Delineation of Soil Boundaries Using Image Enhancement and Spectral Signature Classification of Landsat Data

The concept of using satellite data for soils inventories began with the advent of the first ERTS launch in 1972. Landsat data can be useful in a field survey, if it satisfies one or both of two requirements: the products must improve the accuracy of the survey and/or it must expedite the survey. These goals can be achieved by creating products that enhance and delineate soil surface features that would not necessarily identify specific soil types but rather provide a spatial boundary that a field scientist could observe and evaluate. A 250,000 acre tract of semiarid rangeland in east central Utah was selected as the study area. A June 13, 1977 Landsat scene was chosen for analysis. The color composite combined with such ancillary data as geologic maps and topographic quadrangles aided in partitioning the study site in to areas of physiographic homogeneity. A principle components transformation was performed on the data and a uniform contrast stretch was applied to the unaltered spectral bands and the transformed axes. The contrast stretch increased the dynamic tonal range of the data, and created as many as 32 different tonal classes. Various color combinations and a number of density slices were evaluated for their interpretability. A spectral signature classification of the June scene was developed using both supervised and unsupervised classification algorithms. A canonical analysis was then performed on the thematic maps to improve class separability for image enhancement. The more promising image products were geometrically corrected, scaled to 1:24,000, and merged with data digitized from a partially completed soils map. The resulting map allowed comparisons between soil lines drawn by a field soil mapper and the classes defined by computer analysis. Both the enhanced images and the spectral classification maps aided in the delineation of soil boundaries. Enhanced images are inexpensive to generate and, as no subjective class groupings are made, have the added quality of objectivity. The spectral classification maps defined surface characteristics that could be used to help separate soil units. A cost analysis for the individual products and an indepth field evaluation is being completed

Control of entanglement transitions in quantum spin clusters

Quantum spin clusters provide a new platform for the experimental study of many-body entanglement. Here we address a simple model of a single-molecule nano-magnet featuring N interacting spins in a transverse field. The field can control an entanglement transition (ET). We calculate the magnetisation, low-energy gap and neutron-scattering cross-section and find that the ET has distinct signatures, detectable at temperatures as high as 5% of the interaction strength. The signatures are stronger for smaller clusters

The acheulean handaxe : More like a bird's song than a beatles' tune?

© 2016 Wiley Periodicals, Inc. KV is supported by the Netherlands Organization for Scientific Research. MC is supported by the Canada Research Chairs Program, the Social Sciences and Humanities Research of Canada, the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund, and Simon Fraser UniversityPeer reviewedPublisher PD

Religion, Partisanship, and Attitudes Toward Science Policy

We examine issues involving science which have been contested in recent public debate. These “contested science” issues include human evolution, stem-cell research, and climate change. We find that few respondents evince consistently skeptical attitudes toward science issues, and that religious variables are generally strong predictors of attitudes toward individual issues. Furthermore, and contrary to analyses of elite discourse, partisan identification is not generally predictive of attitudes toward contested scientific issues

The role of dimensionality in neuronal network dynamics

The research leading to these results has received funding from the European Union’s Seventh Framework Programme under grant agreement FP7 ICT 2011 – 284553 (Acronym: Si-CODE), the NEUROSCAFFOLDS Project n. 604263, the National Natural Science Foundation of China (Grant number: 51361130033) and the Ministry of Science and Technology of China (973 Grant number: 2014CB965003)

Recipes and mechanisms of cellular reprogramming: a case study on budding yeast Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>Generation of induced pluripotent stem cells (iPSCs) and converting one cell type to another (transdifferentiation) by manipulating the expression of a small number of genes highlight the progress of cellular reprogramming, which holds great promise for regenerative medicine. A key challenge is to find the recipes of perturbing genes to achieve successful reprogramming such that the reprogrammed cells function in the same way as the natural cells.</p> <p>Results</p> <p>We present here a systems biology approach that allows systematic search for effective reprogramming recipes and monitoring the reprogramming progress to uncover the underlying mechanisms. Using budding yeast as a model system, we have curated a genetic network regulating cell cycle and sporulation. Phenotypic consequences of perturbations can be predicted from the network without any prior knowledge, which makes it possible to computationally reprogram cell fate. As the heterogeneity of natural cells is important in many biological processes, we find that the extent of this heterogeneity restored by the reprogrammed cells varies significantly upon reprogramming recipes. The heterogeneity difference between the reprogrammed and natural cells may have functional consequences.</p> <p>Conclusions</p> <p>Our study reveals that cellular reprogramming can be achieved by many different perturbations and the reprogrammability of a cell depends on the heterogeneity of the original cell state. We provide a general framework that can help discover new recipes for cellular reprogramming in human.</p

Large-Scale Assessment of the Zebrafish Embryo as a Possible Predictive Model in Toxicity Testing

Background: In the drug discovery pipeline, safety pharmacology is a major issue. The zebrafish has been proposed as a model that can bridge the gap in this field between cell assays (which are cost-effective, but low in data content) and rodent assays (which are high in data content, but less cost-efficient). However, zebrafish assays are only likely to be useful if they can be shown to have high predictive power. We examined this issue by assaying 60 water-soluble compounds representing a range of chemical classes and toxicological mechanisms. Methodology/Principal Findings: Over 20,000 wild-type zebrafish embryos (including controls) were cultured individually in defined buffer in 96-well plates. Embryos were exposed for a 96 hour period starting at 24 hours post fertilization. A logarithmic concentration series was used for range-finding, followed by a narrower geometric series for LC 50 determination. Zebrafish embryo LC50 (log mmol/L), and published data on rodent LD50 (log mmol/kg), were found to be strongly correlated (using Kendall’s rank correlation tau and Pearson’s product-moment correlation). The slope of the regression line for the full set of compounds was 0.73403. However, we found that the slope was strongly influenced by compound class. Thus, while most compounds had a similar toxicity level in both species, some compounds were markedly more toxic in zebrafish than in rodents, or vice versa. Conclusions: For the substances examined here, in aggregate, the zebrafish embryo model has good predictivity for toxicit