Dynamical Characterization and Stabilization of Large Gravity-Tractor Designs

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76167/1/AIAA-32554-693.pd

Toward a Socialism for the Future, in the Wake of the Demise of the Socialism of the Past

http://deepblue.lib.umich.edu/bitstream/2027.42/51230/1/464.pd

Republicanism and the political economy of democracy

Europe is experiencing rapidly accelerating poverty and social exclusion, following half a decade of financial crisis and austerity politics. The key problem behind Europe's malaise, in our view, is the economic disenfranchisement of large parts of its population in the winner-takes-all-society. This article proposes that we examine the contribution of republican political theory as a distinctive approach that provides us with the conceptual and normative resources to reclaim what we call the political economy of democracy, the constellation of political and economic institutions aimed at promoting broad economic sovereignty and individuals' capacities to govern their own lives. This article identifies three key ideas that together constitute a distinctively republican approach to political economy: (1) establish an economic floor; (2) impose an economic ceiling to counter excess economic inequality; and (3) democratize the governance and regulation of the main economic institutions

Analysis of CC chemokine and chemokine receptor expression in solid ovarian tumours

To understand the chemokine network in a tissue, both chemokine and chemokine receptor expression should be studied. Human epithelial ovarian tumours express a range of chemokines but little is known about the expression and localisation of chemokine receptors. With the aim of understanding chemokine action in this cancer, we investigated receptors for CC–chemokines and their ligands in 25 biopsies of human ovarian cancer. CC–chemokine receptor mRNA was generally absent from solid tumours, the exception being CCR1 which was detected in samples from 75% of patients. CCR1 mRNA localised to macrophages and lymphocytes and there was a correlation between numbers of CD8+ and CCR1 expressing cells (P = 0.031). mRNA for 6 CC-chemokines was expressed in a majority of tumour samples. In a monocytic cell line in vitro, we found that CCR1 mRNA expression was increased 5-fold by hypoxia. We suggest that the CC-chemokine network in ovarian cancer is controlled at the level of CC-chemokine receptors and this may account for the phenotypes of infiltrating cells found in these tumours. The leukocyte infiltrate may contribute to tumour growth and spread by providing growth survival factors and matrix metalloproteases. Thus, CCR1 may be a novel therapeutic target in ovarian cancer. http://www.bjcancer.com © 2001 Cancer Research Campaignhttp://www.bjcancer.co

Chemokines and their role in airway hyper-reactivity

Airway hyper-reactivity is a characteristic feature of many inflammatory lung diseases and is defined as an exaggerated degree of airway narrowing. Chemokines and their receptors are involved in several pathological processes that are believed to contribute to airway hyper-responsiveness, including recruitment and activation of inflammatory cells, collagen deposition and airway wall remodeling. These proteins are therefore thought to represent important therapeutic targets in the treatment of airway hyper-responsiveness. This review highlights the processes thought to be involved in airway hyper-responsiveness in allergic asthma, and the role of chemokines in these processes. Overall, the application of chemokines to the prevention or treatment of airway hyper-reactivity has tremendous potential

Mapping the Relationship Among Political Ideology, CSR Mindset, and CSR Strategy: A Contingency Perspective Applied to Chinese Managers

The literature on antecedents of corporate social responsibility (CSR) strategies of firms has been predominately content driven. Informed by the managerial sense-making process perspective, we develop a contingency theoretical framework explaining how political ideology of managers affects the choice of CSR strategy for their firms through their CSR mindset. We also explain to what extent the outcome of this process is shaped by the firm’s internal institutional arrangements and external factors impacting on the firm. We develop and test several hypotheses using data collected from 129 Chinese managers. The results show that managers with a stronger socialist ideology are likely to develop a mindset favouring CSR, which induces the adoption of a proactive CSR strategy. The CSR mindset mediates the link between socialist ideology and CSR strategy. The strength of the relationship between the CSR mindset and the choice of CSR strategy is moderated by customer response to CSR, industry competition, the role of government, and CSR-related managerial incentives

Variational autoencoders learn transferrable representations of metabolomics data.

Dimensionality reduction approaches are commonly used for the deconvolution of high-dimensional metabolomics datasets into underlying core metabolic processes. However, current state-of-the-art methods are widely incapable of detecting nonlinearities in metabolomics data. Variational Autoencoders (VAEs) are a deep learning method designed to learn nonlinear latent representations which generalize to unseen data. Here, we trained a VAE on a large-scale metabolomics population cohort of human blood samples consisting of over 4500 individuals. We analyzed the pathway composition of the latent space using a global feature importance score, which demonstrated that latent dimensions represent distinct cellular processes. To demonstrate model generalizability, we generated latent representations of unseen metabolomics datasets on type 2 diabetes, acute myeloid leukemia, and schizophrenia and found significant correlations with clinical patient groups. Notably, the VAE representations showed stronger effects than latent dimensions derived by linear and non-linear principal component analysis. Taken together, we demonstrate that the VAE is a powerful method that learns biologically meaningful, nonlinear, and transferrable latent representations of metabolomics data