Hasil untuk "Information resources (General)"

David Alexander

This book provides a detailed introduction to natural disasters and the ways in which they have had and continue to have, profound effects on human society. Natural Disasters: A Reference Handbook surveys the impact of these events on human civilization. The opening chapter provides a general history and background of the major types of natural disasters, including earthquakes, volcanic eruptions, severe storms, and forest fires. The information presented in this introduction allows the reader to better understand current issues, problems, and solutions related to natural disasters discussed in subsequent chapters. The book covers the role of natural disasters in human life from earliest recorded history (and, to some extent, even earlier) to the present day. It provides an extensive variety of resources that encourage readers to learn more about the topics discussed. The book is intended for readers in the late middle school to high school age range, as well as adults who may have a special interest in the subject.

F. Petroni, Aleksandra Piktus, Angela Fan et al.

Challenging problems such as open-domain question answering, fact checking, slot filling and entity linking require access to large, external knowledge sources. While some models do well on individual tasks, developing general models is difficult as each task might require computationally expensive indexing of custom knowledge sources, in addition to dedicated infrastructure. To catalyze research on models that condition on specific information in large textual resources, we present a benchmark for knowledge-intensive language tasks (KILT). All tasks in KILT are grounded in the same snapshot of Wikipedia, reducing engineering turnaround through the re-use of components, as well as accelerating research into task-agnostic memory architectures. We test both task-specific and general baselines, evaluating downstream performance in addition to the ability of the models to provide provenance. We find that a shared dense vector index coupled with a seq2seq model is a strong baseline, outperforming more tailor-made approaches for fact checking, open-domain question answering and dialogue, and yielding competitive results on entity linking and slot filling, by generating disambiguated text. KILT data and code are available at https://github.com/facebookresearch/KILT.

S. Kaul, R. Yates, M. Gruteser

J. Kellum, N. Lameire, P. Aspelin et al.

SECTION I: USE OF THE CLINICAL PRACTICE GUIDELINE This Clinical Practice Guideline document is based upon the best information available as of February 2011. It is designed to provide information and assist decision-making. It is not intended to define a standard of care, and should not be construed as one, nor should it be interpreted as prescribing an exclusive course of management. Variations in practice will inevitably and appropriately occur when clinicians take into account the needs of individual patients, available resources, and limitations unique to an institution or type of practice. Every health-care professional making use of these recommendations is responsible for evaluating the appropriateness of applying them in the setting of any particular clinical situation. The recommendations for research contained within this document are general and do not imply a specific protocol.

S. Carpenter, H. Mooney, J. Agard et al.

T. Richardson, R. Urbanke

Weiwei Zhang, S. Luck

Sameer Pradhan, Alessandro Moschitti, Nianwen Xue et al.

P. Pierson

Xiaohang Wang, Daqing Zhang, T. Gu et al.

Juliana Magro, Caitlin Plovnick, Gregory Laynor et al.

Introduction Medical students may arrive at medical school with some research background but not necessarily evidence-based medicine (EBM) skills. First-year preclinical medical students require foundational skills for EBM (formulating background and foreground questions, navigating information sources, and conducting database searches) before critically appraising evidence and applying it to clinical scenarios. Methods We developed a flipped classroom EBM workshop for preclinical students combining prework modules and a 60-minute in-person session. After completing the online modules on foundational EBM skills, students participated in an in-person activity based on patient cases. In small groups, students formulated background and foreground questions based on a case and looked for evidence in resources assigned to each group. Small groups reported back to the whole group how they searched for information for their patient cases. A total of 105 first-year medical students were required to complete this workshop after concluding their basic sciences courses. Results Because current EBM assessment tools do not assess the early steps of EBM, we developed an assessment tool for foundational EBM tools. Before the modules, students completed a pretest on formulating questions and searching for information. After the workshop, students completed a posttest. Students showed improvement in differentiating background and foreground questions (p < .001), formulating answerable clinical questions (p < .001), and developing appropriate database searches (p < .001 and p = .002). Discussion This flipped classroom approach to teaching foundational EBM skills may be adapted for different contexts, but educators should consider time limitations, group size, and tools for interactivity.

FRANK FUNKEYE SAPELE, AKUMKA JOSEPH YABAYANZE, KANYINSOLA AZEEZ

This research focuses on global climate change and adaptation strategies. Climate change globally has become one of the shocking certainties of the 21st era and it has made scientists to raise the need to drop worldwide temperatures further by 0.5 °C which makes a substantial difference in some areas of the world, particularly developing countries that are faced with the greater threat of climate change.  Developing States have become exposed to the damaging effects of climate change because of their varied climatic regions and these have affected their food production activities due to the deforestation problem, desertification, soil degradation, erosion, flooding, general habitat loss, depletion of natural resources etc. This study therefore attempts to examine the extent to which continuous climate change has affected the globe and how institutional frameworks have addressed the current situation in ensuring effective control across the globe. The research employed purely on secondary means to gathered data. This research structures its opinions with the human security model as its theoretical framework. Major findings showed that environmental degradation, desertification caused by climate change had greatly stunted agricultural production and government rules universally; climate change has increased food uncertainty, poor statistical analysis and implementation by government. The paper recommends that government should provide alternative means   like renewable energy, reduction of industrial carbons in tackling the menace of climate change globally, there should be reduction of emission of greenhouse gases by stopping deforestation, the use of high yield and disease tolerant crops, and also crops adaptable to high level of weather conditions, there should be easy accessible information on climate change effects to the public.

V. V. Zemskov

This study examines and addresses the most important and critical problems associated with fraud risks and uncertainties in accounting (financial) and tax reporting. Attackers, committing deceptive and fraudulent actions, overestimate assets or write off stolen funds as expenses, as a result of which potential investors, suppliers, and customers may make incorrect financial decisions regarding the alleged counterparty. The author of the article analyzes the uncertainties existing in tax legal relations, and how they divert the resources of business entities (financial, human, technological) to resolve these problems through litigation. The purpose of the study is to analyze and assess both the risks of fraudulent misstatements with estimated liabilities and fair values in financial statements, as well as uncertainties affecting business activities and operations in the conditions of limited financial resources. The risks of fraud and uncertainty act as the key factors in predictive crimes and offences. The article presents the author’s interpretation of the concept of “uncertainty” as the inability of a management entity to make the right financial decisions due to ignorance of relevant regulatory legal documents on various issues of tax relations or incomplete information necessary for effective activity. The study used such general scientific methods as comparative and logical analyses, statistical analysis, and content analysis. The author of the study concluded that when identifying existing uncertainties in tax legal relations, when some of them are not legally regulated, the principle of presumption of innocence of an economic entity should be applied, which, under the conditions of sanctions restrictions, is the only correct decision that directly affects the financial well-being of the latter, and, consequently, the level of the country’s defense capability. The results of the study can be used in practice by employees of financial, accounting services, as well as the employees of regulatory and supervisory authorities in assessing tax risks.

Jan Østergaard

We present a new notion $R_\ell$ of higher-order common information, which quantifies the information that $\ell\geq 2$ arbitrarily distributed random variables have in common. We provide analytical lower bounds on $R_3$ and $R_4$ for jointly Gaussian distributed sources and provide computable lower bounds for $R_\ell$ for any $\ell$ and any sources. We also provide a practical method to estimate the lower bounds on, e.g., real-world time-series data. As an example, we consider EEG data acquired in a setup with competing acoustic stimuli. We demonstrate that $R_3$ has descriptive properties that is not in $R_2$. Moreover, we observe a linear relationship between the amount of common information $R_3$ communicated from the acoustic stimuli and to the brain and the corresponding cortical activity in terms of neural tracking of the envelopes of the stimuli.

Kaan Kale, Homa Esfahanizadeh, Noel Elias et al.

With the exponential growth in data volume and the emergence of data-intensive applications, particularly in the field of machine learning, concerns related to resource utilization, privacy, and fairness have become paramount. This paper focuses on the textual domain of data and addresses challenges regarding encoding sentences to their optimized representations through the lens of information-theory. In particular, we use empirical estimates of mutual information, using the Donsker-Varadhan definition of Kullback-Leibler divergence. Our approach leverages this estimation to train an information-theoretic sentence embedding, called TexShape, for (task-based) data compression or for filtering out sensitive information, enhancing privacy and fairness. In this study, we employ a benchmark language model for initial text representation, complemented by neural networks for information-theoretic compression and mutual information estimations. Our experiments demonstrate significant advancements in preserving maximal targeted information and minimal sensitive information over adverse compression ratios, in terms of predictive accuracy of downstream models that are trained using the compressed data.

Sirous Panahi, Somayeh Ghaffari, Mahshid Lotfi

This research aimed to specify research trends in Library and Information Science (LIS) from 2011 to 2020 and hot papers in this field from July 2020 to July 2021 in the Web of Science (WoS) database. This research was of the type applied, scientometric, and descriptive. The study population was all articles in the field of LIS from 2011 to July 2021. The WoS database was used to collect data. To determine the research trend in the field of LIS, the results were limited to 2011-2020, and to determine the hot papers, this period was limited to July 2020 to July 2021. The obtained data were analyzed using the word co-occurrence technique and social network analysis. UCINET, NetDraw, and VOSviewer software were used to draw scientific maps and identify central subjects and people. "Social media" with 259 and "qualitative" with 53 were the keywords with the highest and lowest frequencies, respectively. Library and emerging technologies (106), citation analysis, scientometrics and webometrics (58), electronic information, information security, and protection (56) were three significant topic clusters in the studied area. The results indicated that the research topics in LIS have changed and evolved in the last ten years despite new and up-to-date topics.

Yuzhou Wang, Jinyi Qian, Fang Yan et al.

Special environmental microorganisms are considered to be of great industrial application value because of their special genotypes, physiological functions and metabolites. The research and development of special environmental microorganisms will certainly bring about some innovations in biotechnology processes and change the face of bioengineering. The Special Environmental Microbial Database (DSEMR) is a comprehensive database that provides information on special environmental microbial resources and correlates them with synthetic biological parts. DSEMR aggregates information on specific environmental microbial genomes, physiological properties, culture media, biological parts, and metabolic pathways, and provides online tool analysis data, including 5268 strains from 620 genera, 31 media, and 42,126 biological parts. In short, DSEMR will become an important resource for the study of microorganisms in special environments and actively promote the development of synthetic biology.

Patrícia Nascimento Silva

Resumo A recuperação de informação é uma área de estudo nativa da ciência da computação, cujo termo foi criado somente em 1951. No entanto, por mais de 5 mil anos, a humanidade vem organizando a informação para sua busca e recuperação. Com o advento dos computadores, o termo que era de interesse apenas de bibliotecários teve seu desenvolvimento acelerado. Desafios atuais envolvendo novos dispositivos e fenômenos, como o Big Data, continuam incitando estudos na área para promover aos usuários o acesso às informações. Este artigo tem o objetivo de identificar a produção acadêmico-científica brasileira sobre a recuperação de informação na ciência da informação nos últimos 10 anos. A Pesquisa é descritiva e exploratória, com abordagem quali-quantitativa, por meio de uma revisão bibliográfica integrativa na Biblioteca Digital Brasileira de Teses e Dissertações no período de 2012 a 2021. Foram selecionados 69 documentos, categorizados em 27 temáticas. A maior frequência de documentos foi observada para as seguintes temáticas: estudo de usuários, mecanismos de busca, representação da informação, modelo de recuperação e representação temática. Observou-se que as temáticas mais recentes são apresentadas a partir de 2016, e que o maior número de trabalhos está vinculado à Universidade Federal de Minas Gerais. No contexto da Ciência da Informação, a recuperação de informação tem forte ligação com a organização e a representação da informação e compõem uma relação quase que indissociável. O estudo é um aporte para novos pesquisadores, contribuindo para publicizar as contribuições existentes e instigando novas reflexões sobre a recuperação de Informação na Ciência da Informação.

Melissa Medich, Shay L Cannedy, Lauren C Hoffmann et al.

BackgroundEarly intervention in mental health crises can prevent negative outcomes. A promising new direction is remote mental health monitoring using smartphone technology to passively collect data from individuals to rapidly detect the worsening of serious mental illness (SMI). This technology may benefit patients with SMI, but little is known about health IT acceptability among this population or their mental health clinicians. ObjectiveWe used the Health Information Technology Acceptability Model to analyze the acceptability and usability of passive mobile monitoring and self-tracking among patients with serious mental illness and their mental health clinicians. MethodsData collection took place between December 2020 and June 2021 in 1 Veterans Administration health care system. Interviews with mental health clinicians (n=16) assessed the acceptability of mobile sensing, its usefulness as a tool to improve clinical assessment and care, and recommendations for program refinements. Focus groups with patients with SMI (n=3 groups) and individual usability tests (n=8) elucidated patient attitudes about engaging in health IT and perceptions of its usefulness as a tool for self-tracking and improving mental health assessments. ResultsClinicians discussed the utility of web-based data dashboards to monitor patients with SMI health behaviors and receiving alerts about their worsening health. Potential benefits included improving clinical care, capturing behaviors patients do not self-report, watching trends, and receiving alerts. Clinicians’ concerns included increased workloads tied to dashboard data review, lack of experience using health IT in clinical care, and how SMI patients’ associated paranoia and financial instability would impact patient uptake. Despite concerns, all mental health clinicians stated that they would recommend it. Almost all patients with SMI were receptive to using smartphone dashboards for self-monitoring and having behavioral change alerts sent to their mental health clinicians. They found the mobile app easy to navigate and dashboards easy to find and understand. Patient concerns centered on privacy and “government tracking,” and their phone’s battery life and data plans. Despite concerns, most reported that they would use it. ConclusionsMany people with SMI would like to have mobile informatics tools that can support their illness and recovery. Similar to other populations (eg, older adults, people experiencing homelessness) this population presents challenges to adoption and implementation. Health care organizations will need to provide resources to address these and support successful illness management. Clinicians are supportive of technological approaches, with adapting informatics data into their workflow as the primary challenge. Despite clear challenges, technological developments are increasingly designed to be acceptable to patients. The research development–clinical deployment gap must be addressed by health care systems, similar to computerized cognitive training. It will ensure clinicians operate at the top of their skill set and are not overwhelmed by administrative tasks, data summarization, or reviewing data that do not indicate a need for intervention. International Registered Report Identifier (IRRID)RR2-10.2196/39010

Olivia A Mac, D. Muscat, J. Ayre et al.

The information needs of people with lower health literacy or from culturally and linguistically diverse backgrounds have received limited attention during the coronavirus disease 2019 (COVID19) pandemic. In one study, the complexity of most governmentproduced COVID19 information in Australia and overseas exceeded the recommended grade 8 reading level, making it too difficult for general audiences, let alone people with lower health literacy.1 We therefore compared the complexity (readability, understandability, actionability) of Australian and overseas COVID19 vaccination information with that of other COVID19related information (physical distancing, mask wearing), including “easy read” resources developed in Australia and New Zealand.