Contesting the role of social movements in post-apartheid South Africa: the Treatment Action Campaign

This article contests the role of social actors within a democratic context by looking at post-apartheid social movements in general and the case study of the Treatment Action Campaign in particular. By illustrating the structure, activities, goals and accomplishments of the Treatment Action Campaign up until the end of 2006, this work will argue that it represents an innovation in social movements in South Africa via its unique strategies and networks that have transformed the issue of HIV/AIDS from a health and service delivery problem, to a political and economic struggle that affects all people. The comparison between primary research conducted in the TAC National Office and interviewing other civil society actors with secondary material on social movements and the South African environment demonstrates that there is often a gap between theory and practice. Further the debate surrounding the ‘naming’ of social movements in South Africa raises questions around the accuracy of the terminology used to describe such groups and organizations which aim towards social transformation via a variety of approaches and techniques. It argues that the use of social movement theory according to Porta and Diani (1999) and others is essential in analyzing the characteristics of a social movement but not adequate

Diffusion map for clustering fMRI spatial maps extracted by independent component analysis

Functional magnetic resonance imaging (fMRI) produces data about activity inside the brain, from which spatial maps can be extracted by independent component analysis (ICA). In datasets, there are n spatial maps that contain p voxels. The number of voxels is very high compared to the number of analyzed spatial maps. Clustering of the spatial maps is usually based on correlation matrices. This usually works well, although such a similarity matrix inherently can explain only a certain amount of the total variance contained in the high-dimensional data where n is relatively small but p is large. For high-dimensional space, it is reasonable to perform dimensionality reduction before clustering. In this research, we used the recently developed diffusion map for dimensionality reduction in conjunction with spectral clustering. This research revealed that the diffusion map based clustering worked as well as the more traditional methods, and produced more compact clusters when needed.Comment: 6 pages. 8 figures. Copyright (c) 2013 IEEE. Published at 2013 IEEE International Workshop on Machine Learning for Signal Processin

Streamlining Microservices Testing: Automation Techniques for Devops Success

Contemporary software development employs microservices for scalability and reliability. Testing for functionality, performance, and stability is essential to decompose monolithic applications into loosely coupled services. High-quality DevOps microservices undergo automated testing. Automated testing and microservices integration. Every technique undergoes microservices testing. Automation commences with the testing of service units or components. Unit tests for individual microservices evaluate their functionality. Mocking frameworks and test doubles simulate dependencies to optimize unit testing. Researchers underscore the significance of JUnit, NUnit, pytest code coverage, and microservice automation. In addition to unit tests, integration testing evaluates the interactions between microservices. Regulates data and service connectivity. Contracts authenticate. Integration testing documentation. Spring Boot Test, Postman, and SOAP UI facilitate the automation of integration testing. Comparable virtual machines and mockups. Due to the necessity for all microservices to collaborate for essential functionality, the solution undergoes user testing. Our objective is to evaluate business processes and user journeys. TestingCafe, Cucumber, and Selenium facilitate end-to-end automation. Research investigates the utilization of testing frameworks within CI/CD pipelines for agile development and rapid deployment. Appropriate tools and frameworks are essential for automated testing in DevOps. Docker and Kubernetes facilitate the containerization of uniform development, testing, and production environments. Jenkins CI/CD is utilized for pipeline and testing automation. These automated testing systems implement optimal techniques for the dissemination of test results and the management of artifacts. Case studies demonstrate that automated testing influences deployment, reliability, and scalability. Automated testing improved deployment frequency, reduced production failures, and stabilized microservices in these case studies. Case studies examine challenges and propose solutions. Dependencies are detrimental, but autotesting is beneficial. Researchers advocate for inter-service communication frameworks and microservice-targeted testing to address these challenges. Data consistency, service orchestration, and failures are evaluated for efficiency and efficacy. This document addresses best practices, tools, and methodologies for automated testing of microservices inside a DevOps framework. Application quality and reliability testing is automated and based on microservices. Test automation and DevOps utilize microservices

case study

A poem about the Mainland in BC

COMPETITIVE EFFECTS OF WEEDS ON CONTAINER-GROWN ORNAMENTAL PLANTS

Thesis (M.S.)--Michigan State University. Horticulture - Master of Science, 2024Weed-infested environments lead to the improper establishment of ornamental crops, particularly in containerized production, where weeds compete more for light, water, nutrients, and space with ornamental plants due to confined conditions. Hence, the objectives of this research project were to evaluate strategic fertilizer placement methods to assess the optimum container size for containerized ornamental production to mitigate weed proliferation while promoting ornamental plant growth. Two ornamental species, Rosa rubiginosa L. (rose) and Spiraea japonica L. f. (spirea), were studied for fertilizer placement studies, while two others, Hydrangea macrophylla (Thunb.) Ser. (hydrangea) and Syringa vulgaris L. (syringa), were evaluated for container size study. These experiments were conducted in a greenhouse setting at the Horticulture Teaching and Research Centre, Michigan State University, using two commonly found weeds in nurseries, Digitaria Sanguinalis (L.) Scop. (large crabgrass) and Amaranthus hybridus L. (smooth pigweed), at densities of 0, 1, 3, and 6 for both experiments. Both studies followed a randomized complete block design with the experiments repeated twice for each study. Results showed that sub-dressing can be an efficient fertilizer placement method that controls weeds and enhances ornamental growth. Three gallon containers appeared to promote ornamental growth, particularly in hydrangeas compared to other container sizes such as 1.5-gallon and 0.67-gallon but failed to eradicate weed proliferation. However, 0.67-gallon containers reduced the growth of both weed species compared to 1.5-gallon and 3-gallon containers, though they did not promote ornamental growth and, in turn, decreased ornamental growth. Therefore, future studies on container sizes should be conducted with different ornamental and weed species possessing different growth habits to determine the optimal container size.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references

winter portrait

A poem about Vancouver, BC

DEVELOPMENT OF GUIDANCE FOR STATES TRANSITIONING TO NEW SAFETY ANALYSIS TOOLS

With about 125 people dying on US roads each day, the US Department of Transportation heightened the awareness of critical safety issues with the passage of SAFETEA - LU (Safe Accountable Flexible Efficient Transportation Equity Act - a Legacy for Users) legislation in 2005. The legislation required each of the states to develop a Strategic Highway Safety Plan (SHSP) and incorporate data-driven approaches to prioritize and evaluate program outcomes: Failure to do so resulted in funding sanctioning. In conjunction with the legislation, research efforts have also been progressing toward the development of new safety analysis tools such as IHSDM (Interactive Highway Safety Design Model), SafetyAnalyst and HSM (Highway Safety Manual). These software and analysis tools are comparatively more advanced in statistical theory and level of accuracy, and have a tendency to be more data intensive. A review of the 2009 five-percent reports and excerpts from the nationwide survey revealed astonishing facts about the continuing use of traditional methods including crash frequencies and rates for site selection and prioritization. The intense data requirements and statistical complexity of advanced safety tools are considered as a hindrance to their adoption. In this context, this research aims at identifying the data requirements and data availability for SafetyAnalyst and HSM by working with both the tools. This research sets the stage for working with the Empirical Bayes approach by highlighting some of the biases and issues associated with the traditional methods of selecting projects such as greater emphasis on traffic volume and regression-to-mean phenomena. Further, the not-so-obvious issue with shorter segment lengths, which effect the results independent of the methods used, is also discussed. The more reliable and statistically acceptable Empirical Bayes methodology requires safety performance functions (SPFs), regression equations predicting the relation between crashes and exposure for a subset of roadway network. These SPFs, specific to a region and the analysis period are often unavailable. Calibration of already existing default national SPFs to the state\u27s data could be a feasible solution, but, how well the state\u27s data is represented is a legitimate question. With this background, SPFs were generated for various classifications of segments in Georgia and compared against the national default SPFs used in SafetyAnalyst calibrated to Georgia data. Dwelling deeper into the development of SPFs, the influence of actual and estimated traffic data on the fit of the equations is also studied questioning the accuracy and reliability of traffic estimations. In addition to SafetyAnalyst, HSM aims at performing quantitative safety analysis. Applying HSM methodology to two-way two-lane rural roads, the effect of using multiple CMFs (Crash Modification Factors) is studied. Lastly, data requirements, methodology, constraints, and results are compared between SafetyAnalyst and HSM

Synthesis and Charecterisation of Methylene Blue Derivatives

Since its discovery, the fluorescent dye known as methylene blue has been employed in a variety of scientific disciplines. Methylene blue (MB) for intraoperative fluorescence imaging has only lately been employed. 10-N-carbamoyl linkage modification of Methylene blue helps us in developing compounds with off-to-on fluorescence switch in the presence of near infrared (NIR). Due to its naturally induced photodamage to normal tissues and deeper penetration of lesion regions when compared to UV and visible light, near infrared (NIR) light is considered favorable among the broad radiation range. The previously synthesized derivatives are not completely soluble in water, they require other co-solvents, acetone etc. So in this study branched polyethyleneimine which is a water soluble polymer is used to conjugate with methylene blue to effect the 10-N-Carbamoyl linkage. The branched structure of polyethyleneimine has several primary amines, so the amount of methylene blue that can be conjugated can also be varied. The carbamoyl linkage with methylene blue is also sensitive to hydroxyl radical. Using this hypothesis the activity was verified using hemoproteins such as hemoglobin. Subsequently this property can be used in the lysis of the malaria parasite. MB and PEI conjugate was synthesized and tested in vitro for the cleavage of the 10-N-Carbamoyl linkage. As the result, PEI-conjugated MB successfully demonstrated the cleavage and also sensitivity to ROS-induce cleavage to release intact MB

ASSESSMENT OF POTENTIAL SITE SELECTION METHODS FOR USE IN PRIORITIZING SAFETY IMPROVEMENTS ON GEORGIA ROADWAYS

With over 40,000 people continuing to die on US roads each year, the US government has heightened the awareness of critical safety issues with the passage of SAFETEA - LU legislation in 2005. The plan requires each of the states to develop a Strategic Highway Safety Plan (SHSP) and incorporate data-driven approaches to prioritize and evaluate program outcomes; else federal funds will be redirected. Seeking to meet the new demands for data-driven approaches, many states are struggling to identify data collection/maintenance requirements for satisfying new approaches to highway safety analysis. Recent research has shown that selecting projects on the basis of crash frequencies and rates are misleading due to selection bias (such as greater emphasis on traffic volume and cash severity etc) and Regression-to-mean phenomena. There are several safety analysis techniques that are preferred over traditional rates and frequencies. These include level of service of safety, empirical bayes method using SafetyAnalyst software techniques. While all the above mentioned methods are macroscopic (giving a bigger picture of the complete road), microscopic analysis could be done using the Interactive Highway Safety Design Model (IHSDM). IHSDM is a set of software analysis tools developed by Federal Highway Administration (FHWA) to evaluate safety on two lane rural highways. This research aims at assessing the usability, data requirements, data availability and expertise required by different techniques that are deemed appropriate for safety analysis in Georgia. To streamline and reduce the scope of work, Cobb County was chosen as the analysis county because it had been used in a prior development effort and was expected to have the best level of completion and accuracy in the state. The procedure of using the state-of-the-art analytical tools is considered as the most comprehensive safety analysis method. Cobb County data set will be used to test the applicability of the four analysis methods: crash frequency, crash rate, critical crash rate and level of service of safety (LOSS). The results from various ranking criteria (crash frequency, crash rate, critical crash rate and LOSS) will be compared to the actual available crash data and enhanced SafetyAnalyst data. SafetyAnalyst uses the Safety Performance Functions generated for northern states and it calibrated to Georgia data. SPFs applicable to Georgia data (generated from Cobb County) are compared to the non-calibrated and calibrated SPFs used in SafetyAnalyst. Analysis of costs and potential benefit of using various network screening methods is carried out to weigh the capabilities and limitations of various ranking methods