Southeast Asian Transformations: Urban and Rural Developments in the 21st Century

Southeast Asia is one of the most dynamic regions in the world. This volume offers a timely approach to Southeast Asian Studies, covering recent transitions in the realms of urbanism, rural development, politics, and media. While most of the contributions deal with the era of post-independence, some tackle the colonial period and the resulting developments. The volume also includes insights from Southern India. As a tribute to the interdisciplinary project of Southeast Asian Studies, this book brings together authors from disciplines as diverse as area studies, sociology, history, geography, and journalism

Southeast Asian Transformations

Southeast Asia is one of the most dynamic regions in the world. This volume offers a timely approach to Southeast Asian Studies, covering recent transitions in the realms of urbanism, rural development, politics, and media. While most of the contributions deal with the era of post-independence, some tackle the colonial period and the resulting developments. The volume also includes insights from Southern India. As a tribute to the interdisciplinary project of Southeast Asian Studies, this book brings together authors from disciplines as diverse as area studies, sociology, history, geography, and journalism

Prevalence and burden of HBV co-infection among people living with HIV:A global systematic review and meta-analysis

Globally, in 2017 35 million people were living with HIV (PLHIV) and 257 million had chronic HBV infection (HBsAg positive). The extent of HIV-HBsAg co-infection is unknown. We undertook a systematic review to estimate the global burden of HBsAg co-infection in PLHIV. We searched MEDLINE, Embase and other databases for published studies (2002-2018) measuring prevalence of HBsAg among PLHIV. The review was registered with PROSPERO (#CRD42019123388). Populations were categorized by HIV-exposure category. The global burden of co-infection was estimated by applying regional co-infection prevalence estimates to UNAIDS estimates of PLHIV. We conducted a meta-analysis to estimate the odds of HBsAg among PLHIV compared to HIV-negative individuals. We identified 506 estimates (475 studies) of HIV-HBsAg co-infection prevalence from 80/195 (41.0%) countries. Globally, the prevalence of HIV-HBsAg co-infection is 7.6% (IQR 5.6%-12.1%) in PLHIV, or 2.7 million HIV-HBsAg co-infections (IQR 2.0-4.2). The greatest burden (69% of cases; 1.9 million) is in sub-Saharan Africa. Globally, there was little difference in prevalence of HIV-HBsAg co-infection by population group (approximately 6%-7%), but it was slightly higher among people who inject drugs (11.8% IQR 6.0%-16.9%). Odds of HBsAg infection were 1.4 times higher among PLHIV compared to HIV-negative individuals. There is therefore, a high global burden of HIV-HBsAg co-infection, especially in sub-Saharan Africa. Key prevention strategies include infant HBV vaccination, including a timely birth-dose. Findings also highlight the importance of targeting PLHIV, especially high-risk groups for testing, catch-up HBV vaccination and other preventative interventions. The global scale-up of antiretroviral therapy (ART) for PLHIV using a tenofovir-based ART regimen provides an opportunity to simultaneously treat those with HBV co-infection, and in pregnant women to also reduce mother-to-child transmission of HBV alongside HIV

30th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing. Conceptual modelling is one of the sub-areas of information modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers

A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness

People increasingly use videos on the Web as a source for learning. To support this way of learning, researchers and developers are continuously developing tools, proposing guidelines, analyzing data, and conducting experiments. However, it is still not clear what characteristics a video should have to be an effective learning medium. In this paper, we present a comprehensive review of 257 articles on video-based learning for the period from 2016 to 2021. One of the aims of the review is to identify the video characteristics that have been explored by previous work. Based on our analysis, we suggest a taxonomy which organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners activities, (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative research directions: (1) proposals of tools to support video-based learning, (2) studies with controlled experiments, (3) data analysis studies, and (4) proposals of design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learner activities, and interactive features. Text of transcripts, video frames, and images (figures and illustrations) are most frequently used by tools that support learning through videos. The learner activity is heavily explored through log files in data analysis studies, and interactive features have been frequently scrutinized in controlled experiments. We complement our review by contrasting research findings that investigate the impact of video characteristics on the learning effectiveness, report on tasks and technologies used to develop tools that support learning, and summarize trends of design guidelines to produce learning video

Improved Molecular Diagnostics for Soil-Transmitted Helminths

Current World Health Organization recommendations for the diagnosis of soil-transmitted helminths (STH) rely on antiquated microscopy-based techniques that lack both diagnostic sensitivity and specificity. While sufficient for providing rough estimates of infection frequency and intensity within high prevalence settings, these techniques lack the capacity to effectively estimate infection levels following successful intervention efforts, as worm burdens decline and community prevalences decrease. Furthermore, an expanding body of evidence is suggesting that microscopy-based misdiagnosis of infection is likely a larger concern then previously believed. As such, with an increase in programmatic support for transmission interruption and an escalating belief in the possibility of regional eradication, recognition of the need for improved diagnostics is expanding. Such diagnostics are critically important for accurately measuring intervention successes, and for making determinations about where and when interventions can be discontinued allowing for the re-prioritization of resources. Given the stakes and acknowledging this need, recent years have witnessed the growth of molecular diagnostic development efforts, centering primarily upon the creation of real-time PCR-based assays. However, while a variety of assays have been developed, these assays have all utilized suboptimal DNA targets, typically exploiting ribosomal and/or mitochondrial sequences for parasite detection. By coupling next-generation sequencing with bioinformatics-based approaches to the analysis of raw sequencing read data, the selection of optimal DNA-based molecular targets becomes possible. Software, such as RepeatExplorer can be utilized to identify high copy-number, species-specific, repetitive DNA elements within a pathogen. These repeat sequences can then be utilized to design sensitive and specific real-time PCR assays. Utilizing such an approach, we have designed, developed, and extensively validated a panel of assays facilitating the improved detection of the human infecting STH. These assays are proving useful in a number of settings, gaining widespread traction within the operational research community and helping to shape and define future intervention strategies. Furthermore, our assays continue to highlight the inadequacies of alternative diagnostic methods, illustrating the potential challenges and risks for misdiagnosis associated with the use of both microscopy-based diagnostics, and assays targeting less sensitive, less specific genomic regions

W+ W- boson pair production in proton-proton collisions at root s=13 TeV

Peer reviewe

Geo-physical parameter forecasting on imagery{based data sets using machine learning techniques

>Magister Scientiae - MScThis research objectively investigates the e ectiveness of machine learning (ML) tools towards predicting several geo-physical parameters. This is based on a large number of studies that have reported high levels of prediction success using ML in the eld. Therefore, several widely used ML tools coupled with a number of di erent feature sets are used to predict six geophysical parameters namely rainfall, groundwater, evapora- tion, humidity, temperature, and wind. The results of the research indicate that: a) a large number of related studies in the eld are prone to speci c pitfalls that lead to over-estimated results in favour of ML tools; b) the use of gaussian mixture models as global features can provide a higher accuracy compared to other local feature sets; c) ML never outperform simple statistically-based estimators on highly-seasonal parame- ters, and providing error bars is key to objectively evaluating the relative performance of the ML tools used; and d) ML tools can be e ective for parameters that are slow- changing such as groundwater

東北大学電気通信研究所研究活動報告 第29号(2022年度)

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