Cavitation induced by explosion in a model of ideal fluid

We discuss the problem of an explosion in the cubic-quintic superfluid model, in relation to some experimental observations. We show numerically that an explosion in such a model might induce a cavitation bubble for large enough energy. This gives a consistent view for rebound bubbles in superfluid and we indentify the loss of energy between the successive rebounds as radiated waves. We compute self-similar solution of the explosion for the early stage, when no bubbles have been nucleated. The solution also gives the wave number of the excitations emitted through the shock wave.Comment: 21 pages,13 figures, other comment

Nucleation and condensational growth to CCN sizes during a sustained pristine biogenic SOA event in a forested mountain valley

The Whistler Aerosol and Cloud Study (WACS 2010), included intensive measurements of trace gases and particles at two sites on Whistler Mountain. Between 6–11 July 2010 there was a sustained high-pressure system over the region with cloud-free conditions and the highest temperatures of the study. During this period, the organic aerosol concentrations rose from <1 μg m<sup>−3</sup> to ∼6 μg m<sup>−3</sup>. Precursor gas and aerosol composition measurements show that these organics were almost entirely of secondary biogenic nature. Throughout 6–11 July, the anthropogenic influence was minimal with sulfate concentrations <0.2 μg m<sup>−3</sup> and SO<sub>2</sub> mixing ratios ≈ 0.05–0.1 ppbv. Thus, this case provides excellent conditions to probe the role of biogenic secondary organic aerosol in aerosol microphysics. Although SO<sub>2</sub> mixing ratios were relatively low, box-model simulations show that nucleation and growth may be modeled accurately if <i>J</i><sub>nuc</sub> = 3 × 10<sup>−7</sup>[H<sub>2</sub>SO<sub>4</sub>] and the organics are treated as effectively non-volatile. Due to the low condensation sink and the fast condensation rate of organics, the nucleated particles grew rapidly (2–5 nm h<sup>−1</sup>) with a 10–25% probability of growing to CCN sizes (100 nm) in the first two days as opposed to being scavenged by coagulation with larger particles. The nucleated particles were observed to grow to ∼200 nm after three days. Comparisons of size-distribution with CCN data show that particle hygroscopicity (κ) was ∼0.1 for particles larger 150 nm, but for smaller particles near 100 nm the κ value decreased near midway through the period from 0.17 to less than 0.06. In this environment of little anthropogenic influence and low SO<sub>2</sub>, the rapid growth rates of the regionally nucleated particles – due to condensation of biogenic SOA – results in an unusually high efficiency of conversion of the nucleated particles to CCN. Consequently, despite the low SO<sub>2</sub>, nucleation/growth appear to be the dominant source of particle number

Heartbeat of the Sun from Principal Component Analysis and prediction of solar activity on a millenium timescale

yesWe derive two principal components (PCs) of temporal magnetic field variations over the solar cycles 21–24 from full disk magnetograms covering about 39% of data variance, with σ = 0.67. These PCs are attributed to two main magnetic waves travelling from the opposite hemispheres with close frequencies and increasing phase shift. Using symbolic regeression analysis we also derive mathematical formulae for these waves and calculate their summary curve which we show is linked to solar activity index. Extrapolation of the PCs backward for 800 years reveals the two 350-year grand cycles superimposed on 22 year-cycles with the features showing a remarkable resemblance to sunspot activity reported in the past including the Maunder and Dalton minimum. The summary curve calculated for the next millennium predicts further three grand cycles with the closest grand minimum occurring in the forthcoming cycles 26–27 with the two magnetic field waves separating into the opposite hemispheres leading to strongly reduced solar activity. These grand cycle variations are probed by α − Ω dynamo model with meridional circulation. Dynamo waves are found generated with close frequencies whose interaction leads to beating effects responsible for the grand cycles (350–400 years) superimposed on a standard 22 year cycle. This approach opens a new era in investigation and confident prediction of solar activity on a millenium timescale

Temperature-dependent accumulation mode particle and cloud nuclei concentrations from biogenic sources during WACS 2010

Submicron aerosol particles collected simultaneously at the mountain peak (2182 m a.s.l.) and at a forested mid-mountain site (1300 m a.s.l.) on Whistler Mountain, British Columbia, Canada, during June and July 2010 were analyzed by Fourier transform infrared (FTIR) spectroscopy for quantification of organic functional groups. Positive matrix factorization (PMF) was applied to the FTIR spectra. Three PMF factors associated with (1) combustion, (2) biogenics, and (3) vegetative detritus were identified at both sites. The biogenic factor was correlated with both temperature and several volatile organic compounds (VOCs). The combustion factor dominated the submicron particle mass during the beginning of the campaign, when the temperature was lower and advection was from the Vancouver area, but as the temperature started to rise in early July, the biogenic factor came to dominate as a result of increased emissions of biogenic VOCs, and thereby increased formation of secondary organic aerosol (SOA). On average, the biogenic factor represented 69% and 49% of the submicron organic particle mass at Whistler Peak and at the mid-mountain site, respectively. The lower fraction at the mid-mountain site was a result of more vegetative detritus there, and also higher influence from local combustion sources. The biogenic factor was strongly correlated (r~0.9) to number concentration of particles with diameter (Dp)> 100 nm, whereas the combustion factor was better correlated to number concentration of particles with Dpr~0.4). The number concentration of cloud condensation nuclei (CCN) was correlated (r~0.7) to the biogenic factor for supersaturations (S) of 0.2% or higher, which indicates that particle condensational growth from biogenic vapors was an important factor in controlling the CCN concentration for clouds where S≥0.2%. Both the number concentration of particles with Dp>100 nm and numbers of CCN for S≥0.2% were correlated to temperature. Considering the biogenic influence, these results indicate that temperature was a primary factor controlling these CCN concentrations at 0.2% supersaturation

Multivariate curve resolution of time course microarray data

BACKGROUND: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), independent component analysis (ICA), or other methods. Such methods do not generally yield factors with a clear biological interpretation. Moreover, implicit assumptions about the measurement errors often limit the application of these methods to log-transformed data, destroying linear structure in the untransformed expression data. RESULTS: In this work, a method for the linear decomposition of gene expression data by multivariate curve resolution (MCR) is introduced. The MCR method is based on an alternating least-squares (ALS) algorithm implemented with a weighted least squares approach. The new method, MCR-WALS, extracts a small number of basis functions from untransformed microarray data using only non-negativity constraints. Measurement error information can be incorporated into the modeling process and missing data can be imputed. The utility of the method is demonstrated through its application to yeast cell cycle data. CONCLUSION: Profiles extracted by MCR-WALS exhibit a strong correlation with cell cycle-associated genes, but also suggest new insights into the regulation of those genes. The unique features of the MCR-WALS algorithm are its freedom from assumptions about the underlying linear model other than the non-negativity of gene expression, its ability to analyze non-log-transformed data, and its use of measurement error information to obtain a weighted model and accommodate missing measurements

Ageism and sexuality

Sexuality remains important throughout a person’s life, but sexual behavior does not receive the same levels of acceptance at all ages. Older people are challenged by ageist attitudes and perceptions that hinder their sexual expression. They are stereotyped as non-sexual beings who should not, cannot, and do not want to have sexual relationships. Expressing sexuality or engaging in sexual activity in later life is considered by many in society as immoral or perverted. False expectations for older people also stem from ideals of beauty, centralization of the biomedical perspective on sexuality of older adults, and the association of sex with reproduction. Unfortunately, older people internalize many ageist attitudes towards sexuality in later life and become less interested in sex and less sexually active. The following chapter explores attitudes towards sexuality in later life among the media, young people, older people themselves, and care providers. In order to enable older people to express their sexuality and sexual identity freely and fully, awareness of ageist perceptions must be raised and defeated

Mapping transcription mechanisms from multimodal genomic data

Background Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene expression data, raising a new computational challenge due to the tremendous size of data. Results We develop a method to identify eQTLs. The method represents eQTLs as information flux between genetic variants and transcripts. We use information theory to simultaneously interrogate SNP and gene expression data, resulting in a Transcriptional Information Map (TIM) which captures the network of transcriptional information that links genetic variations, gene expression and regulatory mechanisms. These maps are able to identify both cis- and trans- regulating eQTLs. The application on a dataset of leukemia patients identifies eQTLs in the regions of the GART, PCP4, DSCAM, and RIPK4 genes that regulate ADAMTS1, a known leukemia correlate. Conclusions The information theory approach presented in this paper is able to infer the dependence networks between SNPs and transcripts, which in turn can identify cis- and trans-eQTLs. The application of our method to the leukemia study explains how genetic variants and gene expression are linked to leukemia.National Human Genome Research Institute (U.S.) (R01HG003354)National Institute of Allergy and Infectious Diseases (U.S.) (U19 AI067854-05)National Heart, Lung, and Blood Institute (grant T32 HL007427-28)National Institutes of Health (U.S.) (grant K99 LM009826

Elucidating real-world vehicle emission factors from mobile measurements over a large metropolitan region: a focus on isocyanic acid, hydrogen cyanide, and black carbon

A mobile laboratory equipped with state-of-the-art gaseous and particulate instrumentation was deployed across the Greater Toronto Area (GTA) during two seasons. A high-resolution time-of-flight chemical ionization mass spectrometer (HR-TOF-CIMS) measured isocyanic acid (HNCO) and hydrogen cyanide (HCN), and a high-sensitivity laser-induced incandescence (HS-LII) instrument measured black carbon (BC). Results indicate that on-road vehicles are a clear source of HNCO and HCN and that their impact is more pronounced in the winter, when influences from biomass burning (BB) and secondary photochemistry are weakest. Plume-based and time-based algorithms were developed to calculate fleet-average vehicle emission factors (EFs); the algorithms were found to yield comparable results, depending on the pollutant identity. With respect to literature EFs for benzene, toluene, C2 benzene (sum of m-, p-, and o-xylenes and ethylbenzene), nitrogen oxides, particle number concentration (PN), and black carbon, the calculated EFs were characteristic of a relatively clean vehicle fleet dominated by light-duty vehicles (LDV). Our fleet-average EF for BC (median: 25&thinsp;mg&thinsp;kgfuel-1; interquartile range, IQR: 10–76&thinsp;mg&thinsp;kgfuel-1) suggests that overall vehicular emissions of BC have decreased over time. However, the distribution of EFs indicates that a small proportion of high-emitters continue to contribute disproportionately to total BC emissions. We report the first fleet-average EF for HNCO (median: 2.3&thinsp;mg&thinsp;kgfuel-1, IQR: 1.4–4.2&thinsp;mg&thinsp;kgfuel-1) and HCN (median: 0.52&thinsp;mg&thinsp;kgfuel-1, IQR: 0.32–0.88&thinsp;mg&thinsp;kgfuel-1). The distribution of the estimated EFs provides insight into the real-world variability of HNCO and HCN emissions and constrains the wide range of literature EFs obtained from prior dynamometer studies. The impact of vehicle emissions on urban HNCO levels can be expected to be further enhanced if secondary HNCO formation from vehicle exhaust is considered.</p

Ice nucleating particles in the marine boundary layer in the Canadian Arctic during summer 2014

Ice nucleating particles (INPs) in the Arctic can influence climate and precipitation in the region; yet our understanding of the concentrations and sources of INPs in this region remain uncertain. In the following, we (1) measured concentrations of INPs in the immersion mode in the Canadian Arctic marine boundary layer during summer 2014 on board the CCGS Amundsen, (2) determined ratios of surface areas of mineral dust aerosol to sea spray aerosol, and (3) investigated the source region of the INPs using particle dispersion modelling. Average concentrations of INPs at −15, −20, and −25&thinsp;∘C were 0.005, 0.044, and 0.154&thinsp;L−1, respectively. These concentrations fall within the range of INP concentrations measured in other marine environments. For the samples investigated the ratio of mineral dust surface area to sea spray surface area ranged from 0.03 to 0.09. Based on these ratios and the ice active surface site densities of mineral dust and sea spray aerosol determined in previous laboratory studies, our results suggest that mineral dust is a more important contributor to the INP population than sea spray aerosol for the samples analysed. Based on particle dispersion modelling, the highest concentrations of INPs were often associated with lower-latitude source regions such as the Hudson Bay area, eastern Greenland, or north-western continental Canada. On the other hand, the lowest concentrations were often associated with regions further north of the sampling sites and over Baffin Bay. A weak correlation was observed between INP concentrations and the time the air mass spent over bare land, and a weak negative correlation was observed between INP concentrations and the time the air mass spent over ice and open water. These combined results suggest that mineral dust from local sources is an important contributor to the INP population in the Canadian Arctic marine boundary layer during summer 2014.</p

Genotype and Gene Expression Associations with Immune Function in Drosophila

It is now well established that natural populations of Drosophila melanogaster harbor substantial genetic variation associated with physiological measures of immune function. In no case, however, have intermediate measures of immune function, such as transcriptional activity of immune-related genes, been tested as mediators of phenotypic variation in immunity. In this study, we measured bacterial load sustained after infection of D. melanogaster with Serratia marcescens, Providencia rettgeri, Enterococcus faecalis, and Lactococcus lactis in a panel of 94 third-chromosome substitution lines. We also measured transcriptional levels of 329 immune-related genes eight hours after infection with E. faecalis and S. marcescens in lines from the phenotypic tails of the test panel. We genotyped the substitution lines at 137 polymorphic markers distributed across 25 genes in order to test for statistical associations among genotype, bacterial load, and transcriptional dynamics. We find that genetic polymorphisms in the pathogen recognition genes (and particularly in PGRP-LC, GNBP1, and GNBP2) are most significantly associated with variation in bacterial load. We also find that overall transcriptional induction of effector proteins is a significant predictor of bacterial load after infection with E. faecalis, and that a marker upstream of the recognition gene PGRP-SD is statistically associated with variation in both bacterial load and transcriptional induction of effector proteins. These results show that polymorphism in genes near the top of the immune system signaling cascade can have a disproportionate effect on organismal phenotype due to the amplification of minor effects through the cascade