Oscillation of Neutral Partial Dynamic Equations

This paper is concerned with the oscillation of solutions of a certain more general neutral type dynamic equation. We establish within the necessary and sufficient conditions for the oscillation of its solutions

Analyses pluridisciplinaires sur la crise sanitaire COVID-19 en Turquie

L’objet de ce dossier vise à croiser les regards et les approches disciplinaires pour proposer des analyses plurielles de la crise sanitaire COVID-19 en Turquie. Les différentes approches font émerger des questionnements transversaux. Un premier questionnement tient à la pertinence des différents pouvoirs (locaux, étatiques, internationaux) face à des épidémies qui présentent toutes des spécificités, tant du point de vue de la diffusion et de la prévention, que des savoirs ou de la prise en charge. Une deuxième interrogation transversale porte sur la compénétration des pratiques et rituels sociaux et des dispositifs techniques. Les épidémies transforment le quotidien en validant ou répudiant certaines pratiques, et en induisant des réponses techniques qui sont à leur tour ritualisées. Comment interpréter cette transformation des pratiques ? Un troisième questionnement porte sur la frontière entre experts et profanes et à son évolution dans la temporalité de la pandémie. L’idée qu’un événement de l’ampleur d’une épidémie nécessitait une réponse organisée, et par conséquent un pilotage politico-sanitaire surplombant s’est heurtée à la durée de la pandémie, à l’évolution des connaissances à son sujet et à la compétition des objectifs stratégiques des politiques publiques, même lorsque ceux-ci, la santé et l’économie notamment, ne pouvaient aller l’un sans l’autre

Supervised learning approaches to flight delay prediction

Delays in flights and other airline operations have significant consequences in quality of service, operational costs, and customer satisfaction. Therefore, it is important to predict the occurrence of delays and take necessary actions accordingly. In this study, we addressed the flight delay prediction problem from a supervised machine learning perspective. Using a realworld airline operations dataset provided by a leading airline company, we identified optimum dataset features for optimum prediction accuracy. In addition, we trained and tested 11 machine learning models on the datasets that we created from the original dataset via feature selection and transformation. CART and KNN showed consistently good performance in almost all cases achieving 0.816 and 0.807 F-Scores respectively. Similarly, GBM, XGB, and LGBM showed very good performance in most of the cases, achieving F-Scores around 0.810. Keywords: air transportation, flight delay prediction, machine learning, data science Mehmet Cemal ATLIOĞLU1 , Mustafa BOLAT1 , Murat ŞAHİN2 , Volkan TUNALI*3 , Deniz KILINÇ 1 Tav Technology, İstanbul, E-Mail: [email protected] E-Mail: [email protected] ORCID: https://orcid.org/0000-0003-1289-2715 ORCID: https://orcid.org/0000-0001-8169-0629 2 Manisa Celal Bayar University, Faculty of Technology, E-Mail: [email protected] ORCID: https://orcid.org/0000-0002-2866-8796 * Corresponding Author: [email protected] 3 Maltepe University, Faculty of Engineering and Natural Sciences ORCID: https://orcid.org/0000-0002-2735-7996 4İzmir Bakırçay University, Faculty of Engineering and Architecture

Oscillatory behaviour of a higher-order dynamic equation

In this paper we are concerned with the oscillation of solutions of a certain more general higher-order nonlinear neutral-type functional dynamic equation with oscillating coefficients. We obtain some sufficient criteria for oscillatory behaviour of its solutions. © 2013 Uçar and Bolat

Prostate-specific Membrane Antigen-Based Nanomedicine Applications in the Diagnosis and Treatment of Prostate Cancer

WOS: 000464095200008Nanomedicine is a branch of nanotechnology that includes the development of nanostructures and nanoanalytical systems for various medical applications. The rapid development of nanomedicine offers new possibilities in cancer diagnosis and treatment. New therapeutic strategies in cancer research using nanoparticles are being developed in order to improve the specificity and efficacy of drug delivery, thus reaching maximal effectiveness with minimal side effects. Due to its selective overexpression in prostate cancer (PCa), prostate-specific membrane antigen (PSMA) has been recognized as a highly promising target for diagnostic and therapeutic applications. This review provides an update on the PSMA-based nanomedicine applications in PCa

Immunotherapy in Prostate Cancer

WOS: 000469807700006In recent years, immunotherapy has become an important treatment alternative in the treatment of many cancers. Research on immunotherapy in prostate cancer has been accelerated by obtaining Food and Drug Administration (FDA) approval of sipuleucel-T for asymptomatic or minimal symptomatic metastatic castration-resistant prostate cancer (CRPC). Despite all these developments, the patients in whom these agents should be used, sequential use and combination strategies remain unclear. In this review, mechanisms of action and survival outcomes of different immunotherapeutic agents and therapeutic cancer vaccines in mCRPC are discussed

Supervised Learning Approaches to Flight Delay Prediction

Delays in flights and other airline operations have significant consequences in quality of service, operational costs, and customer satisfaction. Therefore, it is important to predict the occurrence of delays and take necessary actions accordingly. In this study, we addressed the flight delay prediction problem from a supervised machine learning perspective. Using a realworld airline operations dataset provided by a leading airline company, we identified optimum dataset features for optimum prediction accuracy. In addition, we trained and tested 11 machine learning models on the datasets that we created from the original dataset via feature selection and transformation. CART and KNN showed consistently good performance in almost all cases achieving 0.816 and 0.807 F-Scores respectively. Similarly, GBM, XGB, and LGBM showed very good performance in most of the cases, achieving F-Scores around 0.810. Keywords: air transportation, flight delay prediction, machine learning, data science Mehmet Cemal ATLIOĞLU1 , Mustafa BOLAT1 , Murat ŞAHİN2 , Volkan TUNALI*3 , Deniz KILINÇ 1 Tav Technology, İstanbul, E-Mail: [email protected] E-Mail: [email protected] ORCID: https://orcid.org/0000-0003-1289-2715 ORCID: https://orcid.org/0000-0001-8169-0629 2 Manisa Celal Bayar University, Faculty of Technology, E-Mail: [email protected] ORCID: https://orcid.org/0000-0002-2866-8796 * Corresponding Author: [email protected] 3 Maltepe University, Faculty of Engineering and Natural Sciences ORCID: https://orcid.org/0000-0002-2735-7996 4İzmir Bakırçay University, Faculty of Engineering and Architecture