Clustering of High-Redshift Quasars

In this work, we investigate the clustering of faint quasars in the early Universe and use the clustering strength to gain a better understanding of quasar feedback mechanisms and the growth of central supermassive black holes at early times in the history of the Universe. It has long been understood (e.g., Hopkins et al. 2007a) that the clustering of distant quasars can be used as a probe of different feedback models; however, until now, there was no sample of faint, high-redshift quasars with sufficient density to accurately measure the clustering strength. Therefore we conducted a new survey to increase the number density of these objects. Here, we describe the Spitzer -IRAC Equatorial Survey (SpIES) which is a moderately deep, large-area Spitzer survey which was designed to discover faint, high-redshift (2.9 ≤ z ≤ 5.1) quasars. SpIES spans ~115 deg^2 in the equatorial “Stripe 82” region of the Sloan Digital Sky Survey (SDSS) and probes to 5-[sigma] depths of 6.13 [mu]-Jy (21.93 AB magnitude) and 5.75 [mu]-Jy (22.0 AB magnitude) at 3.6 and 4.5 microns. At these depths, SpIES is able to observe faint quasars, and we show that SpIES recovers ~ 94% of the high-redshift (z > 3.5), spectroscopically-confirmed quasars that lie within its footprint. SpIES is also ideally located on Stripe 82 for two reasons: It surrounds existing infrared data from the Spitzer-HETDEX Exploratory Large-area (SHELA) survey which increases the area of infrared coverage, and there is a wide range of multi-wavelength, multi-epoch ancillary data on Stripe 82 which we can use together to select high-redshift quasar candidates. To photometrically identify quasar candidates, we combined the optical data from the Sloan Digital Sky Survey and the infrared data from SpIES and SHELA and employed three machine learning algorithms. These algorithms were trained on the optical/infrared colors of known, high-redshift quasars. Using this method, we generate a sample of 1378 objects that are both faint (i > 20.2) and high-redshift (2.9 ≤ z ≤ 5.1) which we use to compute the angular two-point correlation function. We fit a single power-law model with an index of delta = 1.39 ± 0.618 and amplitude of theta_0 = 0.71 ± 0.546 arcmin to the correlation function, as well as a dark matter model with a bias of b = 6.78 ± 1.79. The bias in our investigation suggests a model of quasar feedback that considers quasar activity as an intermittent phase in galaxy evolution. If this model is correct, quasar feedback is strong enough to periodically halt the accretion of gas onto the central supermassive black hole of the quasar, which shuts down quasar activity and causes the black hole to stop growing, however it is not strong enough to completely shut down the quasar in the early Universe.Ph.D., Physics -- Drexel University, 201

Effect of Phosphorus Nutrition on Growth and Physiology of Cotton Under Ambient and Elevated Carbon Dioxide

Phosphorous deficiency in soil limits crop growth and productivity in the majority of arable lands worldwide and may moderate the growth enhancement effect of rising atmospheric carbon dioxide (CO2) concentration. To evaluate the interactive effect of these two factors on cotton (Gossypium hirsutum) growth and physiology, plants were grown in controlled environment growth chambers with three levels of phosphate (Pi) supply (0.20, 0.05 and 0.01 mM) under ambient and elevated (400 and 800 μmol mol‒1, respectively) CO2. Phosphate stress caused stunted growth and resulted in early leaf senescence with severely decreased leaf area and photosynthesis. Phosphate stress led to over 77 % reduction in total biomass across CO2 levels. There was a below-ground (roots) shift in biomass partitioning under Pi deficiency. While tissue phosphorus (P) decreased, tissue nitrogen (N) content tended to increase under Pi deficiency. The CO2 × Pi interactions were significant on leaf area, photosynthesis and biomass accumulation. The stimulatory effect of elevated CO2 on growth and photosynthesis was reduced or highly depressed suggesting an increased sensitivity of cotton to Pi deficiency under elevated CO2. Although, tissue P and stomatal conductance were lower at elevated CO2, these did not appear to be the main causes of cotton unresponsiveness to elevated CO2 under severe Pi-stress. The alteration in the uptake and utilization of N was suggested due to a consistent reduction (18–21 %) in the cotton plant tissue N content under elevated CO2

Parents' Active Role and ENgagement in The review of their Stillbirth/perinatal death 2 (PARENTS 2) study: a mixed-methods study of implementation.

OBJECTIVE: When a formal review of care takes places after the death of a baby, parents are largely unaware it takes place and are often not meaningfully involved in the review process. Parent engagement in the process is likely to be essential for a successful review and to improve patient safety. This study aimed to evaluate an intervention process of parental engagement in perinatal mortality review (PNMR) and to identify barriers and facilitators to its implementation. DESIGN: Mixed-methods study of parents' engagement in PNMR. SETTING: Single tertiary maternity unit in the UK. PARTICIPANTS: Bereaved parents and healthcare professionals (HCPs). INTERVENTIONS: Parent engagement in the PNMR (intervention) was based on principles derived through national consensus and qualitative research with parents, HCPs and stakeholders in the UK. OUTCOMES: Recruitment rates, bereaved parents and HCPs' perceptions. RESULTS: Eighty-one per cent of bereaved parents approached (13/16) agreed to participate in the study. Two focus groups with bereaved parents (n=11) and HCP (n=7) were carried out postimplementation to investigate their perceptions of the process.Overarching findings were improved dialogue and continuity of care with parents, and improvements in the PNMR process and patient safety. Bereaved parents agreed that engagement in the PNMR process was invaluable and helped them in their grieving. HCP perceived that parent involvement improved the review process and lessons learnt from the deaths; information to understand the impact of aspects of care on the baby's death were often only found in the parents' recollections. CONCLUSIONS: Parental engagement in the PNMR process is achievable and useful for parents and HCP alike, and critically can improve patient safety and future care for mothers and babies. To learn and prevent perinatal deaths effectively, all hospitals should give parents the option to engage with the review of their baby's death

Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data

BACKGROUND: Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. RESULTS: Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. CONCLUSION: Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring