Dislocation random walk under cyclic deformation.

Dislocation motion under cyclic loading is of great interest from theoretical and practical viewpoints. In this paper, we develop a random walk model for the purpose of evaluating the diffusion coefficient of dislocation under cyclic loading condition. The dislocation behavior was modeled as a series of binomial stochastic processes (one-dimensional random walk), where dislocations are randomly driven by the external load.

Introduction of a Multidisciplinary Preoperative Clinic at Juntendo University Hospital - A Retrospective Observational Study Focusing on Effects of Preoperative Interventions on Clinical Outcomes.

Objectives: To investigate the effects of interventions provided by a multidisciplinary team consisting of anesthesiologists, dentists, pharmacists, and nurses at a Preoperative Clinic (POC) on postoperative outcomes.

Methods: We retrospectively investigated patients who underwent preoperative evaluation at the POC at Juntendo University Hospital between May and July, 2019. Patients were divided into intervention and non-intervention groups according to whether they received intervention(s) at the POC or not.

Immunoreactivity of TTF-1, GATA-3, CEA, and p16/Ki67 cocktail in Cellprep®-processed control samples: Comparison of long-term storage in vials and slides.

Introduction: Cellprep® (CP) is a novel liquid-based cytology (LBC) system. This study aimed to assess the immunoreactivity of control samples stored long-term under two storage conditions using CP.

Methods: The immunoreactivity in control samples was evaluated under two sample storage conditions: CP vial storage at room temperature (RT: 20-25°C) and CP slide storage in a refrigerator (2-6°C).

Inductive Determination of Rate-Reaction Equation Parameters for Dislocation Structure Formation Using Artificial Neural Network.

The reaction-diffusion equation approach, which solves differential equations of the development of density distributions of mobile and immobile dislocations under mutual interactions, is a method widely used to model the dislocation structure formation. A challenge in the approach is the difficulty in the determination of appropriate parameters in the governing equations because deductive (bottom-up) determination for such a phenomenological model is problematic. To circumvent this problem, we propose an inductive approach utilizing the machine-learning method to search a parameter set that produces simulation results consistent with experiments.

Coarse-Grained Molecular Dynamics Simulation of Polycarbonate Deformation: Dependence of Mechanical Performance by the Effect of Spatial Distribution and Topological Constraints.

Polycarbonate is an engineering plastic used in a wide range of applications due to its excellent mechanical properties, which are closely related to its molecular structure. We performed coarse-grained molecular dynamics (CGMD) calculations to investigate the effects of topological constraints and spatial distribution on the mechanical performance of a certain range of molecular weights. The topological constraints and spatial distribution are quantified as the number of entanglements per molecule (Ne) and the radius of gyration (Rg), respectively.