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Parametric Design:Measuring Learning States

Journal of Civil Engineering and Architecture 2020年第12期14卷 658-667页

作者： Ernani Z andona Pazini Andrea Quadrado Mussi Amilton Rodrigo de Quadros Martins Postgraduate Program in Architecture and Urbanism(PPGARQ)of the Polytechnic School at Faculdade Meridional(IMED) Passo Fundo/RSCEP 99070-220Brazil Laboratory of Education Science and Innovation Faculdade Meridional(IMED)Passo Fundo/RSCEP 99070-220Brazil

Project teaching and learning comprises properties,strategies and procedures that currently involve computational thinking and logical *** general,this problem arises from the possibilities offered by the new software and the increase of the level of dominion of the project by the *** this context,this study aims to estimate how much the student profile contemporary of architecture is motivated and engaged in learning new project processes that use computational reasoning and logical reasoning,characteristic of parametric ***,the research is based on the theory of flow,presents results of an investigation of engagement and learning of students of a school of Architecture and Urbanism in Brazil,referring to the themes and uses of parametric *** study contributed to the practice and use of parametric design in the educational environment,besides allowing the integration of computational thinking in the creative process of the project.

关键词： Parametric design project processes learning computational thinking

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Predicting Protein Interaction Network Perturbation by Alternative Splicing with Semi-Supervised Learning

SSRN

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SSRN 2020年

作者： Narykov, Oleksandr Johnson, Nathan Korkin, Dmitry Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA United States Harvard Program in Therapeutic Sciences Harvard Medical School Breast Tumor Immunology Laboratory Dana-Farber Cancer Institute BostonMA United States Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA United States

Alternative splicing introduces a new layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. In particular, recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions, yet the extent to which the macromolecular interactions are affected by alternative splicing has to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here we develop an accurate feature-based machine learning approach that predicts if a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method called ALTernatively Spliced INteractions prediction (ALT-IN) Tool was compared with the state-of-the-art PPI prediction tools and showed superior performance, achieving 0.92 in precision and recall values. © 2020, The Authors. All rights reserved.

关键词： Forecasting

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Determinants and Predictors of Intentionality and Perceived Reliability in Human-AI Interaction as a Means for Innovative Scientific Discovery

Determinants and Predictors of Intentionality and Perceived ...

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IEEE International Conference on Big Data

作者： António Correia Benjamim Fonseca Hugo Paredes Ramon Chaves Daniel Schneider Shoaib Jameel INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research (NCE) Federal University of Rio de Janeiro Brazil School of Computer Science and Electronic Engineering Colchester Campus University of Essex UK

ISBN: (纸本)9781665445993

With the increasing development of human-AI teaming structures within and across geographies, the time is ripe for a continuous and objective look at the predictors, barriers, and facilitators of human-AI scientific collaboration from a multidisciplinary point of view. This paper aims at contributing to this end by exploiting a set of factors affecting attitudes towards the adoption of human-AI interaction into scientific work settings. In particular, we are interested in identifying the determinants of trust and acceptability when considering the combination of hybrid human-AI approaches for improving research practices. This includes the way as researchers assume human-centered artificial intelligence (AI) and crowdsourcing as valid mechanisms for aiding their tasks. Through the lens of a unified theory of acceptance and use of technology (UTAUT) combined with an extended technology acceptance model (TAM), we pursue insights on the perceived usefulness, potential blockers, and adoption drivers that may be representative of the intention to use hybrid intelligence systems as a way of unveiling unknown patterns from large amounts of data and thus enabling novel scientific discoveries.

关键词： Geography Crowdsourcing Technology acceptance model Big Data Predictive models Data models Reliability

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Erratum to “Binder-free ultrathin pellets of nanocomposites based on Fe 3 O 4 @nitrogen-doped reduced graphene oxide aerogel for electromagnetic interference shielding” [J. Alloys Compd., vol. 978, 25 March 2024, 173329]

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Journal of Alloys and Compounds 2024年 983卷

作者： A.S. Carvalho A.R. Santos D.C.O. Cabral D.M. Oliveira L.K.C.S. Assis E.L.T. França F.R.S. Quirino S. Castro-Lopes O.M.M.M. da Costa E. Padrón-Hernández Postgraduate Program in Materials Science (PGMTR) Federal University of Pernambuco (UFPE) Recife PE Brazil Department of Physics (DF) UFPE Recife PE Brazil Pernambuco Polytechnic School (Poli) University of Pernambuco (UPE) Recife PE Brazil Brazilian Synchrotron Light Laboratory (LNLS) Brazilian Center for Research in Energy and Materials (CNPEM) Campinas SP Brazil

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Effect of dual modification on structural, functional and dielectric properties of cassava starch

Food Physics

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Food Physics 2025年 2卷

作者： Cremasco, Paula Figueiredo M. Siqueira, Karine Mayuri Pistoni Sobral, Paulo José do Amaral Velloso, Walter Ferreira de Lima, César Gonçalves Gut, Jorge Andrey Wilhelms Moraes, Izabel Cristina Freitas Postgraduate Program in Materials Science and Engineering Faculty of Animal Science and Food Engineering University of São Paulo Avenue Duque de Caxias Norte São Paulo Pirassununga 13635900 Brazil Department of Biossistems Engineering Faculty of Animal Science and Food Engineering University of São Paulo Avenue Duque de Caxias Norte São Paulo Pirassununga 13635900 Brazil Department of Food Engineering Faculty of Animal Science and Food Engineering University of São Paulo Avenue Duque de Caxias Norte São Paulo Pirassununga 13635900 Brazil Food Research Center (FoRC) University of São Paulo Lake Street São Paulo São Paulo 05508-080 Brazil Departament of Basic Sciences Faculty of Animal Science and Food Engineering University of São Paulo Avenue Duque de Caxias Norte São Paulo Pirassununga 13635900 Brazil Department of Chemical Engineering Polytechnic School University of São Paulo Lake Street São Paulo São Paulo 05508-080 Brazil

The combined effect of hydrocolloid addition and microwave heating on the structural, physical and functional properties of cassava starch remains underexplored, despite individual studies on these modification methods. The dielectric properties, important for the microwave treatment of starch, have received little attention in recent studies. Cassava starch with and without addition of hydrocolloids (guar and xanthan gums) was modified by microwave heating for two different exposure times, and its structural, functional, and dielectric properties were studied. The dual modification enhanced the swelling power and oil holding capacity of the starch, reduced its gelatinization temperature, and did not alter its crystallinity. Notably, xanthan-modified starch microwaved for 6 min exhibited higher color variation (ΔE*) and increased granules agglomeration, while the microwave treatment alone roughened the surface of the starch granules. The mean diameters D[4,3] of starch increased with xanthan gum addition, microwave treatment (6 min), and their combination. The relative permittivity (ε’), loss factor (ε”) and penetration depth (D_p) were lower for samples modified by the combined method. Considering the type of hydrocolloid and the microwave exposure time, the combined modification significantly influenced the properties of starch, offering a promising approach to producing starch with enhanced functional properties. © 2024 KeAi Communications Co., Ltd

关键词： Biopolymers Cassava starch Guar Microwave Xanthan

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Real-time river level estimation based on variations of radar reflectivity—a case study of the Quitandinha River watershed, Petrópolis, Rio de Janeiro (Brazil)

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Bulletin of Atmospheric science and Technology 2021年第1-4期2卷 1-20页

作者： da Silva, Fabricio Polifke Rotunno Filho, Otto Corrêa Justi da Silva, Maria Gertrudes Alvarez Sampaio, Rafael João Pires, Gisele Dornelles de Araújo, Afonso Augusto Magalhães Civil Engineering Program Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering – COPPE Universidade Federal do Rio de Janeiro RJ Rio de Janeiro 21945-970 Brazil Engineering and Society Group Exact Sciences and Technologies School Universidade Iguaçu UNIG Av. Abílio Augusto Távora 2134 Jardim Nova Era RJ Nova Iguaçu 26275-580 Brazil Meteorology Laboratory Science and Technology Center Universidade Estadual do Norte Fluminense Darcy Ribeiro – UENF Avenida Brenand s.n. Imboassica RJ Macaé 27925-535 Brazil Department of Water Resources and Environment Polytechnic School Universidade Federal do Rio de Janeiro – UFRJ Av. Athos da Silveira Ramos CT Escola Politécnica Cidade Universitária RJ Rio de Janeiro 21941-590 Brazil

The real-time warning for flash floods represents one of the major challenges for monitoring centers and civil defenses due to the short time frame in which such phenomena occur. That situation often takes place particularly in mountainous regions where high slope rate favors an increase in the velocity of the water flow and it might generate conditions to impact the water level due to potential for provoking erosion, landslides, and debris flow. An initial one new and unique prototype of hydrometeorological relationship for real-time, site-tunable, water level for flash flood prediction is presented. Time variations of the reflectivity measured by horizontal polarization radar are evaluated and correlated to generate the local estimate of the elevation of the Quitandinha River water level for the next hour. The proposal of this relationship is not intended to act as a simplified hydraulic model but to characterize if a critical elevation of the water level could be obtained from the radar reflectivity data and consequently whether the flash flooding event should be expected. We verified that the proposed relationship that tended to underestimate the water level peaks, however, qualitatively was initially able to indicate if a flood event could occur or not in the next hour. The expectation related to this initial relationship is to improve the obtained results in order to be used as a tool for decision-making in relation to the issuance of warnings delivered by environmental monitoring centers. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature.

关键词： Nowcasting Reflectivity River level Weather radar reflectivity

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Wireless- Powered UAV assisted Communication System in Nakagami-m Fading Channels

Wireless- Powered UAV assisted Communication System in Nakag...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Tharindu D. Ponnimbaduge Perera Dushantha Nalin K. Jayakody Sahil Garg Neeraj Kumar Ling Cheng School of Computer Science and Robotics National Research Tomsk Polytechnic University RUSSIA School of Postgraduate Studies & Research Sri Lanka Technological Campus Padukka SRI LANKA Ecole de technologie supérieure Montreal QC CANADA Thapar Institute of Engineering and Technology INDIA School of Electrical and Information Engineering University of the Witwatersrand SOUTH AFRICA

ISBN: (数字)9781728138930

ISBN: (纸本)9781728138947

Recently, the use of unmanned aerial vehicles (UAVs) as a relay node has been envisaged as an enabling technology in the upcoming wireless communication era. Thus, in this paper, we consider a full-duplex (FD) cooperative communication system with a source and a destination, where UAV serves as a mobile relay. Here, the transmission power cost is debited to energy harvested using simultaneous wireless information and power transfer (SWIPT) and self-interference energy harvesting (EH) via power-splitting (PS) protocol. In poor channel conditions, UAV uses a soft angular modulation scheme to perceive the soft information. In this proposed system, we present the outage probability over the Nakagami-m fading channels. A closed-form solution for the outage probability is derived. In addition, we formulate an optimization problem to minimize end-to-end outage probability subject of the UAV's power profile. The KKT conditions have been used to obtain a closed-form solution of the proposed optimization problem. Finally, numerical results are provided to evaluate the proposed system under various setups.

关键词： autonomous aerial vehicles cooperative communication energy harvesting minimisation mobile radio Nakagami channels probability protocols radiofrequency interference relay networks (telecommunication) telecommunication network reliability telecommunication Nakagami channels cooperative communication Unmanned Aerial Vehicle telecommunication network reliability Radiofrequency interference Mobile radios energy harvesting Telecommunications drone honey bees Probability protocols COMMUNICATION SYSTEMS Trunk Node Fading channels

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Fast, accurate, and versatile data analysis platform for the quantification of molecular spatiotemporal signals

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Cell 2025年第10期188卷 2794-2809.e21页

作者： Mi, Xuelong Chen, Alex Bo-Yuan Duarte, Daniela Carey, Erin Taylor, Charlotte R. Braaker, Philipp N. Bright, Mark Almeida, Rafael G. Lim, Jing-Xuan Ruetten, Virginia M.S. Wang, Yizhi Wang, Mengfan Zhang, Weizhan Zheng, Wei Reitman, Michael E. Huang, Yongkang Wang, Xiaoyu Li, Lei Deng, HanFei Shi, Song-Hai Poskanzer, Kira E. Lyons, David A. Nimmerjahn, Axel Ahrens, Misha B. Yu, Guoqiang Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington 22203 VA United States Janelia Research Campus Howard Hughes Medical Institute Ashburn 20147 VA United States Department of Molecular and Cellular Biology Harvard University Cambridge 02138 MA United States Graduate Program in Neuroscience Harvard Medical School Boston 02115 MA United States Waitt Advanced Biophotonics Center The Salk Institute for Biological Studies La Jolla 92037 CA United States Department of Biochemistry & Biophysics University of California San Francisco San Francisco CA United States Neuroscience Graduate Program University of California San Francisco San Francisco CA United States Centre for Discovery Brain Sciences University of Edinburgh Edinburgh BioQuarter Edinburgh EH16 4SB United Kingdom Gatsby Computational Neuroscience Unit UCL London W1T 4JG United Kingdom Kavli Institute for Fundamental Neuroscience San Francisco CA United States Department of Automation Tsinghua University Beijing 100084 China IDG/McGovern Institute for Brain Research Tsinghua University Beijing 100084 China New Cornerstone Science Laboratory Tsinghua-Peking Center for Life Sciences Beijing Frontier Research Center for Biological Structure School of Life Sciences Tsinghua University Beijing 100084 China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University Shanghai 200032 China Beijing National Research Center for Information Science and Technology Beijing 100084 China

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce activity quantification and analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine-learning techniques. It decomposes complex live-imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, microscopy techniques, and imaging approaches. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, as well as distinct sensorimotor signal propagation patterns in the mouse spinal cord. © 2025 The Author(s)

关键词： AQuA2 astrocytes cell interaction analysis functional units glial cells image analysis machine learning molecular spatiotemporal signals neurons time-lapse imaging

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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A Step Towards a Reinforcement Learning De Novo Genome Assembler

Research Square

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Research Square 2021年

作者： Padovani, Kleber Xavier, Roberto Carvalho, André Reali, Anna Chateau, Annie Alves, Ronnie Federal University of Pará Computer Science Graduate Program Belém66.075-110 Brazil University of the State of Amazonas Itacoatiara-AM 69.101-416 Brazil Vale Technology Institute Sustainable Development Belém66.055-090 Brazil Institute of Mathematics and Computer Sciences University of São Paulo São Carlos-SP 13566-590 Brazil Polytechnic School University of São Paulo São Paulo-SP 05508-010 Brazil LIRMM-Montpellier Laboratory of Informatics Robotics and Microelectronics Univ Montpellier CNRS Montpellier France

Genome assembly is one of the most relevant and computationally complex tasks in genomics projects. It aims to reconstruct a genome through the analysis of several small textual fragments of such genome — named reads. Ideally, besides ignoring any errors contained in reads, the reconstructed genome should also optimally combine these reads, thus reaching the original genome. The quality of the genome assembly is relevant because the more reliable the genomes, the more accurate the understanding of the characteristics and functions of living beings, and it allows generating many positive impacts on society, including the prevention and treatment of diseases. The assembly becomes even more complex (and it is termed de novo in this case) when the assembler software is not supplied with a similar genome to be used as a reference. Current assemblers have predominantly used heuristic strategies on computational graphs. Despite being widely used in genomics projects, there is still no irrefutably best assembler for any genome, and the proper choice of these assemblers and their configurations depends on Bioinformatics experts. The use of reinforcement learning has proven to be very promising for solving complex activities without human supervision during their learning process. However, their successful applications are predominantly focused on fictional and entertainment problems - such as games. Based on the above, this work aims to shed light on the application of reinforcement learning to solve this relevant real-world problem, the genome assembly. By expanding the only approach found in the literature that addresses this problem, we carefully explored the aspects of intelligent agent learning, performed by the Q-learning algorithm, to understand its suitability to be applied in scenarios whose characteristics are more similar to those faced by real genome projects. The improvements proposed here include changing the previously proposed reward system and including stat

关键词： Reinforcement learning

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