Crystallization modeling of two semi-crystalline polyamides during material extrusion additive manufacturing.

In this work, a heat transfer model is developed for thermally-driven material extrusion additive manufacturing of semicrystalline polymers that considers the heat generated during crystallization by coupling crystallization kinetics with heat transfer. The materials used in this work are Technomelt PA 6910, a semicrystalline hot melt adhesive with sub-ambient glass transition temperature (T) and slow crystallization, and PA 6/66, a traditional semicrystalline polyamide with a higher T and fast crystallization. The coupled model shows that the released heat during crystallization depends on material selection, with Technomelt PA 6910 and PA 6/66's temperatures increased by less than 1 °C and up to 6.

Active learning for prediction of tensile properties for material extrusion additive manufacturing.

Machine learning techniques were used to predict tensile properties of material extrusion-based additively manufactured parts made with Technomelt PA 6910, a hot melt adhesive. An adaptive data generation technique, specifically an active learning process based on the Gaussian process regression algorithm, was employed to enable prediction with limited training data. After three rounds of data collection, machine learning models based on linear regression, ridge regression, Gaussian process regression, and K-nearest neighbors were tasked with predicting properties for the test dataset, which consisted of parts fabricated with five processing parameters chosen using a random number generator.

Predictive factors for re-displacement in diaphyseal forearm fractures in children-role of radiographic indices.

Background and purpose - Manipulation and cast immobilization is the primary management for diaphyseal forearm fractures in children, and re-displacement is the most common complication. We wanted (1) to analyze the incidence of re-displacement in a group of children treated with close reduction and casting; (2) to determine predictive factors such as demographics, mechanism of injury, affected bone, fracture pattern, degree of initial displacement and angulation, and reduction accuracy; and (3) to determine the prognostic effect of previously defined radiographic indices. Patients and methods - We prospectively studied 269 consecutive children with closed and complete middle-third diaphyseal fractures treated with close reduction and casting from October 2014 to April 2015.

Serum gamma-glutamyltransferase, alanine aminotransferase, and aspartate aminotransferase activity in Iranian healthy blood donor men.

Aim: To determine serum gamma-glutamyltransferase (GGT), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) activity, and to assess their correlation with demographic and clinical findings in healthy blood donors.

Methods: This cross-sectional study was performed in 934 male blood donors, aged 18 to 68 years, who consecutively attended Tehran blood transfusion service in 2006. All participants were seronegative for HBV or HCV infections, non alcohol users, and all underwent a standard interview and anthropometric tests.