Spatially-resolved magnetic resonance study of the dissolution interface between soaps and water

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BEAMS: separating the wheat from the chaff in supernova analysis

We introduce Bayesian Estimation Applied to Multiple Species (BEAMS), an algorithm designed to deal with parameter estimation when using contaminated data. We present the algorithm and demonstrate how it works with the help of a Gaussian simulation. We then apply it to supernova data from the Sloan Digital Sky Survey (SDSS), showing how the resulting confidence contours of the cosmological parameters shrink significantly.Comment: 23 pages, 9 figures. Chapter 4 in "Astrostatistical Challenges for the New Astronomy" (Joseph M. Hilbe, ed., Springer, New York, forthcoming in 2012), the inaugural volume for the Springer Series in Astrostatistic

Semi-supervised Learning for Photometric Supernova Classification

We present a semi-supervised method for photometric supernova typing. Our approach is to first use the nonlinear dimension reduction technique diffusion map to detect structure in a database of supernova light curves and subsequently employ random forest classification on a spectroscopically confirmed training set to learn a model that can predict the type of each newly observed supernova. We demonstrate that this is an effective method for supernova typing. As supernova numbers increase, our semi-supervised method efficiently utilizes this information to improve classification, a property not enjoyed by template based methods. Applied to supernova data simulated by Kessler et al. (2010b) to mimic those of the Dark Energy Survey, our methods achieve (cross-validated) 95% Type Ia purity and 87% Type Ia efficiency on the spectroscopic sample, but only 50% Type Ia purity and 50% efficiency on the photometric sample due to their spectroscopic follow-up strategy. To improve the performance on the photometric sample, we search for better spectroscopic follow-up procedures by studying the sensitivity of our machine learned supernova classification on the specific strategy used to obtain training sets. With a fixed amount of spectroscopic follow-up time, we find that deeper magnitude-limited spectroscopic surveys are better for producing training sets. For supernova Ia (II-P) typing, we obtain a 44% (1%) increase in purity to 72% (87%) and 30% (162%) increase in efficiency to 65% (84%) of the sample using a 25th (24.5th) magnitude-limited survey instead of the shallower spectroscopic sample used in the original simulations. When redshift information is available, we incorporate it into our analysis using a novel method of altering the diffusion map representation of the supernovae. Incorporating host redshifts leads to a 5% improvement in Type Ia purity and 13% improvement in Type Ia efficiency.Comment: 16 pages, 11 figures, accepted for publication in MNRA

Results from the Supernova Photometric Classification Challenge

We report results from the Supernova Photometric Classification Challenge (SNPCC), a publicly released mix of simulated supernovae (SNe), with types (Ia, Ibc, and II) selected in proportion to their expected rate. The simulation was realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point-spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). A spectroscopically confirmed subset was provided for training. We challenged scientists to run their classification algorithms and report a type and photo-z for each SN. Participants from 10 groups contributed 13 entries for the sample that included a host-galaxy photo-z for each SN, and 9 entries for the sample that had no redshift information. Several different classification strategies resulted in similar performance, and for all entries the performance was significantly better for the training subset than for the unconfirmed sample. For the spectroscopically unconfirmed subset, the entry with the highest average figure of merit for classifying SNe~Ia has an efficiency of 0.96 and an SN~Ia purity of 0.79. As a public resource for the future development of photometric SN classification and photo-z estimators, we have released updated simulations with improvements based on our experience from the SNPCC, added samples corresponding to the Large Synoptic Survey Telescope (LSST) and the SDSS, and provided the answer keys so that developers can evaluate their own analysis.Comment: accepted by PAS

On the Usefulness of Modern Animism: Co-Creating Architecture with Soils as Ontopolitical Practice

In opposition to the general understanding of animism as an irrational religious set of beliefs, the—secular—modern animism embodied in this practice of built and grown architecture is operative. It conceives of places—ecosystems—as beings with agency that we garden with to nurture and express their resilience. It is a useful ontology for ecological practice; this architectural animism is ontopolitical; it co-creates a common world. At a recent symposium, a number of projects were presented as architectural soils and to give a voice to these earthly beings, the method was to write a letter from them to me. This first letter with the response in this article forms the beginning of an animistic correspondence. The medium places the reader in a pluriverse, in between the multiple voices of various “actants.” The text is isomorphic to the embodied dialogue of this earthy practice. It is useful both to nurture societal awareness—empathy and care—towards these fragmentary ecosystemic beings, and as research method to conceive them, and our relationship

Designing the selenium and bladder cancer trial (SELEBLAT), a phase lll randomized chemoprevention study with selenium on recurrence of bladder cancer in Belgium

<p>Abstract</p> <p>Background</p> <p>In Belgium, bladder cancer is the fifth most common cancer in males (5.2%) and the sixth most frequent cause of death from cancer in males (3.8%). Previous epidemiological studies have consistently reported that selenium concentrations were inversely associated with the risk of bladder cancer. This suggests that selenium may also be suitable for chemoprevention of recurrence.</p> <p>Method</p> <p>The SELEBLAT study opened in September 2009 and is still recruiting all patients with non-invasive transitional cell carcinoma of the bladder on TURB operation in 15 Belgian hospitals. Recruitment progress can be monitored live at <url>http://www.seleblat.org.</url> Patients are randomly assigned to selenium yeast (200 μg/day) supplementation for 3 years or matching placebo, in addition to standard care. The objective is to determine the effect of selenium on the recurrence of bladder cancer. Randomization is stratified by treatment centre. A computerized algorithm randomly assigns the patients to a treatment arm. All study personnel and participants are blinded to treatment assignment for the duration of the study.</p> <p>Design</p> <p>The SELEnium and BLAdder cancer Trial (SELEBLAT) is a phase III randomized, placebo-controlled, academic, double-blind superior trial.</p> <p>Discussion</p> <p>This is the first report on a selenium randomized trial in bladder cancer patients.</p> <p>Trial registration</p> <p>ClinicalTrials.gov identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00729287">NCT00729287</a></p

Systematic functional analysis of Leishmania protein kinases identifies regulators of differentiation or survival

Differentiation between distinct stages is fundamental for the life cycle of intracellular protozoan parasites and for transmission between hosts, requiring stringent spatial and temporal regulation. Here, we apply kinome-wide gene deletion and gene tagging in Leishmania mexicana promastigotes to define protein kinases with life cycle transition roles. Whilst 162 are dispensable, 44 protein kinase genes are refractory to deletion in promastigotes and are likely core genes required for parasite replication. Phenotyping of pooled gene deletion mutants using bar-seq and projection pursuit clustering reveal functional phenotypic groups of protein kinases involved in differentiation from metacyclic promastigote to amastigote, growth and survival in macrophages and mice, colonisation of the sand fly and motility. This unbiased interrogation of protein kinase function in Leishmania allows targeted investigation of organelle-associated signalling pathways required for successful intracellular parasitism

Intravesical Treatments of Bladder Cancer: Review

For bladder cancer, intravesical chemo/immunotherapy is widely used as adjuvant therapies after surgical transurethal resection, while systemic therapy is typically reserved for higher stage, muscle-invading, or metastatic diseases. The goal of intravesical therapy is to eradicate existing or residual tumors through direct cytoablation or immunostimulation. The unique properties of the urinary bladder render it a fertile ground for evaluating additional novel experimental approaches to regional therapy, including iontophoresis/electrophoresis, local hyperthermia, co-administration of permeation enhancers, bioadhesive carriers, magnetic-targeted particles and gene therapy. Furthermore, due to its unique anatomical properties, the drug concentration-time profiles in various layers of bladder tissues during and after intravesical therapy can be described by mathematical models comprised of drug disposition and transport kinetic parameters. The drug delivery data, in turn, can be combined with the effective drug exposure to infer treatment efficacy and thereby assists the selection of optimal regimens. To our knowledge, intravesical therapy of bladder cancer represents the first example where computational pharmacological approach was used to design, and successfully predicted the outcome of, a randomized phase III trial (using mitomycin C). This review summarizes the pharmacological principles and the current status of intravesical therapy, and the application of computation to optimize the drug delivery to target sites and the treatment efficacy