Tradeoffs or Synergies? Assessing Local and Regional Food Aid Procurement through Case Studies in Burkina Faso and Guatemala

We compare the impacts across a range of criteria of local and regional procurement (LRP) relative to transoceanic shipment of food aid in Burkina Faso and Guatemala. We find that neither instrument dominates the other across all criteria in either country, although LRP commonly performs at least as well as transoceanic shipment with respect to timeliness, cost, market price impacts, satisfying recipients' preferences, food quality and safety, and in benefiting smallholder suppliers. LRP is plainly a valuable food assistance tool, but its advantages and disadvantages must be carefully weighed, compared, and prioritized depending on the context and program objectives. (C) 2013 Elsevier Ltd. All rights reserved.

Assessing the Influence of Brain-based Instructional Methods and Its Impact on Systemic Change for Learning Communities

Background: As scholars who prepare future school leaders to be innovative instructional leaders for their learning communities, we are on the verge of a curriculum design revolution. The application of brain research findings promotes educational reform efforts to systemically change the way in which children experience school. However, most educators, school leaders, board members, and policy makers are ill prepared to reconsider the implications for assessment, pedagogy, school climate, daily schedules, and use of technology. This qualitative study asked future school leaders to reconsider how school leadership preparedness programs prepared them to become instructional leaders for the 21st century. The findings from this study will enhance the field of school leadership, challenging the current emphasis placed on standardized testing, traditional school calendars, assessments, monocultural instructional methods, and meeting the needs of diverse learning communities. [See PDF for complete abstract]

Sources and contributions of wood smoke during winter in London: assessing local and regional influences

Determining the contribution of wood smoke to air pollution in large cities such as London is becoming increasingly important due to the changing nature of domestic heating in urban areas. During winter, biomass burning emissions have been identified as a major cause of exceedances of European air quality limits. The aim of this work was to quantify the contribution of biomass burning in London to concentrations of PM2:5 and determine whether local emissions or regional contributions were the main source of biomass smoke. To achieve this, a number of biomass burning chemical tracers were analysed at a site within central London and two sites in surrounding rural areas. Concentrations of levoglucosan, elemental carbon (EC), organic carbon (OC) and K+ were generally well correlated across the three sites. At all the sites, biomass burning was found to be a source of OC and EC, with the largest contribution of EC from traffic emissions, while for OC the dominant fraction included contributions from secondary organic aerosols, primary biogenic and cooking sources. Source apportionment of the EC and OC was found to give reasonable estimation of the total carbon from non-fossil and fossil fuel sources based upon comparison with estimates derived from 14C analysis. Aethalometer-derived black carbon data were also apportioned into the contributions frombiomass burning and traffic and showed trends similar to those observed for EC. Mean wood smoke mass at the sites was estimated to range from 0.78 to 1.0 μgm-3 during the campaign in January–February 2012. Measurements on a 160m tower in London suggested a similar ratio of brown to black carbon (reflecting wood burning and traffic respectively) in regional and London air. Peaks in the levoglucosan and K+ concentrations were observed to coincide with low ambient temperature, consistent with domestic heating as a major contributing local source in London. Overall, the source of biomass smoke in London was concluded to be a background regional source overlaid by contributions from local domestic burning emissions. This could have implications when considering future emission control strategies during winter and may be the focus of future work in order to better determine the contributing local sources.

Assessing the influence and distribution of shrimp pond effluent in a tidal mangrove creek in north-east Australia

Effluent from a land based shrimp farm was detected in a receiving creek as changes in physical, chemical and biological parameters. The extent and severity of these changes depended on farm operations. This assessment was conducted at three different stages of shrimp-pond maturity, including (1) when the ponds were empty, (2) full and (3) being harvested. Methods for assessing farm effluent in receiving waters included physical/chemical analyses of the water column, phytoplankton bioassays and nitrogen isotope signatures of marine flora. Comparisons were made with an adjacent creek that served as the farms intake creek and did not directly receive effluent. Physical/chemical parameters identified distinct changes in the receiving creek with respect to farm operations. Elevated water column NH4+ (18.5+/-8.0 muM) and chlorophyll a concentrations (5.5+/-1.9 mug/l) were measured when the farm was in operation, in contrast to when the farm was inactive (1.3+/-0.3 muM and 1.2+/-0.6 mug/l, respectively). At all times, physically chemical parameters at the mouth of the effluent creek, were equivalent to control values, indicating effluent was contained within the effluent-receiving creek. However, elevated delta(15)N signatures of mangroves (up to similar to8parts per thousand) and macroalgae (up to similar to5parts per thousand) indicated a broader influence of shrimp farm effluent, extending to the lower regions of the farms intake creek. Bioassays at upstream sites close to the location of farm effluent discharge indicated that phytoplankton at these sites did not respond to further nutrient additions, however downstream sites showed large growth responses. This suggested that further nutrient loading from the shrimp farm, resulting in greater nutrient dispersal, will increase the extent of phytoplankton blooms downstream from the site of effluent discharge. When shrimp ponds were empty water quality in the effluent and intake creeks was comparable. This indicated that observed elevated nutrient and phytoplankton concentrations were directly attributable to farm operations. (C) 2003 Elsevier Ltd. All rights reserved.

Assessing the influence of organizational personality, applicants' need motivation, expectancy beliefs, and person-organization fit on applicant attraction

This research explored the thesis that organizational personality is related to applicants’ attraction to an organization through a process which involves need motivation, expectancy beliefs, and applicants’ perceptions of person-organization fit. Organizational personality may be defined as a collection of trait-like characteristics that individuals use to describe organizational practices, policies, values, and culture. Specifically, this research investigated the hypothesis that organizational personality information is useful to applicants because it helps individuals to determine their perceptions of fit. A sample of students (N = 198) and working adults (N = 198) participated in an online experiment. Findings indicated that individuals’ beliefs about the instrumentality of desirable work related outcomes are essential to determining their perceptions of fit and organizational attraction. Additionally, organizational personality perceptions interacted with need motivation to affect perceptions of fit and organizational attraction. For instance, perceptions of fit mediated the influence of the interaction between need for achievement and perceptions of innovativeness on organizational attraction. The interaction of need motivation and perceptions of organizational personality helped individuals to better determine their perceptions of fit and subsequent attraction toward organizations.^

Assessing local food systems in China for building healthy mega-cities

Despite the long-lasting concern for food security in China at the national level, policy attempts to cope with this issue have often resulted to be ineffective. More importantly, they have rarely addressed the question from a local perspective. International experiences of urban food strategies proved to be quite efficacious in enhancing the local provision of food and improving the overall city sustainability by shortening the supply chain, preserving peri-urban areas and improving the nutrition of citizens. By reviewing existing practices of city farming in China, mainly ascribable to urban agriculture experiences, the intention of this paper is to reflect upon the challenges of implementing more comprehensive local food systems. In the conclusion the paper argues that, given the current institutional, socio-economic, and environmental constrains of Chinese cities there is a need of introducing holistic planning tool to assess local food systems in order to ensure the building of real healthy cities.

Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change

Local influence analysis in general spatial models

Assessing the influence of dam construction on the spatial and temporal evolution of population density across the United States of America

Finding the optimum location for placing a dam on a river is usually a complicated process which generally forces thousands of people to flee their homes because they will be inundated during the filling of the dam. Dams could also attract people living in the surrounding area after their construction. The goal of this research is to check for dam attractiveness for people by comparing growth rates of population density in surrounding areas after dam construction to those associated with the period antecedent to the dam construction. To this aim, 1859 dams across the United States of America and high-resolution population distribution from 1790 to 2010 are examined. By grouping dams as a function of their main purpose, water supply dams are found to be, as expected, the most attractive dams for people, with the biggest growth in population density. Irrigation dams are next, followed by hydroelectricity, flood control, Navigation, and finally Recreation dams. Fishery dams and dams for other uses suffered a decrease in population in the years after their construction. The regions with the greatest population growth were found approximately 40-45 km from the dam and at distances greater than 90 km, whereas the regions with the greatest population decline or only a modest gain were located within 10-15 km of the dam.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Diagnostic tools in beta regression with varying dispersion

We consider the issue of performing residual and local influence analyses in beta regression models with varying dispersion, which are useful for modelling random variables that assume values in the standard unit interval. In such models, both the mean and the dispersion depend upon independent variables. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. An application using real data is presented and discussed.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

Influence diagnostics in nonlinear mixed-effects elliptical models

In this work we propose and analyze nonlinear elliptical models for longitudinal data, which represent an alternative to gaussian models in the cases of heavy tails, for instance. The elliptical distributions may help to control the influence of the observations in the parameter estimates by naturally attributing different weights for each case. We consider random effects to introduce the within-group correlation and work with the marginal model without requiring numerical integration. An iterative algorithm to obtain maximum likelihood estimates for the parameters is presented, as well as diagnostic results based on residual distances and local influence [Cook, D., 1986. Assessment of local influence. journal of the Royal Statistical Society - Series B 48 (2), 133-169; Cook D., 1987. Influence assessment. journal of Applied Statistics 14 (2),117-131; Escobar, L.A., Meeker, W.Q., 1992, Assessing influence in regression analysis with censored data, Biometrics 48, 507-528]. As numerical illustration, we apply the obtained results to a kinetics longitudinal data set presented in [Vonesh, E.F., Carter, R.L., 1992. Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics 48, 1-17], which was analyzed under the assumption of normality. (C) 2009 Elsevier B.V. All rights reserved.

Influence diagnostics in beta regression

We consider the issue of assessing influence of observations in the class of beta regression models, which is useful for modelling random variables that assume values in the standard unit interval and are affected by independent variables. We propose a Cook-like distance and also measures of local influence under different perturbation schemes. Applications using real data are presented. (c) 2008 Elsevier B.V.. All rights reserved.