Influence of gas flow rate on liquid distribution in trickle-beds using perforated plates as liquid distributors

Two wire mesh tomography devices and a liquid collector were used to study the influence of the gas flow rate on liquid distribution when fluids distribution on top of the reactor is ensured by a perforated plate. In opposition to most of the studies realized by other authors, conditions in which the gas has a negative impact in liquid distribution were evidenced. Indeed, the obtained results show that the influence of gas flow rate depends on the quality of the initial distribution, as the gas forces the liquid to "respect" the distribution imposed at the top of the reactor. Finally, a comparison between the two measuring techniques shows the limitations of the liquid collector and the improper conclusions to which its use could lead

Pseudogaucher cells obscuring multiple myeloma: a case report

Gaucher-like or pseudo-Gaucher cells have been noted in a variety of conditions including acute lymphoblastic leukemia, Hodgkin's disease, thalassemia, and multiple myeloma. They have an eccentric, lobulated nucleus, foamy cytoplasm but lack the tubular inclusions seen in Gaucher cells. The pseudo-Gaucher cells have distinct appearances on electron microscopy which distinguish them from true Gaucher cells

Quantitative analysis of fatty acid in Indian goat milk and its comparison with other livestock

Abstract Milk fat contains 400 vital fatty acids beneficial for human health. Special attention is given to fatty acids (FAs) that could play a positive role for human health; such are butyric, oleic acid, caproic, caprylic and capric acids. Keeping the medicinal properties of milk fatty acids in consideration, goat milk samples were analyzed for estimation of fatty acid contents in Indian goat milk by using gas chromatography. Analysis of goat milk samples revealed the highest concentration saturated fatty acids (SFA) out of total milk fatty acids (FA) with an average of 69.55 g/100g of fatty acid methyl ester (FAME) ranging from 43.26 to 88.05g/100g of FAME. Within saturated fatty acid the major contribution was given by palmitic (C16:0) 26.99% followed by myristic (C14:0) 11.77%, stearic (C18:0) 7.66% and capric (C10:0) 6.75% respectively. The concentration of short chain fatty acids (SCFAs, C4 to C10) was found to be 13.51 g/100g varying from 2.23 to 33.63 g/100g of FAME. Whereas the concentration of medium chain fatty acids (MCFAs , C12to C15) was 20.05% varying from 7.470 to 45.27 g/100 g of FAME and Long chain FA (LFA, C16 to C24) was 35.08% varying from 4.77 to 51.22 g/100g of FAME. The average concentration of unsaturated fatty acids (UFAs) was 28.50 g/100grm of FAME varying from 10.44 to 45.74 g/100g of FAME which includes monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) with an average of 24.57 g/100g of FAME ranges varying from 4.79 to 39.40 g/100g of FAME and 3.96 g/100g of FAME ranges varying from 0.5928 to 18.30g/100 g of FAME, respectively

#CDCGrandRounds and #VitalSigns : A Twitter Analysis

BACKGROUND: The CDC hosts monthly panel presentations titled 'Public Health Grand Rounds' and publishes monthly reports known as Vital Signs. Hashtags #CDCGrandRounds and #VitalSigns were used to promote them on Twitter. Objectives: This study quantified the effect of hashtag count, mention count, and URL count and attaching visual cues to #CDCGrandRounds or #VitalSigns tweets on their retweet frequency. METHODS: Through Twitter Search Application Programming Interface, original tweets containing the hashtag #CDCGrandRounds (n = 6,966; April 21, 2011-October 25, 2016) and the hashtag #VitalSigns (n = 15,015; March 19, 2013-October 31, 2016) were retrieved respectively. Negative binomial regression models were applied to each corpus to estimate the associations between retweet frequency and three predictors (hashtag count, mention count, and URL link count). Each corpus was sub-set into cycles (#CDCGrandRounds: n = 58, #VitalSigns: n = 42). We manually coded the 30 tweets with the highest number of retweets for each cycle, whether it contained visual cues (images or videos). Univariable negative binomial regression models were applied to compute the prevalence ratio (PR) of retweet frequency for each cycle, between tweets with and without visual cues. FINDINGS: URL links increased retweet frequency in both corpora; effects of hashtag count and mention count differed between the two corpora. Of the 58 #CDCGrandRounds cycles, 29 were found to have statistically significantly different retweet frequencies between tweets with and without visual cues. Of these 29 cycles, one had a PR estimate < 1; twenty-four, PR > 1 but < 3; and four, PR > 3. Of the 42 #VitalSigns cycles, 19 were statistically significant. Of these 19 cycles, six were PR > 1 and < 3; and thirteen, PR > 3. Conclusions: The increase of retweet frequency through attaching visual cues varied across cycles for original tweets with #CDCGrandRounds and #VitalSigns. Future research is needed to determine the optimal choice of visual cues to maximize the influence of public health tweets

Fission and cluster decay of 76^{76}Sr nucleus in the ground-state and formed in heavy-ion reactions

Calculations for fission and cluster decay of $^{76}Sr$ are presented for this nucleus to be in its ground-state or formed as an excited compound system in heavy-ion reactions. The predicted mass distribution, for the dynamical collective mass transfer process assumed for fission of $^{76}Sr$, is clearly asymmetric, favouring $\alpha$-nuclei. Cluster decay is studied within a preformed cluster model, both for ground-state to ground-state decays and from excited compound system to the ground-state(s) or excited states(s) of the fragments.Comment: 14 pages LaTeX, 5 Figures available upon request Submitted to Phys. Rev.

Emission of intermediate mass fragments from hot 116^{116}Ba∗^* formed in low-energy 58^{58}Ni+58^{58}Ni reaction

The complex fragments (or intermediate mass fragments) observed in the low-energy $^{58}$Ni+$^{58}$Ni$\to ^{116}$Ba$^*$ reaction, are studied within the dynamical cluster decay model for s-wave with the use of the temperature-dependent liquid drop, Coulomb and proximity energies. The important result is that, due to the temperature effects in liquid drop energy, the explicit preference for $\alpha$-like fragments is washed out, though the $^{12}$C (or the complementary $^{104}$Sn) decay is still predicted to be one of the most probable $\alpha$-nucleus decay for this reaction. The production rates for non-$\alpha$ like intermediate mass fragments (IMFs) are now higher and the light particle production is shown to accompany the IMFs at all incident energies, without involving any statistical evaporation process in the model. The comparisons between the experimental data and the (s-wave) calculations for IMFs production cross sections are rather satisfactory and the contributions from other $\ell$-waves need to be added for a further improvement of these comparisons and for calculations of the total kinetic energies of fragments.Comment: 22 pages, 15 figure

#CDCGrandRounds and #VitalSigns: A Twitter Analysis

Background: The CDC hosts monthly panel presentations titled ‘Public Health Grand Rounds’ and publishes monthly reports known as Vital Signs. Hashtags #CDCGrandRounds and #VitalSigns were used to promote them on Twitter. Objectives: This study quantified the effect of hashtag count, mention count, and URL count and attaching visual cues to #CDCGrandRounds or #VitalSigns tweets on their retweet frequency. Methods: Through Twitter Search Application Programming Interface, original tweets containing the hashtag #CDCGrandRounds (n = 6,966; April 21, 2011–October 25, 2016) and the hashtag #VitalSigns (n = 15,015; March 19, 2013–October 31, 2016) were retrieved respectively. Negative binomial regression models were applied to each corpus to estimate the associations between retweet frequency and three predictors (hashtag count, mention count, and URL link count). Each corpus was sub-set into cycles (#CDCGrandRounds: n = 58, #VitalSigns: n = 42). We manually coded the 30 tweets with the highest number of retweets for each cycle, whether it contained visual cues (images or videos). Univariable negative binomial regression models were applied to compute the prevalence ratio (PR) of retweet frequency for each cycle, between tweets with and without visual cues. Findings: URL links increased retweet frequency in both corpora; effects of hashtag count and mention count differed between the two corpora. Of the 58 #CDCGrandRounds cycles, 29 were found to have statistically significantly different retweet frequencies between tweets with and without visual cues. Of these 29 cycles, one had a PR estimate 1 but 3. Of the 42 #VitalSigns cycles, 19 were statistically significant. Of these 19 cycles, six were PR > 1 and 3. Conclusions: The increase of retweet frequency through attaching visual cues varied across cycles for original tweets with #CDCGrandRounds and #VitalSigns. Future research is needed to determine the optimal choice of visual cues to maximize the influence of public health tweets

Transcriptional analysis of adipose tissue during development reveals depot-specific responsiveness to maternal dietary supplementation

Brown adipose tissue (BAT) undergoes pronounced changes after birth coincident with the loss of the BAT-specifc uncoupling protein (UCP)1 and rapid fat growth. The extent to which this adaptation may vary between anatomical locations remains unknown, or whether the process is sensitive to maternal dietary supplementation. We, therefore, conducted a data mining based study on the major fat depots (i.e. epicardial, perirenal, sternal (which possess UCP1 at 7 days), subcutaneous and omental) (that do not possess UCP1) of young sheep during the frst month of life. Initially we determined what effect adding 3% canola oil to the maternal diet has on mitochondrial protein abundance in those depots which possessed UCP1. This demonstrated that maternal dietary supplementation delayed the loss of mitochondrial proteins, with the amount of cytochrome C actually being increased. Using machine learning algorithms followed by weighted gene co-expression network analysis, we demonstrated that each depot could be segregated into a unique and concise set of modules containing co-expressed genes involved in adipose function. Finally using lipidomic analysis following the maternal dietary intervention, we confrmed the perirenal depot to be most responsive. These insights point at new research avenues for examining interventions to modulate fat development in early life