten different classes, the first class being horizontal polarization and the last class being vertical polarization. The model, which adopts the supervised learning model and includes convolutional neural networks and fully connected layers, has yielded faster results than classical algorithms. The proposed approach has revealed the potential to be used in real-time systems. Within the scope of polarization estimation performance, the algorithm that estimates neighboring classes even with erroneous estimates has given more successful results compared to the classical MUSIC algorithm, especially at low SNR values. In addition, within the scope of the thesis, a hybrid algorithm is proposed for the estimation of the angle of arrrival. The proposed hybrid algorithm primarily performs polarization estimation with a convolutional neural network based algorithm. Then, the classical Multiple Signal Classification (MUSIC) algorithm is used to estimate the angle of arrival. As a result of polarization estimation with convolutional neural networks, the classical MUSIC algorithm estimated the arrival angle faster, since it will search directly only spatial angles without scanning polarization parameters. Since the proposed hybrid algorithm estimates polarization more successfully at low SNR values, it has given more successful results compared to the classical MUSIC algorithm in the scope of angle of arrival estimation.Günümüzde elektronik harp sistemlerinin önemi dramatik olarak artmaktadır. Elektronik Harp sistemlerinin unsurlarından olan elektronik destek sistemleri, elektromanyetik spektrumu pasif olarak kullanmaktadır. Yayılan sinyalleri analiz eden bu sistemler, düşman ve dost unsurların, yönlerini, konumlarını, kimliklerini, birlikler arası haberleşme içeriğini tespit edebilmektedir. Bu sayede, elektronik destek sistemleri istihbarat verilerinin çıkarılmasında büyük rol oynamaktadır. Teknolojinin gelişmesiyle birlikte, radar veya haberleşme sinyallerini analiz eden sistemler kabiliyetlerini genişletmektedir. Elektronik harp ve radar uygulamaları, keşif kabiliyetini artırmanın yanı sıra sinyal polarizasyon bilgilerini kullanarak hedef yön ve konum bulma performansını arttırmaya çalışmaktadır. Bu faktörler, sinyalin polarizasyon bilgisinin bahsedilen mevcut sistemlere dahil edilmesine yol açmıştır. Alıcının veya vericinin bulunduğu platformun konumuna veya yönüne bağlı olarak alıcı-verici arası polarizasyon uyumsuzluğu meydana gelebilmektedir. Hedef sinyallerin yüksek güçte alınabilmesi, başarılı bir yön bulma performansı veya elektronik harp sistemlerine karşı etkili bir karşı önlem alınabilmesi için alıcı ve vericideki polarizasyon uyumsuzluğunun önlenmesi gerekmektedir. Bu yüzden elektronik destek sistemlerinde, yayılan sinyalin polarizasyonunun tespiti, kimliklendirme, yön ve konum bulma sistemlerinde kritik bir rol oynamaktadır. Bu çalışmada, gelen sinyalin polarizasyonunu derin öğrenme yoluyla kestiren bir yaklaşım önerilmiştir. Önerilen yaklaşımda, öncelikle klasik geliş açısı ve polarizasyon kestirimi gerçekleştiren algoritmalar gibi kovaryans matrisi hesaplanmaktadır. Hesaplanan kovaryans matrisinin gerçek, sanal ve faz değerlerinden algoritmanın giriş görüntüleri elde edilmiştir. Evrişimsel sinir ağları sayesinde giriş görüntülerinden öznitelikler çıkarılıp, tam bağlı katmanlar sayesinde polarizasyon kestirimi yapılmaktadır. Çalışmada doğrusal polarizasyon belli çözünürlüklerde ele alınmıştır. İlk sınıf yatay polarizasyon ve son sınıf dikey polarizasyon olmak üzere, doğrusal polarizasyon on farklı sınıfa ayrılmıştır. Gözetimli öğrenme modelini benimseyen ve evrişimsel sinir ağlarını ve tam bağlı katmanları içeren model, klasik algoritmalara göre daha hızlı sonuç vermiştir. Önerilen yaklaşım gerçek-zamanlı sistemlerde kullanılma potansiyelini ortaya koymuştur. Polarizasyon sınıfı kestirme performansı kapsamında, hatalı kestirimlerde dahi komşu sınıfları kestiren algoritma özellikle düşük SNR değerlerinde klasik MUSIC algoritmasına göre daha başarılı sonuçlar vermiştir. Ayrıca tez kapsamında, geliş açısı kestirimi için de hibrit bir algoritma önerilmiştir. Önerilen hibrit algoritma, öncelikle evrişimsel sinir ağı tabanlı bir algoritma ile polarizasyon kestirimi yapmaktadır. Sonrasında geliş açısı kestirimi için klasik Çoklu Sinyal Sınıflandırma (Multiple Signal Classification-MUSIC) algoritması kullanılmaktadır. Evrişimsel sinir ağları ile polarizasyon kestiriminin sonucunda, klasik MUSIC algoritması polarizasyon parametrelerini taramadan doğrudan sadece uzamsal açılarda arama yapacağından, geliş açısını daha hızlı kestirmiştir. Önerilen hibrit algoritma, düşük SNR değerlerinde, polarizasyonu daha başarılı kestirdiğinden, geliş açısı kestirimi kapsamında klasik MUSIC algoritmasına göre daha başarılı sonuçlar vermiştir
Measurement of the Nuclear Modification Factor for Muons From Charm and Bottom Hadrons in Pb+pb Collisions at 5.02 Tev With the Atlas Detector
No full textHeavy-flavour hadron production provides information about the transport properties and microscopic structure of the quark–gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the muons from semileptonic decays of charm and bottom hadrons produced in Pb+Pb and pp collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208?b?1 and 38?b?1, respectively, and pp data with a sampled integrated luminosity of 1.17pb?1 were collected in 2017. Muons from heavy-flavour semileptonic decays are separated from the light-flavour hadronic background using the momentum imbalance between the inner detector and muon spectrometer measurements, and muons originating from charm and bottom decays are further separated via the muon track's transverse impact parameter. Differential yields in Pb+Pb collisions and differential cross sections in pp collisions for such muons are measured as a function of muon transverse momentum from 4 GeV to 30 GeV in the absolute pseudorapidity interval |?|2. Nuclear modification factors for charm and bottom muons are presented as a function of muon transverse momentum in intervals of Pb+Pb collision centrality. The bottom muon results are the most precise measurement of b quark nuclear modification at low transverse momentum where reconstruction of B hadrons is challenging. The measured nuclear modification factors quantify a significant suppression of the yields of muons from decays of charm and bottom hadrons, with stronger effects for muons from charm hadron decays. © 2022 The Author(s)We acknowledge the support of ANPCyT , Argentina; YerPhI , Armenia; ARC , Australia; BMWFW and FWF , Austria; ANAS , Azerbaijan; SSTC , Belarus; 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; JINR ; MES of Russia and NRC KI , Russian Federation; 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; TAEK , Turkey; 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; 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 GIF , 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.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; SSTC, Belarus; 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; JINR; MES of Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZ?, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; 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; 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 GIF, 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; G?ran 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. [75].IN2P3-CNRS; CC-IN2P3; 2014-2021; National Science Foundation, NSF; U.S. Department of Energy, USDOE; Alexander von Humboldt-Stiftung, AvH; Arkansas Space Grant Consortium, ASGC; Brookhaven National Laboratory, BNL; Canarie; Karlsruhe Institute of Technology, KIT; H2020 Marie Sk?odowska-Curie Actions, MSCA; Arizona-Nevada Academy of Science, ANAS; 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; Royal Society; European Research Council, ERC; European Cooperation in Science and Technology, COST; Australian Research Council, ARC; Neurosurgical Research Foundation, NRF; Singapore Eye Research Institute, SERI; Helmholtz-Gemeinschaft, HGF; 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, Mláde?e a T?lov?chovy, 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; 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; Joint Institute for Nuclear Research, JINR; 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; Ministry of Science and Technology, Taiwan, MOST; Ministerio de Ciencia e Innovación, MICINN; Centre National pour la Recherche Scientifique et Technique, CNRST; Horizon 2020; British Columbia Knowledge Development Fund, BCKDF; European Regional Development Fund, ERDF; Defence Science Institute, DSI; Council on grants of the President of the Russian Federation; National Research Center "Kurchatov Institute", NRC KI; Narodowa Agencja Wymiany Akademickiej, NAW
Effects of Artichoke Leaf Extract on Hepatic Ischemia- Reperfusion Injury
No full textOBJECTIVE: The aim of this study was to evaluate the hepatoprotective effect and mechanism of action of artichoke leaf extract in hepatic ischemia/ reperfusion injury. METHODS: Rats were divided into three groups such as sham, control, and artichoke leaf extract groups. Antioxidant enzyme activities and biochemical parameters were examined from the tissue and serum obtained from the subjects. Histopathological findings were scored semiquantitatively. RESULTS: Statistically, the antioxidant activity was highest in the artichoke leaf extract group, the difference in biochemical parameters and C-reactive protein was significant compared with the control group, and the histopathological positive effects were found to be significantly higher. CONCLUSIONS: As a result, artichoke leaf extract had a hepatoprotective effect and that this effect was related to the antioxidant and antiinflammatory effects of artichoke
Bunching Below Thresholds To Manipulate Public Procurement
No full textManipulative authorities can bunch tenders just below thresholds to implement noncompetitive procurement practices. I use regression discontinuity manipulation tests to identify the bunching manipulation scheme. I investigate the European Union public procurement data set that covers more than two million contracts. The results show that 10-13% of the examined authorities exhibit a high probability of bunching. These authorities are less likely to employ competitive procurement procedures. Local firms are more likely to win contracts from a bunching authority. The probability that the same firm wins contracts repeatedly is high when an authority has high bunching probability. Empirical results suggest that policy makers can effectively employ regression discontinuity manipulation tests to determine manipulative authorities
Modelling and Computational Improvements To the Simulation of Single Vector-Boson Plus Jet Processes for the Atlas Experiment
No full textThis paper presents updated Monte Carlo configurations used to model the production of single electroweak vector bosons (W, Z/gamma*) in association with jets in proton-proton collisions for the ATLAS experiment at the Large Hadron Collider. Improvements pertaining to the electroweak input scheme, parton-shower splitting kernels and scale-setting scheme are shown for multi-jet merged configurations accurate to next-to-leading order in the strong and electroweak couplings. The computational resources required for these set-ups are assessed, and approximations are introduced resulting in a factor three reduction of the per-event CPU time without affecting the physics modelling performance. Continuous statistical enhancement techniques are introduced by ATLAS in order to populate low cross-section regions of phase space and are shown to match or exceed the generated effective luminosity. This, together with the lower per-event CPU time, results in a 50% reduction in the required computing resources compared to a legacy set-up previously used by the ATLAS collaboration. The set-ups described in this paper will be used for future ATLAS analyses and lay the foundation for the next generation of Monte Carlo predictions for single vector-boson plus jets production.ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW, Austria; FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq, Brazil; FAPESP, Brazil; NSERC, Canada; NRC, Canada; CFI, Canada; CERN; ANID, Chile; CAS, China; MOST, China; NSFC, China; Minciencias, Colombia; MSMT CR, Czech Republic; MPO CR, Czech Republic; VSC 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, The Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MES of Russia; NRC KI, Russian Federation; 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; TAEK, Turkey; STFC, U.K.; DOE, U.S.A.; NSF, U.S.A.; BCKDF, Canada; CANARIE, Canada; Compute Canada, Canada; CRC, Canada; 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; GIF, 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, U.K; Leverhulme Trust, U.KWe acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MSMT CR, MPO CR and VSC 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, The Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MES of Russia and NRC KI, Russian Federation; 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; TAEK, Turkey; STFC, U.K.; DOE and NSF, U.S.A.. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; 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 GIF, 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, U.K
Virtual Reality in Anatomy Instruction: a Preliminary Study
No full textModern practical and theoretical instruction sessions need to be up-to-date, and nested with creativity and technology. Virtual reality (VR) is a state-of-the-art user interface interacting with multiple sensory channels and creating real-time simulations. In this study, we examined the effect of VR on the learning of the anatomy of the head and neck region. Seventeen students from 12 different medical schools in Turkey participated in this study. After one hour of theoretical training, the students were trained on cadavers for five hours. Then, a pre-test examination was given. After the pre-test, all students were given one-to-one virtual reality training and then a post-test. A statistically significant increase in the achievement of the students was found between the mean pre- and post-VR test scores (p=0.003). VR is considered as a rising trend in medicine when the skills and competencies of the generation Z on digital technologies are taken into consideration
Adil Yargılanma Hakkının Etkin Kullanımı Açısından Adli Yardım Kurumu ve Yabancıların Durumu
No full text[No Abstract Available
Medically Important Candida Spp. Identification: an Era Beyond Traditional Methods
No full textBackground/aim: Candida infections are gaining more attention for the last few decades so diagnostic tools are very important for early diagnosis. Conventional identification of yeasts is time-consuming, molecular methods are more complicated and relatively expensive gold-standard methods. Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) was put into the market due to its speed and high accuracy. The aim of this study was to evaluate the performance of corn meal tween-80 agar (CMTA), CHROMagar Candida medium, and MALDI-TOF MS and to compare the obtained results with DNA sequencing. Materials and methods: The CHROMagar Candida medium, CMTA, and MALDI-TOF MS Biotyper System were used to test 416 isolates. The isolates with discrepant results by at least one of the three methods were subjected to sequence analysis. Results: The identification results of the 351 (%84.4) were compatible with all three methods. When compared to the sequencing results, the most accurate results were obtained by the MALDI-TOF MS, especially for rare Candida species. Conclusion: MALDI-TOF MS is found to be the most accurate identification tool for clinically important Candida strains. CMTA alone should not be used for the final identification of Candida species and the chromogenic medium should always be considered presumptive. © TÜBİTAK
Ticari İşlemlerde Taşınır Rehnine Konu Olabilecek Varlıkların Yeknesak Ticaret Kanunu (ucc) ve Uncitral Teminatlı İşlemler Model Kanunu ile Karşılaştırmalı Olarak İncelenmesi
No full textThe aim of this thesis to compare the movable assets that can be subject to pledge within the scope of the Law on Pledge over Movable Assets in Commercial Transactions numbered 6750, Uniform Commercial Code article 9 and UNCITRAL Model Law on Secured Transactions. In the first part of the study, it was mentioned about the aim and legislative process related to non-possessory pledge over movable assets as well as the term of commercial transactions, parties to pledge agreement as well as secured transations, moveable asset and the function of registry were explained. In the second part it was mentioned about the scope of pledge over movable assets in commercial transactions, the assets that can be subject to non-possessory pledge as compared with Uniform Commercial Code and UNCITRAL Model Law. In the third and last part it was mentioned about other assets which are included in the scope of pledge, commingled goods and the assests transformed into a product on security right.Bu tez çalışmasında, 6750 sayılı Ticari İşlemlerde Taşınır Rehni Kanunu kapsamında rehne konu olabilecek varlıkların, Yeknesak Ticaret Kanunu'nun 9. maddesi (UCC) ve UNCITRAL Teminatlı İşlemler Model Kanunu ile karşılaştırmalı olarak incelenmesi amaçlanmıştır. Çalışmanın birinci bölümünde, teslimsiz taşınır rehnine ilişkin yasal düzenlemelerin kanunlaştırma süreci ve amacına değinilmiş, ticari işlem kavramı, rehin sözleşmenin ve teminatlı işlemlerin tarafları, taşınır varlık ile sicilin fonksiyonu ele alınmıştır. İkinci bölümde, ticari işlemlerde taşınır rehninin uygulama alanı ile rehin konusu olabilecek varlıklar, Yeknesak Ticaret Kanunu ve UNCITRAL Model Kanunu ile karşılaştırmalı olarak incelenmiştir. Üçüncü ve son bölümde ise taşınır rehninin kapsamına giren diğer unsurlar ile taşınır varlıkların birleşmesi, karışması ve yeni bir ürüne dönüşmesinin rehin hakkına etkisi açıklanmıştır