125 research outputs found
Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree
In this work, a computational intelligence (CI) technique named flexible neural tree (FNT) was developed to predict die filling performance of pharmaceutical granules and to identify significant die filling process variables. FNT resembles feedforward neural network, which creates a tree-like structure by using genetic programming. To improve accuracy, FNT parameters were optimized by using differential evolution algorithm. The performance of the FNT-based CI model was evaluated and compared with other CI techniques: multilayer perceptron, Gaussian process regression, and reduced error pruning tree. The accuracy of the CI model was evaluated experimentally using die filling as a case study. The die filling experiments were performed using a model shoe system and three different grades of microcrystalline cellulose (MCC) powders (MCC PH 101, MCC PH 102, and MCC DG). The feed powders were roll-compacted and milled into granules. The granules were then sieved into samples of various size classes. The mass of granules deposited into the die at different shoe speeds was measured. From these experiments, a dataset consisting true density, mean diameter (d50), granule size, and shoe speed as the inputs and the deposited mass as the output was generated. Cross-validation (CV) methods such as 10FCV and 5x2FCV were applied to develop and to validate the predictive models. It was found that the FNT-based CI model (for both CV methods) performed much better than other CI models. Additionally, it was observed that process variables such as the granule size and the shoe speed had a higher impact on the predictability than that of the powder property such as d50. Furthermore, validation of model prediction with experimental data showed that the die filling behavior of coarse granules could be better predicted than that of fine granules
Production of phi mesons at mid-rapidity in sqrt(s_NN) = 200 GeV Au+Au collisions at RHIC
We present the first results of meson production in the K^+K^- decay channel
from Au+Au collisions at sqrt(s_NN) = 200 GeV as measured at mid-rapidity by
the PHENIX detector at RHIC. Precision resonance centroid and width values are
extracted as a function of collision centrality. No significant variation from
the PDG accepted values is observed. The transverse mass spectra are fitted
with a linear exponential function for which the derived inverse slope
parameter is seen to be constant as a function of centrality. These data are
also fitted by a hydrodynamic model with the result that the freeze-out
temperature and the expansion velocity values are consistent with the values
previously derived from fitting single hadron inclusive data. As a function of
transverse momentum the collisions scaled peripheral.to.central yield ratio RCP
for the is comparable to that of pions rather than that of protons. This result
lends support to theoretical models which distinguish between baryons and
mesons instead of particle mass for explaining the anomalous proton yield.Comment: 326 authors, 24 pages text, 23 figures, 6 tables, RevTeX 4. To be
submitted to Physical Review C as a regular article. Plain text data tables
for the points plotted in figures for this and previous PHENIX publications
are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm
Effects of maternal immune activation on gene expression patterns in the fetal brain
We are exploring the mechanisms underlying how maternal infection increases the risk for schizophrenia and autism in the offspring. Several mouse models of maternal immune activation (MIA) were used to examine the immediate effects of MIA induced by influenza virus, poly(I:C) and interleukin IL-6 on the fetal brain transcriptome. Our results indicate that all three MIA treatments lead to strong and common gene expression changes in the embryonic brain. Most notably, there is an acute and transient upregulation of the α, β and γ crystallin gene family. Furthermore, levels of crystallin gene expression are correlated with the severity of MIA as assessed by placental weight. The overall gene expression changes suggest that the response to MIA is a neuroprotective attempt by the developing brain to counteract environmental stress, but at a cost of disrupting typical neuronal differentiation and axonal growth. We propose that this cascade of events might parallel the mechanisms by which environmental insults contribute to the risk of neurodevelopmental disorders such as schizophrenia and autism
Growth, cell division and sporulation in mycobacteria
Bacteria have the ability to adapt to different growth conditions and to survive in various environments. They have also the capacity to enter into dormant states and some bacteria form spores when exposed to stresses such as starvation and oxygen deprivation. Sporulation has been demonstrated in a number of different bacteria but Mycobacterium spp. have been considered to be non-sporulating bacteria. We recently provided evidence that Mycobacterium marinum and likely also Mycobacterium bovis bacillus Calmette–Guérin can form spores. Mycobacterial spores were detected in old cultures and our findings suggest that sporulation might be an adaptation of lifestyle for mycobacteria under stress. Here we will discuss our current understanding of growth, cell division, and sporulation in mycobacteria
J/psi production from proton-proton collisions at sqrt(s) = 200 GeV
J/psi production has been measured in proton-proton collisions at sqrt(s)=
200 GeV over a wide rapidity and transverse momentum range by the PHENIX
experiment at RHIC. Distributions of the rapidity and transverse momentum,
along with measurements of the mean transverse momentum and total production
cross section are presented and compared to available theoretical calculations.
The total J/psi cross section is 3.99 +/- 0.61(stat) +/- 0.58(sys) +/-
0.40(abs) micro barns. The mean transverse momentum is 1.80 +/- 0.23(stat) +/-
0.16(sys) GeV/c.Comment: 326 authors, 6 pages text, 4 figures, 1 table, RevTeX 4. To be
submitted to PRL. Plain text data tables for the points plotted in figures
for this and previous PHENIX publications are (or will be) publicly available
at http://www.phenix.bnl.gov/papers.htm
Measurement of Single Electron Event Anisotropy in Au+Au Collisions at sqrt(s_NN) = 200 GeV
The transverse momentum dependence of the azimuthal anisotropy parameter v_2,
the second harmonic of the azimuthal distribution, for electrons at
mid-rapidity (|eta| < 0.35) has been measured with the PHENIX detector in Au+Au
collisions at sqrt(s_NN) = 200 GeV. The measurement was made with respect to
the reaction plane defined at high rapidities (|eta| = 3.1 -- 3.9). From the
result we have measured the v_2 of electrons from heavy flavor decay after
subtraction of the v_2 of electrons from other sources such as photon
conversions and Dalitz decay from light neutral mesons. We observe a non-zero
single electron v_2 with a 90% confidence level in the intermediate p_T region.Comment: 330 authors, 11 pages text, RevTeX4, 9 figures, 1 tables. Submitted
to Physical Review C. Plain text data tables for the points plotted in
figures for this and previous PHENIX publications are (or will be) publicly
available at http://www.phenix.bnl.gov/papers.htm
Systematic Studies of the Centrality and sqrt(s_NN) Dependence of dE_T/deta and dN_ch/deta in Heavy Ion Collisions at Mid-rapidity
The PHENIX experiment at RHIC has measured transverse energy and charged
particle multiplicity at mid-rapidity in Au+Au collisions at sqrt(s_NN) = 19.6,
130 and 200 GeV as a function of centrality. The presented results are compared
to measurements from other RHIC experiments, and experiments at lower energies.
The sqrt(s_NN) dependence of dE_T/deta and dN_ch/deta per pair of participants
is consistent with logarithmic scaling for the most central events. The
centrality dependence of dE_T/deta and dN_ch/deta is similar at all measured
incident energies. At RHIC energies the ratio of transverse energy per charged
particle was found independent of centrality and growing slowly with
sqrt(s_NN). A survey of comparisons between the data and available theoretical
models is also presented.Comment: 327 authors, 25 pages text, 19 figures, 17 tables, RevTeX 4. To be
submitted to Physical Review C as a regular article. Plain text data tables
for the points plotted in figures for this and previous PHENIX publications
are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm
Centrality Dependence of Charm Production from Single Electrons in Au+Au Collisions at sqrt(s_NN) = 200 GeV
The PHENIX experiment has measured mid-rapidity transverse momentum spectra
(0.4 < p_T < 4.0 GeV/c) of single electrons as a function of centrality in
Au+Au collisions at sqrt(s_NN) = 200 GeV. Contributions to the raw spectra from
photon conversions and Dalitz decays of light neutral mesons are measured by
introducing a thin (1.7% X_0) converter into the PHENIX acceptance and are
statistically removed. The subtracted ``non-photonic'' electron spectra are
primarily due to the semi-leptonic decays of hadrons containing heavy quarks
(charm and bottom). For all centralities, charm production is found to scale
with the nuclear overlap function, T_AA. For minimum-bias collisions the charm
cross section per binary collision is N_cc^bar/T_AA = 622 +/- 57 (stat.) +/-
160 (sys.) microbarns.Comment: 326 authors, 4 pages text, 3 figures, 1 table, RevTeX 4. To be
submitted to Physical Review Letters. Plain text data tables for the points
plotted in figures for this and previous PHENIX publications are (or will be)
publicly available at http://www.phenix.bnl.gov/papers.htm
Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic
Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer
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