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P¿Countries are showing interest in accumulating foreign reserves to ensure macroeconomic stability. There has been some debate whether to beef up the level of nations' foreign reserves or make it lower, especially in developing countries like Nigeria. Whereas some argue that the foreign reserve determines the country's rating in the global market, others hold opposing views. In this light, this paper examined the interactive influence of foreign reserve (FRS) on some macroeconomic variables such as: economic size (GDP); trade; level of capital inflows (KFL); exchange rate (EXR); and inflation. Analyzing secondary data from CBN statistical bulletins (1970-2007), the econometric results obtained from cointegration test, vector error correction (VEC) within the framework of autoregressive distributed lags (ARDL) revealed the following: (1) existence of a long-run relationship between the variables and two cointegrating equations; (2) possibility of convergence of the variables from the short run to the long run with slow speed of adjustment. It is thus the conclusion of this paper that accumulation of large foreign reserves is not very productive in Nigeria due to its inability to induce some of the macroeconomic variables.

In this paper, we examine the differences in information asymmetry and financing patterns and a generalized version of the trade-off theory across countries with different institutional environments. We find that firms in Civil law countries have higher information asymmetry, rely more on internally generated funds, and use more short-term debt to finance their financing deficit, relative to those in Common law countries. In both Civil law and Common law countries, factors suggested by the trade-off theory explain the financing deficit coefficient in the generalized version of the trade-off model. Overall, the generalized version of the trade-off theory provides a better explanation for the changes in capital structure relative to the pecking order theory, even in countries with higher information asymmetry.

How do noise and manipulation affect the accuracy of collective decision rules? This paper presents simulation results that measure the accuracy of ten well known collective decision rules under noise and manipulation. When noise is low these rules can be divided into accurate ("good") and inaccurate ("bad") groups. The bad rules' accuracy improves, sometimes significantly, when noise increases while the good rules' performance steadily worsens with noise. Also, when noise increases the accuracy of the good rules deteriorates at different rates. Manipulation delays the effects of noise: Accuracy improvement and deterioration due to noise emerge only at higher noise levels with manipulation than without it. In some cases at high noise levels there is only a negligible difference between the accuracy of good and bad collective decision rules. © 2009 Springer-Verlag Berlin Heidelberg.

For small open economies, an understanding of movements in the exchange rate is imperative in analyzing trade and capital flows. In addition, reliable forecasting of exchange rate volatility is important in risk-taking assessment and investment decision-making, both of which are critical to long-term growth. Using an asymmetric GARCH-type approach, this paper examines the implications of economic liberalization on the stochastic behavior of the exchange rate series in a sample of sub-Sahara African (SSA) countries over the 1970-2004 period. The results indicate that exchange rate volatility is variable, and is less volatile under fixed exchange rate regime (pre-economic liberalization) and higher under flexible regime (post-economic liberalization), that is, it is asymmetric. For most of the countries, the EGARCH and TGARCH models are robust to parameter stability and gives better forecasting performance compared to the standard GARCH model.

Emerging market stock returns have been characterized as having higher volatility than returns in the more developed markets. But previous studies give little attention to the fundamentals driving the reported levels of volatility. This paper investigates whether dynamics in key macroeconomic indicators like exchange rates, interest rates, industrial production and money supply in four Latin American countries significantly explain market returns. The MSCI world index and the U.S. 3-month T-bill yield are also included to proxy the effects of global variables. Using a six-variable vector autoregressive (VAR) model, the study finds that the global factors are consistently significant in explaining returns in all the markets. The country variables are found to impact the markets at varying significance and magnitudes. These findings may have important implications for decision-making by investors and national policymakers. © 2006 Elsevier Inc. All rights reserved.

In an attempt to predict a peak in the US economy using a classical statistical decision methodology and a Bayesian methodology and using the 1996 revised composite leading economic indicators (CLI), it is learned that the Bayesian models have generally outperformed the classical statistical ones and, among the Bayesian models, the two using two and three consecutive CLI growth rates are superior in reliability and in accuracy. These two models, however, failed to correctly predict the 2001 recession. In investigating the reasons behind their failures, we learned that: (1) if the concurrent data for the economic structure of 1983-1999 are used for the prediction, they have also been able to predict the 2001 recession correctly, but their overall reliability is not as strong as before; (2) given the overwhelming weight of the monetary policy tools in the CLI-1996 design and the combination of the economic and political events in the year 2000, the less than expected effectiveness of the monetary policy since 2001 has contributed to this failure; and (3) a possible structural change in the US economy since 2000 has also contributed to this prediction failure. © World Scientific Publishing Company.

The Ferrar Large Igneous Province forms a linear belt for 3500 km along the Transantarctic Mountains, and as a geochemical province extends into southeastern Australasia. The principal components of the Ferrar are: intrusive - Ferrar Dolerite sills and dikes, and Dufek intrusion; pyroclastic - the Prebble, Mawson and Exposure Hill Formations; effusive - the Kirkpatrick Basalt. In terms of the three dimensional architecture of the Ferrar, a range of "facies" can be recognized in each of the principal components. The Ferrar province was initiated with a major episode of phreatomagmatism leading to formation of tephra cones and associated deposits, and near-surface vent structures. Activity switched to predominantly quiet effusion of alternating thick flood basalt flows and thin pahoehoe lobes and flows. Intrusive bodies were emplaced early, given the occurrence of dolerite clasts in tuff-breccias, but most sills were probably intruded after accumulation of extrusive rocks. Pre-existing rift structures played a major role in controlling the transport and distribution of the Ferrar magmas and the apparent centers of extrusive activity. The associated paleohydrology controlled the eruption styles. © 2008.

Albeit growing in number, lesbian mothers and their children remain a statistical minority in schools. Lesbian mothers in this study described their families as “normal” or “just like any other family.” From the perspective of queer theory, normal is a socially constructed and insidious concept. This study analyzes both the strategies participants used to be recognized as normal in their children’s schools and the reasons such recognition was perceived to be important by participants. © 2009 Taylor & Francis Group, LLC.

Recent debates regarding same-sex marriage and gay and lesbian adoption highlight the role of schools as sociopolitical institutions. Accordingly, teachers operating within social norms have considerable influence through their interactions with students and their families. Previous research points to lesbian, gay, bisexual, and transgender (LGBT) parents' frustrations with their children's schools, particularly as teachers resist representing LGBT families within curricula and fail to intervene when homophobic comments are made. Yet teachers' capacity to embrace diverse family structures while adhering to cultural expectations for teachers remains unexplored. This study, rooted in queer theory, explores the social norms teachers name for parenting in school settings and the way teachers position LGBT parents within these norms. Findings point to social norms for teachers and parents which indicate that teachers operate within heteronormative frameworks. They consider heterosexuality to be normal, while positioning LGBT identities as deviant. This is troubling given documented connections between teacher attitudes and parental involvement and between parental involvement and student achievement. Unchecked, heteronormative practices may result in inequitable school experiences for LGBT parents and their children. Teacher education must minimize heteronormativity through equipping teachers to attend to their own notions and assumptions regarding the intersection of parenting and sexual orientation. © 2009 Taylor & Francis.

The Ecology of Education: Knowledge Systems for Sustainable Development and SustainabilityResearch in knowledge systems for sustainable development (KSSD) seeks to determine how science and technology can be put into effective action at a local level. Teachers in education for sustainability attempt to achieve the same goal. KSSD research has indicated that success is context driven, that panaceas are inappropriate and that knowledge systems at best provide solutions in evolution. In this paper, we describe a teaching framework that we are developing to support KSSD researchers and teachers in education for sustainability based in ecology of education. While a need for ecology in education may be apparent, there is concurrently an equally important need for ecology of education. We argue that one cannot teach ecology in education adequately without an appropriate ecology of education. This paper first explains why teachers need to know this and then describes how teachers of education for sustainability can implement and assess this approach in the classroom.

The purpose of the present study was to explore the themes that counselor education doctoral students perceive as influencing their experience. The results of an exploratory qualitative study in which counselor education doctoral students provided their perceptions of what helped or hindered their progress are presented. Themes identified as both positively and negatively influencing their experiences were departmental culture, mentoring, academics, support systems, and personal issues. Recommendations are provided for counselor educators to consider in their work with doctoral students. © 2009 by the American Counseling Association. All rights reserved.

Despite living in disadvantaged urban communities experiencing social and economic hardships, many children emerge with positive outcomes. Social-emotional competence and social support were hypothesized to have strong influences on academic trajectories during the critical period of academic skill acquisition. Participants were 282 third-grade students from six elementary schools in a Northwestern urban community. Beyond the importance of prior levels of academic competence, considerable variance in end-of-year academic outcomes was predicted by initial levels of academic social-emotional competence and improvements in social-emotional competence and perceived teacher support over the course of the year. Noteworthy is that findings were strongest for African-American students, but methodological caveats regarding research with underachieving minority youth were discussed. The findings suggest that school psychologists and others designing interventions to improve achievement of disadvantaged students should address social-emotional competencies and classroom climate, especially teacher support of students.

During the software lifecycle, the software structure is subject to many changes in order to fulfill the customer's requirements. In Distributed Object Oriented systems, software engineers face many challenges to solve the software-hardware mismatch problem in which the software structure does not match the customer's underlying hardware. A major design problem of Object Oriented software systems is the efficient distribution of software classes among the different nodes in the system while maintaining two features: low-coupling and high software quality. In this paper, we present a new methodology for efficiently restructuring Distributed Object Oriented software systems to improve the overall system performance and to solve the softwarehardware mismatch problem. Our method has two main phases. In the first phase, we use the hierarchical clustering method to restructure the target software application. As a result, all the possible clustering solutions that could be applied to the target software application are generated. In the second phase, we decide on the best-fit clustering solution according to the customer hardware organization.

The primary purpose of this study was to investigate the feasibility of using simulated data from the United Kingdom Meteorological Office (UKMO) global climate mathematical model to serve as boundary values for a regional model RM3 which has been used by NASA to make predictions about climate dynamics in West Africa. In the past, historical data has been used successfully as boundary data but this approach limits outcomes to time periods in the past. The advantage of using the UKMO data is its potential to provide input boundary data for future time periods resulting in future regional predictions. This study has provided NASA scientists with graphical and statistical summaries including visual animations that provide qualitative and quantitative information necessary for evaluating whether the UKMO data can be used as a driving force for the RM3 model. One definite conclusion of this investigation is that both spatial and temporal interpolation of UKMO results will be necessary in order to make its results compatible with the RM3 model.

The software restructuring techniques present solutions for the software-hardware mismatch problem in which the software structure does not match the available hardware platform. In Distributed Object Oriented (DOO) systems, software engineers face many challenges to solve the software-hardware mismatch problem. One important aspect of DOO software systems is the efficient distribution of software classes among the different nodes while maintaining low-coupling and high software quality. In this paper, we present a new methodology for efficiently restructuring the DOO software systems to improve the performance and to solve the software-hardware mismatch problem. In our method, we use the hierarchical clustering technique to opt the classes to be grouped together and according to the customer hardware organization, we pick the level of the hierarchy that have the appropriate number of clusters to be allocated to the set of available nodes in the customer distributed system.

The use of Transmission Electron Microscopy (TEM) to characterize the microstructure of a material continues to grow in importance as technological advancements become increasingly more dependent on nanotechnology 1. Since nanoparticle properties such as size (diameter) and size distribution are often important in determining potential applications, a particle analysis is often performed on TEM images. Traditionally done manually, this has the potential to be labor intensive, time consuming, and subjective 2. To resolve these issues, automated particle analysis routines are becoming more widely accepted within the community 3. When using such programs, it is important to compare their performance, in terms of functionality and cost. The primary goal of this study was to apply one such software package, ImageJ to grayscale TEM images of nanoparticles with known size. A secondary goal was to compare this popular open-source general purpose image processing program to two commercial software packages. After a brief investigation of performance and price, ImageJ was identified as the software best suited for the particle analysis conducted in the study. While many ImageJ functions were used, the ability to break agglomerations that occur in specimen preparation into separate particles using a watershed algorithm was particularly helpful 4. © 2009 SPIE-IS&T.

A web-based lidar experimentation and data analysis system (LEDAS) was developed, with support from a National Science Foundation award, to support resource sharing of lidar equipment, datasets and data analysis routines and collaboration between members of the Connecticut State University System (CSUS) Lidar Collaboratory. The system allows users at different geographical locations to conduct remote sensing research and education over the Web through remote access and control of a single shared lidar system and web-based data analysis. Users need not have any specialized instrumentation or software at their institutions, thereby making real remote sensing research available to students and faculty from institutions which may not have the internal budgets for such facilities. An original structure providing basic functionality was developed and implemented. This paper describes the second generation data analysis system which provides significant new enhancements and capabilities. © 2008 IEEE.