Towards automated tracking of initiation and propagation of cracks in aluminium alloy coupons using thermoelastic stress analysis

Raw Thermoelastic Stress Analysis (TSA) data to accompany submitted paper. Data collected during constant amplitude tensile-tensile cyclic loading. Manuscript submitted to Journal of Nondestructive Evaluation (Springer). Submission Date June 2018

Comparing full-field data from structural components with complicated geometries

A new decomposition algorithm based on QR factorization is introduced for processing and comparing irregularly shaped stress and deformation datasets found in structural analysis. The algorithm improves the comparison of two-dimensional data fields from the surface of components where data is missing from the field of view due to obstructed measurement systems or component geometry that results in areas where no data is present. The technique enables the comparison of these irregularly shaped datasets without the need for interpolation or warping of the data necessary in some other decomposition techniques, for example, Chebyshev or Zernike decomposition. This ensures comparisons are only made between the available data in each dataset and thus similarity metrics are not biased by missing data. The decomposition and comparison technique has been applied during an impact experiment, a modal analysis, and a fatigue study, with the stress and displacement data obtained from finite-element analysis, digital image correlation and thermoelastic stress analysis. The results demonstrate that the technique can be used to process data from a range of sources and suggests the technique has the potential for use in a wide variety of applications

Towards automated characterisation of fatigue damage in composites using thermoelastic stress analysis

Composite materials demonstrate complicated fatigue behaviour due to their microstructure and the varied types of defects that can occur during loading. This necessitates experimentation to determine their performance under loading. In this study an algorithm is introduced for identifying and categorising different defects forming during fatigue tests. Thermoelastic stress analysis was used to obtain high spatial and temporal resolution stress information from the surface of notched composite specimens. Specimens with three different geometries were loaded in tension–tension fatigue to failure. An algorithm was used to identify when and where matrix cracking and delaminations formed within the specimens as well as quantify how this changed over time. By improving how damage events are identified and characterised, the algorithm reduces the amount of time needed to process experimental fatigue data and helps to provide greater understanding of fatigue processes in new materials from early small-scale cracking all the way to final failure

The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems

In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the products that they export are relevant for understanding the dynamics of economic development. Here we study the presence and absence of industries at the global and national levels and show that these networks are significantly nested. This means that the less filled rows and columns of these networks' adjacency matrices tend to be subsets of the fuller rows and columns. Moreover, we show that nestedness remains relatively stable as the matrices become more filled over time and that this occurs because of a bias for industries that deviate from the networks' nestedness to disappear, and a bias for the missing industries that reduce nestedness to appear. This makes the appearance and disappearance of individual industries in each location predictable. We interpret the high level of nestedness observed in these networks in the context of the neutral model of development introduced by Hidalgo and Hausmann (2009). We show that, for the observed fills, the model can reproduce the high level of nestedness observed in these networks only when we assume a high level of heterogeneity in the distribution of capabilities available in countries and required by products. In the context of the neutral model, this implies that the high level of nestedness observed in these economic networks emerges as a combination of both, the complementarity of inputs and heterogeneity in the number of capabilities available in countries and required by products. The stability of nestedness in industrial ecosystems, and the predictability implied by it, demonstrates the importance of the study of network properties in the evolution of economic networks.Comment: 26 page

Establishing the precise evolutionary history of a gene improves prediction of disease-causing missense mutations

PURPOSE: Predicting the phenotypic effects of mutations has become an important application in clinical genetic diagnostics. Computational tools evaluate the behavior of the variant over evolutionary time and assume that variations seen during the course of evolution are probably benign in humans. However, current tools do not take into account orthologous/paralogous relationships. Paralogs have dramatically different roles in Mendelian diseases. For example, whereas inactivating mutations in the NPC1 gene cause the neurodegenerative disorder Niemann-Pick C, inactivating mutations in its paralog NPC1L1 are not disease-causing and, moreover, are implicated in protection from coronary heart disease. METHODS: We identified major events in NPC1 evolution and revealed and compared orthologs and paralogs of the human NPC1 gene through phylogenetic and protein sequence analyses. We predicted whether an amino acid substitution affects protein function by reducing the organism’s fitness. RESULTS: Removing the paralogs and distant homologs improved the overall performance of categorizing disease-causing and benign amino acid substitutions. CONCLUSION: The results show that a thorough evolutionary analysis followed by identification of orthologs improves the accuracy in predicting disease-causing missense mutations. We anticipate that this approach will be used as a reference in the interpretation of variants in other genetic diseases as well. Genet Med 18 10, 1029–1036

Coronary artery bypass grafting and sensorineural hearing loss, a cohort study

BACKGROUND: Sudden sensorineural hearing loss is routinely encountered by the otologist. The etiology is varied and often identifiable. One of the relatively less frequent causes is surgery. Apart from being an established entity with otological surgeries, sensorineural hearing loss has also been known to occur after non-otological procedures under general anesthesia. Commonest amongst these procedures is cardiopulmonary bypass, an association that has long been recognized. However, despite the proposition of diverse hypotheses in the past, the pathophysiology remains unclear. METHODS: The study is a prospective matched cohort study that will be carried out in Aga Khan University Hospital, Karachi, Pakistan. Participants among exposed would include all those patients who would be undergoing coronary artery bypass surgery in the hospital who fall under the criteria for inclusion. Unexposed group would comprise of patients undergoing a non-bypass procedure of similar duration under the same type of anesthesia who meet the selection criteria. Both these groups will undergo audiometric testing at our hospital on three different occasions during the course of this study. Initially before the procedure to test the baseline hearing capacity; then one week after the procedure to assess any changes in hearing ability following the surgery; and finally a third audiogram at six weeks follow-up to assess further changes in any hearing deficits noted during the second phase of testing. Certain variables including the subjects' demographics and those concerning the procedure itself will be noted and used later for risk factors analysis. A detailed past medical and surgical history will also be obtained. Data analysis would include calculation of relative risk and significance of the results, by running the chi-square test. Other statistical tests like Fisher exact test may then be employed to facilitate data interpretation. Continuous scale may then be employed and multivariate linear regression used. DISCUSSION: This study is planned to obtain a better understanding of the correlation between sudden sensorineural hearing loss and cardiopulmonary bypass. Being the first major cohort trial in this line of investigation, the project is designed to identify the existence of any significant relationship between cardiopulmonary bypass and sensorineural hearing deficit