Towards hierarchical affiliation resolution: framework, baselines, dataset

Author affiliations provide key information when attributing academic performance like publication counts. So far, such measures have been aggregated either manually or only to top-level institutions, such as universities. Supervised affiliation resolution requires a large number of annotated alignments between affiliation strings and known institutions, which are not readily available. We introduce the task of unsupervised hierarchical affiliation resolution, which assigns affiliations to institutions on all hierarchy levels (e.g. departments), discovering the institutions as well as their hierarchical ordering on the fly. From the corresponding requirements, we derive a simple conceptual framework based on the subset partial order that can be extended to account for the discrepancies evident in realistic affiliations from the Web of Science. We implement initial baselines and provide datasets and evaluation metrics for experimentation. Results show that mapping affiliations to known institutions and discovering lower-level institutions works well with simple baselines, whereas unsupervised top-level- and hierarchical resolution is more challenging. Our work provides structured guidance for further in-depth studies and improved methodology by identifying and discussing a number of observed difficulties and important challenges that future work needs to address

The clinical relevance of omega-3 fatty acids in the management of hypertriglyceridemia

Hypertriglyceridemia (triglycerides > 150 mg/dL) affects ~25 % of the United States (US) population and is associated with increased cardiovascular risk. Severe hypertriglyceridemia (≥ 500 mg/dL) is also a risk factor for pancreatitis. Three omega-3 fatty acid (OM3FA) prescription formulations are approved in the US for the treatment of adults with severe hypertriglyceridemia: (1) OM3FA ethyl esters (OM3EE), a mixture of OM3FA ethyl esters, primarily eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) (Lovaza®, Omtryg™, and generics); (2) icosapent ethyl (IPE), EPA ethyl esters (Vascepa®); and (3) omega-3 carboxylic acids (OM3CA), a mixture of OM3FAs in free fatty acid form, primarily EPA, DHA, and docosapentaenoic acid (Epanova®). At approved doses, all formulations substantially reduce triglyceride and very-low-density lipoprotein levels. DHA-containing formulations may also increase low-density lipoprotein cholesterol. However, this is not accompanied by increased non-high-density lipoprotein cholesterol, which is thought to provide a better indication of cardiovascular risk in this patient population. Proposed mechanisms of action of OM3FAs include inhibition of diacylglycerol acyltransferase, increased plasma lipoprotein lipase activity, decreased hepatic lipogenesis, and increased hepatic β-oxidation. OM3CA bioavailability (area under the plasma concentration-time curve from zero to the last measurable concentration) is up to 4-fold greater than that of OM3FA ethyl esters, and unlike ethyl esters, the absorption of OM3CA is not dependent on pancreatic lipase hydrolysis. All three formulations are well tolerated (the most common adverse events are gastrointestinal) and demonstrate a lack of drug-drug interactions with other lipid-lowering drugs, such as statins and fibrates. OM3FAs appear to be an effective treatment option for patients with severe hypertriglyceridemia

Granular Gym: High Performance Simulation for Robotic Tasks with Granular Materials

Granular materials are of critical interest to many robotic tasks in planetary science, construction, and manufacturing. However, the dynamics of granular materials are complex and often computationally very expensive to simulate. We propose a set of methodologies and a system for the fast simulation of granular materials on Graphics Processing Units (GPUs), and show that this simulation is fast enough for basic training with Reinforcement Learning algorithms, which currently require many dynamics samples to achieve acceptable performance. Our method models granular material dynamics using implicit timestepping methods for multibody rigid contacts, as well as algorithmic techniques for efficient parallel collision detection between pairs of particles and between particle and arbitrarily shaped rigid bodies, and programming techniques for minimizing warp divergence on Single-Instruction, Multiple-Thread (SIMT) chip architectures. We showcase our simulation system on several environments targeted toward robotic tasks, and release our simulator as an open-source tool

From Paper to Digital Maintenance With Electronic Signature

This research paper reviewed the impact of the implementation of digital maintenance records replacing paper documents in the commercial aviation through gains in efficiency and cost reduction in airplane transitions. Throughout the lifecycle of a commercial airplane, repairs are incorporated, components are replaced and maintenance tasks are accomplished every day, each of those activities generate records that need to be kept and reconciled. Lessors have strict contract terms that require operators to keep all required maintenance documents stored and available so that asset value is maintained, this process is done today mostly with paper documents and is very costly and difficult for the Industry to manage. The implementation of electronic records can help eliminate usage of up to 30,000 sheets of paper a year per aircraft, while increasing control and efficiency in the airline daily operation. Such approach would optimize processes reducing labor hours in the Maintenance Records Quality Assurance process by 50% or more. Other savings include reduction delays in the airplane transition and duplication of maintenance activities due to missing records. Besides the research, interviews were conducted with airline representatives and personnel from digital records software solution provider. Result of the study demonstrated that the Aviation Industry can greatly benefit from the migration to digital records, such benefits come from improving controls and reduce errors, remote reconciliation and audit, and decrease labor in quality assurance

Jogos eletrônicos: uma análise sobre as percepções de alunos e professores do Colégio de Aplicação

Os jogos eletrônicos estão cada vez mais comuns devido à popularização da internet nos últimos anos e vêm gerando diversas dúvidas sobre as suas aproximações com os temas violência, educação e lazer. Esta é uma pesquisa que teve como objetivo principal analisar as percepções de alunos e professores de uma escola de ensino básico e perceber os diferentes modos de interpretação de questões sobre jogos eletrônicos. Para atingir os objetivos propostos, foi realizado um questionário virtual distribuído para os alunos de francês do oitavo ano do Colégio de Aplicação da UFRGS (n=16) e para os professores do Projeto Pixel, etapa referente ao 8º e 9º anos escolares. Os resultados obtidos com a pesquisa indicaram que as diferenças entre as percepções de alunos e professores foram poucas. Verificou-se que os jogos eletrônicos estão cada vez sendo mais presentes e bem aceitos, inclusive por professores, podendo ser considerados instrumentos de educação

A novel multi-objective quantum particle swarm algorithm for suspension optimization

In this paper, a novel multi-objective archive-based Quantum Particle Optimizer (MOQPSO) is proposed for solving suspension optimization problems. The algorithm has been adapted from the well-knownsingle objectiveQPSOby substantialmodifications in the core equations and implementation of new multi-objectivemechanisms. The novel algorithmMOQPSO and the long-establishedNSGA-II andCOGA-II (Compressed-ObjectiveGenetic Algorithm with Convergence Detection) are compared. Two situations are considered in this paper: a simple half-car suspension model and a bus suspension model. The numerical model of the bus allows complex dynamic interactions not considered in previous studies. The suitability of the solution is evaluated based on vibration-related ISO Standards, and the efficiency of the proposed algorithm is tested by dominance comparison. For a specifically chosen Pareto front solution found by MOQPSO in the second case, the passengers and driver accelerations attenuated about 50% and 33%, respectively, regarding non-optimal suspension parameters. All solutions found by NSGA-II are dominated by those found byMOQPSO,which presented a Pareto front noticeably wider for the same number of objective function calls

miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database

Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways

BALL-SNP: combining genetic and structural information to identify candidate non-synonymous single nucleotide polymorphisms

Background: High-throughput genetic testing is increasingly applied in clinics. Next-Generation Sequencing (NGS) data analysis however still remains a great challenge. The interpretation of pathogenicity of single variants or combinations of variants is crucial to provide accurate diagnostic information or guide therapies. Methods: To facilitate the interpretation of variants and the selection of candidate non-synonymous polymorphisms (nsSNPs) for further clinical studies, we developed BALL-SNP. Starting from genetic variants in variant call format (VCF) files or tabular input, our tool, first, visualizes the three-dimensional (3D) structure of the respective proteins from the Protein Data Bank (PDB) and highlights mutated residues, automatically. Second, a hierarchical bottom up clustering on the nsSNPs within the 3D structure is performed to identify nsSNPs, which are close to each other. The modular and flexible implementation allows for straightforward integration of different databases for pathogenic and benign variants, but also enables the integration of pathogenicity prediction tools. The collected background information of all variants is presented below the 3D structure in an easily interpretable table format. Results: First, we integrated different data resources into BALL-SNP, including databases containing information on genetic variants such as ClinVar or HUMSAVAR; third party tools that predict stability or pathogenicity in silico such as I-Mutant2.0; and additional information derived from the 3D structure such as a prediction of binding pockets. We then explored the applicability of BALL-SNP on the example of patients suffering from cardiomyopathies. Here, the analysis highlighted accumulation of variations in the genes JUP, VCL, and SMYD2. Conclusion: Software solutions for analyzing high-throughput genomics data are important to support diagnosis and therapy selection. Our tool BALL-SNP, which is freely available at http://www.ccb.uni-saarland.de/BALL-SNP , combines genetic information with an easily interpretable and interactive, graphical representation of amino acid changes in proteins. Thereby relevant information from databases and computational tools is presented. Beyond this, proximity to functional sites or accumulations of mutations with a potential collective effect can be discovered