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arXiv 2020年

作者： Siebert, Luciano Cavalcante Mercuur, Rijk Dignum, Virginia van den Hoven, Jeroen Jonker, Catholijn Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Netherlands Faculty of Technology Policy and Management Delft University of Technology Netherlands Department of Computing Sciences Ume University Sweden Leiden Institute of Advance Computer Science Leiden University Netherlands

Autonomous agents (AA) will increasingly be interacting with us in our daily lives. While we want the benefits attached to AAs, it is essential that their behavior is aligned with our values and norms. Hence, an AA will need to estimate the values and norms of the humans it interacts with, which is not a straightforward task when solely observing an agent's behavior. This paper analyses to what extent an AA is able to estimate the values and norms of a simulated human agent (SHA) based on its actions in the ultimatum game. We present two methods to reduce ambiguity in profiling the SHAs: one based on search space exploration and another based on counterfactual analysis. We found that both methods are able to increase the confidence in estimating human values and norms, but differ in their applicability, the latter being more efficient when the number of interactions with the agent is to be minimized. These insights are useful to improve the alignment of AAs with human values and norms. Copyright © 2020, The Authors. All rights reserved.

关键词： Autonomous agents

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The IDEAL framework for surgical robotics: development, comparative evaluation and long-term monitoring (vol 30, pg 61, 2024)

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NATURE MEDICINE 2024年第4期30卷 1213-1213页

作者： Marcus, Hani J. Ramirez, Pedro T. Khan, Danyal Z. Horsfall, Hugo Layard Hanrahan, John G. Williams, Simon C. Beard, David J. Bhat, Rani Catchpole, Ken Cook, Andrew Hutchison, Katrina Martin, Janet Melvin, Tom Stoyanov, Danail Rovers, Maroeska Raison, Nicholas Dasgupta, Prokar Noonan, David Stocken, Deborah Sturt, Georgia Vanhoestenberghe, Anne Vasey, Baptiste McCulloch, Peter Department of Neurosurgery National Hospital of Neurology and Neurosurgery London UK Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS) London UK Department of Obstetrics and Gynaecology Houston Methodist Hospital Neal Cancer Center Houston TX USA RCS Surgical Interventional Trials Unit (SITU) & Robotic and Digital Surgery Initiative (RADAR) Nuffield Dept Orthopaedics Rheumatology and Musculo-skeletal Sciences University of Oxford Oxford UK Department of Gynaecological Oncology Apollo Hospital Bengaluru India Department of Anaesthesia and Perioperative Medicine Medical University of South Carolina Charleston SC USA NIHR Coordinating Centre and Clinical Trials Unit University of Southampton Southampton UK Department of Philosophy Macquarie University Sydney Australia Department of Anesthesia & Perioperative Medicine University of Western Ontario Ontario Canada Department of Medical Gerontology School of Medicine Trinity College Dublin Dublin Republic of Ireland Department of Medical Imaging Radboudumc Nijmegen the Netherlands Department of Biomedical Engineering and Imaging Sciences King’s College London London UK King’s Health Partners Academic Surgery King’s College London London UK Moon Surgical Paris France RCSEng Surgical Trials Centre Leeds Institute of Clinical Trials Research University of Leeds Leeds UK Bowel Research UK London UK School of Biomedical Engineering & Imaging Sciences King’s College London London UK Department of Surgery Geneva University Hospital Geneva Switzerland Nuffield Department of Surgical Sciences University of Oxford John Radcliffe Hospital Oxford UK PRISMA Lab University of Naples Federico II Naples Italy Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich Switzerland School of Computer Science University of Birmingham Birmingham UK Division of Cardiac Surgery Brigham and Women’s Hospital Harvard Medical Schoo

The next generation of surgical robotics is poised to disrupt healthcare systems worldwide, requiring new frameworks for evaluation. However, evaluation during a surgical robot’s development is challenging due to their complex evolving nature, potential for wider system disruption and integration with complementary technologies like artificial intelligence. Comparative clinical studies require attention to intervention context, learning curves and standardized outcomes. Long-term monitoring needs to transition toward collaborative, transparent and inclusive consortiums for real-world data collection. Here, the Idea, Development, Exploration, Assessment and Long-term monitoring (IDEAL) Robotics Colloquium proposes recommendations for evaluation during development, comparative study and clinical monitoring of surgical robots—providing practical recommendations for developers, clinicians, patients and healthcare systems. Multiple perspectives are considered, including economics, surgical training, human factors, ethics, patient perspectives and sustainability. Further work is needed on standardized metrics, health economic assessment models and global applicability of recommendations.

关键词： Medical research Surgery

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Genome-Wide Association Analyses in Family Triads and Dyads Following Assisted Reproductive Technology

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Genetic Epidemiology 2025年第5期49卷 e70011页

作者： Skodvin, Siri N. Gjessing, Håkon K. Jugessur, Astanand Romanowska, Julia Havdahl, Alexandra Håberg, Siri E. Hanevik, Hans Ivar Lyle, Robert Lie, Rolv Terje Gjerdevik, Miriam Centre for Fertility and Health Norwegian Institute of Public Health Oslo Norway Department of Global Public Health and Primary Care University of Bergen Bergen Norway PsychGen Centre for Genetic Epidemiology and Mental Health Norwegian Institute of Public Health Oslo Norway Nic Waals Institute Lovisenberg Diaconal Hospital Oslo Norway Department of Fertility Telemark Hospital Trust Porsgrunn Norway Department of Medical Genetics Oslo University Hospital and University of Oslo Oslo Norway Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen Norway

Genetic selection occurs at different stages before a successful birth. The genetic makeup of a couple may influence the likelihood of needing assisted reproductive technology (ART) to achieve conception. However, frequent early fetal losses may also be perceived as reduced couple fertility and may thus be a contributing factor to the need for ART treatment. As ART procedures may enhance early fetal survival, genes that impact fetal viability may have a different allele distribution in ART offspring than expected under Mendelian transmission, as well as compared with the general population. With genetic data available from the Norwegian Mother, Father, and Child Cohort Study, we defined fetal survival as the study outcome and analyzed 1336 case-parent triads and dyads where the offspring were conceived by ART. Using log-linear models implemented in the R package Haplin, we conducted genome-wide scans to estimate fetal, maternal, and parent-of-origin effects and provided a detailed discussion on how these effects are estimated and interpreted. We detected fetal effects for single-nucleotide polymorphisms (SNPs) located in CXXC4-AS1, OPCML, and DYNLRB2-AS1. Since these effects were not observed in a limited follow-up analysis of non-ART triads, the identified effects are unlikely caused by genetic selection before fertilization. © 2025 The Author(s). Genetic Epidemiology published by Wiley Periodicals LLC.

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Categorizing E-cigarette-related tweets using BERT topic modeling

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Emerging Trends in Drugs, Addictions, and Health 2024年 4卷 100160-100160页

作者： Murthy, D. Keshari, S. Arora, S. Yang, Q. Loukas, A. Schwartz, S.J. Harrell, M.B. Hébert, E.T. Wilkinson, A.V. Professor of Media Studies Sociology and Information University of Texas at Austin United States Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX United States Department of Kinesiology & Health Education College of Education The University of Texas at Austin Austin TX United States Department of Communication Studies Bob Schieffer College of Communication Texas Christian University Fort Worth TX United States Department of Kinesiology & Health Education College of Education University of Texas at Austin TX United States Professor of Kinesiology Health Education and Educational Psychology College of Education The University of Texas at Austin United States Department of Epidemiology University of Texas Health Science Center at Houston School of Public Health Austin TX United States Department of Health Promotion and Behavioral Sciences University of Texas Health Science Center at Houston School of Public Health Austin TX United States

Background: Social media platforms are critical channels for promoting e-cigarettes, particularly among youth, making analysis of their vast and diverse content essential for public health interventions. Prevalence rates of e-cigarette use are high and evidence suggests that social media are popular forums that promote e-cigarette use through direct and indirect marketing techniques. The volume and diverse nature of e-cigarette-related information on social media is challenging and may obfuscate public health prevention messaging. Traditional hand-coding methods are labor-intensive and limit scalability. In contrast, unsupervised machine learning approaches, such as topic modeling, allow for efficient analysis of large datasets, uncovering patterns and trends that manual methods cannot achieve at scale. The present study focused on ascertaining the extent to which themes and topics in tweets related to e-cigarettes can be successfully rendered into useful homogenous units using machine learning. A better understanding of current depictions and discussions around e-cigarette products and use on social media can inform public health counter messaging and policy interventions. Methods: We used topic modeling (BERTopic) to iteratively derive vape-related tweet clusters and calculate the importance of particular words to these groupings. We conducted a qualitative content analysis to study clustered tweets. We also sought to determine the geographic locations of e-cigarette conversations using automated geoparsing methods, which translate toponyms in textual data into geographic identifiers, to attempt to infer the location of tweets. Results: We were able to successfully identify >100,000 tweets in broad thematic categories in English and Spanish. Our correlation and inter-topic map analysis of the machine-derived topics, which examines the relationships between topics, indicated that most of the topics were unique (correlation value < 0.5) and did not overlap with each

关键词： Bertopic E-cigarettes Natural language processing Topic modeling Vape

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Systems biology and bioinformatics approach to identify gene signatures, pathways and therapeutic targets of Alzheimer's disease

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Informatics in Medicine Unlocked 2020年 21卷

作者： Chowdhury, Utpala Nanda Islam, M. Babul Ahmad, Shamim Moni, Mohammad Ali Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh Department of Electrical and Electronic Engineering University of Rajshahi Bangladesh Department of Computer Science and Engineering Pabna University of Science and Technology Pabna Bangladesh WHO Collaborating Centre on eHealth School of Public Health and Community Medicine Faculty of Medicine University of New South Wales Sydney Australia

Alzheimer's disease (AD) develops relentlessly in affected individuals and its occurrence is increasing. A clinical test to diagnose early-stage AD could be an important means of enabling interventions to slow its progression. However, available neuroimaging and cerebrospinal fluid-based diagnoses are very costly. Therefore, detecting AD from blood transcripts that mirror the expression of brain transcripts in the AD could improve the diagnosis. To achieve this goal, we employed a transcriptional analysis of affected tissues and integrated them with cis-eQTL data. In this study, we analyzed microarray gene expression data of brain and blood cells from AD patients and control individuals. Differentially expressed genes (DEGs) common to both brain tissue and blood cells were identified. Potential common genes and molecular pathways were identified using overlapping DEGs through the pathway and gene ontology enrichment analysis. We identified 18 significantly dysregulated genes shared by both brain and blood cells in AD affected individuals. We validated these candidates as disease-associated genes using gold-standard benchmarking databases (gene SNP-disease linkage). Significant molecular pathway and gene ontology indicating AD progression were identified. This study also identified regulatory factors, including transcription factors (TFs), microRNAs and candidate drugs. In sum, we identified new putative links between pathological processes in brain tissue and blood cells in AD that may allow assessment of AD status using blood samples. Thus, our formulated methodologies demonstrate the power of gene and gene expression analysis for brain-related pathologies transcriptomics, cis-eQTL, and epigenetics data from brain and blood cells. © 2020 The Author(s)

关键词： Alzheimer's disease (AD) Blood Brain cis-eQTL GWAS

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Microplastics and nanoplastics in environment: Sampling, characterization and analytical methods

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Groundwater for Sustainable Development 2024年 26卷

作者： Mahapatra, Sarbanee Maity, Jyoti Prakash Singha, Shuvendu Mishra, Tanisha Dey, Gobinda Chandra Samal, Alok Banerjee, Pritam Biswas, Chhanda Chattopadhyay, Sourasis Patra, Rasmi Ranjan Patnaik, Sneha Bhattacharya, Prosun Environmental Science laboratory Department of Chemistry School of Applied Sciences KIIT Deemed to be University Odisha Bhubaneswar751024 India Department of Agricultural Chemistry National Taiwan University Taipei106319 Taiwan Department of Environmental Science University of Kalyani Nadia West Bengal 741235 India Department of Environmental Science Policy and Management University of California University Avenue and Oxford St BerkeleyCA94720 United States Research & Development KIIT Deemed to be University Odisha Bhubaneswar751024 India Department of Computer Science & Application Odisha University of Agriculture & Technology Odisha Bhubaneswar India School of Public Health KIMS Medical College KIIT University Bhubaneswar751024 India Department of Healthcare Administration Asia University ROC Taiwan KTH-International Groundwater Arsenic Research Group Department of Sustainable Development Environmental Science and Engineering KTH Royal Institute of Technology Teknikringen 10B StockholmSE-100 44 Sweden

Microplastics (MPs) and nanoplastics (NPs) have gained increasing attention in environmental research due to their ubiquitousness and potential impacts on natural environments and human health as per the UN Sustainable Development Goals (SDGs), particularly SDG-14 to address global threats where at least 12 SDGs, directly/indirectly impacts. Present review is undertaken to highlight the process of breakdown of diverse groups of plastic products in soil, surface water, and groundwater under the influence of different factors (UV, light, heat, microbe, etc.), which are mobilized as MPs/NPs to the surface water, groundwater, air, soil, and living organisms by different natural and anthropogenic processes. Review also highlights a comprehensive overview of the methodology for sampling, characterization, and analysis for these minuscule plastic particles (PPs) in various environmental samples, encompassing surface/subsurface water, sediments, soils, and biological organisms. The collection, extraction, and characterization of MPs/NPs, typically employ filtration processes, wherein a known volume of water is passed through a fine mesh to capture MPs/NPs from water samples. Sediment/soil samples require sieving and density separation techniques to isolate PPs from the surrounding matrix. Biological samples require digestion steps to remove organic matter, leaving behind plastics for analysis. Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and scanning electron microscopy (SEM) are commonly utilized to determine the polymer composition, size, shape, and surface characteristics of PPs. Quantification involves several approaches, visual counting, image analysis, and spectroscopic techniques. Abundance of MPs/NPs in the respective environmental samples (water, air, soil, etc.) can be determined by comparing the richness (i.e., number/mass) of plastics to the volume or weight of the original sample. Such comprehensive analytical methodologies contribute to

关键词： Sustainable development

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FTP1.7 Critical decision analysis of pre-hospital major haemorrhage protocol activation

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British Journal of Surgery 2023年第SUPPLEMENT_6期110卷

作者： Wohlgemut, Jared McMullen, Heather Marsden, Max Marsh, William Perkins, Zane Tai, Nigel Centre for Trauma Sciences Blizard Institute Queen Mary University of London London UK Global Public Health Unit Centre for Public Health and Policy Wolfson Institute of Population Health Queen Mary University of London London UK Department of Electrical Engineering and Computer Science Queen Mary University of London London UK London’s Air Ambulance 17th Floor Royal London Hospital London UK Trauma Service Royal London Hospital Barts Health NHS Trust London UK

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Capacity/cost trade-off for 5G small cell networks in the UHF and SHF bands

Capacity/cost trade-off for 5G small cell networks in the UH...

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International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Emanuel B. Teixeira Anderson R. Ramos Marisa S. Lourenço Fernando J. Velez Jon M. Peha Instituto de Telecomunicacções DEM Universidade da Beira Interior Covilhã Portugal Dept. of Electrical and Computer Engineering Dept. of Engineering & Public Policy Carnegie Mellon University Pittsburgh USA

ISBN: (数字)9781728154190

ISBN: (纸本)9781728154206

To fulfill the demand for high data rates from a wide number of users, higher frequencies can be used to provide the required capacity but with a different cost structure. 5G allows for very high data rates, which needs large bandwidths and requires very high throughput. This paper studies the economic trade-off of small cell networks deployed in Ultra High Frequency (UHF) and Super High Frequency (SHF) bands. Aiming at evaluating the variation of the carrier-to-noise-plus-interference ratio with the cell radius one considers the two-slope urban micro Line-of-Sight (UMiLoS) path loss model (ITU-R 2135 Report). The system capacity is analysed by the implicit function formulation to compute the supported cell throughput through the mapping of the PHY throughput into the step distances that correspond to the minimum carrier-to-interference-plus-noise ratio for each consecutive modulation and coding scheme. The variation of the equivalent supported throughput with the cell size at the 2.6, 3.5 and 5.62 GHz frequency bands facilitates to study the influence of the carrier-to-noise-plus-interference ratio in the dimensioning process. It is possible to conclude that, for the shortest cell radii, the profit is very low, starting to increase at a distance equal to the ratio between the break-point distance and the co-channel reuse factor attaining maxima for values of the cell radius approximately equal to 310, 390 and 740 m, at 2.6, 3.5 and 5.62 GHz, respectively (by assuming that the 5.62 GHz frequency band is unlicensed).

关键词： Throughput 5G mobile communication computer architecture Bandwidth Microprocessors Topology Modulation

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Publisher Correction: wMel replacement of dengue-competent mosquitoes is robust to near-term climate change

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Nature Climate Change 2024年第1期14卷 106页

作者： Váleri N. Vásquez Lara M. Kueppers Gordana Rašić John M. Marshall Energy and Resources Group University of California Berkeley CA USA Department of Electrical Engineering and Computer Sciences College of Engineering University of California Berkeley CA USA Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USA Mosquito Genomics QIMR Berghofer Medical Research Institute Brisbane Queensland Australia Divisions of Epidemiology and Biostatistics School of Public Health University of California Berkeley CA USA Innovative Genomics Institute University of California Berkeley CA USA

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Discovery method for distributed denial-of-service attack behavior in SDNs using a feature-pattern graph model

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Frontiers of Information Technology & Electronic engineering 2019年第9期20卷 1195-1208页

作者： Ya XIAO Zhi-jie FAN Amiya NAYAK Cheng-xiang TAN College of Electronics and Information Engineering Tongji UniversityShanghai 201804China School of Electrical Engineering and Computer Science University of OttawaOttawa K1N 6N5Canada The Third Research Institute of the Ministry of Public Security Shanghai 200120China

The security threats to software-defined networks(SDNs)have become a significant problem,generally because of the open framework of *** all the threats,distributed denial-of-service(DDoS)attacks can have a devastating impact on the *** propose a method to discover DDoS attack behaviors in SDNs using a feature-pattern graph *** feature-pattern graph model presented employs network patterns as nodes and similarity as weighted links;it can demonstrate not only the traffc header information but also the relationships among all the network *** similarity between nodes is modeled by metric learning and the Mahalanobis *** proposed method can discover DDoS attacks using a graph-based neighborhood classification method;it is capable of automatically finding unknown attacks and is scalable by inserting new nodes to the graph model via local or global *** on two datasets prove the feasibility of the proposed method for attack behavior discovery and graph update tasks,and demonstrate that the graph-based method to discover DDoS attack behaviors substantially outperforms the methods compared herein.

关键词： Software-defined network Distributed denial-of-service(DDoS) Behavior discovery Distance metric learning Feature-pattern graph

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