Hidden Amongst the Crowd: Experiences of Students from Underrepresented Religions and Denominations

This research addresses the lived experiences of students from underrepresented religions and denominations at a small Catholic college. There has been increased interest in promoting inclusive practices in higher education around race, ethnicity, gender. An article published in 2012 by Bowman and Smedley, outlines the dissatisfaction of college students from marginalized religions on campuses where they do not identify with the majority religion. This research seeks to expand the research to include religion, particularly at institutions with religious affiliation.Using ethnographic research methods, including participant observations and semi-structured interviews, this research explores student understandings, experiences and practices of religion as well as the institutional involvement, support and perspective religious inclusivity. Adapting an applied framework, this research, seeks make suggestions regarding fostering a more inclusive campus environment

Finance for low-emission food systems: For the CGIAR Research Initiative on Low-Emission Food Systems

The objective of this note is to map the global finance landscape that is relevant to the CGIAR Research Initiative on Low-Emission Food Systems (the Project). The note is part of the initial research phase of the project’s work stream on financial instruments as a tool for scaling of measures for achieving lower emissions in food systems (WP4). The objective of this research phase is to develop a typology of most adopted financial instruments for low-emission investments

Web Development and Its Interaction with the Social Media

The study assesses the factors associated with designing a trading website that functions and operates through social media channels as well as through its own independent web infrastructure for optimized performance and self-sufficient marketing. The aim of the study is to highlight the significance of social media integration in the website development process. An additional objective is to draft a database design for the application development of the trading site. In order to implement this project, the back-end application was built in PHP using eclipse IDE and the front-end was written using HTML5, CSS and JavaScript. This study transformed the traditional goods exchange trend to an enhanced way of transaction method by providing online availability for users. The study found out that social media interaction with the web facilitates the reach of potential customers through channels where they usually spend much of their time, such as Facebook, Google+ and Twitter. In addition, interaction of the web with the social media makes accessibility easier for customers or users

Probabilistic safety analysis of dams: Methods and applications

Successful dam design endeavor involves generating technical solutions that can meet intended functional objectives and choosing the best one among the alternative technical solutions. The process of choosing the best among the alternative technical solutions depends on evaluation of design conformance with technical specifications and reliability standards (such as capacity, environmental, safety, social, political etc pecifications). The process also involves evaluation on whether an optimal balance is set between safety and economy. The process of evaluating alternative design solutions requires generating a quantitative expression for lifetime performance and safety. An objective and numerical evaluation of lifetime performance and safety of dams is an essential but complex undertaking. Its domain involves much uncertainty (uncertainty in loads, hazards, strength parameters, boundary conditions, models and dam failure consequences) all of which should be characterized. Arguably uncertainty models and risk analysis provide the most complete characterization of dam performance and safety issues. Risk is a combined measure of the probability and severity of an adverse effect (functional and/or structural failure), and is often estimated by the product of the probability of the adverse event occurring and the expected consequences. Thus, risk analysis requires (1) determination of failure probabilities. (2) probabilistic estimation of consequences. Nonetheless, there is no adequately demonstrated, satisfactorily comprehensive and precise method for explicit treatment and integration of all uncertainties in variables of dam design and risk analysis. Therefore, there is a need for evaluating existing uncertainty models for their applicability, to see knowledge and realization gaps, to drive or adopt new approaches and tools and to adequately demonstrate their practicability by using real life case studies. This is required not only for hopefully improving the performance and safety evaluation process accuracy but also for getting better acceptance of the probabilistic approaches by those who took deterministic design based research and engineering practices as their life time career. These problems have motivated the initiation of this research. In this research the following have been accomplished: (1) Identified various ways of analyzing and representing uncertainty in dam design parameters pertinent to three dominant dam failure causes (sliding, overtopping and seepage), and tested a suite of stochastic models capable of capturing design parameters uncertainty to better facilitate evaluation of failure probabilities; (2) Studied three classical stochastic models: Monte Carlo Simulation Method (MCSM), First Order Second Moment (FOSM) and Second Order Second Moment (SOSM), and applied them for modeling dam performance and for evaluating failure probabilities in line with the above mentioned dominant dam failure causes; (3) Presented an exact new for the purpose analytical method of transforming design parameters distributions to a distribution representing dam performance (Analytical Solution for finding Derived Distributions (ASDD) method). Laid out proves of its basic principles, prepared a generic implementation architecture and demonstrated its applicability for the three failure modes using a real life case study data; (4) Presented a multitude of tailor-made reliability equations and solution procedures that will enable the implementations of the above stochastic and analytical methods for failure probability evaluation; (5) Implemented the stochastic and analytical methods using real life data pertinent to the three failure mechanisms from Tendaho Dam, Ethiopia. Compared the performance of the various stochastic and analytical methods with each other and with the classical deterministic design approach; and (6) Provided solution procedures, implementation architectures, and Mathematica 5.2, Crystal Ball 7 and spreadsheet based tools for doing the above mentioned analysis. The results indicate that: (1) The proposed approaches provide a valid set of procedures, internally consistent logic and produce more realistic solutions. Using the approaches engineers could design dams to meet a quantified level of performance (volume of failure) and could set a balance between safety and economy; (2) The research is assumed to bridge the gap between the available probability theories in one hand and the suffering distribution problems in dam safety evaluation on the other; (3) Out of the suite of stochastic approaches studied the ASDD method out perform the classical methods (MCSM, FOSM and SOSM methods) by its theoretical foundation, accuracy and reproducibility. However, when compared with deterministic approach, each of the stochastic approaches provides valid set of procedures, consistent logic and they gave more realistic solution. Nonetheless, it is good practice to compare results from the proposed probabilistic approaches; (4) The different tailor-made reliability equations and solution approaches followed are proved to work for stochastic safety evaluation of dams; and (5) The research drawn from some important conclusions and lessons, in relation to stochastic safety analysis of dams against the three dominant failure mechanisms, are. The end result of the study should provide dam engineers and decision makers with perspectives, methodologies, techniques and tools that help them better understand dam safety related issues and enable them to conduct quantitative safety analysis and thus make intelligent dam design, upgrading and rehabilitation decisions

Probabilistic safety analysis of dams: Methods and applications

Successful dam design endeavor involves generating technical solutions that can meet intended functional objectives and choosing the best one among the alternative technical solutions. The process of choosing the best among the alternative technical solutions depends on evaluation of design conformance with technical specifications and reliability standards (such as capacity, environmental, safety, social, political etc pecifications). The process also involves evaluation on whether an optimal balance is set between safety and economy. The process of evaluating alternative design solutions requires generating a quantitative expression for lifetime performance and safety. An objective and numerical evaluation of lifetime performance and safety of dams is an essential but complex undertaking. Its domain involves much uncertainty (uncertainty in loads, hazards, strength parameters, boundary conditions, models and dam failure consequences) all of which should be characterized. Arguably uncertainty models and risk analysis provide the most complete characterization of dam performance and safety issues. Risk is a combined measure of the probability and severity of an adverse effect (functional and/or structural failure), and is often estimated by the product of the probability of the adverse event occurring and the expected consequences. Thus, risk analysis requires (1) determination of failure probabilities. (2) probabilistic estimation of consequences. Nonetheless, there is no adequately demonstrated, satisfactorily comprehensive and precise method for explicit treatment and integration of all uncertainties in variables of dam design and risk analysis. Therefore, there is a need for evaluating existing uncertainty models for their applicability, to see knowledge and realization gaps, to drive or adopt new approaches and tools and to adequately demonstrate their practicability by using real life case studies. This is required not only for hopefully improving the performance and safety evaluation process accuracy but also for getting better acceptance of the probabilistic approaches by those who took deterministic design based research and engineering practices as their life time career. These problems have motivated the initiation of this research. In this research the following have been accomplished: (1) Identified various ways of analyzing and representing uncertainty in dam design parameters pertinent to three dominant dam failure causes (sliding, overtopping and seepage), and tested a suite of stochastic models capable of capturing design parameters uncertainty to better facilitate evaluation of failure probabilities; (2) Studied three classical stochastic models: Monte Carlo Simulation Method (MCSM), First Order Second Moment (FOSM) and Second Order Second Moment (SOSM), and applied them for modeling dam performance and for evaluating failure probabilities in line with the above mentioned dominant dam failure causes; (3) Presented an exact new for the purpose analytical method of transforming design parameters distributions to a distribution representing dam performance (Analytical Solution for finding Derived Distributions (ASDD) method). Laid out proves of its basic principles, prepared a generic implementation architecture and demonstrated its applicability for the three failure modes using a real life case study data; (4) Presented a multitude of tailor-made reliability equations and solution procedures that will enable the implementations of the above stochastic and analytical methods for failure probability evaluation; (5) Implemented the stochastic and analytical methods using real life data pertinent to the three failure mechanisms from Tendaho Dam, Ethiopia. Compared the performance of the various stochastic and analytical methods with each other and with the classical deterministic design approach; and (6) Provided solution procedures, implementation architectures, and Mathematica 5.2, Crystal Ball 7 and spreadsheet based tools for doing the above mentioned analysis. The results indicate that: (1) The proposed approaches provide a valid set of procedures, internally consistent logic and produce more realistic solutions. Using the approaches engineers could design dams to meet a quantified level of performance (volume of failure) and could set a balance between safety and economy; (2) The research is assumed to bridge the gap between the available probability theories in one hand and the suffering distribution problems in dam safety evaluation on the other; (3) Out of the suite of stochastic approaches studied the ASDD method out perform the classical methods (MCSM, FOSM and SOSM methods) by its theoretical foundation, accuracy and reproducibility. However, when compared with deterministic approach, each of the stochastic approaches provides valid set of procedures, consistent logic and they gave more realistic solution. Nonetheless, it is good practice to compare results from the proposed probabilistic approaches; (4) The different tailor-made reliability equations and solution approaches followed are proved to work for stochastic safety evaluation of dams; and (5) The research drawn from some important conclusions and lessons, in relation to stochastic safety analysis of dams against the three dominant failure mechanisms, are. The end result of the study should provide dam engineers and decision makers with perspectives, methodologies, techniques and tools that help them better understand dam safety related issues and enable them to conduct quantitative safety analysis and thus make intelligent dam design, upgrading and rehabilitation decisions

Probabilistic safety analysis of dams: Methods and applications

Successful dam design endeavor involves generating technical solutions that can meet intended functional objectives and choosing the best one among the alternative technical solutions. The process of choosing the best among the alternative technical solutions depends on evaluation of design conformance with technical specifications and reliability standards (such as capacity, environmental, safety, social, political etc pecifications). The process also involves evaluation on whether an optimal balance is set between safety and economy. The process of evaluating alternative design solutions requires generating a quantitative expression for lifetime performance and safety. An objective and numerical evaluation of lifetime performance and safety of dams is an essential but complex undertaking. Its domain involves much uncertainty (uncertainty in loads, hazards, strength parameters, boundary conditions, models and dam failure consequences) all of which should be characterized. Arguably uncertainty models and risk analysis provide the most complete characterization of dam performance and safety issues. Risk is a combined measure of the probability and severity of an adverse effect (functional and/or structural failure), and is often estimated by the product of the probability of the adverse event occurring and the expected consequences. Thus, risk analysis requires (1) determination of failure probabilities. (2) probabilistic estimation of consequences. Nonetheless, there is no adequately demonstrated, satisfactorily comprehensive and precise method for explicit treatment and integration of all uncertainties in variables of dam design and risk analysis. Therefore, there is a need for evaluating existing uncertainty models for their applicability, to see knowledge and realization gaps, to drive or adopt new approaches and tools and to adequately demonstrate their practicability by using real life case studies. This is required not only for hopefully improving the performance and safety evaluation process accuracy but also for getting better acceptance of the probabilistic approaches by those who took deterministic design based research and engineering practices as their life time career. These problems have motivated the initiation of this research. In this research the following have been accomplished: (1) Identified various ways of analyzing and representing uncertainty in dam design parameters pertinent to three dominant dam failure causes (sliding, overtopping and seepage), and tested a suite of stochastic models capable of capturing design parameters uncertainty to better facilitate evaluation of failure probabilities; (2) Studied three classical stochastic models: Monte Carlo Simulation Method (MCSM), First Order Second Moment (FOSM) and Second Order Second Moment (SOSM), and applied them for modeling dam performance and for evaluating failure probabilities in line with the above mentioned dominant dam failure causes; (3) Presented an exact new for the purpose analytical method of transforming design parameters distributions to a distribution representing dam performance (Analytical Solution for finding Derived Distributions (ASDD) method). Laid out proves of its basic principles, prepared a generic implementation architecture and demonstrated its applicability for the three failure modes using a real life case study data; (4) Presented a multitude of tailor-made reliability equations and solution procedures that will enable the implementations of the above stochastic and analytical methods for failure probability evaluation; (5) Implemented the stochastic and analytical methods using real life data pertinent to the three failure mechanisms from Tendaho Dam, Ethiopia. Compared the performance of the various stochastic and analytical methods with each other and with the classical deterministic design approach; and (6) Provided solution procedures, implementation architectures, and Mathematica 5.2, Crystal Ball 7 and spreadsheet based tools for doing the above mentioned analysis. The results indicate that: (1) The proposed approaches provide a valid set of procedures, internally consistent logic and produce more realistic solutions. Using the approaches engineers could design dams to meet a quantified level of performance (volume of failure) and could set a balance between safety and economy; (2) The research is assumed to bridge the gap between the available probability theories in one hand and the suffering distribution problems in dam safety evaluation on the other; (3) Out of the suite of stochastic approaches studied the ASDD method out perform the classical methods (MCSM, FOSM and SOSM methods) by its theoretical foundation, accuracy and reproducibility. However, when compared with deterministic approach, each of the stochastic approaches provides valid set of procedures, consistent logic and they gave more realistic solution. Nonetheless, it is good practice to compare results from the proposed probabilistic approaches; (4) The different tailor-made reliability equations and solution approaches followed are proved to work for stochastic safety evaluation of dams; and (5) The research drawn from some important conclusions and lessons, in relation to stochastic safety analysis of dams against the three dominant failure mechanisms, are. The end result of the study should provide dam engineers and decision makers with perspectives, methodologies, techniques and tools that help them better understand dam safety related issues and enable them to conduct quantitative safety analysis and thus make intelligent dam design, upgrading and rehabilitation decisions

Does access to improved grain storage technology increase farmers' welfare? Experimental evidence from maize farming in Ethiopia

Seasonal price variability for cereals is two to three times higher in Africa than on the international reference market. Seasonality is even more pronounced when access to appropriate storage and opportunities for price arbitrage are limited. As smallholder farmers typically sell their production after harvest, when prices are low, this leads to lower incomes as well as higher food insecurity during the lean season, when prices are high. One solution to reduce seasonal stress is the use of improved storage technologies. Using data from a randomised controlled trial, in a major maize-growing region of Western Ethiopia, we study the impact of hermetic bags, a technology that protects stored grain against insect pests, so that the grain can be stored longer. Despite considerable price seasonality—maize prices in the lean season are 36% higher than after harvesting—we find no evidence that hermetic bags improve welfare, except that access to these bags allowed for a marginally longer storage period of maize intended for sale by 2 weeks. But this did not translate into measurable welfare gains as we found no changes in any of our welfare outcome indicators. This ‘near-null’ effect is due to the fact that maize storage losses in our study region are relatively lower than previous studies suggested—around 10% of the quantity stored—likely because of the widespread use of an alternative to protect maize during storage, for example a cheap but highly toxic fumigant. These findings are important for policies that seek to promote improved storage technologies in these settings.PRIFPRI3; CRP2; DCA; ISI; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food IndustryDevelopment Strategies and Governance (DSG); Transformation Strategies; PIMCGIAR Research Program on Policies, Institutions, and Markets (PIM