70 research outputs found
Flat control of industrial robotic manipulators
Published ArticleA new approach to tracking control of industrial robot manipulators is presented in this paper. The highly
coupled nonlinear dynamics of a six degrees of freedom (6-DOF) serial robot is decoupled by expressing
its variables as a function of a flat output and a finite number of its derivatives. Hence the derivation of the
flat output for the 6-DOF robot is presented. With the flat output, trajectories for each of the generalized
coordinates are easily designed and open loop control is made possible. Using MATLAB/Simulink Sfunctions
combined with the differential flatness property of the robot, trajectory tracking is carried out
in closed loop by using a linear flat controller. The merit of this approach reduces the computational
complexity of the robot dynamics by allowing online computation of a high order system at a lower
computational cost. Using the same processor, the run time for tracking arbitrary trajectories is reduced
significantly to about 10 s as compared to 30 min in the original study (Hoifodt, 2011). The design is taken
further by including a Jacobian transformation for tracking of trajectories in cartesian space. Simulations
using the ABB IRB140 industrial robot with full dynamics are used to validate the study
Does narrative writing instruction enhance the benefits of expressive writing?
We examined whether instructing participants to write in a narrative fashion about stressful life events would produce superior physical and psychological health benefits relative to standard expressive writing instructions that do not specify the essay's structure. Undergraduates (N=101) were randomly assigned to engage in two, 20-minute narrative writing, standard expressive writing, or control writing tasks. Follow-up data were obtained one month later. The essays of the narrative writing group evidenced higher levels of narrative structure than did those of the expressive writing group. Greater narrative structure was associated with mental health gains, and self-rated emotionality of the essays was associated with lesser perceived stress at follow-up. In addition, the narrative and expressive writing groups reported lower levels of perceived stress and depressive symptoms relative to controls but did not differ from each other with regard to these outcomes. Health care utilization at follow-up did not vary by group assignment. Findings suggest that both emotional expression and narrative structure may be key factors underlying expressive writing's mental health benefits. Results also suggest that, among college students, instruction in narrative formation does not increase the positive effects of expressive writing relative to standard expressive writing instructions
Gastroesophageal reflux GWAS identifies risk loci that also associate with subsequent severe esophageal diseases
Funder: The Swedish Esophageal Cancer Study was funded by grants (R01 CA57947-03) from the National Cancer Institute he California Tobacco Related Research Program (3RT-0122; and; 10RT-0251) Marit Peterson Fund for Melanoma Research. CIDR is supported by contract HHSN268200782096CAbstract: Gastroesophageal reflux disease (GERD) is caused by gastric acid entering the esophagus. GERD has high prevalence and is the major risk factor for Barrett’s esophagus (BE) and esophageal adenocarcinoma (EA). We conduct a large GERD GWAS meta-analysis (80,265 cases, 305,011 controls), identifying 25 independent genome-wide significant loci for GERD. Several of the implicated genes are existing or putative drug targets. Loci discovery is greatest with a broad GERD definition (including cases defined by self-report or medication data). Further, 91% of the GERD risk-increasing alleles also increase BE and/or EA risk, greatly expanding gene discovery for these traits. Our results map genes for GERD and related traits and uncover potential new drug targets for these conditions
Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use
Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders 1 . They are heritable 2,3 and etiologically related 4,5 behaviors that have been resistant to gene discovery efforts 6–11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures
Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies
Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)
A numerical investigation of wind speed effects on lake-effect storms
Observations of lake-effect storms that occur over the Great Lakes region during late autumn and winter indicate a high sensitivity to ambient wind speed and direction. In this paper, a two-dimensional version of the Penn State University/National Center for Atmospheric Research (PSU/NCAR) model is used to investigate the wind speed effects on lake-effect snowstorms that occur over the Great Lakes region.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42510/1/10546_2004_Article_BF00708966.pd
Recommended from our members
Ecological effects of alternative fuel-reduction treatments: highlights of the National Fire and Fire Surrogate study (FFS)
The 12-site National Fire and Fire Surrogate study (FFS) was a multivariate experiment that evaluated ecological consequences of alternative fuel-reduction treatments in seasonally dry forests of the US. Each site was a replicated experiment with a common design that compared an un-manipulated control, prescribed fire, mechanical and mechanical + fire treatments. Variables within the vegetation, fuelbed, forest floor and soil, bark beetles, tree diseases and wildlife were measured in 10-ha stands, and ecological response was compared among treatments at the site level, and across sites, to better understand the influence of differential site conditions. For most sites, treated stands were predicted to be more resilient to wildfire if it occurred shortly after treatment, but for most ecological variables, short-term response to treatments was subtle and transient. Strong site-specificity was observed in the response of most ecosystem variables, suggesting that practitioners employ adaptive management at the local scale. Because ecosystem components were tightly linked, adaptive management would need to include monitoring of a carefully chosen set of key variables. Mechanical treatments did not serve as surrogates for fire for most variables, suggesting that fire be maintained whenever possible. Restoration to pre-settlement conditions will require repeated treatments over time, with eastern forests requiring more frequent applications.Keywords: Oak, Prescribed fire, Frequent fire regimes, Pine, Mechanical treatment, Forest thinning, Dry forest management, Seasonally dry forest
Identification of common genetic risk variants for autism spectrum disorder
Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD
Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals
We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57
- …