Free Expression in Arts Funding

The result of almost two years of research, this report surveys free expression policies among state and local arts agencies, including procedures for anticipating and handling controversy. Its purpose is to provide the arts community, as well as others interested in censorship or cultural policy, with solid research that will enable grant-making agencies to take a principled stand on artistic freedom without alienating their audiences or losing their funding. The report includes candid interviews with agency officials regarding funding disputes, political accountability, and most important, ways of reaching out to communities and opening up dialogue about challenging or provocative art. The report also contains extensive background on the "funding wars" of the 1990s, illustrations, and two appendices summarizing free expression statements and policies among all state arts agencies and a random sample of local agencies.As the Executive Summary points out, despite America's recent history of attacks on controversial art, artistic freedom in the context of public funding remains a critical issue. The ability to make challenging art that can explore all facets of the human condition, including unpleasant ones, is essential to a vibrant culture and a healthy democracy. Neither private philanthropy nor the mass media conglomerates that dominate commercial entertainment can be counted upon to support the give-and-take of diverse viewpoints, reflected through literature, theater, music, film, and other visual art, or to provide visibility for the multi-layered, varied, and inventive cultures of America

Pattern recognition with a magnon-scattering reservoir

Magnons are elementary excitations in magnetic materials and undergo nonlinear multimode scattering processes at large input powers. In experiments and simulations, we show that the interaction between magnon modes of a confined magnetic vortex can be harnessed for pattern recognition. We study the magnetic response to signals comprising sine wave pulses with frequencies corresponding to radial mode excitations. Three-magnon scattering results in the excitation of different azimuthal modes, whose amplitudes depend strongly on the input sequences. We show that recognition rates above 95\% can be attained for four-symbol sequences using the scattered modes, with strong performance maintained with the presence of amplitude noise in the inputs

Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis

Purpose: To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim was to predict individual risks for developing CRF.Methods: Two pre-existing datasets were used. The Nivel-Primary Care Database and the Netherlands Cancer Registry (NCR) formed the Primary Secondary Cancer Care Registry (PSCCR). NCR data with Patient Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship (PROFILES) data resulted in the PSCCR-PROFILES dataset. Predictors were patient, tumor and treatment characteristics, and pre-diagnosis health. Fatigue was GP-reported (PSCCR) or patient-reported (PSCCR-PROFILES). Machine learning models were developed, and performances compared using the C-statistic.Results: In PSCCR, 2224/12813 (17%) experienced fatigue up to 7.6 ± 4.4 years after diagnosis. In PSCCR-PROFILES, 254 (65%) of 390 patients reported fatigue 3.4 ± 1.4 years after diagnosis. For both, models predicted fatigue poorly with best C-statistics of 0.561 ± 0.006 (PSCCR) and 0.669 ± 0.040 (PSCCR-PROFILES).Conclusion: Fatigue (GP-reported or patient-reported) could not be predicted accurately using available data of the PSCCR and PSCCR-PROFILES datasets.Implications for Cancer Survivors: CRF is a common but underreported problem after breast cancer. We aimed to develop a model that could identify individuals with a high risk of developing CRF, ideally to help them prevent (chronic) CRF. As our models had poor predictive abilities, they cannot be used for this purpose yet. Adding patient-reported data as predictor could lead to improved results. Until then, awareness for CRF stays crucial

Factors associated with the appearance of gingival papillae

Chow YC, Eber RM, Tsao Y-P, Shotwell JL, Wang H-L. Factors associated with the appearance of gingival papillae. J Clin Periodontol 2010; 37: 719-727 doi: . The purpose of this study was to evaluate factors associated with the fill of inter-dental spaces by gingival papillae.Ninety-six adult subjects were evaluated. Papilla score (PS), tooth form/shape, interproximal contact length and gingival thickness were recorded for 672 maxillary anterior and first pre-molar interproximal sites. Statistical analyses included a non-parametric χ 2 test, anova , the Mixed Procedure for SAS and Pearson's correlation coefficient ( r ).Papilla deficiency was more frequent in older subjects ( p <0.05), as papilla height decreased 0.012 mm with each year of increasing age ( p <0.05). Competent papillae (complete fill inter-dentally) were associated with: (1) crown width: length ges;0.87; (2) proximal contact length ges;2.8 mm; (3) bone crest-contact point ≤5 mm; and (4) interproximal gingival tissue thickness ges;1.5 mm. Gingival thickness correlated negatively with PS ( r =−0.37 to −0.54) and positively with tissue height ( r =0.23–0.43). Tooth form (i.e. crown width to length ratio) correlated negatively with PS ( r =−0.37 to −0.61). Other parameters failed to show any significant effects.Gingival papilla appearance was associated significantly with subject age, tooth form/shape, proximal contact length, crestal bone height and interproximal gingival thickness.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79213/1/j.1600-051X.2010.01594.x.pd

Dynamically Correct Formulations of the Linearised Navier-Stokes Equations

Motivated by the need to efficiently obtain low-order models of fluid flows around complex geometries for the purpose of feedback control system design, this paper considers the effect on system dynamics of basing plant models on different formulations of the linearised Navier-Stokes equations. We consider the dynamics of a single computational node formed by spatial discretisation of the governing equations in both primitive variables (momentum equation & continuity equation) and pressure Poisson equation (PPE) formulations. This reveals fundamental numerical differences at the nodal level, whose effects on the system dynamics at the full system level are exemplified by considering the corresponding formulations of a two-dimensional (2D) channel flow, subjected to a variety of different boundary conditions

MAPping out distribution routes for kinesin couriers

In the crowded environment of eukaryotic cells, diffusion is an inefficient distribution mechanism for cellular components. Long-distance active transport is required and is performed by molecular motors including kinesins. Furthermore, in highly polarized, compartmentalized and plastic cells such as neurons, regulatory mechanisms are required to ensure appropriate spatio-temporal delivery of neuronal components. The kinesin machinery has diversified into a large number of kinesin motor proteins as well as adaptor proteins that are associated with subsets of cargo. However, many mechanisms contribute to the correct delivery of these cargos to their target domains. One mechanism is through motor recognition of subdomain-specific microtubule (MT) tracks, sign-posted by different tubulin isoforms, tubulin post-translational modifications (PTMs), tubulin GTPase activity and MT associated proteins (MAPs). With neurons as a model system, a critical review of these regulatory mechanisms is presented here, with particular focus on the emerging contribution of compartmentalised MAPs. Overall, we conclude that – especially for axonal cargo – alterations to the MT track can influence transport, although in vivo, it is likely that multiple track-based effects act synergistically to ensure accurate cargo distribution

Results from a Large, Multinational Sample Using the Childhood Trauma Questionnaire

Childhood maltreatment has diverse, lifelong impact on morbidity and mortality. The Childhood Trauma Questionnaire (CTQ) is one of the most commonly used scales to assess and quantify these experiences and their impact. Curiously, despite very widespread use of the CTQ, scores on its Minimization-Denial (MD) subscale—originally designed to assess a positive response bias—are rarely reported. Hence, little is known about this measure. If response biases are either common or consequential, current practices of ignoring the MD scale deserve revision. Therewith, we designed a study to investigate 3 aspects of minimization, as defined by the CTQ’s MD scale: 1) its prevalence; 2) its latent structure; and finally 3) whether minimization moderates the CTQ’s discriminative validity in terms of distinguishing between psychiatric patients and community volunteers. Archival, item-level CTQ data from 24 multinational samples were combined for a total of 19,652 participants. Analyses indicated: 1) minimization is common; 2) minimization functions as a continuous construct; and 3) high MD scores attenuate the ability of the CTQ to distinguish between psychiatric patients and community volunteers. Overall, results suggest that a minimizing response bias—as detected by the MD subscale—has a small but significant moderating effect on the CTQ’s discriminative validity. Results also may suggest that some prior analyses of maltreatment rates or the effects of early maltreatment that have used the CTQ may have underestimated its incidence and impact. We caution researchers and clinicians about the widespread practice of using the CTQ without the MD or collecting MD data but failing to assess and control for its effects on outcomes or dependent variables

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts