Windfall Wealth and Shale Development in Appalachian Ohio: Preliminary Results

The response by agriculture/natural resources and community development Extension educators to shale development in Ohio has been proactive. There is a need, however, to understand the impact that shale development is having broadly on families and communities and specifically as it relates to lease payments and the perceptions and realities of resource windfalls or sudden wealth. This article presents the preliminary results of a qualitative study. In the course of data analysis, themes emerged around the topics of money, family and community life, and land. A discussion of the role of Extension professionals is provided

Organometallic Neptunium Chemistry

Fifty years have passed since the foundation of organometallic neptunium chemistry, and yet only a handful of complexes have been reported, and even fewer fully characterised. Yet increasingly, combined synthetic/spectroscopic/computational studies are demonstrating how covalently binding, soft, carbocyclic organometallic ligands provide an excellent platform for advancing the fundamental understanding of the differences in orbital contributions and covalency in f-block metal – ligand bonding. Understanding the subtleties are key to the safe handling and separations of the highly radioactive nuclei. This review describes the complexes that have been synthesised to date, presents a critical assessment on the successes and difficulties in their analysis, and the bonding information they have provided. Because of the recent work to start new Np air-sensitive inorganic chemistry labs, the importance of radioactivity, the basics of Np decay and its ramifications (including the radiochemical synthesis of one organometallic) and the available anhydrous starting materials are also surveyed. The review also highlights a range of instances in which important differences in the chemical behaviour between Np and its closest neighbours, uranium and plutonium, are found.JRC.G.I.5-Advanced Nuclear Knowledg

How sustainable agriculture can address the environmental and human health harms of industrial agriculture.

The industrial agriculture system consumes fossil fuel, water, and topsoil at unsustainable rates. It contributes to numerous forms of environmental degradation, including air and water pollution, soil depletion, diminishing biodiversity, and fish die-offs. Meat production contributes disproportionately to these problems, in part because feeding grain to livestock to produce meat--instead of feeding it directly to humans--involves a large energy loss, making animal agriculture more resource intensive than other forms of food production. The proliferation of factory-style animal agriculture creates environmental and public health concerns, including pollution from the high concentration of animal wastes and the extensive use of antibiotics, which may compromise their effectiveness in medical use. At the consumption end, animal fat is implicated in many of the chronic degenerative diseases that afflict industrial and newly industrializing societies, particularly cardiovascular disease and some cancers. In terms of human health, both affluent and poor countries could benefit from policies that more equitably distribute high-protein foods. The pesticides used heavily in industrial agriculture are associated with elevated cancer risks for workers and consumers and are coming under greater scrutiny for their links to endocrine disruption and reproductive dysfunction. In this article we outline the environmental and human health problems associated with current food production practices and discuss how these systems could be made more sustainable

Identifying Target Populations for Screening or Not Screening Using Logic Regression

Colorectal cancer remains a significant public health concern despite the fact that effective screening procedures exist and that the disease is treatable when detected at early stages. Numerous risk factors for colon cancer have been identified, but none are very predictive alone. We sought to determine whether there are certain combinations of risk factors that distinguish well between cases and controls, and that could be used to identify subjects at particularly high or low risk of the disease to target screening. Using data from the Seattle site of the Colorectal Cancer Family Registry (C-CFR), we fit logic regression models to combine risk factor information. Logic regression is a methodology that identifies subsets of the population, described by Boolean combinations of binary coded risk factors. This method is well suited to situations in which interactions between many variables result in differences in disease risk. Neither the logic regression models nor stepwise logistic regression models fit for comparison resulted in criteria that could be used to direct subjects to screening. However, we believe that our novel statistical approach could be useful in settings where risk factors do discriminate between cases and controls, and illustrate this with a simulated dataset

Cell Size Effects on Concentrator Solar Cell Performance

The sun is an abundant power source that is clean and inexhaustible. Photovoltaic devices facilitate the collection of this energy The practice of using relatively inexpensive optics to concentrate light to reduce the amount of expensive semiconductor required has been a large driver in terrestrial application of concentrator photovoltaics (CPV). Solar cell design is critical in optimizing the device for CPV conditions. The goal of this project was to design and optimize GaAs solar cells of sizes ranging from 0.0125cm2 to 0.25cm2 for operation under a light concentration of 500 suns. The parameter of cell size was investigated in this study, as it has major impacts on solar cell perform a nce

Estimating forecast error covariances for strongly coupled atmosphere-ocean 4D-Var data assimilation

Strongly coupled data assimilation emulates the real world pairing of the atmosphere and ocean by solving the assimilation problem in terms of a single combined atmosphere-ocean state. A significant challenge in strongly coupled variational atmosphere-ocean data assimilation is a priori specification of the cross-covariances between the errors in the atmosphere and ocean model forecasts. These covariances must capture the correct physical structure of interactions across the air-sea interface as well as the different scales of evolution in the atmosphere and ocean; if prescribed correctly, they will allow observations in one medium to improve the analysis in the other. Here we investigate the nature and structure of atmosphere-ocean forecast error cross-correlations using an idealised strongly coupled single-column atmosphere-ocean 4D-Var assimilation system. We present results from a set of identical twin experiments that use an ensemble of coupled 4D-Var assimilations to derive estimates of the atmosphere-ocean error cross-correlations. Our results show significant variation in the strength and structure of cross-correlations in the atmosphere-ocean boundary layer between summer and winter and between day and night. These differences provide a valuable insight into the nature of coupled atmosphere-ocean correlations for different seasons and points in the diurnal cycle

The role of cross-domain error correlations in strongly coupled 4D-Var atmosphere-ocean data assimilation

Strongly coupled atmosphere-ocean data assimilation offers the ability to improve information exchange across the modelled air-sea interface by enabling observations in one domain to have a direct influence on the analysis in the other. For incremental 4D-Var assimilation a strongly coupled approach enables both domains to be updated at the beginning of the assimilation window, whether they are observed or not, and is hence more likely to produce consistent initial model states. This is made possible by the explicit inclusion of cross-domain forecast error covariance information in the coupled forecast error covariance matrix. In this study we use an idealised 1D single column coupled atmosphere-ocean model to examine the extent to which explicit cross-domain forecast error covariances play a role in shaping the coupled analysis increments compared to those implicitly generated in the inner-loop of the incremental formulation of the 4D-Var algorithm. This is done via a set of single observation experiments with and without initial cross-domain forecast error covariances prescribed. Using single observations allows us to obtain explicit expressions for the atmosphere and ocean analysis updates, separating out the individual effects of the explicitly prescribed and implicitly generated cross-domain covariances. Our experiments show that when only one domain is observed,including explicit cross-domain error covariances allows more consistent adjustment of the unobserved domain. Neglecting the cross-domain terms and relying solely on the covariances implicitly generated by the coupled tangent linear and adjoint models restricts the ability of the covariance matrix to impose balance between the two domains. In this case the coupling is essentially one-way; the update to the observed domain is independent of the unobserved domain and so is likely to produce atmosphere and ocean updates that are inconsistent with one another. As we show, this has important consequences for the balance of the coupled analysis state

Utilising patient and public involvement to increase the acceptability of brief CBT for OCD in young people

Obsessive Compulsive Disorder (OCD) is a common and debilitating disorder that frequently begins in childhood and adolescence. Previous work (Bolton et al., 2011) has demonstrated that brief CBT (5 sessions), supplemented by therapeutic workbooks, is as effective as more traditional length (12 session) therapist-delivered treatment for adolescents with OCD. However, as was typical at the time, the treatment was developed with very limited patient and public involvement (PPI) and was delivered in the context of a randomised controlled trial which might affect translation to routine child and adolescent mental health services (CAMHS). To be able to implement such treatment within routine clinical services, it is crucial that it acceptable to young people, their families and the clinicians delivering the treatment. The aim of this project was to improve the acceptability of the brief treatment through PPI and consultation with clinicians and consider issues relating to implementation. This was done through written feedback, interviews and focus groups with five adolescents and two parents, and a focus group and a half-day workshop with 12 clinicians. This led to revisions to the workbooks and materials to improve (a) acceptability by updating the design through changes to wording, language, and images and to ensure that they were consistent with values of equality, diversity, and inclusion, and (b) usability by clarifying, adding, removing content, and organising the materials in new ways. We emphasise the importance of continued PPI throughout the project to maximise the translation of findings into practice

Sex-specific predictors of improved walking with step-monitored, home-based exercise in peripheral artery disease

The aim of this study was to determine whether baseline clinical characteristics and the duration and intensity of ambulation during our step-monitored home-based exercise program were predictive of changes in ambulatory outcomes at completion of the program in symptomatic patients with peripheral artery disease (PAD). Twenty-two men (ankle–brachial index (ABI) = 0.71 ± 0.19) and 24 women (ABI = 0.66 ± 0.23) completed the home exercise program, consisting of intermittent walking to mild-to-moderate claudication pain for 3 months. Ambulatory outcome measures were peak walking time (PWT) and claudication onset time (COT) during a treadmill test, and the distance recorded during a 6-minute walk distance test (6MWD). Men experienced significant increases (p<0.01) in COT, PWT, and 6MWD following the home exercise program, and women had significant increases in 6MWD (p<0.01) and PWT (p<0.05). In women, average exercise cadence during the home exercise sessions was the only predictor that entered the model for change in COT (p=0.082), and was the first predictor in the model for change in PWT (p=0.029) and 6MWD (p=0.006). In men, the ABI was the only predictor that entered the model for change in 6MWD (p=0.002), and ABI was a predictor along with metabolic syndrome in the model for change in COT (p=0.003). No variables entered the model for change in PWT. Faster ambulatory cadence during the step-monitored home-based exercise program may predict greater improvements in ambulatory function in women, whereas having less severe PAD and comorbid burden at baseline may predict greater improvements in ambulatory function in men. ClinicalTrials.gov Identifier: NCT00618670Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline