Cognitive and Educational Interventions for Orphans and Vulnerable Children Affected by HIV/AIDS: A Meta-Analysis

Orphans and vulnerable children affected by HIV/AIDS (HIV OVC) are at risk for cognitive difficulties and lack of access to education. Interventions addressing cognitive or educational outcomes for HIV OVC worldwide were examined through systematic searches conducted from October 2016 to 2019. We examined the summative effectiveness of interventions and the specific effects of participant age and intervention length. Interventions targeting cognitive outcomes had a small, significant effect, with no effect of moderating variables. Interventions targeting educational outcomes had significant effects. Educational interventions over 1 year were effective, but effects of intervention length were not significant. Overall, this review provides support for the effectiveness of interventions targeting cognitive and educational outcomes for OVC and highlights the need for more research on such interventions.     

Effect of simultaneous sodium oxalate and methionine feeding with and without Varuna (Crataeva nurvala hook & Frost) therapy on urolithogenesis in guinea pigs

The effect of sodium oxalate and methionine supplementation on stone-related constituents of urine was studied in 18 adult male guinea pigs. Their serum and tissue chemistry and histological changes in urinary tract and liver were also studied. The calciuretic effect of methionine was blocked by oxalate. The decrease in uric acid and citric acid, caused by oxalate, was offset by methionine. Oxalate-induced crystalluria and calcium and oxalate deposition in kidney tissue were lessened by methionine. Administration of Varuna, an indigenuous drug, to oxalate and methionine-supplemented animals prevented either totally or partially most of the urolithogenic effects of oxalate and methionine.     

Towards utilising emerging technologies to address the challenges of using Open Educational Resources: a vision of the future

Educational technology research and development - The rapid advancements in online education have pointed to a new open learning approach using Open Educational Resources (OER). In this approach,...     

A new approach for conservation treatment of a silk textile in Islamic Art Museum, Cairo

The paper presents strategies for the conservation of historical textiles in Egypt that have been in uncontrolled storage and display. The silk textile is highly decorated, multicoloured and dates to the Ottoman period, and was exhibited in case # 12014. The textile has various types of deterioration. An examination and analysis of the textile was undertaken in order to develop a plan of conservation treatment. FTIR was used to identify the kinds of dyes and organic stains, and XR-D was used to identify mordants and dust. Light microscope and SEM were used to identify the kind of fibers, their condition and surface morphology. The effects of cleaning materials on the natural dyes were tested. The researcher designed a new metallic frame support system which has advantages over the wooden frames commonly used in Egypt. This presentation will review the conservation treatment step by step. Poultices were used to remove all the sticking cardboard and adhesive. Old conservation repairs were removed. Separated parts were supported. Cleaning included mechanical and wet cleaning. New silk fabrics dyed with natural dyes were used to complete the missing parts. The textile was supported on new linen fabric which was stretched on a metal frame. The method of exhibition will be discussed. Photographs are included to document the conservation process.     

Consensus of fractional-order multiagent system via sampled-data event-triggered control

This paper investigates the consensus of fractional-order multiagent systems via sampled-data event-triggered control. Firstly, an event-triggered algorithm is defined using sampled states. Thus, Zeno behaviors can be naturally avoided. Then, a distributed control protocol is proposed to ensure the consensus of fractional-order multiagent systems, where each agent updates its current state based on its neighbors’ states at event-triggered instants. Furthermore, the pinning control technology is taken into account to ensure all agents in multiagent systems reach the specified reference state. With the aid of linear matrix inequalities (LMI), some sufficient conditions are obtained to guarantee the consensus of fractional-order multiagent system. Finally, numerical simulations are presented to demonstrate the theoretical analysis.     

Predicting elections from social media: a three-country,three-method comparative study

ABSTRACT

This study introduces and evaluates the robustness of different volumetric, sentiment, and social network approaches to predict the elections in three Asian countries – Malaysia, India, and Pakistan from Twitter posts. We find that predictive power of social media performs well for India and Pakistan but is not effective for Malaysia. Overall, we find that it is useful to consider the recency of Twitter posts while using it to predict a real outcome, such as an election result. Sentiment information mined using machine learning models was the most accurate predictor of election outcomes. Social network information is stable despite sudden surges in political discussions, for e.g. around elections-related news events. Methods combining sentiment and volume information, or sentiment and social network information, are effective at predicting smaller vote shares, for e.g. vote shares in the case of independent candidates and regional parties. We conclude with a detailed discussion on the caveats of social media analysis for predicting real-world outcomes and recommendations for future work.     

Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization

ABSTRACT

This study examines algorithm effects on user opinion, utilizing a real-world recommender algorithm of a highly popular video-sharing platform, YouTube. We experimentally manipulate user search/watch history by our custom programming. A controlled laboratory experiment is then conducted to examine whether exposure to algorithmically recommended content reinforces and polarizes political opinions. Results suggest that political self-reinforcement, as indicated by the political emotion-ideology alignment, and affective polarization are heightened by political videos – selected by the YouTube recommender algorithm – based on participants’ own search preferences. Suggestions for how to reduce algorithm-induced political polarization and implications of algorithmic personalization for democracy are discussed.     

The Support Model for interactive assessment

The two most common models for assessment involve measuring how well students perform on a task (the quality model), and how difficult a task students can succeed on (the difficulty model). By exploiting the interactive potential of computers we may be able to use a third model: measuring how much help a student needs to complete a task. We assume that every student can complete it, but some need more support than others. This kind of tailored support will give students a positive experience of assessment, and a learning experience, while allowing us to differentiate them by ability. The computer can offer several kinds of support, such as help with understanding a question, hints on the meanings of key concepts, and examples or analogies. A further type of support has particular importance for test validity: the computer can probe students for a deeper explanation than they have so far given. In subjects like geography or science, markers often would like to ask ‘yes, but why?’, suspecting that students understand more than they have written. We describe a series of studies in which students were given a high level task as an oral interview and then as an interactive computerised assessment with varying types of support. Implications of the support model for future modes of assessment are discussed.