221 research outputs found

    Video Summarization Using Unsupervised Deep Learning

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    In this thesis, we address the task of video summarization using unsupervised deep-learning architectures. Video summarization aims to generate a short summary by selecting the most informative and important frames (key-frames) or fragments (key-fragments) of the full-length video, and presenting them in temporally-ordered fashion. Our objective is to overcome observed weaknesses of existing video summarization approaches that utilize RNNs for modeling the temporal dependence of frames, related to: i) the small influence of the estimated frame-level importance scores in the created video summary, ii) the insufficiency of RNNs to model long-range frames' dependence, and iii) the small amount of parallelizable operations during the training of RNNs. To address the first weakness, we propose a new unsupervised network architecture, called AC-SUM-GAN, which formulates the selection of important video fragments as a sequence generation task and learns this task by embedding an Actor-Critic model in a Generative Adversarial Network. The feedback of a trainable Discriminator is used as a reward by the Actor-Critic model in order to explore a space of actions and learn a value function (Critic) and a policy (Actor) for video fragment selection. To tackle the remaining weaknesses, we investigate the use of attention mechanisms for video summarization and propose a new supervised network architecture, called PGL-SUM, that combines global and local multi-head attention mechanisms which take into account the temporal position of the video frames, in order to discover different modelings of the frames' dependencies at different levels of granularity. Based on the acquired experience, we then propose a new unsupervised network architecture, called CA-SUM, which estimates the frames' importance using a novel concentrated attention mechanism that focuses on non-overlapping blocks in the main diagonal of the attention matrix and takes into account the attentive uniqueness and diversity of the associated frames of the video. All the proposed architectures have been extensively evaluated on the most commonly-used benchmark datasets, demonstrating their competitiveness against other approaches and documenting the contribution of our proposals on advancing the current state-of-the-art on video summarization. Finally, we make a first attempt on producing explanations for the video summarization results. Inspired by relevant works in the Natural Language Processing domain, we propose an attention-based method for explainable video summarization and we evaluate the performance of various explanation signals using our CA-SUM architecture and two benchmark datasets for video summarization. The experimental results indicate the advanced performance of explanation signals formed using the inherent attention weights, and demonstrate the ability of the proposed method to explain the video summarization results using clues about the focus of the attention mechanism

    Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021.

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    BACKGROUND: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. METHODS: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. FINDINGS: In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. INTERPRETATION: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. FUNDING: Bill & Melinda Gates Foundation

    Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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    Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world’s highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%.Peer ReviewedPostprint (published version

    La Montología Global 4D: Hacia las Ciencias Convergentes y Transdisciplinarias de Montaña a través del Tiempo y el Espacio

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    With mountain studies we use integrative approaches for geoliteracy about productive socioecological landscapes, and motivate further transdisciplinary research in montology. We conceived this white paper as a confluence of individual expertise and collective reasoning towards forming synergistic research clusters dealing with convergent mountain science, to advance montology to a new level, whereby innovative thinking about sustainability science and regenerative development incorporates alternative propositions for maintenance, improvement, or regeneration of living conditions of mountainscapes. We seek to use this contemporary framing of sustainability and ecological restoration as the impetus to better understand nature-culture relations, framed on lived-in mountains that operate in four dimensions (length, width, depth, and time) oriented at maximizing the cross-cutting of themes around mountains as productive socioecological systems, in a new academic institutionalized convergent unit. We conclude with a call for consilient, sustainable, regenerative development in the world’s mountains.La utilización de los estudios de montaña requiere de narrativas integradoras para la geoalfabetización sobre paisajes socioecológicos productivos y motiva más investigaciones transdisciplinares en el campo de la montología. Concebimos este artículo como la confluencia de la experiencia individual y el razonamiento colectivo hacia la formación de grupos de investigación sinérgicos que se ocupan de la ciencia de montaña convergente, para hacer avanzar la montología a un nuevo nivel, mediante el cual el pensamiento innovador sobre la ciencia de la sustentabilidad y el desarrollo regenerativo incorpora propuestas alternativas para el mantenimiento, la mejora, o regeneración de las condiciones de vida de los paisajes de montaña. Buscamos utilizar este marco contemporáneo de sustentabilidad y restauración ecológica como el ímpetu para comprender mejor las relaciones de la naturaleza y la cultura, desde una perspectiva transdisciplinar, en montañas habitadas que operan en cuatro dimensiones (largo, ancho, alto y tiempo). El artículo está orientado a potenciar la transversalidad de temáticas en torno a las montañas como sistemas socioecológicos productivos, en una nueva disciplina académica institucionalizada y convergente. Concluimos con un llamado a un desarrollo regenerativo, sustentable y consiliente en las montañas del mundo

    Contrastive Video Question Answering via Video Graph Transformer

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    We propose to perform video question answering (VideoQA) in a Contrastive manner via a Video Graph Transformer model (CoVGT). CoVGT's uniqueness and superiority are three-fold: 1) It proposes a dynamic graph transformer module which encodes video by explicitly capturing the visual objects, their relations and dynamics, for complex spatio-temporal reasoning. 2) It designs separate video and text transformers for contrastive learning between the video and text to perform QA, instead of multi-modal transformer for answer classification. Fine-grained video-text communication is done by additional cross-modal interaction modules. 3) It is optimized by the joint fully- and self-supervised contrastive objectives between the correct and incorrect answers, as well as the relevant and irrelevant questions respectively. With superior video encoding and QA solution, we show that CoVGT can achieve much better performances than previous arts on video reasoning tasks. Its performances even surpass those models that are pretrained with millions of external data. We further show that CoVGT can also benefit from cross-modal pretraining, yet with orders of magnitude smaller data. The results demonstrate the effectiveness and superiority of CoVGT, and additionally reveal its potential for more data-efficient pretraining. We hope our success can advance VideoQA beyond coarse recognition/description towards fine-grained relation reasoning of video contents. Our code is available at https://github.com/doc-doc/CoVGT.Comment: Accepted by IEEE T-PAMI'2

    Recent Research Trends in Medical and Health Sciences

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    The present volume is based on the contributions made by various authors on different important topic of “Recent Research Trends in Medical and Health Sciences” and introduces the subject along the following topics: Methods in Improving Short Term Memory: A Brief Review; Are Children Falling into the Trench of Fast Food?; Biomedical Research Ethics: Past, Present and Future; Early (Short-Term) Side-Effects of Chemotherapy in Pediatric Solid Tumors; Health and Pollution in Banbishnupur village, Haldia, West Bengal; A Study to Evaluate the Morphometric measures of Gonial angle and Bi-gonial width for Healthy Individuals in Garden City university dental camp; Prevalence of Overweight and Obesity (overnutrition) among the Bengali Adolescent Girls: A Cross-Sectional Study from Darjeeling District, West Bengal (India). We must place on record our sincere gratitude to the authors not only for their effort in preparing the papers for the present volume, but also their patience in waiting to see their work in print

    Re-emergence of Neglected Tropical Diseases amid the COVID-19 Pandemic : Epidemiology, Transmission, Mitigation Strategies, and Recent Advances in Chemotherapy and Vaccines

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    The current re-emergence of neglected tropical diseases (NTD) amid the global COVID-19 pandemic requires increased attention. These include communicable and vector-borne diseases caused by various fungi, bacteria (e.g. tuberculosis), viruses (e.g. dengue, Chikungunya fever, monkeypox, Marburg and Ebola virus disease, poliomyelitis, rabies), and parasites (e.g. filariasis, malaria, trypanosomiasis, leishmaniasis, schistosomiasis, onchocerciasis). Whilst the vast majority of such diseases remain endemic to specific regions of the world (e.g. tropical Africa), some - like those caused by the Ebola virus, the Marburg virus, and more recently the Monkeypox virus - have been reported elsewhere (e.g. Europe and America), forcing public health boards in various countries to take all necessary precautions to control such a spread. The Department for Control of Neglected Tropical Disease was created in 2005 by the World Health Organization (WHO) to tackle NTD. In 2021, the 74th World Health Assembly proposed a 9-year plan (2021-2030) intended to eradicate neglected diseases. Over the past three years, COVID-19 has had a significant impact on socio-economic activities and healthcare systems worldwide. With the WHO recently declaring the global monkeypox outbreak a Public Health Emergency of International Concern, a coordinated effort among high-income and low/middle-income countries is now more than ever recommended to address the threat posed by the worldwide re-emergence of some NTD. There is currently a lack of knowledge on understanding how such diseases are transmitted and what mitigation strategies should be put in place to control their spread. Better availability of diagnostic tests, vaccines, and drugs in affected countries is also required. In this Research Topic, we wish to address how to best tackle the re-emergence of NTD in the context of the COVID-19 pandemic. This collection welcomes a range of articles including opinion, commentary, systematic reviews, and original research articles on epidemiology, transmission, mitigation strategies, and recent advances in chemotherapy and vaccines for these NTD
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