Determinants of stock market development in Nigeria using error correction model approach

Harnessing economic resources for national development is a major goal of governments; the stock market provides the medium through which funds could be mobilized and allocated for investments for development. This study sought to examine empirically whether stock market liquidity, savings rate, investment ratio, and foreign direct investment (FDI) were determinants of stock market development in Nigeria from 1970-2007. Using secondary data from the Central Bank of Nigeria Statistical Bulletin, 2007, and adopting co-integration and error correction mechanism (ECM), we found that stock market liquidity, savings rate, and one-period lagged stock market development were significant predictors of stock market development in Nigeria. It implies that improving liquidity of the market would impact the stock market; more domestic firms should be encouraged to enlist in the market and Nigerian businessmen abroad should enlist their  companies in their home stock market to increase liquidity in the market

A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection

Background: Applying a statistical method implies identifying underlying (model) assumptions and checking their validity in the particular context. One of these contexts is association modeling for epistasis detection. Here, depending on the technique used, violation of model assumptions may result in increased type I error, power loss, or biased parameter estimates. Remedial measures for violated underlying conditions or assumptions include data transformation or selecting a more relaxed modeling or testing strategy. Model-Based Multifactor Dimensionality Reduction (MB-MDR) for epistasis detection relies on association testing between a trait and a factor consisting of multilocus genotype information. For quantitative traits, the framework is essentially Analysis of Variance (ANOVA) that decomposes the variability in the trait amongst the different factors. In this study, we assess through simulations, the cumulative effect of deviations from normality and homoscedasticity on the overall performance of quantitative Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect 2-locus epistasis signals in the absence of main effects. Methodology: Our simulation study focuses on pure epistasis models with varying degrees of genetic influence on a quantitative trait. Conditional on a multilocus genotype, we consider quantitative trait distributions that are normal, chi-square or Student's t with constant or non-constant phenotypic variances. All data are analyzed with MB-MDR using the built-in Student's t-test for association, as well as a novel MB-MDR implementation based on Welch's t-test. Traits are either left untransformed or are transformed into new traits via logarithmic, standardization or rank-based transformations, prior to MB-MDR modeling. Results: Our simulation results show that MB-MDR controls type I error and false positive rates irrespective of the association test considered. Empirically-based MB-MDR power estimates for MB-MDR with Welch's t-tests are generally lower than those for MB-MDR with Student's t-tests. Trait transformations involving ranks tend to lead to increased power compared to the other considered data transformations. Conclusions: When performing MB-MDR screening for gene-gene interactions with quantitative traits, we recommend to first rank-transform traits to normality and then to apply MB-MDR modeling with Student's t-tests as internal tests for association

A novel optical microscope for imaging large embryos and tissue volumes with sub-cellular resolution throughout

Current optical microscope objectives of low magnification have low numerical aperture and therefore have too little depth resolution and discrimination to perform well in confocal and nonlinear microscopy. This is a serious limitation in important areas, including the phenotypic screening of human genes in transgenic mice by study of embryos undergoing advanced organogenesis. We have built an optical lens system for 3D imaging of objects up to 6 mm wide and 3 mm thick with depth resolution of only a few microns instead of the tens of microns currently attained, allowing sub-cellular detail to be resolved throughout the volume. We present this lens, called the Mesolens, with performance data and images from biological specimens including confocal images of whole fixed and intact fluorescently-stained 12.5-day old mouse embryos

Multilocus sequence typing (MLST) analysis of Vibrio cholerae O1 El Tor isolates from Mozambique that harbour the classical CTX prophage.

Vibrio cholerae O1 isolates belonging to the Ogawa serotype, El Tor biotype, harbouring the classical CTX prophage were first isolated in Mozambique in 2004. Multilocus sequence typing (MLST) analysis using nine genetic loci showed that the Mozambique isolates have the same sequence type (ST) as O1 El Tor N16961, a representative of the current seventh cholera pandemic. Analysis of the CTX prophage in the Mozambique isolates indicated that there is one type of rstR in these isolates: the classical CTX prophage. It was also found that the ctxB-rstR-rstA-rstB-phs-cep fragment was PCR-amplified from these isolates, which indicates the presence of a tandem repeat of the classical CTX prophage in the genome of the Mozambique isolates. The possible origin of these isolates and the presence of the tandem repeat of the classical prophage in them implicate the presence of the classical CTX phage

The IL-33:ST2 axis is unlikely to play a central fibrogenic role in idiopathic pulmonary fibrosis

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a devastating interstitial lung disease (ILD) with limited treatment options. Interleukin-33 (IL-33) is proposed to play a role in the development of IPF however the exclusive use of prophylactic dosing regimens means that the therapeutic benefit of targeting this cytokine in IPF is unclear. METHODS: IL-33 expression was assessed in ILD lung sections and human lung fibroblasts (HLFs) by immunohistochemistry and gene/protein expression and responses of HLFs to IL-33 stimulation measured by qPCR. In vivo, the fibrotic potential of IL-33:ST2 signalling was assessed using a murine model of bleomycin (BLM)-induced pulmonary fibrosis and therapeutic dosing with an ST2-Fc fusion protein. Lung and bronchoalveolar lavage fluid were collected for measurement of inflammatory and fibrotic endpoints. Human precision-cut lung slices (PCLS) were stimulated with transforming growth factor-β (TGFβ) or IL-33 and fibrotic readouts assessed. RESULTS: IL-33 was expressed by fibrotic fibroblasts in situ and was increased by TGFβ treatment in vitro. IL-33 treatment of HLFs did not induce IL6, CXCL8, ACTA2 and COL1A1 mRNA expression with these cells found to lack the IL-33 receptor ST2. Similarly, IL-33 stimulation had no effect on ACTA2, COL1A1, FN1 and fibronectin expression by PCLS. Despite having effects on inflammation suggestive of target engagement, therapeutic dosing with the ST2-Fc fusion protein failed to reduce BLM-induced fibrosis measured by hydroxyproline content or Ashcroft score. CONCLUSIONS: Together these findings suggest the IL-33:ST2 axis does not play a central fibrogenic role in the lungs with therapeutic blockade of this pathway unlikely to surpass the current standard of care for IPF

Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region

Background: Effective response to emerging infectious disease (EID) threats relies on health care systems that can detect and contain localised outbreaks before they reach a national or international scale. The Asia-Pacific region contains low and middle income countries in which the risk of EID outbreaks is elevated and whose health care systems may require international support to effectively detect and respond to such events. The absence of comprehensive data on populations, health care systems and disease characteristics in this region makes risk assessment and decisions about the provision of such support challenging.\ud \ud Methodology/principal findings: We describe a mathematical modelling framework that can inform this process by integrating available data sources, systematically explore the effects of uncertainty, and provide estimates of outbreak risk under a range of intervention scenarios. We illustrate the use of this framework in the context of a potential importation of Ebola Virus Disease into the Asia-Pacific region. Results suggest that, across a wide range of plausible scenarios, preemptive interventions supporting the timely detection of early cases provide substantially greater reductions in the probability of large outbreaks than interventions that support health care system capacity after an outbreak has commenced.\ud \ud Conclusions/significance: Our study demonstrates how, in the presence of substantial uncertainty about health care system infrastructure and other relevant aspects of disease control, mathematical models can be used to assess the constraints that limited resources place upon the ability of local health care systems to detect and respond to EID outbreaks in a timely and effective fashion. Our framework can help evaluate the relative impact of these constraints to identify resourcing priorities for health care system support, in order to inform principled and quantifiable decision making

Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

Nitrogen fixation by the Haber–Bosch process has more than doubled the amount of fixed N on Earth, significantly influencing the global N cycle. Much of this fixed N is made into N fertilizer that is used to produce nearly half of the world’s food. Too much of the N fertilizer pollutes air and water when it is lost from agroecosystems through volatilization, denitrification, leaching, and runoff. Most of the N fertilizer used in the United States is applied to corn (Zea mays L.), and the profitability and environmental footprint of corn production is directly tied to N fertilizer applications. Accurately predicting the amount of N needed by corn, however, has proven to be challenging because of the effects of rainfall, temperature, and interactions with soil properties on the N cycle. For this reason, improving N recommendations is critical for profitable corn production and for reducing N losses to the environment. The objectives of this paper were to review current methods for estimating N needs of corn by: (i) reviewing fundamental background information about how N recommendations are created; (ii) evaluating the performance, strengths, and limitations of systems and tools used for making N fertilizer recommendations; (iii) discussing how adaptive management principles and methods can improve recommendations; and (iv) providing a framework for improving N fertilizer rate recommendations

Attitudes of Illinois Farmers Regarding Deer and Deer Hunters, 1990

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