Applications of Artificial Intelligence and Graphy Theory to Cyberbullying

Cyberbullying is an ongoing and devastating issue in today\u27s online social media. Abusive users engage in cyber-harassment by utilizing social media to send posts, private messages, tweets, or pictures to innocent social media users. Detecting and preventing cases of cyberbullying is crucial. In this work, I analyze multiple machine learning, deep learning, and graph analysis algorithms and explore their applicability and performance in pursuit of a robust system for detecting cyberbullying. First, I evaluate the performance of the machine learning algorithms Support Vector Machine, Naïve Bayes, Random Forest, Decision Tree, and Logistic Regression. This yielded positive results and obtained upwards of 86% accuracy. Further enhancements were achieved using Evolutionary Algorithms, improving the overall results of the machine learning models. Deep Learning algorithms was the next experiment in which efficiency was monitored in terms of training time and performance. Next, analysis of Recurrent Neural Networks and Hierarchical Attention Networks was conducted, achieving 82% accuracy. The final research project used graph analysis to explore the relation among different social media users, and analyze the connectivity and communities of users who were discovered to have posted offensive messages

Global Spatial Risk Assessment of Sharks Under the Footprint of Fisheries

Effective ocean management and conservation of highly migratory species depends on resolving overlap between animal movements and distributions and fishing effort. Yet, this information is lacking at a global scale. Here we show, using a big-data approach combining satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively) and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of high-seas fishing effort. Results demonstrate an urgent need for conservation and management measures at high-seas shark hotspots and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real time, dynamic management

A chromosome conformation capture ordered sequence of the barley genome

201

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Pump-probe microscope imaging of Jurassic-aged eumelanin

Melanins are biological pigments found throughout the animal kingdom that have many diverse functions. Pump-probe imaging can differentiate the two kinds of melanins found in human skin, eumelanin and pheomelanin, the distributions of which are relevant to the diagnosis of melanoma. The long-term stability of melanins is central to using this technology to analyze melanin distributions in archived tissue samples to improve diagnostic procedures. This report shows that most of the pump-probe signal from eumelanin derived from a Jurassic cephalopod is is essentially identical to that of eumelanin extracted from its modern counterpart, Sepia officinalis. However, additional classes of eumelanin signals found in the fossil reveal that the pump-probe signature is sensitive to iron content, which could be a valuable tool for pathologists who cannot otherwise know the microscopic distributions of iron in melanins