Electro-Hydraulic Variable-Speed Drive Networks—Idea, Perspectives, and Energy Saving Potentials

Electro-hydraulic differential cylinder drives with variable-speed displacement units as their central transmission element are subject to an increasing focus in both industry and academia. A main reason is the potential for substantial efficiency increases due to avoidance of throttling of the main flows. Research contributions have mainly been focusing on appropriate compensation of volume asymmetry and the development of standalone self-contained and compact solutions, with all necessary functions onboard. However, as many hydraulic actuator systems encompass multiple cylinders, such approaches may not be the most feasible ones with respect to efficiency or commercial feasibility. This article presents the idea of multi-cylinder drives, characterized by electrically and hydraulically interconnected variable-speed displacement units essentially allowing for completely avoiding throttle elements, while allowing for hydraulic and electric power sharing as well as the sharing of auxiliary functions and fluid reservoir. With drive topologies taking offset in communication theory, the concept of electro-hydraulic variable-speed drive networks is introduced. Three different drive networks are designed for an example application, including component sizing and controls in order to demonstrate their potentials. It is found that such drive networks may provide simple physical designs with few building blocks and increased energy efficiencies compared to standalone drives, while exhibiting excellent dynamic properties and control performance

Testing Conditional Independence via Quantile Regression Based Partial Copulas

The partial copula provides a method for describing the dependence between two random variables $X$ and $Y$ conditional on a third random vector $Z$ in terms of nonparametric residuals $U_1$ and $U_2$. This paper develops a nonparametric test for conditional independence by combining the partial copula with a quantile regression based method for estimating the nonparametric residuals. We consider a test statistic based on generalized correlation between $U_1$ and $U_2$ and derive its large sample properties under consistency assumptions on the quantile regression procedure. We demonstrate through a simulation study that the resulting test is sound under complicated data generating distributions. Moreover, in the examples considered the test is competitive to other state-of-the-art conditional independence tests in terms of level and power, and it has superior power in cases with conditional variance heterogeneity of $X$ and $Y$ given $Z$

Analysing Political Biases in Danish Newspapers Using Sentiment Analysis

Traditionally, the evaluation of political biases in Danish newspapers has been carried out throughhighly subjective methods. The conventional approach has been surveys asking samples of thepopulation to place various newspapers on the political spectrum, coupled with analysing votinghabits of the newspapers’ readers (Hjarvard, 2007). This paper seeks to examine whether it ispossible to use sentiment analysis to objectively assess political biases in Danish newspapers. Byusing the sentiment dictionary AFINN (Nielsen et al., 2011), the mean sentiment scores for 360articles was calculated. The articles were published in the Danish newspapers Berlingske andInformation and were all regarding the political parties Alternativet and Liberal Alliance. Asignificant interaction effect between the parties and newspapers was discovered. This effect wasmainly driven by Information’s coverage of the two parties. Moreover, Berlingske was found topublish a disproportionately greater number of articles concerning Liberal Alliance thanAlternativet. Based on these findings, an integration of sentiment analysis into the evaluation ofbiases in news outlets is proposed. Furthermore, future studies are suggested to construct datasetsfor evaluation of AFINN on news and to utilize web-mining methods to gather greater amounts ofdata in order to analyse more parties and newspapers

TextDescriptives: A Python package for calculating a large variety of metrics from text

TextDescriptives is a Python package for calculating a large variety of metrics from text. It is built on top of spaCy and can be easily integrated into existing workflows. The package has already been used for analysing the linguistic stability of clinical texts, creating features for predicting neuropsychiatric conditions, and analysing linguistic goals of primary school students. This paper describes the package and its features.Comment: 3 pages, 0 figures. Submitted to Journal of Open Source Softwar

Gender Bias in Language Comprehension: Exploring the Role of Gender Bias in Adjectives of the Danish Language

Humans depend on top-down processes in their understanding of language. Previous studies have shown how gender biases are apparent in human communication and have suggested that these come from previous experiences that lay the grounds for a heuristical approach to language comprehension. In this paper, we suggest that there is a gender bias in some of the most common Danish adjectives. Furthermore, we indicate that this gender bias can be used to alter the way in which Danish speakers understand seemingly gender-neutral, syntactical subjects. This is done through statistical analyses made on the basis of results from online questionnaires. We discuss our results with a starting point in literature about social role theory and gender bias and use this as grounds for proposing that Danish speakers are heuristically limited by gender stereotypes when assessing the gender of a gender-neutral, grammatical subject in written Danish.Humans depend on top-down processes in their understanding of language. Previous studies have shown how gender biases are apparent in human communication and have suggested that these come from previous experiences that lay the grounds for a heuristical approach to language comprehension. In this paper, we suggest that there is a gender bias in some of the most common Danish adjectives. Furthermore, we indicate that this gender bias can be used to alter the way in which Danish speakers understand seemingly gender-neutral, syntactical subjects. This is done through statistical analyses made on the basis of results from online questionnaires. We discuss our results with a starting point in literature about social role theory and gender bias and use this as grounds for proposing that Danish speakers are heuristically limited by gender stereotypes when assessing the gender of a gender-neutral, grammatical subject in written Danish