2,876 research outputs found
Community-level characteristics of high infant mortality: A tool to identify at-risk communities
Infant mortality (IM) rate is a key indicator of population health and has been gradually improving in the United States. However, it is still a public health problem among minority and low-income communities. Maternal factors explain some of the variation, but community-level factors may also be a contributor. This study examines measures to identify a set of indicators that explain variations in IM at the community-level. Data for 77 communities in a city were obtained from local health databases. We used multivariable linear regression models to examine the strength of the association between IM and maternal, population, community wealth, and social capital characteristics. Community-level IM rates ranged from 2.1 – 25.6 deaths per 1,000 live births in 2000-2002. The final model explained 75% of the variation in IM rates at the community-level (R2=0.75). The model included a high percentage of low birth weight babies, a decline in mothers who began prenatal care in the second trimester, an increase in the percentage of Hispanics, increased unemployment rates, an increase in the percentage of veterans, an increased rate of foreign-born residents, and smaller average family sizes. Social capital variables, homicide rate and vacant housing, were also significant in the final model. Identifying communities at risk for high IM rates is imperative to improve maternal and child health outcomes because of shortages in public health resources. The development of a parsimonious set of community-level indicators can assist public health practitioners in targeting their resources to prevent infant mortality in high-risk communities
Evaluating the Impacts of Information and Communication Technology (ICT) on Trade in Fruit and Vegetables within the APEC Countries
The global food marketing network is being constantly reshaped, providing opportunities and challenges to the use of information and communication technology (ICT) to develop international trade in food products. ICT is likely to be especially important for food products such as fresh fruit and vegetables that are differentiated and sensitive to timeliness in supply, possess varied quality dimensions, and involve considerable supply accumulation and assortment. Digital ICT (Internet and mobile phones), in particular, is expected to facilitate international trade and encourage efficiency in the fruit and vegetables marketing system in two main ways. First, it reduces communication and search costs through cheaper and more effective media. Second, it improves market information and corrects information externalities along the supply chain, by promoting greater price transparency and enabling consumer preferences and tastes to be more precisely met. We employed a gravity model of international trade to test the hypothesis that ICT positively affects bilateral international trade in fruit and vegetables between member Asia-Pacific Economic Cooperation (APEC) economies in the period from 1997 to 2006. Explanatory variables include the usage of the Internet, mobile telephones and fixed telephone lines, and a broad range of factors that might determine the value of bilateral trade such as income per capita, population, distance between trading partners and common language. A Poisson pseudo-maximum likelihood model was estimated in order to handle zero trade observations and reduce biases caused by heteroskedasticity. Empirical results were not quite as expected, with relatively minor impact of digital ICT. They suggest that using digital ICT has significant positive effects on trade in fruit and vegetables between APEC countries only for the Internet in exporting countries. A stronger positive impact was discerned for the traditional form of ICT, fixed telephone lines in exporting importing countries. Nevertheless, fostering the development of digital ICT infrastructure and its diffusion should make exporters in APEC countries more competitive in the fruit and vegetables supply chain through the Internet effect, and boost their trade values in these products.International Relations/Trade,
Growth and population parameters of the world’s northernmost harbour seals Phoca vitulina residing in Svalbard, Norway
Self-assembling nanoparticles containing dexamethasone as a novel therapy in allergic airways inflammation.
Nanocarriers can deliver a wide variety of drugs, target them to sites of interest, and protect them from degradation and inactivation by the body. They have the capacity to improve drug action and decrease undesirable systemic effects. We have previously developed a well-defined non-toxic PEG-dendritic block telodendrimer for successful delivery of chemotherapeutics agents and, in these studies, we apply this technology for therapeutic development in asthma. In these proof-of-concept experiments, we hypothesized that dexamethasone contained in self-assembling nanoparticles (Dex-NP) and delivered systemically would target the lung and decrease allergic lung inflammation and airways hyper-responsiveness to a greater degree than equivalent doses of dexamethasone (Dex) alone. We found that ovalbumin (Ova)-exposed mice treated with Dex-NP had significantly fewer total cells (2.78 ± 0.44 × 10(5) (n = 18) vs. 5.98 ± 1.3 × 10(5) (n = 13), P<0.05) and eosinophils (1.09 ± 0.28 × 10(5) (n = 18) vs. 2.94 ± 0.6 × 10(5) (n = 12), p<0.05) in the lung lavage than Ova-exposed mice alone. Also, lower levels of the inflammatory cytokines IL-4 (3.43 ± 1.2 (n = 11) vs. 8.56 ± 2.1 (n = 8) pg/ml, p<0.05) and MCP-1 (13.1 ± 3.6 (n = 8) vs. 28.8 ± 8.7 (n = 10) pg/ml, p<0.05) were found in lungs of the Dex-NP compared to control, and they were not lower in the Dex alone group. In addition, respiratory system resistance was lower in the Dex-NP compared to the other Ova-exposed groups suggesting a better therapeutic effect on airways hyperresponsiveness. Taken together, these findings from early-stage drug development studies suggest that the encapsulation and protection of anti-inflammatory agents such as corticosteroids in nanoparticle formulations can improve efficacy. Further development of novel drugs in nanoparticles is warranted to explore potential treatments for chronic inflammatory diseases such as asthma
Perturbative Wilson loops from unquenched Monte Carlo simulations at weak couplings
Perturbative expansions of several small Wilson loops are computed through
next-to-next-to-leading order in unquenched lattice QCD, from Monte Carlo
simulations at weak couplings. This approach provides a much simpler
alternative to conventional diagrammatic perturbation theory, and is applied
here for the first time to full QCD. Two different sets of lattice actions are
considered: one set uses the unimproved plaquette gluon action together with
the unimproved staggered-quark action; the other set uses the one-loop-improved
Symanzik gauge-field action together with the so-called ``asqtad''
improved-staggered quark action. Simulations are also done with different
numbers of dynamical fermions. An extensive study of the systematic
uncertainties is presented, which demonstrates that the small third-order
perturbative component of the observables can be reliably extracted from
simulation data. We also investigate the use of the rational hybrid Monte Carlo
algorithm for unquenched simulations with unimproved-staggered fermions. Our
results are in excellent agreement with diagrammatic perturbation theory, and
provide an important cross-check of the perturbation theory input to a recent
determination of the strong coupling by the HPQCD
collaboration.Comment: 14 pages, 8 figure
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