Enhancements in Cloud Condensation Nuclei Activity From Turbulent Fluctuations in Supersaturation

The effect of aerosols on the properties of clouds is a large source of uncertainty in predictions of weather and climate. These aerosol-cloud interactions depend critically on the ability of aerosol particles to form cloud droplets. A challenge in modeling aerosol-cloud interactions is the representation of interactions between turbulence and cloud microphysics. Turbulent mixing leads to small-scale fluctuations in water vapor and temperature that are unresolved in large-scale atmospheric models. To quantify the impact of turbulent fluctuations on cloud condensation nuclei (CCN) activation, we used a high-resolution Large Eddy Simulation of a convective cloud chamber to drive particle-based cloud microphysics simulations. We show small-scale fluctuations strongly impact CCN activity. Once activated, the relatively long timescales of evaporation compared to fluctuations causes droplets to persist in subsaturated regions, which further increases droplet concentrations

Adaptive Evolutionary Clustering

In many practical applications of clustering, the objects to be clustered evolve over time, and a clustering result is desired at each time step. In such applications, evolutionary clustering typically outperforms traditional static clustering by producing clustering results that reflect long-term trends while being robust to short-term variations. Several evolutionary clustering algorithms have recently been proposed, often by adding a temporal smoothness penalty to the cost function of a static clustering method. In this paper, we introduce a different approach to evolutionary clustering by accurately tracking the time-varying proximities between objects followed by static clustering. We present an evolutionary clustering framework that adaptively estimates the optimal smoothing parameter using shrinkage estimation, a statistical approach that improves a naive estimate using additional information. The proposed framework can be used to extend a variety of static clustering algorithms, including hierarchical, k-means, and spectral clustering, into evolutionary clustering algorithms. Experiments on synthetic and real data sets indicate that the proposed framework outperforms static clustering and existing evolutionary clustering algorithms in many scenarios.Comment: To appear in Data Mining and Knowledge Discovery, MATLAB toolbox available at http://tbayes.eecs.umich.edu/xukevin/affec

Association of maternal sleep practices with pre‐eclampsia, low birth weight, and stillbirth among Ghanaian women

ObjectiveTo assess sleep practices, and investigate their relationship with maternal and fetal outcomes, among pregnant Ghanaian women.MethodsIn a cross‐sectional study conducted at Korle Bu Teaching Hospital, Accra, Ghana, between June and July 2011, postpartum women were interviewed within 48 hours of delivery about sleep quality and practices during pregnancy. Interviews were coupled with a systematic review of participants’ medical charts for key outcomes including maternal hypertension, pre‐eclampsia, premature delivery, low birth weight, and stillbirth.ResultsMost women reported poor sleep quality during pregnancy. Snoring during pregnancy was independently associated with pre‐eclampsia (odds ratio [OR], 3.5; 95% confidence interval [CI], 1.4–8.5; P = 0.007). The newborns of women who reported supine sleep during pregnancy were at increased risk of low birth weight (OR, 5.0; 95% CI, 1.2–20.2; P = 0.025) and stillbirth (OR, 8.0; 95% CI, 1.5–43.2; P = 0.016). Low birth weight was found to mediate the relationship between supine sleep and stillbirth.ConclusionThe present findings in an African population demonstrate that maternal sleep, a modifiable risk factor, has a significant role in pre‐eclampsia, low birth weight, and subsequently stillbirth.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135150/1/ijgo261.pd

Population Structure Shapes Copy Number Variation in Malaria Parasites.

If copy number variants (CNVs) are predominantly deleterious, we would expect them to be more efficiently purged from populations with a large effective population size (Ne) than from populations with a small Ne. Malaria parasites (Plasmodium falciparum) provide an excellent organism to examine this prediction, because this protozoan shows a broad spectrum of population structures within a single species, with large, stable, outbred populations in Africa, small unstable inbred populations in South America and with intermediate population characteristics in South East Asia. We characterized 122 single-clone parasites, without prior laboratory culture, from malaria-infected patients in seven countries in Africa, South East Asia and South America using a high-density single-nucleotide polymorphism/CNV microarray. We scored 134 high-confidence CNVs across the parasite exome, including 33 deletions and 102 amplifications, which ranged in size from <500 bp to 59 kb, as well as 10,107 flanking, biallelic single-nucleotide polymorphisms. Overall, CNVs were rare, small, and skewed toward low frequency variants, consistent with the deleterious model. Relative to African and South East Asian populations, CNVs were significantly more common in South America, showed significantly less skew in allele frequencies, and were significantly larger. On this background of low frequency CNV, we also identified several high-frequency CNVs under putative positive selection using an FST outlier analysis. These included known adaptive CNVs containing rh2b and pfmdr1, and several other CNVs (e.g., DNA helicase and three conserved proteins) that require further investigation. Our data are consistent with a significant impact of genetic structure on CNV burden in an important human pathogen

Dealing with the mess (we made): Unraveling hybridity, normativity, and complexity in journalism studies

In this article, we discuss the rise and use of the concept of hybridity in journalism studies. Hybridity afforded a meaningful intervention in a discipline that had the tendency to focus on a stabilized and homogeneous understanding of the field. Nonetheless, we now need to reconsider its deployment, as it only partially allows us to address and understand the developments in journalism. We argue that if scholarship is to move forward in a productive manner, we need, rather than denote everything that is complex as hybrid, to develop new approaches to our object of study. Ultimately, this is an open invitation to the field to adopt experientialist, practice-based approaches that help us overcome the ultimately limited binary dualities that have long governed our theoretical and empirical work in the field

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

The Development of a Code for Australian Psychologists

Section 35(1)(c) of the Health Practitioner Regulation National Law Act (200929. Health Practitioner Regulation National Law Act of 2009. (Queensland). View all references) requires the newly formed Psychology Board of Australia (PsyBA) “to develop or approve standards, codes and guidelines.” In 2010 the PsyBA decided to initially adopt the Australian Psychological Society\u27s (APS) Code of Ethics (200711. Australian Psychological Society . 2007 . Code of ethics , Melbourne, , Australia : Author . View all references) and develop a new code in the future with the involvement of key stakeholders without deciding what the nature of this code will be. The PsyBA now has to decide exactly how it will proceed in future. My aim in this article is to examine the options available to the PsyBA by exploring the definition and function of codes; presenting a history of the APS Code; and considering approaches that had been followed in Europe, Israel, New Zealand, and South Africa

Influence of water uptake on the aerosol particle light scattering coefficients of the Central European aerosol

The influence of aerosol water uptake on the aerosol particle light scattering was examined at the regional continental research site Melpitz, Germany. The scattering enhancement factor f(RH), defined as the aerosol particle scattering coefficient at a certain relative humidity (RH) divided by its dry value, was measured using a humidified nephelometer. The chemical composition and other microphysical properties were measured in parallel. f(RH) showed a strong variation, e.g. with values between 1.2 and 3.6 at RH=85% and λ=550 nm. The chemical composition was found to be the main factor determining the magnitude of f(RH), since the magnitude of f(RH) clearly correlated with the inorganic mass fraction measured by an aerosol mass spectrometer (AMS). Hysteresis within the recorded humidograms was observed and explained by long-range transported sea salt. A closure study using Mie theory showed the consistency of the measured parameters

Comparative and Joint Analysis of Two Metagenomic Datasets from a Biogas Fermenter Obtained by 454-Pyrosequencing

Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus bourgensis. While rarefaction analyses still indicate incomplete coverage, examination of the GS FLX Titanium dataset resulted in the identification of additional genera and functional elements, providing a far more complete coverage of the community involved in anaerobic fermentative pathways leading to methane formation