ESTIMATION OF WHEAT ACREAGE RESPONSE FUNCTIONS FOR THE NORTHWEST

Acreage response functions for wheat are fitted to aggregate data and pooled time-series and cross-sectional data for the Northwest. It was hypothesized that the pooled data approach provides a useful alternative to using aggregate data since it requires fewer timer-series observations for reliable parameter estimation and it does not require the assumption of constant acreage response elasticities throughout the region. The results of this study verify this hypothesis as well as indicate that regional response elasticities for Northwest wheat acreage may differ greatly from national estimates.Crop Production/Industries,

What Are the Predictors of System-Wide Trust Loss in Transportation Automation?

Prior research has examined how individuals place trust in single (e.g., Meyer, 2001, 2004) and multiple (e.g., Geels-Blair, Rice, & Schwark, 2013) automated devices when one fails. This has shown that participants are influenced by system-wide trust (SWT). What has been missing is an investigation into what types of people succumb to SWT effects. The current study attempts to replicate SWT findings and identify possible predictors of individuals likely to be influenced by SWT. The findings did demonstrate a replication of SWT. The study found that ‘‘feelings of negativity when automated devices fail’’ was a significant predictor of SWT theory

Gut inflammation provides a respiratory electron acceptor for Salmonella.

Salmonella enterica serotype Typhimurium (S. Typhimurium) causes acute gut inflammation by using its virulence factors to invade the intestinal epithelium and survive in mucosal macrophages. The inflammatory response enhances the transmission success of S. Typhimurium by promoting its outgrowth in the gut lumen through unknown mechanisms. Here we show that reactive oxygen species generated during inflammation react with endogenous, luminal sulphur compounds (thiosulphate) to form a new respiratory electron acceptor, tetrathionate. The genes conferring the ability to use tetrathionate as an electron acceptor produce a growth advantage for S. Typhimurium over the competing microbiota in the lumen of the inflamed gut. We conclude that S. Typhimurium virulence factors induce host-driven production of a new electron acceptor that allows the pathogen to use respiration to compete with fermenting gut microbes. Thus the ability to trigger intestinal inflammation is crucial for the biology of this diarrhoeal pathogen

Creation of Two Valid Scales: Willingness to Fly in an Aircraft and Willingness to Pilot an Aircraft

The purpose of the current study was to develop two scales that could be used concurrently or independently to measure passenger willingness to fly (WTF), and aviator willingness to pilot (WTP), respectively. This is especially useful to determine challenges involving acceptance of new aviation technology for both pilots and passengers. There were five stages in developing the WTF scale for passengers, following Hinkin’s scale development process. Cronbach’s Alpha and Guttmann’s Split Half tests were used to confirm high internal consistency and reliability, while factor analysis was used to confirm construct validity. The scale was tested in order to confirm sensitivity to differences in actual participant willingness to fly. After developing the WTF scale for passengers, researchers made minor lexical adjustments and created the WTP scale, calculating Cronbach’s Alpha, Guttmann’s Split Half test, and factor analysis; thus, ensuring high internal consistency, reliability and validity. These two scales may help provide researchers with a better applied understanding of applications within the aviation and consumer perceptions literature and also assist with pilot training and acceptance of new aviation technology

Posttranscriptional regulation of PARG mRNA by HuR facilitates DNA repair and resistance to PARP inhibitors

The majority of pancreatic ductal adenocarcinomas (PDAC) rely on the mRNA stability factor HuR (ELAV-L1) to drive cancer growth and progression. Here, we show that CRISPR-Cas9–mediated silencing of the HuR locus increases the relative sensitivity of PDAC cells to PARP inhibitors (PARPi). PDAC cells treated with PARPi stimulated translocation of HuR from the nucleus to the cytoplasm, specifically promoting stabilization of a new target, poly (ADP-ribose) glycohydrolase (PARG) mRNA, by binding a unique sequence embedded in its 30 untranslated region. HuR-dependent upregulation of PARG expression facilitated DNA repair via hydrolysis of polyADP-ribose on related repair proteins. Accordingly, strategies to inhibit HuR directly promoted DNA damage accumulation, inefficient PAR removal, and persistent PARP-1 residency on chromatin (PARP-1 trapping). Immunoprecipitation assays demonstrated that the PARP-1 protein binds and posttranslationally modifies HuR in PARPi-treated PDAC cells. In a mouse xenograft model of human PDAC, PARPi monotherapy combined with targeted silencing of HuR significantly reduced tumor growth compared with PARPi therapy alone. Our results highlight the HuR–PARG axis as an opportunity to enhance PARPi-based therapies. ©2017 AACR

Toe clearance when walking in people with unilateral transtibial amputation: Effects of passive hydraulic ankle

YesMost clinically available prosthetic feet have a rigid attachment or incorporate an “ankle” device allowing elastic articulation during stance, with the foot returning to a “neutral” position at toe-off. We investigated whether using a foot with a hydraulically controlled articulating ankle that allows the foot to be relatively dorsiflexed at toe-off and throughout swing would increase minimum toe clearance (MTC). Twenty-one people with unilateral transtibial amputation completed overground walking trials using their habitual prosthetic foot with rigid or elastic articulating attachment and a foot with a hydraulic ankle attachment (hyA-F). MTC and other kinematic variables were assessed across multiple trials. When using the hyA-F, mean MTC increased on both limbs (p= 0.03). On the prosthetic limb this was partly due to the device being in its fully dorsiflexed position at toe-off, which reduced the “toes down” foot angle throughout swing (p = 0.01). Walking speed also increased when using the hyA-F (p = 0.001) and was associated with greater swing-limb hip flexion on the prosthetic side (p = 0.04), which may have contributed to the increase in mean MTC. Variability in MTC increased on the prosthetic side when using the hyA-F (p = 0.03), but this did not increase risk of tripping

Curvature-direction measures of self-similar sets

We obtain fractal Lipschitz-Killing curvature-direction measures for a large class of self-similar sets F in R^d. Such measures jointly describe the distribution of normal vectors and localize curvature by analogues of the higher order mean curvatures of differentiable submanifolds. They decouple as independent products of the unit Hausdorff measure on F and a self-similar fibre measure on the sphere, which can be computed by an integral formula. The corresponding local density approach uses an ergodic dynamical system formed by extending the code space shift by a subgroup of the orthogonal group. We then give a remarkably simple proof for the resulting measure version under minimal assumptions.Comment: 17 pages, 2 figures. Update for author's name chang

The impact of uncertainties in ice sheet dynamics on sea-level allowances at tide gauge locations

Sea level is projected to rise in the coming centuries as a result of a changing climate. One of the major uncertainties is the projected contribution of the ice sheets in Greenland and Antarctica to sea-level rise (SLR). Here, we study the impact of different shapes of uncertainty distributions of the ice sheets on so-called sea-level allowances. An allowance indicates the height a coastal structure needs to be elevated to keep the same frequency and likelihood of sea-level extremes under a projected amount of mean SLR. Allowances are always larger than the projected SLR. Their magnitude depends on several factors, such as projection uncertainty and the typical variability of the extreme events at a location. Our results show that allowances increase significantly for ice sheet dynamics uncertainty distributions that are more skewed (more than twice, compared to Gaussian uncertainty distributions), due to the increased probability of a much larger ice sheet contribution to SLR. The allowances are largest in regions where a relatively small observed variability in the extremes is paired with relatively large magnitude and/or large uncertainty in the projected SLR, typically around the equator. Under the RCP8.5 (Representative Concentration Pathway) projections of SLR, the likelihood of extremes increases more than a factor 104 at more than 50-87% of the tide gauges

Canonical Correlation Analysis and Partial Least Squares for identifying brain-behaviour associations: a tutorial and a comparative study

Canonical Correlation Analysis (CCA) and Partial Least Squares (PLS) are powerful multivariate methods for capturing associations across two modalities of data (e.g., brain and behaviour). However, when the sample size is similar or smaller than the number of variables in the data, CCA and PLS models may overfit, i.e., find spurious associations that generalise poorly to new data. Dimensionality reduction and regularized extensions of CCA and PLS have been proposed to address this problem, yet most studies using these approaches have some limitations. This work gives a theoretical and practical introduction into the most common CCA/PLS models and their regularized variants. We examine the limitations of standard CCA and PLS when the sample size is similar or smaller than the number of variables. We discuss how dimensionality reduction and regularization techniques address this problem and explain their main advantages and disadvantages. We highlight crucial aspects of the CCA/PLS analysis framework, including optimising the hyperparameters of the model and testing the identified associations for statistical significance. We apply the described CCA/PLS models to simulated data and real data from the Human Connectome Project and the Alzheimer's Disease Neuroimaging Initiative (both of n>500). We use both low and high dimensionality versions of each data (i.e., ratios between sample size and variables in the range of ∼1-10 and ∼0.1-0.01) to demonstrate the impact of data dimensionality on the models. Finally, we summarize the key lessons of the tutorial