The Cognitive Link Between Geography and Development: Iodine Deficiency and Schooling Attainment in Tanzania

An estimated 20 million children born each year are at risk of brain damage from in utero iodine deficiency, the only micronutrient deficiency known to have significant, non-reversible effects on cognitive development. Cognitive damage from iodine deficiency disorders (IDD) has potentially important implications for economic growth through its effect on human capital attainment. To gauge the magnitude of this influence, we evaluate the impact of reductions in fetal IDD on child schooling attainment that resulted from an intensive distribution of iodized oil capsules (IOC) in Tanzania. We look for evidence of improvements in cognitive ability attributable to the intervention by assessing whether children who benefited from IOC in utero exhibit higher rates of grade progression at ages 10 to 14 relative to siblings and older and younger children in the district who did not. Our findings suggest that reducing fetal IDD has significant benefits for child cognition: Protection from IDD in utero is associated with 0.36 years of additional schooling. Furthermore, the effect appears to be substantially larger for girls, consistent with new evidence from laboratory studies indicating greater cognitive sensitivity of the female fetus to maternal thyroid deprivation. There is no indication that IOC improved rates of illness or school absence due to illness, suggesting that IOC improves schooling through its effect on cognition rather than its effect on health. However, there is weak evidence that the program also reduced child but not fetal or infant mortality, which may bias downward the estimated effect on education. Cross-country regression estimates corroborate the results from Tanzania, indicating a strong negative influence of total goiter rate and strong positive influence of salt iodization on female school participation. Together, these findings provide micro-level evidence of the direct influence of ecological conditions on economic development and suggest a potentially important role of variation in rates of learning disability in explaining cross-country growth patterns and gender differences in schooling attainment.

Building Social Capital Through MicroFinance

A number of development assistance programs promote community interaction as a means of building social capital. Yet, despite strong theoretical underpinnings, the role of repeat interactions in sustaining cooperation has proven difficult to identify empirically. We provide the first experimental evidence on the economic returns to social interaction in the context of microfinance. Random variation in the frequency of mandatory meetings across first-time borrower groups generates exogenous and persistent changes in clients' social ties. We show that the resulting increases in social interaction among clients more than a year later are associated with improvements in informal risk-sharing and reductions in default. A second field experiment among a subset of clients provides direct evidence that more frequent interaction increases economic cooperation among clients. Our results indicate that group lending is successful in achieving low rates of default without collateral not only because it harnesses existing social capital, as has been emphasized in the literature, but also because it builds new social capital among participants.

Social security health insurance for the informal sector in Nicaragua: a randomized evaluation

This article presents the results from an experimental evaluation of a voluntary health insurance program for informal sector workers in Nicaragua. Costs of the premiums as well as enrollment location were randomly allocated. Overall, take-up of the program was low, with only 20% enrollment. Program costs and streamlined bureaucratic procedures were important determinants of enrollment. Participation of local microfinance institutions had a slight negative effect on enrollment. One year later, those who received insurance substituted toward services at covered facilities and total out-of-pocket expenditures fell. However, total expenditures fell by less than the insurance premiums. We find no evidence of an increase in health-care utilization among the newly insured. We also find very low retention rates after the expiration of the subsidy, with less than 10% of enrollees still enrolled after one year. To shed light on the findings from the experimental results, we present qualitative evidence of institutional and contextual factors that limited the success of this program. Copyright © 2010 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77966/1/1635_ftp.pd

Two Origins for the Gene Encoding α-Isopropylmalate Synthase in Fungi

BACKGROUND: The biosynthesis of leucine is a biochemical pathway common to prokaryotes, plants and fungi, but absent from humans and animals. The pathway is a proposed target for antimicrobial therapy. METHODOLOGY/PRINCIPAL FINDINGS: Here we identified the leuA gene encoding alpha-isopropylmalate synthase in the zygomycete fungus Phycomyces blakesleeanus using a genetic mapping approach with crosses between wild type and leucine auxotrophic strains. To confirm the function of the gene, Phycomyces leuA was used to complement the auxotrophic phenotype exhibited by mutation of the leu3+ gene of the ascomycete fungus Schizosaccharomyces pombe. Phylogenetic analysis revealed that the leuA gene in Phycomyces, other zygomycetes, and the chytrids is more closely related to homologs in plants and photosynthetic bacteria than ascomycetes or basidiomycetes, and suggests that the Dikarya have acquired the gene more recently. CONCLUSIONS/SIGNIFICANCE: The identification of leuA in Phycomyces adds to the growing body of evidence that some primary metabolic pathways or parts of them have arisen multiple times during the evolution of fungi, probably through horizontal gene transfer events

Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Development and validation of HERWIG 7 tunes from CMS underlying-event measurements

This paper presents new sets of parameters (“tunes”) for the underlying-event model of the HERWIG7 event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in HERWIG7, and are obtained from a fit to minimum-bias data collected by the CMS experiment at s=0.9, 7, and 13Te. The tunes are based on the NNPDF 3.1 next-to-next-to-leading-order parton distribution function (PDF) set for the parton shower, and either a leading-order or next-to-next-to-leading-order PDF set for the simulation of MPI and the beam remnants. Predictions utilizing the tunes are produced for event shape observables in electron-positron collisions, and for minimum-bias, inclusive jet, top quark pair, and Z and W boson events in proton-proton collisions, and are compared with data. Each of the new tunes describes the data at a reasonable level, and the tunes using a leading-order PDF for the simulation of MPI provide the best description of the dat

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe