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2022 International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Tomsovsky, Lubos Lopot, Frantisek Kubovy, Petr Jezdik, Roman Hajkova, Barbora Rulc, Vojtech Jelen, Karel Charles University in Prague Department of Anatomy and Biomechanics Czech Republic Czech Technical University Department of Designing and Machine Components Prague Czech Republic Research Development and Testing of Railway Rolling Stock Prague Czech Republic Research Development and Technology Skoda Transportation A.s. Prague Czech Republic Project Engineering Advanced Engineering S.r.o. Prague Czech Republic

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

The goal of the study was to conduct a series of tram-pedestrian collisions to assess the head injuries as the result of the secondary impact with the surrounding infrastructure (ground). The crash tests were conducted with an anthropomorphic test device for two collision scenarios: the initial frontal and side impact with a tram. Four tram types travelling at four different speeds (5 km/h, 10 km/h, 15 km/h, 20 km/h) were used. The primary outcome variable was the resultant head acceleration. The risk and severity of possible head injuries were assessed using the head injury criterion (HIC15). The results showed increasing head impacts with increasing speed for all tram types and collisions. The higher values of head acceleration were reached during the frontal impact (97-1677 g) compared to the side one (19-607 g). The HIC15 values showed a similar trend, exceeding the value of 1000 consistently during the initial frontal impact compared to the side one. This corresponded to a very high probability of AIS4+ injuries in the case of initial frontal impact. The secondary impact with the surrounding infrastructure was found more dangerous in the case of initial frontal impact, possibly resulting in more severe injuries. However, both collision scenarios showed much higher values compared to the primary impact between a tram and pedestrian. © 2022 IEEE.

关键词： Risk assessment

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Development,validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults:a prospective study of 0.5 million adults

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Stroke & Vascular Neurology 2022年第4期7卷 328-336,I0023-I0045页

作者： Matthew Chun Robert Clarke Tingting Zhu David Clifton Derrick A Bennett Yiping Chen Yu Guo Pei Pei Jun Lv Canqing Yu Ling Yang Liming Li Zhengming Chen Benjamin J Cairns 无 Clinical Trial Service Unit and Epidemiological Studies Nuffield Department of Population HealthUniversity of OxfordOxfordUK Department of Engineering Science University of OxfordOxfordUK Department of Biomedical Engineering Oxford-Suzhou Centre for Advanced ResearchSuzhouChina Medical Research Council Health Research Unit Nuffield Department of Population HealthUniversity of OxfordOxfordUK CKB Project Department Fuwai Hospital Chinese Academy of Medical SciencesNational Center for Cardiovascular DiseasesBeijingChina CKB Project Department Chinese Academy of Medical SciencesBeijingChina Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijingChina Department of Epidemiology Peking University Center for Public Health and Epidemic Preparedness and ResponseBeijingChina On behalf of the China Kadoorie Biobank Collaborative Group

Background and purpose Low-income and middle-income countries have the greatest stroke burden,yet remain *** study compared the utility of Framingham versus novel risk scores for prediction of total stroke and stroke types in Chinese *** China Kadoorie Biobank(CKB)is a prospective study of 512726 adults,aged 30-79 years,recruited from 10 areas in China in *** 1 January 2018,43234 incident first stroke cases(36310 ischaemic stroke(IS);8865 haemorrhagic stroke(HS))were recorded in 503842 participants with no history of stroke at *** compared the predictive utility of the Framingham Stroke Risk Profile(FSRP)with novel CKB stroke risk scores and included recalibration,refitting,stratifying by study area and addition of other risk *** was assessed using area under the receiver operating characteristic curve(AUC)and calibration was assessed using Greenwood-Nam-D’Agostinoχ^(2) *** Incidence of total stroke varied fivefold by area in *** FSRP had good discrimination for total stroke(AUC(95%CI);men:0.78(0.77 to 0.79),women:0.77(95%CI 0.76 to 0.78)),but poor calibration(χ^(2);men:1,825,women:3,053),substantially underestimating absolute *** reducedχ^(2) by>80%,but did not improve *** the FSRP did not materially improve discrimination,but further improved *** by area improved discrimination(AUC;men:0.82(0.82 to 0.83);women:0.82(0.82 to 0.83)),but not *** other risk factors yielded modest,but statistically significant,improvements in the *** findings for IS and HS were similar to those for total *** The FSRP reliably differentiated Chinese adults with incident stroke,but substantially underestimated the absolute risks of *** local risk prediction equations that took account of differences in stroke incidence within China enhanced risk prediction of total stroke and major stroke pathological type

关键词： prediction income absolute

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Weighted Trudinger-Moser inequalities in the subcritical Sobolev spaces and their applications

arXiv

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arXiv 2024年

作者： Ikeda, Masahiro Sano, Megumi Taniguchi, Koichi Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan Center for Advanced Intelligence Project RIKEN Japan Laboratory of Mathematics School of Engineering Hiroshima University Higashi-Hiroshima739-8527 Japan Department of Mathematical and Systems Engineering Faculty of Engineering Shizuoka University 3-5-1 Johoku Chuo-ku Shizuoka Hamamatsu432-8561 Japan

We study boundedness, optimality and attainability of Trudinger-Moser type maximization problems in the radial and the subcritical homogeneous Sobolev spaces W0 , rad1 , p (BRN) (p Copyright © 2024, The Authors. ... 详细信息

关键词： Sobolev spaces

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Estimating counterfactual treatment outcomes over time in complex multiagent scenarios

arXiv

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arXiv 2022年

作者： Fujii, Keisuke Takeuchi, Koh Kuribayashi, Atsushi Takeishi, Naoya Kawahara, Yoshinobu Takeda, Kazuya Graduate School of Informatics Nagoya University Japan RIKEN Center for Advanced Intelligence Project Japan Graduate School of Informatics Kyoto University RIKEN Japan Graduate School of Engineering The University of Tokyo RIKEN Center for Advanced Intelligence Project Japan Graduate School of Information Science and Technology Osaka University RIKEN Center for Advanced Intelligence Project Japan

Evaluation of intervention in a multiagent system, e.g., when humans should intervene in autonomous driving systems and when a player should pass to teammates for a good shot, is challenging in various engineering and scientific fields. Estimating the individual treatment effect (ITE) using counterfactual long-term prediction is practical to evaluate such interventions. However, most of the conventional frameworks did not consider the time-varying complex structure of multiagent relationships and covariate counterfactual prediction. This may lead to erroneous assessments of ITE and difficulty in interpretation. Here we propose an interpretable, counterfactual recurrent network in multiagent systems to estimate the effect of the intervention. Our model leverages graph variational recurrent neural networks and theory-based computation with domain knowledge for the ITE estimation framework based on long-term prediction of multiagent covariates and outcomes, which can confirm the circumstances under which the intervention is effective. On simulated models of an automated vehicle and biological agents with time-varying confounders, we show that our methods achieved lower estimation errors in counterfactual covariates and the most effective treatment timing than the baselines. Furthermore, using real basketball data, our methods performed realistic counterfactual predictions and evaluated the counterfactual passes in shot scenarios. © 2022, CC BY-NC-ND.

关键词： Multi agent systems

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Hybrid Optimization Approach for Energy Savings in Cooling Tower using IoT and Gradient Boosting

Hybrid Optimization Approach for Energy Savings in Cooling T...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： R. Selvakumar Raveendra N Amarnath Pramod Pandey Sakthisaravanan B K. Sasikala S. Murugan Department of Artificial Intelligence and Machine Learning Saveetha Engineering College Chennai Tamil Nadu India Project Lead Mphasis Melissa Texas USA Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune Maharashtra India Department of Computer Science and Engineering Sri Venkateshwara College of Engineering Bengaluru Karnataka India Department of Electrical and Electronics Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai Tamil Nadu India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

Improving operational efficiency and lowering environmental impact are made possible by optimizing energy usage in industrial cooling tower systems. This paper presents a new method for optimizing the management of industrial cooling towers, with a particular emphasis on energy savings, by combining Internet of Things (IoT) technologies with Gradient Boosting approaches. IoT sensors monitor the cooling system’s temperature, flow rate, and humidity in real time. This data makes predictive analytics on system performance and energy usage possible by training Gradient Boosting models. It shows that the proposed approach successfully achieves substantial energy savings while keeping cooling tower performance at its optimum via extensive testing and analysis. The findings show that Gradient Boosting and IoT monitoring might help industrial settings with proactive energy management. By providing a workable framework for improving cooling tower operations' energy efficiency of sustainable industrial practices. The results highlight the significance of using data-driven strategies and advanced technology to solve energy problems in manufacturing, which will enhance efficiency and sustainability while reducing costs. Data analysis from the real world, performance measurements, and comparison findings show that the system is more efficient and system performance of assessment.

关键词： Temperature sensors Cooling System performance Poles and towers Energy conservation Predictive models Boosting Real-time systems Sustainable development Predictive analytics

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Beyond Click to Cognition: Effective Interventions for Promoting Examination of False Beliefs in Misinformation 25

Beyond Click to Cognition: Effective Interventions for Promo...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Tanaka, Yuko Arai, Hiromi Inuzuka, Miwa Takahashi, Yoichi Kukita, Minao Iseki, Ryuta Inui, Kentaro Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan Center for Advanced Intelligence Project RIKEN Tokyo Japan Department of Education Tokyo Gakugei University Tokyo Japan Graduate School of Informatics Nagoya University Nagoya Japan Department of Human Sciences Taisho University Tokyo Japan Natural Language Processing Department MBZUAI Abu Dhabi United Arab Emirates

ISBN: (纸本)9798400713941

In the digital information ecosystem, clicks serve as a crucial gateway to fact-checking, yet the essential challenge extends beyond this to fostering cognitive shifts that update entrenched false beliefs. This study investigates effective interventions aimed at encouraging users vulnerable to misinformation, particularly those who tend to avoid incongruent facts, to examine their false beliefs. We conducted an online experiment with 627 participants, comparing metacognitive and ranking interventions. Both interventions successfully improved click behavior, with the metacognitive intervention increasing belief-examining clicks by 14 percentage points and the ranking intervention by 33 percentage points. However, only the metacognitive intervention significantly promoted users examination of misinformation. This finding underscores the importance of interventions that go beyond merely influencing easily measurable clicks to facilitating thoughtful engagement with factchecking content. We discuss implications for designing strategies to enhance online fact-checking engagement and mitigate misinformation's societal impact. © 2025 Copyright held by the owner/author(s).

关键词： Misinformation

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One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement

arXiv

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arXiv 2022年

作者： Xu, Ning Qiao, Congyu Lv, Jiaqi Geng, Xin Zhang, Min-Ling School of Computer Science and Engineering Southeast University Nanjing210096 China RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan

Multi-label learning (MLL) learns from the examples each associated with multiple labels simultaneously, where the high cost of annotating all relevant labels for each training example is challenging for real-world applications. To cope with the challenge, we investigate single-positive multi-label learning (SPMLL) where each example is annotated with only one relevant label and show that one can successfully learn a theoretically grounded multi-label classifier on SPMLL training examples. In this paper, a novel SPMLL method named SMILE, i.e., Single-positive MultI-label learning with Label Enhancement, is proposed. Specifically, an unbiased risk estimator is derived, which could be guaranteed to approximately converge to the optimal risk minimizer in fully supervised learning and shows that one positive label of each instance is sufficient to train a model. Then, the corresponding empirical risk estimator is established via recovering the latent soft label as a label enhancement process, where the posterior density of the latent soft labels is approximate to the variational Beta density parameterized by an inference model. Experiments on twelve corrupted MLL datasets show the effectiveness of SMILE over several existing SPMLL approaches. Source code is available at https://***/palm-ml/smile. Copyright © 2022, The Authors. All rights reserved.

关键词： Learning systems

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Dynamic Structure Estimation from Bandit Feedback using Nonvanishing Exponential Sums

arXiv

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arXiv 2022年

作者： Ohnishi, Motoya Ishikawa, Isao Kuroki, Yuko Ikeda, Masahiro Paul G. Allen School of Computer Science & Engineering University of Washington United States Ehime University RIKEN Center for Advanced Intelligence Project Japan CENTAI Institute Italy RIKEN Center for Advanced Intelligence Project Keio University Japan

This work tackles the dynamic structure estimation problems for periodically behaved discrete dynamical system in the Euclidean space. We assume the observations become sequentially available in a form of bandit feedback contaminated by a sub-Gaussian noise. Under such fairly general assumptions on the noise distribution, we carefully identify a set of recoverable information of periodic structures. Our main results are the (computation and sample) efficient algorithms that exploit asymptotic behaviors of exponential sums to effectively average out the noise effect while preventing the information to be estimated from vanishing. In particular, the novel use of the Weyl sum, a variant of exponential sums, allows us to extract spectrum information for linear systems. We provide sample complexity bounds for our algorithms, and we experimentally validate our theoretical claims on simulations of toy examples, including Cellular Automata. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear systems

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Crystal field magnetostriction of spin ice under ultrahigh magnetic fields

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Physical Review B 2024年第21期110卷 214414-214414页

作者： Nan Tang Masaki Gen Martin Rotter Huiyuan Man Kazuyuki Matsuhira Akira Matsuo Koichi Kindo Akihiko Ikeda Yasuhiro H. Matsuda Experimental Physics VI Center for Electronic Correlations and Magnetism University of Augsburg 86159 Augsburg Germany Institute for Solid State Physics University of Tokyo Kashiwa Chiba 277-8581 Japan McPhase Project 01159 Dresden Germany Geballe Laboratory for Advanced Materials Stanford University California 94305 USA Faculty of Engineering Kyushu Institute of Technology Kitakyushu Fukuoka 804-8550 Japan Department of Engineering Science University of Electro-Communications Chofu Tokyo 182-8585 Japan

We present a comprehensive study of the magnetoelastic properties of the Ising pyrochlore oxide Ho2Ti2O7, known as spin ice, by means of high-field magnetostriction measurements and numerical calculations. When a magnetic field is applied along the crystallographic 〈111〉 axis, the longitudinal magnetostriction exhibits a broad maximum in the low-field regime around 30 T, followed by a dramatic lattice contraction due to crystal-field (CF) level crossing at Bcf∼65 T. The transverse magnetostriction exhibits a contrasting behavior, highlighting the anisotropic nature of the CF striction. By applying a magnetic field at varying sweep rates, we identify distinct timescales of spin dynamics that are relevant to monopole formation and annihilation, as well as CF-phonon dynamics. Our mean-field calculations, based on a point-charge model, successfully reproduce the overall magnetostriction behavior, revealing the competition between the exchange striction and CF striction. A signature of the CF level crossing is also observed through adiabatic magnetocaloric-effect measurements, consistent with our magnetostriction data.

关键词： Crystal field excitations Elasticity High magnetic fields Lattice dynamics Magnetostriction Spin dynamics Spin-phonon coupling Rare-earth magnetic materials Single crystal materials Spin ice Mean field theory

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Adult dental epithelial stem cell-derived organoids deposit hydroxylapatite biomineral

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International Journal of Oral Science 2023年第4期15卷 676-690页

作者： Hyun-Yi Kim Victoria Cooley Eun-Jung Kim Shujin Li Jong-Min Lee Dina Sheyfer Wenjun Liu Ophir D.Klein Derk Joester Han-Sung Jung NGeneS Inc. Ansan-siGyeonggi-doKorea Department of Materials Science and Engineering Northwestern UniversityEvanstonILUSA X-ray Science Division Advanced Photon SourceArgonne National LaboratoryLemontILUSA Division in Anatomy and Developmental Biology Department of Oral BiologyOral Science Research CenterBK21 FOUR ProjectYonsei University College of DentistrySeoulKorea Department of Orofacial Sciences and Program in Craniofacial Biology University of CaliforniaSan FranciscoCAUSA Department of Pediatrics Cedars-Sinai Guerin Children’sLos AngelesCAUSA

Ameloblasts are specialized cells derived from the dental epithelium that produce enamel,a hierarchically structured tissue comprised of highly elongated hydroxylapatite(OHAp)*** unique function of the epithelial cells synthesizing crystallites and assembling them in a mechanically robust structure is not fully elucidated yet,partly due to limitations with in vitro experimental ***,we demonstrate the ability to generate mineralizing dental epithelial organoids(DEOs)from adult dental epithelial stem cells(aDESCs)isolated from mouse incisor *** expressed ameloblast markers,could be maintained for more than five months(11 passages)in vitro in media containing modulators of Wnt,Egf,Bmp,Fgf and Notch signaling pathways,and were amenable to *** transplanted underneath murine kidney capsules,organoids produced OHAp crystallites similar in composition,size,and shape to mineralized dental tissues,including some enamel-like elongated *** are thus a powerful in vitro model to study mineralization process by dental epithelium,which can pave the way to understanding amelogenesis and developing regenerative therapy of enamel.

关键词： epithelium maintained specialized

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