Titlebook: Scientific Computing, Computer Arithmetic, and Validated Numerics; 16th International S Marco Nehmeier,Jürgen Wolff von Gudenberg,Warwick

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Chemseddine Chohra,Philippe Langlois,David Parelloological approaches for scholars at various levels of academic life. Accompanied by introductory sections of prominent scholars, the majority of empirical studies gathered in this volume are accomplished throug978-3-319-40699-2978-3-319-40700-5

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David Hartman,Milan Hladíkological approaches for scholars at various levels of academic life. Accompanied by introductory sections of prominent scholars, the majority of empirical studies gathered in this volume are accomplished throug978-3-319-40699-2978-3-319-40700-5

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Sliding Mode Approaches Considering Uncertainty for Reliable Control and Computation of Confidence Rically only known within given tolerance bounds. Therefore, this paper combines interval arithmetics with the advantages of sliding mode approaches for control and estimation of states and parameters taking into account also stochastic disturbances. The efficiency of these approaches is shown in ter

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e immune aging and autoimmunity remain elusive. We reported that a PD-1. memory phenotype (MP) CD4. T cell population is increased as normal mice age, termed senescence-associated (SA-) T cells. The SA-T cells show characteristic signs and features of cellular senescence and emerge as follicular T c

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John Prycenals assess childhood maltreatment through prospective or retrospective measures, with the assumption that both measures are interchangeable. In this chapter, we critically evaluate this assumption by reviewing evidence examining whether prospective and retrospective measures of child maltreatment (

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mination violates assumptions within counterfactual models of causal inference and results in two systematic and sequential problems: (1) measurement error in the form of misclassification of units in a control condition, and (2) bias in statistical modeling that affects the direction, magnitude, an

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Boris Dobronets,Olga Popovae evaluated the effectiveness of deep learning algorithms used in object detection for medical image analysis. Additionally, we conducted Meningioma detection by examining the importance of hyperparameter tuning and its impact on performance using the YOLO deep learning model. While the majority of