33,037 research outputs found
Economic Well-Being of Farm Households
Farm subsidy programs were introduced in the 1930s largely due to concern for chronically low, and highly variable, incomes of US farm households. Today commodity-based support programs are still prominent, though income and wealth of the average farm household now exceed that of the average nonfarm households - by a large margin. Farm income continues to be highly variable, but the small set of farm households most at risk for income variability - because farm income represents more than one-third of household income - are those operating large farms. And they have substantial net worth, which cushions uncertain farm income.Farm households, household income, household wealth, household net worth, living expenses, joint income-wealth indicator, economic well-being, financial well-being, Off-farm employment, Income variability, ERS, USDA, Consumer/Household Economics,
Structural templating as a route to improved photovoltaic performance in copper phthalocyanine/fullerene (C60) heterojunctions
We have developed a method to improve the short circuit current density in copper phthalocyanine (CuPc)/fullerene (C60) organic solar cells by ~60% by modifying the CuPc crystal orientation through use of a molecular interlayer to maximize charge transport in the direction between the two electrodes. Powder x-ray diffraction and electronic absorption spectroscopy show that a thin 3,4,9,10-perylenetetracarboxylic dianhydride interlayer before CuPc growth templates the CuPc film structure, forcing the molecules to lie flat with respect to the substrate surface, although the intrastack orientation is unaffected. This modified stacking configuration facilitates charge transport and improves charge collection
The OSIRIS Lens-Amplified Survey (OLAS) I: Dynamical Effects of Stellar Feedback in Low Mass Galaxies at z ~ 2
We introduce the OSIRIS Lens-Amplified Survey (OLAS), a kinematic survey of
gravitationally lensed galaxies at cosmic noon taken with Keck adaptive optics.
In this paper we present spatially resolved spectroscopy and nebular emission
kinematic maps for 17 star forming galaxies with stellar masses 8 <
log(/) < 9.8 and redshifts 1.2 < z < 2.3. OLAS is designed to
probe the stellar mass () and specific star formation rate (sSFR) range
where simulations suggest that stellar feedback is most effective at driving
gaseous outflows that create galaxy-wide potential fluctuations which can
generate dark matter cores. We compare our kinematic data with the trend
between sSFR, and H velocity dispersion, , from the
Feedback In Realistic Environments (FIRE) simulations. Our observations reveal
a correlation between sSFR and sigma at fixed that is similar to the
trend predicted by simulations: feedback from star formation drives
star-forming gas and newly formed stars into more dispersion dominated orbits.
The observed magnitude of this effect is in good agreement with the FIRE
simulations, in which feedback alters the central density profiles of low mass
galaxies, converting dark matter cusps into cores over time. Our data support
the scenario that stellar feedback drives gaseous outflows and potential
fluctuations, which in turn drive dark matter core formation in dwarf galaxies.Comment: 9 pages (5 figures) with 9 page appendix (17 figures). Accepted to
Ap
Healthcare decision-making: past present and future, in light of a diagnosis of dementia
End-of-life care policy in the UK states that all people should identify their needs, priorities and preferences for end-of-life care in the form of advance care planning. Advance care planning in dementia is less well developed than in some other disease groups such as cancer and, arguably, may be more complex. A person with dementia may lose the capacity to make decisions associated with advance care planning early in the course of the disease, requiring more involvement of family carers. This study explores the 'lived' context to health care decision-making of dyads (the person with dementia and their carer) in respect of past, present and future healthcare decision-making
Biodiversity assessment across a dynamic riverine system: A comparison of eDNA metabarcoding versus traditional fish surveying methods
While many studies have considered the ability of eDNA to assess animal communities in lacustrine settings, fewer have considered riverine systems, particularly those spanning the environmental gradients present in large river basins. Such dynamic systems are challenging for eDNA biomonitoring due to differing eDNA transport distances in rivers and the effects of river chemistry. To address this challenge, we focused on the Thames River system, UK, which has exceptional historical fish records providing a baseline to test the accuracy of eDNA metabarcoding in recovering fish community structure across both fresh and tidal zones. Two primer sets targeting 12S and CO1 regions were used to capture fish communities across the Thames catchment, from the upper freshwaters to the mid estuary. eDNA was collected at 35Â sites, 14 of which were simultaneously paired with traditional fish surveys for direct comparison. We demonstrated that eDNA metabarcoding consistently detected more freshwater species than traditional methods, despite extensive sampling effort using the latter. In contrast, metabarcoding did not perform as well as traditional approaches in estuarine waters, although results included the novel detection of the protected sea lamprey. We further demonstrated that minor variations in the recovery of all approaches would not impact on the assessment of simple ecological models of community structure and, thus, some variability between approaches should not be viewed as a serious hindrance to uptake. Rather, our findings support a growing consensus that eDNA can reliably detect fish communities across dynamic freshwater habitats
High frequency environmental DNA metabarcoding provides rapid and effective monitoring of fish community dynamics
Long-term monitoring is critical to measure the response of biodiversity patterns and processes to human-mediated environmental pressures. This is particularly pertinent in freshwaters, where recent estimates indicated a third of all fish species are threatened with extinction, making ongoing biomonitoring essential for conservation management. High frequency annual monitoring is critical for identifying temporal changes in fish community composition; however, traditional survey methods are typically less practical over such timeframes. While environmental (e)DNA measurement represents a potentially powerful tool for monitoring temporal community dynamics, studies are lacking. To address this deficit, we generated a high frequency time-series dataset of entire fish communities using eDNA metabarcoding, to directly assess the repeatability and sensitivity of this method for detecting annual population trends. We targeted two differing environments (freshwater vs. intertidal) within the Thames catchment, UK, where detailed historical records from traditional monitoring were available for comparison. To test how robust eDNA data is for inferring the known community, we applied a hierarchical, nested design encompassing short and longer-term variation in eDNA data. Our analyses showed that irrespective of environment, eDNA metabarcoding represented known seasonal shifts in fish communities, where increased relative read abundance of eDNA coincided with known migratory and spawning events, including those of the critically endangered native species Anguilla anguilla (European eel). eDNA species detections across a single year included over 75% of species recorded in a ca. 30-year historical dataset, highlighting the power of eDNA for species detection. Our findings provide greater insight into the utility of eDNA metabarcoding for recovering temporal trends in fish communities from dynamic freshwater systems and insight into the potential best sampling strategy for future eDNA surveys
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Enrichment and preserved functionality of multipotential stromal cells in bone marrow concentrate processed by vertical centrifugation
The concentration of bone marrow (BM) aspirate (BMA) is increasingly valued for bone and cartilage repair, particularly with the rarity and donor-variability of BM-multipotential stromal cells (BM-MSCs). The present study aimed to assess BM-MSC yield following BM concentration using a fast and compact-sized vertical centrifugation system. BMA concentrate (BMAC) was separated in a 1 min process and collected easily after an automatic discarding of plasma and red blood cells. A significant increase in CD45low CD271high cells per BMAC volume (measured using flow-cytometry) was noted (4-fold, p = 0.0001). Additionally, the vertical centrifugation system helped to enrich colony numbers (assessed by CFU-F assays) in BMAC comparably with conventional centrifugation systems, BioCUE™ and SmartPReP-2® (4.3-fold, 4.6-fold and 3-fold, respectively). Next, a functional assessment of BM-MSCs processed by vertical centrifugation was performed, and MSC viability and proliferation were not affected. Also, these BM-MSCs showed similar alkaline phosphatase and calcium levels to those of BMA-MSCs when osteogenically induced. Furthermore, glycosaminoglycans and Nile red levels in addition to the gene expression assays confirmed that there was no significant change in chondrogenic or adipogenic abilities between BMA-MSCs and BMAC-MSCs. The expression levels of selected angiogenic and immunomodulatory mediators were also similar between the two groups. Collectively, the vertical centrifugation system helped to enrich BM-MSCs effectively, while maintaining cell viability and functions. Thus, such a vertical centrifugation system for BM concentration can be valuable for various regenerative therapies
The Glucocorticoid Receptor and Certain KRÃœPPEL-Like Transcription Factors have the Potential to Synergistically Stimulate Bovine Herpesvirus 1 Transcription and Reactivation from Latency
Bovine herpesvirus 1 (BoHV-1), an important bovine pathogen, establishes life-long latency in sensory neurons within trigeminal ganglia (TG). Stress, as mimicked by the synthetic corticosteroid dexamethasone, consistently induces reactivation in calves latently infected with BoHV-1. Dexamethasone induces expression of several transcription factors in TG neurons during early stages of reactivation, including Krüppel-like transcription factors (KLF): KLF4, KLF6, KLF15, and promyelocytic leukemia zinc finger. Furthermore, the glucocorticoid receptor (GR) is consistently detected in TG neurons expressing viral regulatory proteins during reactivation from latency. The viral immediate early transcription unit 1 (IEtu1) promoter that drives expression of two viral transcription factors (bICP0 and bICP4) contains two GR response elements (GREs) and is stimulated by DEX. KLF15 and the GR form a feed forward transcription loop that synergistically stimulates productive infection and IEtu1 promoter activity. New studies demonstrate the GR and KLF6 synergistically stimulate productive infection and IEtu1 promoter activity if the GREs are intact. Furthermore, the GR and KLF6 interact with wild-type GREs within the IEtu1 promoter, but not GRE mutants. These studies suggest that certain KLF family members and the GR can convert a silent viral genome in latently infected neurons into an actively transcribing genome during reactivation from latency
Episodes in space: qualitative representation and reasoning over spatio-temporal objects
There is growing interest in many application domains for the temporal treatment and manipulation of spatially referenced objects. Handling the time dimension in spatial databases can greatly enhance and extend their functionality and usability by offering means of understanding the spatial behaviour in time. Few works, to date, have been directed towards the development of formalisms for representation and reasoning in this domain. In this paper, a new approach is presented for the representation and reasoning over spatio-temporal relationships. The approach is simple and aims to satisfy the requirements of coherency, expressiveness and reasoning power. Consistent behaviours of spatial objects in time are denoted episodes. The topology of the domain is defined by decomposing episodes into representative components and relationships are defined between those components. Spatio-temporal reasoning is achieved by composing the relationships between the object components using constraint networks. New composition tables between simple spatio-temporal regions and between regions and volumes are also derived and used in the reasoning process
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