How the Linguistic Styles of Donald Trump and Joe Biden Reflect Different Forms of Power

Can theories of power be used to explain differences in the linguistic styles of Donald Trump and Joe Biden? We argue that the two candidates possess and use different forms of power—and that this is associated with typical language patterns. Based on their personal history, news reports, and empirical studies, we expect that Trump’s approach to power is characterized by coercive power forms and Biden’s by collaborative power forms. Using several LIWC categories and the moral foundations dictionary, we analyzed over 500 speeches and 15,000 tweets made during the 2020 election battle. Biden’s speeches can be described as analytical and frequently relating to moral values, whereas Trump’s speeches were characterized by a positive emotional tone. In tweets, Biden used more social words and words related to virtue, honesty, and achievement than Trump did. Trump’s coercive power and Biden’s collaborative power were more observable in tweets than speeches, which may reflect the fact that tweets are more spontaneous than speeches

An integrated System Development Approach for Mobile Machinery in consistence with Functional Safety Requirements

The article identifies the challenges during the system and specifically the software development process for safety critical electro-hydraulic control systems by using the example of the hydrostatic driveline with a four speed transmission of a feeder mixer. An optimized development approach for mobile machinery has to fulfill all the requirements according to the Machinery Directive 2006/42/EC, considering functional safety, documentation and testing requirements from the beginning and throughout the entire machine life cycle. The functionality of the drive line control could be verified in advance of the availability of a prototype by using a “software-in-the-loop” development approach, based on a MATLAB/SIMULINK model of the drive line in connection with the embedded software

SMAuC -- The Scientific Multi-Authorship Corpus

With an ever-growing number of new publications each day, scientific writing poses an interesting domain for authorship analysis of both single-author and multi-author documents. Unfortunately, most existing corpora lack either material from the science domain or the required metadata. Hence, we present SMAuC, a new metadata-rich corpus designed specifically for authorship analysis in scientific writing. With more than three million publications from various scientific disciplines, SMAuC is the largest openly available corpus for authorship analysis to date. It combines a wide and diverse range of scientific texts from the humanities and natural sciences with rich and curated metadata, including unique and carefully disambiguated author IDs. We hope SMAuC will contribute significantly to advancing the field of authorship analysis in the science domain

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

<p>Abstract</p> <p>Background</p> <p>The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches.</p> <p>Results</p> <p>We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at <url>http://genome.tugraz.at/maspectras</url></p> <p>Conclusion</p> <p>Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community.</p

Leaf Trait-Environment Relationships in a Subtropical Broadleaved Forest in South-East China

Although trait analyses have become more important in community ecology, trait-environment correlations have rarely been studied along successional gradients. We asked which environmental variables had the strongest impact on intraspecific and interspecific trait variation in the community and which traits were most responsive to the environment. We established a series of plots in a secondary forest in the Chinese subtropics, stratified by successional stages that were defined by the time elapsed since the last logging activities. On a total of 27 plots all woody plants were recorded and a set of individuals of every species was analysed for leaf traits, resulting in a trait matrix of 26 leaf traits for 122 species. A Fourth Corner Analysis revealed that the mean values of many leaf traits were tightly related to the successional gradient. Most shifts in traits followed the leaf economics spectrum with decreasing specific leaf area and leaf nutrient contents with successional time. Beside succession, few additional environmental variables resulted in significant trait relationships, such as soil moisture and soil C and N content as well as topographical variables. Not all traits were related to the leaf economics spectrum, and thus, to the successional gradient, such as stomata size and density. By comparing different permutation models in the Fourth Corner Analysis, we found that the trait-environment link was based more on the association of species with the environment than of the communities with species traits. The strong species-environment association was brought about by a clear gradient in species composition along the succession series, while communities were not well differentiated in mean trait composition. In contrast, intraspecific trait variation did not show close environmental relationships. The study confirmed the role of environmental trait filtering in subtropical forests, with traits associated with the leaf economics spectrum being the most responsive ones

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Abstract: Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Variant annotation was supported by software resources provided via the Caché Campus program of the InterSystems GmbH to Alexander Teumer

Fungal community composition and metabolism under elevated CO 2 and O 3

Atmospheric CO 2 and O 3 concentrations are increasing due to human activity and both trace gases have the potential to alter C cycling in forest ecosystems. Because soil microorganisms depend on plant litter as a source of energy for metabolism, changes in the amount or the biochemistry of plant litter produced under elevated CO 2 and O 3 could alter microbial community function and composition. Previously, we have observed that elevated CO 2 increased the microbial metabolism of cellulose and chitin, whereas elevated O 3 dampened this response. We hypothesized that this change in metabolism under CO 2 and O 3 enrichment would be accompanied by a concomitant change in fungal community composition. We tested our hypothesis at the free-air CO 2 and O 3 enrichment (FACE) experiment at Rhinelander, Wisconsin, in which Populus tremuloides , Betula papyrifera , and Acer saccharum were grown under factorial CO 2 and O 3 treatments. We employed extracellular enzyme analysis to assay microbial metabolism, phospholipid fatty acid (PLFA) analysis to determine changes in microbial community composition, and polymerase chain reaction–denaturing gradient gel electrophoresis (PCR–DGGE) to analyze the fungal community composition. The activities of 1,4-β-glucosidase (+37%) and 1,4,-β- N -acetylglucosaminidase (+84%) were significantly increased under elevated CO 2 , whereas 1,4-β-glucosidase activity (−25%) was significantly suppressed by elevated O 3 . There was no significant main effect of elevated CO 2 or O 3 on fungal relative abundance, as measured by PLFA. We identified 39 fungal taxonomic units from soil using DGGE, and found that O 3 enrichment significantly altered fungal community composition. We conclude that fungal metabolism is altered under elevated CO 2 and O 3 , and that there was a concomitant change in fungal community composition under elevated O 3 . Thus, changes in plant inputs to soil under elevated CO 2 and O 3 can propagate through the microbial food web to alter the cycling of C in soil.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47711/1/442_2005_Article_249.pd

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms