Evaluation of the Specialist Community Public Health Nursing Peripatetic Assessment Model

The Health Visitor Implementation Plan 2011-15: a call to action, called for an additional 4200 health visitors to be trained by 2015. To accommodate larger numbers of students, specialist community public health nursing (SCPHN) programmes across the UK have undergone significant transformation in terms of practice supervision. Somerset Partnership NHS Trust introduced a peripatetic assessment model involving practice teachers and practice mentors. This differed from traditional one-to-one approaches of supervision to one-to-three. Practice teachers mostly supervised students through close collaboration with mentors who worked directly with students on a daily basis. Using a mixed methods approach, the evaluation aimed to assess the effectiveness of the new model from the perspective of SCPHN students, mentors, practice teachers (PTs) and managers. Data was collected through an anonymous online survey and individual interviews or focus groups. Overall, participants were positive about the peripatetic model’s impact on student learning and practice experience, in addition to the general up-skilling of the wider health visiting workforce and possible implications of continuation into the future. Any concerns raised focused on adequate preparation and support for mentors and the need for clear communication and role differentiation between practice teachers and mentors

Healthcare Outcomes and Resource Utilization Associated with Neonatal Hypoglycemia: Analysis of Data from the HCUP Kid’s Inpatient Database

Neonatal hypoglycemia is the most common metabolic abnormality in infants and is associated with neurological damage and death. The risk of developing hypoglycemia among infants born from diabetic mothers is even higher. Although much work has been performed addressing issues for treatment and care, research related to neonatal hypoglycemia has been focused on the clinical or individual level risk factors. Contextual risk factors such as hospital characteristics, neighborhood economic status, and regional variations were not considered in earlier studies. Additionally, although healthcare resources utilization of hypoglycemia has been adequately addressed in the adult population, this topic has not been studied in hypoglycemic neonates. The overarching purpose of this dissertation was to investigate healthcare outcomes and resource utilization related to neonatal hypoglycemia. The first purpose was to conduct a systematic review in order to investigate whether previous studies only focused on clinical risk factors or included a broader health service-related contextual risk factors in assessing the determinants of neonatal hypoglycemia. The second purpose was to identify the key factors associated with increased hospital cost associated with neonatal hypoglycemia in the United States. The third and final purpose of the dissertation was to construct multi-level models that include individual-level and contextual-level characteristics. The systematic review (Project I) determined that previous studies mainly focus on the clinical characteristics of infants and mothers. The systematic review suggested that contextual variables should be included in future research. Project II found that increased cost was observed, when more than five procedures were performed during the same hospitalization, when hospital bed size was between 100 and 300 or ≥ 400, when hospital length of stay exceeded 15 days, in teaching hospitals, in the presence of chronic conditions, comorbidities, prematurity, and death. In project III we found that infant of diabetic mothers had more than 5-fold increased risk of developing neonatal hypoglycemia compared to infants of non-diabetic mothers. Infants born in urban and teaching hospitals also had significantly higher chance of developing neonatal hypoglycemia. Project III also determined that the inclusion of the contextual risk factors improved the final model that was constructed to predict neonatal hypoglycemia

Understanding extreme behavior by optimizing tail dependence with application to ground level ozone via data mining and spatial modeling

Includes bibliographical references.2015 Summer.This dissertation presents novel work in statistical methods for extremes. Our underlying modeling procedure identifies the linear combination of covariates that is associated with extreme values of a response variable, and is based on the framework of bivariate regular variation. We propose a data mining strategy that is suitable for an analysis of ground level ozone, and spatially model the primary drivers of extreme ozone over a large study region. In this dissertation, we first review statistical methods for univariate and multivariate extremes. We then discuss tail dependence parameters and their estimators and introduce γ, a tail dependence metric which is better suited for optimization than other existing metrics. We also introduce the idea of tail dependence estimators that utilize a smooth threshold rather than the 'hard' threshold common to extremes. A smooth threshold is necessary to perform optimization, which has not previously been considered in extremes studies. We also show consistency of estimators with smooth thresholds. Subsequently, we outline our procedure for optimizing tail dependence and discuss parameter estimation. We also propose a model selection procedure that is based on cross-validation. Then we give a simulation study where we demonstrate our method's ability to detect complicated conditions which lead to extreme behavior and compare our approach to competing methods. Next, we propose a data mining procedure that can be used to find the set of covariates that produces the linear combination that has the highest degree of tail dependence with a response variable. Our data mining procedure is a model selection exercise where the model space is too large to be searched exhaustively. We use an automated model search procedure based on simulated annealing. We also give an analysis of ground level ozone, applying our data mining procedure to data from Atlanta, Georgia and Charlotte, North Carolina. We discuss how our method can be modified to deal with non-continuous covariates such as precipitation. Lastly, we seek to model how a set of primary drivers varies spatially over a study region. We utilize data from 160 EPA stations in 13 US states plus the District of Columbia. We model the parameters in our extreme value procedure spatially using a hierarchical modeling technique. For inference, we utilize a two-step procedure

The Role of Cold Flows in the Assembly of Galaxy Disks

We use high resolution cosmological hydrodynamical simulations to demonstrate that cold flow gas accretion, particularly along filaments, modifies the standard picture of gas accretion and cooling onto galaxy disks. In the standard picture, all gas is initially heated to the virial temperature of the galaxy as it enters the virial radius. Low mass galaxies are instead dominated by accretion of gas that stays well below the virial temperature, and even when a hot halo is able to develop in more massive galaxies there exist dense filaments that penetrate inside of the virial radius and deliver cold gas to the central galaxy. For galaxies up to ~L*, this cold accretion gas is responsible for the star formation in the disk at all times to the present. Even for galaxies at higher masses, cold flows dominate the growth of the disk at early times. Within this modified picture, galaxies are able to accrete a large mass of cold gas, with lower initial gas temperatures leading to shorter cooling times to reach the disk. Although star formation in the disk is mitigated by supernovae feedback, the short cooling times allow for the growth of stellar disks at higher redshifts than predicted by the standard model.Comment: accepted to Ap

Letter from T. Brook White to John Muir, 1896 Apr 2.

[1][letterhead]Historian [Mazamas?]April 2. 1896.John Muir EsqPresident Sierra ClubSan Francisco Cal.Dear SirA determined effort is now being made in Congress to restore threefourths of the Cascade Range Forest Reserve to public entry. The entire Oregon delegation headed by Senator Mitchell favors the reopening of the reserve. The move is being made solely in the interest of the sheep men.Judge Bellinger of the United States Circuit Court is one of several influential men here who are strongly opposed to any encroachments on the Reserve and he is able personally to reach the President and thus checkmate the proposed move. He desires to obtain the views of any prominent men who are at all02076 [2]interested in the subject.One extract from your Mountains of California has already been quoted and will reach the President\u27s eye. But I venture to ask knowing your warm interest in the matter that you will address a communication to the President setting forth your views on the subject and reasons for the protection of the Reserve. Or in case you feel any delicacy in addressing the President personally a letter addressed to Judge Bellinger or to me will reach him (through the Judge) with equal certainty.I am not certain whether you were ever officially notified of your election at the first annual meeting of the Mazamas as the first Honorary member of the Society. If not it was due to the change of Secretaries and [letterhead][3]2I fear that I am to blame for the omission.The other Honary Members are Prof. Le Conte Prof Candon, Prof Davidson and General Greely.The next outing of the Society is to be at Crater Lake and if you have not already been officially communictaed with by the present Secretary you will shortly hear from him further in reagrd to it.Yours very trulyT. Brook White.N.B. The fact that Senator Mitchell is connected by marriage with one of the prinicipal sheep ranchesr of Eastern Oregon may - or may not have any bearing on his present attitudes in regard to the Reserve.0207

Hierarchical formation of bulgeless galaxies II: Redistribution of angular momentum via galactic fountains

Within a fully cosmological hydrodynamical simulation, we form a galaxy which rotates at 140 km/s, and is characterised by two loose spiral arms and a bar, indicative of a Hubble Type SBc/d galaxy. We show that our simulated galaxy has no classical bulge, with a pure disc profile at z=1, well after the major merging activity has ended. A long-lived bar subsequently forms, resulting in the formation of a secularly-formed "pseudo" bulge, with the final bulge-to-total light ratio B/T=0.21. We show that the majority of gas which loses angular momentum and falls to the central region of the galaxy during the merging epoch is blown back into the hot halo, with much of it returning later to form stars in the disc. We propose that this mechanism of redistribution of angular momentum via a galactic fountain, when coupled with the results from our previous study which showed why gas outflows are biased to have low angular momentum, can solve the angular momentum/bulgeless disc problem of the cold dark matter paradigm.Comment: 9 Pages, 10 Figures, accepted MNRAS version. Comments welcom

Macroalgae and eelgrass mapping in Great Bay Estuary using AISA hyperspectral imagery

Increase in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending problems for NH’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the New Hampshire Estuaries Project (NHEP) adopted the assumption that eelgrass survival can be used as the water quality target for nutrient criteria development for NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that a possible eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To test this hypothesis, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral imagery was conducted by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. This report outlines the configured procedure for mapping the macroalgae and eelgrass beds using hyperspectral imagery. No ground truth measurements of eelgrass or macroalgae were collected as part of this project, although eelgrass ground truth data was collected as part of a separate project. Guidance from eelgrass and macroalgae experts was used for identifying training sets and evaluating the classification results. The results produced a comprehensive eelgrass and macroalgae map of the estuary. Three recommendations are suggested following the experience gained in this study: conducting ground truth measurements at the time of the HS survey, acquiring the current DEM model of Great Bay Estuary, and examining additional HS datasets with expert eelgrass and macroalgae guidance. These three issues can improve the classification results and allow more advanced applications, such as identification of macroalgae types

Restoration of Oyster (Crassostrea virginica) Habitat for Multiple Estuarine Species Benefits

Increase in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending problems for NH’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the New Hampshire Estuaries Project (NHEP) adopted the assumption that eelgrass survival can be used as the water quality target for nutrient criteria development for NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that a possible eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To test this hypothesis, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral imagery was conducted by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. This report outlines the configured procedure for mapping the macroalgae and eelgrass beds using hyperspectral imagery. No ground truth measurements of eelgrass or macroalgae were collected as part of this project, although eelgrass ground truth data was collected as part of a separate project. Guidance from eelgrass and macroalgae experts was used for identifying training sets and evaluating the classification results. The results produced a comprehensive eelgrass and macroalgae map of the estuary. Three recommendations are suggested following the experience gained in this study: conducting ground truth measurements at the time of the HS survey, acquiring the current DEM model of Great Bay Estuary, and examining additional HS datasets with expert eelgrass and macroalgae guidance. These three issues can improve the classification results and allow more advanced applications, such as identification of macroalgae types