Lost in Numbers? Anchoring Effects in Advertising Claims and Product Information

The file attached to this record is the author's final peer reviewed version.According to anchoring theory, if unsure, human beings are predisposed to treat the first information they see as a starting point when making a judgement. This, often sub-conscious process, means random information can influence decisions in ways consumers are often unaware of. This paper tests this principle in advertising contexts to understand how anchoring may affect the way consumers interpret numbers within marketing messages. The results support the semantic priming and semantic anchoring models, which predict that random numbers will bias estimates when the wording of the ‘anchor’ is similar to the object of the estimate. We present evidence that this is the case even when the information is not directly relevant to the task. Contrastingly, no evidence is found to support the ‘simple numeric priming’ view of anchoring, which predicts that entirely abstract information can bias estimates

Hotspots of change in use of public transport to work: A geospatial mixed method study

Introduction: Several studies have supported the role of public transport in encouraging active transport through commuting. Investigating actual increases in public transport use within focussed local areas can help unravel what causes such increases. Methods: In this study, we investigated factors related to the increase in public transport use in focussed local areas (hotspots) through a geospatial mixed-method approach using data from South Western Sydney, Australia, spatial cluster detection, and local stakeholder interviews. We also examined areas with low levels of public transport use. Results: We found that while distance to train station is a significant predictor of usage, other important factors include the professional and socioeconomic profile of the neighbourhood around the train station, the train line's deemed attractiveness and parking availability. Conclusions: Thus, researchers and planners must consider a range of built environment factors when planning for changes that encourage public transport use. In addition, focusing on small local areas utilising geospatial mixed methods can provide important insights into the local drivers of public transport use

The amyloid precursor protein of Alzheimer’s disease clusters at the organelle/microtubule interface on organelles that bind microtubules in an ATP dependent manner

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS One 11 (2016): e0147808, doi:10.1371/journal.pone.0147808.The amyloid precursor protein (APP) is a causal agent in the pathogenesis of Alzheimer’s disease and is a transmembrane protein that associates with membrane-limited organelles. APP has been shown to co-purify through immunoprecipitation with a kinesin light chain suggesting that APP may act as a trailer hitch linking kinesin to its intercellular cargo, however this hypothesis has been challenged. Previously, we identified an mRNA transcript that encodes a squid homolog of human APP770. The human and squid isoforms share 60% sequence identity and 76% sequence similarity within the cytoplasmic domain and share 15 of the final 19 amino acids at the C-terminus establishing this highly conserved domain as a functionally import segment of the APP molecule. Here, we study the distribution of squid APP in extruded axoplasm as well as in a well-characterized reconstituted organelle/microtubule preparation from the squid giant axon in which organelles bind microtubules and move towards the microtubule plus-ends. We find that APP associates with microtubules by confocal microscopy and co-purifies with KI-washed axoplasmic organelles by sucrose density gradient fractionation. By electron microscopy, APP clusters at a single focal point on the surfaces of organelles and localizes to the organelle/microtubule interface. In addition, the association of APP-organelles with microtubules is an ATP dependent process suggesting that the APP-organelles contain a microtubule-based motor protein. Although a direct kinesin/APP association remains controversial, the distribution of APP at the organelle/microtubule interface strongly suggests that APP-organelles have an orientation and that APP like the Alzheimer’s protein tau has a microtubule-based function.Research reported in this publication was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103430

Forecasting carbon monoxide on a global scale for the ATom-1 aircraft mission: insights from airborne and satellite observations and modeling

The first phase of the Atmospheric Tomography Mission (ATom-1) took place in July–August 2016 and included flights above the remote Pacific and Atlantic oceans. Sampling of atmospheric constituents during these flights is designed to provide new insights into the chemical reactivity and processes of the remote atmosphere and how these processes are affected by anthropogenic emissions. Model simulations provide a valuable tool for interpreting these measurements and understanding the origin of the observed trace gases and aerosols, so it is important to quantify model performance. Goddard Earth Observing System Model version 5 (GEOS-5) forecasts and analyses show considerable skill in predicting and simulating the CO distribution and the timing of CO enhancements observed during the ATom-1 aircraft mission. We use GEOS-5's tagged tracers for CO to assess the contribution of different emission sources to the regions sampled by ATom-1 to elucidate the dominant anthropogenic influences on different parts of the remote atmosphere. We find a dominant contribution from non-biomass-burning sources along the ATom transects except over the tropical Atlantic, where African biomass burning makes a large contribution to the CO concentration. One of the goals of ATom is to provide a chemical climatology over the oceans, so it is important to consider whether August 2016 was representative of typical boreal summer conditions. Using satellite observations of 700&thinsp;hPa and column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument, 215&thinsp;hPa&thinsp;CO from the Microwave Limb Sounder (MLS), and aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS), we find that CO concentrations and aerosol optical thickness in August 2016 were within the observed range of the satellite observations but below the decadal median for many of the regions sampled. This suggests that the ATom-1 measurements may represent relatively clean but not exceptional conditions for lower-tropospheric CO.</p

Cotton breeding in Australia : meeting the challenges of the 21st century

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program is the sole breeding effort for cotton in Australia, developing high performing cultivars for the local industry which is worth∼AU$3 billion per annum. The program is supported by Cotton Breeding Australia, a Joint Venture between CSIRO and the program’s commercial partner, Cotton Seed Distributors Ltd. (CSD). While the Australian industry is the focus, CSIRO cultivars have global impact in North America, South America, and Europe. The program is unique compared with many other public and commercial breeding programs because it focuses on diverse and integrated research with commercial outcomes. It represents the full research pipeline, supporting extensive long-term fundamental molecular research; native and genetically modified (GM) trait development; germplasm enhancement focused on yield and fiber quality improvements; integration of third-party GM traits; all culminating in the release of new commercial cultivars. This review presents evidence of past breeding successes and outlines current breeding efforts, in the areas of yield and fiber quality improvement, as well as the development of germplasm that is resistant to pests, diseases and abiotic stressors. The success of the program is based on the development of superior germplasm largely through field phenotyping, together with strong commercial partnerships with CSD and Bayer CropScience. These relationships assist in having a shared focus and ensuring commercial impact is maintained, while also providing access to markets, traits, and technology. The historical successes, current foci and future requirements of the CSIRO cotton breeding program have been used to develop a framework designed to augment our breeding system for the future. This will focus on utilizing emerging technologies from the genome to phenome, as well as a panomics approach with data management and integration to develop, test and incorporate new technologies into a breeding program. In addition to streamlining the breeding pipeline for increased genetic gain, this technology will increase the speed of trait and marker identification for use in genome editing, genomic selection and molecular assisted breeding, ultimately producing novel germplasm that will meet the coming challenges of the 21st Century

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the Version 2 validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities

Global Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using Assimilation Diagnostics

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with ~2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of ~0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under ~3 K), the soil moisture increments (under ~0.01 cu.m/cu.m), and the surface soil temperature increments (under ~1 K). Typical instantaneous values are ~6 K for O-F residuals, ~0.01 (~0.003) cu.m/cu.m for surface (root-zone) soil moisture increments, and ~0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing

Influenza Outbreaks during World Youth Day 2008 Mass Gathering

Novel viruses were introduced and seasonal viruses were amplified

Does Consideration and Assessment of Effects on Health Equity Affect the Conclusions of Systematic Reviews? A Methodology Study

INTRODUCTION: Tackling health inequities both within and between countries remains high on the agenda of international organizations including the World Health Organization and local, regional and national governments. Systematic reviews can be a useful tool to assess effects on equity in health status because they include studies conducted in a variety of settings and populations. This study aims to describe the extent to which the impacts of health interventions on equity in health status are considered in systematic reviews, describe methods used, and assess the implications of their equity related findings for policy, practice and research. METHODS: We conducted a methodology study of equity assessment in systematic reviews. Two independent reviewers extracted information on the reporting and analysis of impacts of health interventions on equity in health status in a group of 300 systematic reviews collected from all systematic reviews indexed in one month of MEDLINE, using a pre-tested data collection form. Any differences in data extraction were resolved by discussion. RESULTS: Of the 300 systematic reviews, 224 assessed the effectiveness of interventions on health outcomes. Of these 224 reviews, 29 systematic reviews assessed effects on equity in health status using subgroup analysis or targeted analyses of vulnerable populations. Of these, seven conducted subgroup analyses related to health equity which were reported in insufficient detail to judge their credibility. Of these 29 reviews, 18 described implications for policy and practice based on assessment of effects on health equity. CONCLUSION: The quality and completeness of reporting should be enhanced as a priority, because without this policymakers and practitioners will continue lack the evidence base they need to inform decision-making about health inequity. Furthermore, there is a need to develop methods to systematically consider impacts on equity in health status that is currently lacking in systematic reviews