A Content Analysis-Based Approach to Explore Simulation Verification and Identify Its Current Challenges

Verification is a crucial process to facilitate the identification and removal of errors within simulations. This study explores semantic changes to the concept of simulation verification over the past six decades using a data-supported, automated content analysis approach. We collect and utilize a corpus of 4,047 peer-reviewed Modeling and Simulation (M&S) publications dealing with a wide range of studies of simulation verification from 1963 to 2015. We group the selected papers by decade of publication to provide insights and explore the corpus from four perspectives: (i) the positioning of prominent concepts across the corpus as a whole; (ii) a comparison of the prominence of verification, validation, and Verification and Validation (V&V) as separate concepts; (iii) the positioning of the concepts specifically associated with verification; and (iv) an evaluation of verification\u27s defining characteristics within each decade. Our analysis reveals unique characterizations of verification in each decade. The insights gathered helped to identify and discuss three categories of verification challenges as avenues of future research, awareness, and understanding for researchers, students, and practitioners. These categories include conveying confidence and maintaining ease of use; techniques\u27 coverage abilities for handling increasing simulation complexities; and new ways to provide error feedback to model users

Temporal and Spatiotemporal Investigation of Tourist Attraction Visit Sentiment on Twitter

In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists\u27 emotions when visiting a city\u27s tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and activities like concerts, impact tourists\u27 emotions. In addition, our analysis suggests that tourists experience greater levels of enjoyment in places such as observatories rather than zoos. Finally, we find that local and international visitors tend to convey negative sentiment when visiting more than one attraction in a day whereas the opposite holds for out of state visitors

Simulation for Cybersecurity: State of the Art and Future Directions

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans in cybersecurity research. The proposed way forward section posits that the advancement of collecting and accessing sociotechnological data to inform models, the creation of new theoretical constructs, and the integration and improvement of behavioral models are needed to advance cybersecurity efforts

Flexible and expandable robot for tissue therapies - Modeling and design

Objective: Implantable technologies should be mechanically compliant with the tissue in order to maximize tissue quality and reduce inflammation during tissue reconstruction. We introduce the development of a flexible and expandable implantable robotic (FEIR) device for the regenerative elongation of tubular tissue by applying controlled and precise tension to the target tissue while minimizing the forces produced on the surrounding tissue. Methods: We introduce a theoretical framework based on iterative beam theory static analysis for the design of an expandable robot with a flexible rack. The model takes into account the geometry and mechanics of the rack to determine a trade-off between its stiffness and capability to deliver the required tissue tension force. We empirically validate this theory on the benchtop and with biological tissue. Results: We show that FEIR can apply the required therapeutical forces on the tissue while reducing the amount of force it applies to the surrounding tissues as well as reducing self-damage. Conclusion: The study demonstrates a method to develop robots that can change size and shape to fit their dynamic environment while maintaining the precision and delicacy necessary to manipulate tissue by traction. Significance: The method is relevant to designers of implantable technologies. The robot is a precursor medical device for the treatment of Long-Gap Esophageal Atresia and Short Bowel Syndrome

Thermal and Mechanical Characteristics of Polymer Composites Based on Epoxy Resin, Aluminium Nanopowders and Boric Acid

The epoxy polymers are characterized by low thermal stability and high flammability. Nanoparticles are considered to be effective fillers of polymer composites for improving their thermal and functional properties. In this work, the epoxy composites were prepared using epoxy resin ED-20, polyethylene polyamine as a hardener, aluminum nanopowder and boric acid fine powder as flame-retardant filler. The thermal characteristics of the obtained samples were studied using thermogravimetric analysis and differential scanning calorimetry. The mechanical characteristics of epoxy composites were also studied. It was found that an addition of all fillers enhances the thermal stability and mechanical characteristics of the epoxy composites. The best thermal stability showed the epoxy composite filled with boric acid. The highest flexural properties showed the epoxy composite based on the combination of boric acid and aluminum nanopowder

Discovery and genotyping of novel sequence insertions in many sequenced individuals

Motivation: Despite recent advances in algorithms design to characterize structural variation using high-throughput short read sequencing (HTS) data, characterization of novel sequence insertions longer than the average read length remains a challenging task. This is mainly due to both computational difficulties and the complexities imposed by genomic repeats in generating reliable assemblies to accurately detect both the sequence content and the exact location of such insertions. Additionally, de novo genome assembly algorithms typically require a very high depth of coverage, which may be a limiting factor for most genome studies. Therefore, characterization of novel sequence insertions is not a routine part of most sequencing projects. There are only a handful of algorithms that are specifically developed for novel sequence insertion discovery that can bypass the need for the whole genome de novo assembly. Still, most such algorithms rely on high depth of coverage, and to our knowledge there is only one method (PopIns) that can use multi-sample data to "collectively" obtain a very high coverage dataset to accurately find insertions common in a given population. Result: Here, we present Pamir, a new algorithm to efficiently and accurately discover and genotype novel sequence insertions using either single or multiple genome sequencing datasets. Pamir is able to detect breakpoint locations of the insertions and calculate their zygosity (i.e. heterozygous versus homozygous) by analyzing multiple sequence signatures, matching one-end-anchored sequences to small-scale de novo assemblies of unmapped reads, and conducting strand-aware local assembly. We test the efficacy of Pamir on both simulated and real data, and demonstrate its potential use in accurate and routine identification of novel sequence insertions in genome projects. © 2017 The Author. Published by Oxford University Press. All rights reserved

Male mice with deleted Wolframin (Wfs1) gene have reduced fertility

Background: Wolfram Syndrome (WS) is an autosomal recessive disorder characterised by non-autoimmune diabetes mellitus, optic atrophy, cranial diabetes insipidus and sensorineural deafness. Some reports have described hypogonadism in male WS patients. The aim of our study was to find out whether Wfs1 deficient (Wfs1KO) male mice have reduced fertility and, if so, to examine possible causes. Methods: Wfs1KO mice were generated by homologous recombination. Both Wfs1KO and wild type (wt) male mice were mated with wt female mice. The number of litters and the number of pups were counted and pregnancy rates calculated. The motility and morphology of the sperm and the histology of testes were analysed. Serum testosterone and FSH concentrations were also measured. Results: The pregnancy rate in wt females mated with Wfs1KO males was significantly lower than in the control group (15% vs. 32%; p < 0.05), but there was no significant difference in litter size. Analysis of male fertility showed that, in the Wfs1KO group, eight males out of 13 had pups whereas in the control group all 13 males had at least one litter. Sperm motility was not affected in Wfs1KO mice, but Wfs1KO males had less proximal bent tails (14.4 +/- 1.2% vs. 21.5 +/- 1.3 p < 0.05) and less abnormal sperm heads (22.8 +/- 1.8 vs. 31.5 +/- 3.5, p < 0.05) than wt males. Testes histology revealed significantly reduced number of spermatogonia (23.9 +/- 4.9 vs. 38.1 +/- 2.8; p < 0.05) and Sertoli cells (6.4 +/- 0.5 vs. 9.2 +/- 1.0; p < 0.05) in Wfs1KO mice. Serum testosterone and FSH concentrations did not differ between the two groups. Conclusion: The impaired fertility of Wfs1KO male mice is most likely due to changes in sperm morphology and reduced number of spermatogenic cells. The exact mechanism through which the Wfs1 gene influences sperm morphology needs to be clarified in further studies

Record linkage to obtain birth outcomes for the evaluation of screening biomarkers in pregnancy: a feasibility study

<p>Abstract</p> <p>Background</p> <p>Linking population health data to pathology data is a new approach for the evaluation of predictive tests that is potentially more efficient, feasible and efficacious than current methods. Studies evaluating the use of first trimester maternal serum levels as predictors of complications in pregnancy have mostly relied on resource intensive methods such as prospective data collection or retrospective chart review. The aim of this pilot study is to demonstrate that record-linkage between a pathology database and routinely collected population health data sets provides follow-up on patient outcomes that is as effective as more traditional and resource-intensive methods. As a specific example, we evaluate maternal serum levels of PAPP-A and free <it>β</it>-hCG as predictors of adverse pregnancy outcomes, and compare our results with those of prospective studies.</p> <p>Methods</p> <p>Maternal serum levels of PAPP-A and free <it>β</it>-hCG for 1882 women randomly selected from a pathology database in New South Wales (NSW) were linked to routinely collected birth and hospital databases. Crude relative risks were calculated to investigate the association between low levels (multiples of the median ≤ 5^thpercentile) of PAPP-A or free <it>β</it>-hCG and the outcomes of preterm delivery (<37 weeks), small for gestational age (<10^thpercentile), fetal loss and stillbirth.</p> <p>Results</p> <p>Using only full name, sex and date of birth for record linkage, pregnancy outcomes were available for 1681 (89.3%) of women included in the study. Low levels of PAPP-A had a stronger association with adverse pregnancy outcomes than a low level of free <it>β</it>-hCG which is consistent with results in published studies. The relative risk of having a preterm birth with a low maternal serum PAPP-A level was 3.44 (95% CI 1.96–6.10) and a low free <it>β</it>-hCG level was 1.31 (95% CI 0.55–6.16).</p> <p>Conclusion</p> <p>This study provides data to support the use of record linkage for outcome ascertainment in studies evaluating predictive tests. Linkage proportions are likely to increase if more personal identifiers are available. This method of follow-up is a cost-efficient technique and can now be applied to a larger cohort of women.</p

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors

Bias associated with delayed verification in test accuracy studies: accuracy of tests for endometrial hyperplasia may be much higher than we think!

BACKGROUND: To empirically evaluate bias in estimation of accuracy associated with delay in verification of diagnosis among studies evaluating tests for predicting endometrial hyperplasia. METHODS: Systematic reviews of all published research on accuracy of miniature endometrial biopsy and endometr ial ultrasonography for diagnosing endometrial hyperplasia identified 27 test accuracy studies (2,982 subjects). Of these, 16 had immediate histological verification of diagnosis while 11 had verification delayed > 24 hrs after testing. The effect of delay in verification of diagnosis on estimates of accuracy was evaluated using meta-regression with diagnostic odds ratio (dOR) as the accuracy measure. This analysis was adjusted for study quality and type of test (miniature endometrial biopsy or endometrial ultrasound). RESULTS: Compared to studies with immediate verification of diagnosis (dOR 67.2, 95% CI 21.7–208.8), those with delayed verification (dOR 16.2, 95% CI 8.6–30.5) underestimated the diagnostic accuracy by 74% (95% CI 7%–99%; P value = 0.048). CONCLUSION: Among studies of miniature endometrial biopsy and endometrial ultrasound, diagnostic accuracy is considerably underestimated if there is a delay in histological verification of diagnosis