Healing of Internal Defects in a Compressive Stress Field Using the Plastic Properties of Materials

Numerical simulation of defect healing process in the field of previously created compressive stresses is performed. Isotropic cylinders with small axisymmetrically located defects are used as samples. The pressure created the initial field of compressive stresses inside the cylinder. The defects were modeled as a small blind closed annular cavity or as a through annular cut located around the cylinder axis. In the first case, a numerical three-dimensional solution is considered. For the second defect, the plane stress state model was used. The problems were solved in both elastic and elastoplastic formulations with an ideally elastoplastic behavior of the material. The external pressure was varied from values significantly lower than the yield strength to the yield strength and (for the first problem) for values slightly exceeding it. Based on the results of the numerical solution, the radial displacements of the cavity sides parallel to the cylinder axis are obtained depending on the external pressure. We found the values of pressure at which the cylindrical surfaces of the void defect were in contact. For the blind cavity, at any external pressure, there were unhealed areas. Healing was assessed by the volume of the material filling the initial cavity at the initial residual stresses. The value of the newly formed contact pressure at a certain value of the compressive stresses was determined by the ratio of the height of the healed area to the cavity height. The evaluation of the healing effect for a through cut in the cylinder was performed by varying the size of the gap formed by the cut between the inner cylinder and the outer ring depending on the applied external pressure. When the gap is completely healed, the values of the maximal contact pressure in the notch zone are determined.

Introducing the Contextual Ambidexterity Scale for Public Organizations (CASPO): Scale development and initial evidence

Contextual ambidexterity describes the organizational capacity of being simultaneously able to adapt and change in the face contextual requirements while keeping alignment and predictability. Contextual ambidexterity has been recognized as an appropriate explanation of organizational performance, and its influence has already permeated accounts of public organizations’ dynamics. We join this line of reasoning by suggesting that some specific characteristics of public organizations call for refinement of the contextual ambidexterity concept, and the correspondent evolution in measuring this organizational ability, thus introducing the Contextual Ambidexterity Scale for Public Organizations (CASPO). We suggest going beyond the original measure of alignment and adaptability created by Gibson and Birkinshaw (2004), to include psychological safety, reflexive spaces, and flexibility as sub-dimensions of adaptability and imprinting, rulefollowing and shared vision as sub-dimensions of alignment. On the basis of a sample of civil servants (n=200), we used exploratory factor analysis to identify a six-dimensional solution covering alignment and adaptability. Using another sample of civil servants (n=200), we used confirmatory factor analysis to test CASPO’s construct validity and regression analysis in testing the criterion validity. The results reveal that CASPO shows appropriate metric qualities and that it surpasses Gibson and Birkinshaw’s (2004) scale in predicting both their measure of generic organizational performance and a measure of performance specific for public organizations. This study contributes to the creation of sound measures of relevant concepts explaining the performance of public organizations.

Design Of Fuzzy Rule-Based System Using Genetic Algorithms

The aim of this paper is to obtain a compact and optimal fuzzy rule-based model from observation data by utilizing the Genetic algorithm technique. The approach is optimized by applying Genetic Algorithms, owing to its capability of searching irregular and high dimensional solution spaces. Genetic Algorithms has been applied to learn consequent part of fuzzy rules and models with fixed number of rules. In the work we propose a Genetic algorithm approach to a non-linear air conditioning system for the construction of optimal fuzzy rules in two steps. First, fuzzy clustering is applied to obtain an initial rule based model having pre-calculated number of rules with antecedents only. In the second step, the regions of rule-consequents are obtained by a binary coded Genetic Algorithm which leads to the extraction of an optimal rule based model.

Dimensional Latent Structure of Callous-Unemotional Traits in German Adolescents: Results from Taxometric Analyses

A large amount of research has addressed the issue of the latent status of psychiatric disorders and related phenomena. We used a new taxometric approach developed by Ruscio to examine the latent status of callous-unemotional (CU) traits in a large representative study of German ninth graders (N = 3,878). Rather than estimating a putative taxon base rate and using that estimate to generate the taxon comparative data, we estimated CCFI profiles with each base rate estimate between 2.5% and 97.5% in increments of 2.5%. Results of different indicator sets clearly suggested a dimensional solution. This finding is consistent with different studies showing the dimensionality of psychopathy in adolescents. In summary, the results of this study point to the need for critical reflection in defining a high-risk-group in the context of CU traits. However, further studies are necessary to substantiate this result in different samples using different measurement approaches.

Machine learning for laser-induced electron diffraction imaging of molecular structures

Ultrafast diffraction imaging is a powerful tool to retrieve the geometric structure of gas-phase molecules with combined picometre spatial and attosecond temporal resolution. However, structural retrieval becomes progressively difficult with increasing structural complexity, given that a global extremum must be found in a multi-dimensional solution space. Worse, pre-calculating many thousands of molecular configurations for all orientations becomes simply intractable. As a remedy, here, we propose a machine learning algorithm with a convolutional neural network which can be trained with a limited set of molecular configurations. We demonstrate structural retrieval of a complex and large molecule, Fenchone (C10H16O), from laser-induced electron diffraction (LIED) data without fitting algorithms or ab initio calculations. Retrieval of such a large molecular structure is not possible with other variants of LIED or ultrafast electron diffraction. Combining electron diffraction with machine learning presents new opportunities to image complex and larger molecules in static and time-resolved studies.

Numerical Simulation and Parametric Analysis of Fatigue Crack in UIC60 Rail Thermite Welded Joint

The mechanism of rail-wheel contact is the most essential field of study in railway engineering since it requires extensive application expertise, diagnostic skills, and a trustworthy analysis technique. In this research the fatigue life of a UIC60 rail AT weld under vertical load and its parametric effect has been studied, and for that a three-dimensional elastic-plastic finite element model is created using ANSYS space-claim software, and then finite element method is employed to analyse the full-scale model of wheel-track and weld system with realistic three-dimensional solution. Model assembly components include axle, wheel, and thermite-welded rail. Simulation of contact between wheel and UIC60 rail weld with crack on weld at angles of 30 and 60 degrees with different coefficients of friction between the weld wheel contact and between crack surfaces was carried out under vertical loadings. In general, the Hertz contact theory assumptions are taken into consideration throughout the analysis, and the impacts on fatigue life are given by using damage mechanics method. The results of the wheel/weld fatigue crack analysis have been displayed to demonstrate the influence of different parameters on the fatigue life of cracks. The purpose of this study is to identify and safeguard the rail against failure, as well as to ensure the safety of passengers and to reduce the cost of maintaining the rail system.

Validation and Psychometric Properties of the Chinese Version of the Fear of Missing Out Scale

Objectives: The present study aimed to examine the psychometric properties of Przybylski’s 10-item Fear of Missing Out scale and to investigate the measurement invariance across age and gender among Chinese adolescents and emerging adults. Methods: A convenient sample of 2886 subjects (Mage = 14.79, SD = 4.03; 47.96% male) was recruited in south China. Item analysis, EFA, CFA, testing of measurement invariance across gender and age, reliability analysis, and concurrent validity analysis were conducted. A subsample of 154 subjects (Mage = 15.3, SD = 2.22; 54% male) completed the scale again after 6 months to assess the test–retest reliability. Results: The EFA strongly indicated a two-dimensional solution, including fear of missing novel information and fear of missing social opportunities, for the Chinese version of the FoMO scale, which the CFA confirmed. Adequate internal consistency was found. Concurrent validity and discriminant validity were also demonstrated. Conclusions: Based on the results, the Chinese version of the FoMO scale is suitable for use among young Chinese people.