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2020 AVI2CH Workshop on Advanced Visual Interfaces and Interactions in Cultural Heritage, AVI2CH 2020

作者： Nasrolahi, Ahmad Messina, Vito Gena, Cristina Tech4Culture Phd program University of Torino Turin Italy Historical Studies Dept. University of Torino Turin Italy Computer Science Dept. University of Torino Turin Italy

This paper presents iCommunity, an application that will be aimed at finding a universal method for inclusive societies in decision-making processes for cultural heritage management. iCommunity is being designed as a mobile application facilitating public participation in cultural heritage management. The main idea is to give all people, who are affected by a decision, the opportunity to be involved in the decision-making process. Any cultural heritage institution will be able to publish its activities on the application so as to evaluate users' feedback before the implementation of the activity itself. Based on the user's location, the application displays ongoing activities to the user himself. As a part of a participatory approach, users share each other's experience or data related to the posted activity. They also can show their agreement or disagreement to the activities by voting. The comments, votes and user's activities will be analysed real time for helping authorities to consider the consequence of their activities for more transparent and effective decision-making. © Copyright 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Decision making

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Cryo-EM structure of the plant 26S proteasome

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Plant Communications 2022年第3期3卷 116-126页

作者： Susanne Kandolf Irina Grishkovskaya Katarina Belacic Derek L.Bolhuis Sascha Amann Brent Foster Richard Imre Karl Mechtler Alexander Schleiffer Hemant D.Tagare Ellen D.Zhong Anton Meinhart Nicholas G.Brown David Haselbach Research Institute of Molecular Pathology(IMP) Vienna BioCenter(VBC)Campus-Vienna-BioCenter 11030 ViennaAustria Department of Radiology and Biomedical Imaging Yale UniversityNew HavenCT 06510USA Department of Pharmacology and Lineberger Comprehensive Cancer Center University of North Carolina School of MedicineChapel HillNC 27599USA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of TechnologyCambridgeMA 02139USA Vienna BioCenter PhD Program Doctoral School of the University at Vienna and Medical University of ViennaVienna BioCenter(VBC)ViennaAustria Institute of Physical Chemistry University of FreiburgAlbertstraße 21Freiburg 79104Germany CIBSS Centre for Integrative Biological Signalling Studies University of FreiburgFreiburgGermany

Targeted proteolysis is a hallmark of *** is especially important in long-lived cells that can be found in higher eukaryotes,like *** task is mainly fulfilled by the ubiquitin–proteasome ***,proteolysis by the 26S proteasome is vital to development,immunity,and cell *** the yeast and animal proteasomes are well characterized,there is only limited information on the plant *** determined the first plant 26S proteasome structure from Spinacia oleracea by single-particle electron cryogenic microscopy at an overall resolution of 3.3 A°.We found an almost identical overall architecture of the spinach proteasome compared with the known structures from mammals and ***,we noticed a structural difference in the proteolytic active b1 ***,we uncovered an unseen compression state by characterizing the proteasome’s conformational *** suspect that this new conformation of the 20S core protease,in correlation with a partial opening of the unoccupied gate,may contribute to peptide release after *** data provide a structural basis for the plant proteasome,which is crucial for further studies.

关键词： 26S proteasome spinach UPS cryo-EM conformational landscape

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Implementing ASLNet V1.0: Progress and plans 11

Implementing ASLNet V1.0: Progress and plans

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11th Global Wordnet Conference, GWC 2021

作者： Lualdi, Colin P. Wright, Elaine Hudson, Jack Caselli, Naomi K. Fellbaum, Christiane SignSchool Inc. MadisonWI United States Department of Physics University of Illinois Urbana-ChampaignIL United States Department of Electrical Engineering Princeton University PrincetonNJ United States Program in Linguistics Princeton University PrincetonNJ United States Programs in Deaf Studies Boston University BostonMA United States Department of Computer Science Princeton University PrincetonNJ United States

ISBN: (纸本)9789464027310

We report on the development of ASLNet, a wordnet for American Sign Language (ASL). ASLNet V1.0 is currently under construction by mapping easy-to-translate ASL lexical nouns to Princeton WordNet synsets. We describe our data model and mapping approach, which can be extended to any sign language. Analysis of the 390 synsets processed to date indicates the success of our procedure yet also highlights the need to supplement our mapping with the "merge" method. We outline our plans for upcoming work to remedy this, which include use of ASL free-association data. © GWC 2021. All rights reserved.

关键词： Mapping

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Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development

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Yearbook of Medical Informatics 2021年第1期30卷 44-55页

作者： Liaw, Siaw-Teng Kuziemsky, Craig Schreiber, Richard Jonnagaddala, Jitendra Liyanage, Harshana Chittalia, Aliasgar Bahniwal, Ravninder He, Jennifer W. Ryan, Bridget L. Lizotte, Daniel J. Kueper, Jacqueline K. Terry, Amanda L. de Lusignan, Simon WHO Collaborating Centre on eHealth UNSW Sydney Australia MacEwan University Edmonton AB Canada Penn State Health Holy Spirit Medical Center Camp Hill PA United States Nuffield Department of Primary Care Health Sciences University of Oxford United Kingdom Family Practice Center PA United States Schulich Interfaculty Program in Public Health Western University London Canada Graduate Program in Epidemiology and Biostatistics Western University London Canada Centre for Studies in Family Medicine Department of Family Medicine Western University London Canada Department of Computer Science Western University London Canada

OBJECTIVE: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned. METHODS: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives. RESULTS: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits. CONCLUSIONS: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, tran

关键词： health policy Primary Health Care public health severe acute respiratory syndrome coronavirus 2 Telemedicine

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Surrogate approximation of the grad-shafranov free boundary problem via stochastic collocation on sparse grids

arXiv

引用

arXiv 2021年

作者： Elman, Howard C. Liang, Jiaxing Sánchez-Vizuet, Tonatiuh Department of Computer Science Institute for Advanced Computer Studies University of Maryland College Park United States Applied Mathematics & Statistics and Scientific Computing Program University of Maryland College Park United States Courant Institute of Mathematical Sciences New York University Department of Mathematics The University of Arizona

In magnetic confinement fusion devices, the equilibrium configuration of a plasma is determined by the balance between the hydrostatic pressure in the fluid and the magnetic forces generated by an array of external coils and the plasma itself. The location of the plasma is not known a priori and must be obtained as the solution to a free boundary problem. The partial differential equation that determines the behavior of the combined magnetic field depends on a set of physical parameters (location of the coils, intensity of the electric currents going through them, magnetic permeability, etc.) that are subject to uncertainty and variability. The confinement region is in turn a function of these stochastic parameters as well. In this work, we consider variations on the current intensities running through the external coils as the dominant source of uncertainty. This leads to a parameter space of dimension equal to the number of coils in the reactor. With the aid of a surrogate function built on a sparse grid in parameter space, a Monte Carlo strategy is used to explore the effect that stochasticity in the parameters has on important features of the plasma boundary such as the location of the x-point, the strike points, and shaping attributes such as triangularity and elongation. The use of the surrogate function reduces the time required for the Monte Carlo simulations by factors that range between 7 and over *** Codes 65C30, 65C05, 65N35, 65N99, 65Z05 Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Depression and Anxiety on Twitter During the COVID-19 Stay-At-Home Period in 7 Major U.S. Cities

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AJPM Focus 2023年第1期2卷 100062-100062页

作者： Levanti, Danielle Monastero, Rebecca N. Zamani, Mohammadzaman Eichstaedt, Johannes C. Giorgi, Salvatore Schwartz, H. Andrew Meliker, Jaymie R. Undergraduate Studies Cornell University Ithaca NY United States Renaissance School of Medicine Stony Brook University Stony Brook NY United States Department of Computer Science College of Engineering and Applied Sciences Stony Brook University Stony Brook NY United States Department of Psychology School of Humanities and Sciences Stanford University Palo Alto CA United States Department of Computer and Information Science University of Pennsylvania Philadelphia PA United States Program in Public Health Department of Family Population & Preventive Medicine Renaissance School of Medicine Stony Brook University Stony Brook NY United States

Introduction: Although surveys are a well-established instrument to capture the population prevalence of mental health at a moment in time, public Twitter is a continuously available data source that can provide a broader window into population mental health. We characterized the relationship between COVID-19 case counts, stay-at-home orders because of COVID-19, and anxiety and depression in 7 major U.S. cities utilizing Twitter data. Methods: We collected 18 million Tweets from January to September 2019 (baseline) and 2020 from 7 U.S. cities with large populations and varied COVID-19 response protocols: Atlanta, Chicago, Houston, Los Angeles, Miami, New York, and Phoenix. We applied machine learning‒based language prediction models for depression and anxiety validated in previous work with Twitter data. As an alternative public big data source, we explored Google Trends data using search query frequencies. A qualitative evaluation of trends is presented. Results: Twitter depression and anxiety scores were consistently elevated above their 2019 baselines across all the 7 locations. Twitter depression scores increased during the early phase of the pandemic, with a peak in early summer and a subsequent decline in late summer. The pattern of depression trends was aligned with national COVID-19 case trends rather than with trends in individual states. Anxiety was consistently and steadily elevated throughout the pandemic. Google search trends data showed noisy and inconsistent results. Conclusions: Our study shows the feasibility of using Twitter to capture trends of depression and anxiety during the COVID-19 public health crisis and suggests that social media data can supplement survey data to monitor long-term mental health trends. © 2022 The Author(s)

关键词： coronavirus mental health Social media stay-at-home order

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Emergent dimer-model topological order and quasi-particle excitations in liquid crystals: combinatorial vortex lattices

arXiv

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arXiv 2025年

作者： Meng, Cuiling Wu, Jin-Sheng Kos, Žiga Dunkel, Jörn Nisoli, Cristiano Smalyukh, Ivan I. Department of Physics and Chemical Physics Program University of Colorado BoulderCO80309 United States Hiroshima University Hiroshima Higashihiroshima Japan Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States Faculty of Mathematics and Physics University of Ljubljana Ljubljana Slovenia Department of Condensed Matter Physics Jožef Stefan Institute Ljubljana Slovenia Theoretical Division Physics of Condensed Matter and Complex Systems Center For Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program University of Colorado BoulderCO80309 United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

Liquid crystals have proven to provide a versatile experimental and theoretical platform for studying topological objects such as vortices, skyrmions, and hopfions. In parallel, in hard condensed matter physics, the concept of topological phases and topological order has been introduced in the context of spin liquids to investigate emergent phenomena like quantum Hall effects and high-temperature superconductivity. Here, we bridge these two seemingly disparate perspectives on topology in physics. Combining experiments and simulations, we show how topological defects in liquid crystals can be used as versatile building blocks to create complex, highly degenerate topological phases, which we refer to as ‘Combinatorial Vortex Lattices’ (CVLs). CVLs exhibit extensive residual entropy and support locally stable quasi-particle excitations in the form of charge-conserving topological monopoles, which can act as mobile information carriers and be linked via Dirac strings. CLVs can be rewritten and reconfigured on demand, endowed with various symmetries, and modified through laser-induced topological surgery — an essential capability for information storage and retrieval. We demonstrate experimentally the realization, stability, and precise optical manipulation of CVLs, thus opening new avenues for understanding and technologically exploiting higher-hierarchy topology in liquid crystals and other ordered media. Copyright © 2025, The Authors. All rights reserved.

关键词： Laser surgery

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BPS2025 - Systematic embedding of biomechanics within dynamical graph grammars with application to actin networks in dendritic spine heads

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Biophysical Journal 2025年第3期124卷 206a-206a页

作者： Eric Mjolsness Matthew Hur Thomas M. Bartol Terrence J. Sejnowski Departments of Computer Science and Mathematics University of California Irvine Irvine CA USA Mathematical Computational and Systems Biology Program University of California Irvine Irvine CA USA Computational Neurobiology Laborartory Salk Institute for Biological Studies San Diego CA USA

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The 2020 power blackout in the brazilian state of amapá: Lessons learned and opportunities

The 2020 power blackout in the brazilian state of amapá: Le...

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2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021

作者： Do Prado, Josue Campos Santos, Marcos Vinicius Ramos, Lucas Feksa Canha, Luciane Neves Konzen, Gabriel School of Engineering Computer Science Washington State University VancouverWA98686 United States School of Engineering Newcastle University Newcastle Upon TyneNE1 7RU United Kingdom Federal University of Rondônia Department of Electrical Engineering Porto Velho Brazil Graduate Program in Electrical Engineering Federal University of Santa Maria Santa Maria Brazil Division of Energy Economics and Environmental Studies Rio de Janeiro Brazil

ISBN: (纸本)9781665444217

The Brazilian state of Amapa=-notable for having 70% of its area consisting of unexplored Amazonian forests-experienced a massive power blackout in November 2020. An internal short-circuit in a transformer led to an explosion followed by a fire at the Macapa substation. This event left about 90% of the Amapa's population without power for several days in the middle of the COVID-19 pandemic, disrupting the lives of hundreds of thousands of people and raising concerns from several electricity sector stakeholders. This paper discusses select lessons learned from the power blackout and presents future opportunities to improve power system reliability and resilience for the grids in Amapá, and other similar Brazilian states, with a special focus on the increasingly important role of of distributed energy resources and smart grid technologies. © 2021 IEEE.

关键词： Outages

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Mining GIS data to predict urban sprawl

arXiv

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arXiv 2021年

作者： Pampoore-Thampi, Anita Varde, Aparna S. Yu, Danlin Department of Computer Science Montclair State University MontclairNJ United States Department of Earth and Environmental Studies Montclair State University MontclairNJ United States Environmental Management PhD Program Montclair State University MontclairNJ United States

This paper addresses the interesting problem of processing and analyzing data in geographic information systems (GIS) to achieve a clear perspective on urban sprawl. The term "urban sprawl" refers to overgrowth and expansion of low-density areas with issues such as car dependency and segregation between residential versus commercial use. Sprawl has impacts on the environment and public health. In our work, spatiotemporal features related to real GIS data on urban sprawl such as population growth and demographics are mined to discover knowledge for decision support. We adapt data mining algorithms, Apriori for association rule mining and J4.8 for decision tree classification to geospatial analysis, deploying the ArcGIS tool for mapping. Knowledge discovered by mining this spatiotemporal data is used to implement a prototype spatial decision support system (SDSS). This SDSS predicts whether "urban sprawl" is likely to occur. Further, it estimates the values of pertinent variables to understand how the variables impact each other. The SDSS can help decision-makers identify problems and create solutions for avoiding future sprawl occurrence and conducting urban planning where sprawl already occurs, thus aiding sustainable development. This work falls in the broad realm of geospatial intelligence and sets the stage for designing a large scale SDSS to process big data in complex environments, which constitutes part of our future work. © 2021, CC BY-SA.

关键词： Association rules

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