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37th International Cosmic Ray Conference, ICRC 2021

作者： Mazin, D. Abe, H. Aguasca, A. Agudo, I. Antonelli, L.A. Aramo, C. Armstrong, T. Artero, M. Asano, K. Ashkar, H. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Becerra González, J. Bernardos, M.I. Berti, A. Biederbeck, N. Bigongiari, C. Blanch, O. Bonnoli, G. Bordas, P. Bose, D. Bulgarelli, A. Burelli, I. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Cassol, F. Cerruti, M. Chai, Y. Cheng, K. Chikawa, M. Chytka, L. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. De Angelis, A. de Bony de Lavergne, M. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Depaoli, D. Di Pierro, F. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsässer, D. Emery, G. Escudero, J. Fiasson, A. Foffano, L. Fonseca, M.V. Freixas Coromina, L. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Green, D. Grespan, P. Gunji, S. Hackfeld, J. Hadasch, D. Hahn, A. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Inada, T. Inome, Y. Iori, M. Ishio, K. Iwamura, Y. Jacquemont, M. Jimenez Martinez, I. Jouvin, L. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kong, A. Kubo, H. Kushida, J. Lamanna, G. Lamastra, A. Le Flour, T. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Luque-Escamilla, P.L. Majumdar, P. Makariev, M. Mandat, D. Manganaro, M. Mannheim, K. Mariotti, M. Marquez, P. Marsella, G. Martí, J. Martinez, O. Martínez, G. Martínez, M. Marusevec, P. Mas, A. Maurin, G. Mestre Guillen, E. Micanovic, S. Miceli, D. Miener, T. Miranda, J.M. Miranda, L.D.M. Mirzoyan, R. Mizuno, T. Molina, E. Montaruli, T. Monteiro, I. Moralejo, A. Morcuende, D. Moretti, E. Morselli, A. Mrakovcic, K. Murase, K. Nagai, A. Nakamori, T. Nickel, L. Nieto, D. Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Max-Planck-Institut für Physik München80805 Germany Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain Instituto de Astrofísica de Andalucía-CSIC Spain INAF - Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy Aix Marseille Univ CNRS IN2P3 CPPM France The Barcelona Institute of Science and Technology Spain IRFU CEA Université Paris-Saclay France LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan EMFTEL department IPARCOS Universidad Complutense de Madrid Spain INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil INFN Sezione di Padova Università degli Studi di Padova Italy Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain Department of Physics TU Dortmund University Germany Saha Institute of Nuclear Physics India INFN Sezione di Trieste Università degli Studi di Udine Italy INFN Sezione di Catania Italy Italy University of Geneva Département de Physique Nucléaire et Corpusculaire Switzerland Palacky University Olomouc Faculty of Science Czech Republic CIEMAT Port d'Informació Científica INFN Sezione di Torino Italy Dipartimento di Fisica Universitá degli Studi di Torino Italy INFN Sezione di Bari Università di Bari Italy University of Rijeka Department of Physics Croatia Institute for Theoretical Physics and Astrophysics Universität Würzburg Germany Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Japan INFN Sezione di Bari Politecnico di Bari Italy Faculty of Physics and Applied Informatics University of Lodz Poland University of Split FESB Croatia Department of Physics

The Large-Sized Telescopes (LSTs) of Cherenkov Telescope Array (CTA) are designed for gamma-ray studies focusing on low energy threshold, high flux sensitivity, rapid telescope repositioning speed and a large field of view. Once the CTA array is complete, the LSTs will be dominating the CTA performance between 20 GeV and 150 GeV. During most of the CTA Observatory construction phase, however, the LSTs will be dominating the array performance until several TeVs. In this presentation we will report on the status of the LST-1 telescope inaugurated in La Palma, Canary islands, Spain in 2018. We will show the progress of the telescope commissioning, compare the expectations with the achieved performance, and give a glance of the first physics results. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Telescopes

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Perspectives on nano-nutraceuticals to manage pre and post COVID-19 infections

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Biotechnology Reports 2022年 33卷 e00712页

作者： Dubey, Ankit Kumar Chaudhry, Suman Kumar Singh, Harikesh Bahadur Gupta, Vijai Kumar Kaushik, Ajeet Department of Biotechnology Bhupat and Jyoti Mehta School of Biosciences Indian Institute of Technology Madras Tamil Nadu 600036 India Institute of Scholars (InSc) Karnataka Bengaluru 560091 India Department of Computer Science and Engineering Tezpur University Sonitpur Assam 784028 India Department of Biotechnology GLA University Mathura Uttar Pradesh 281406 India Biorefining and Advanced Materials Research Center SRUC Kings Buildings West Mains Road Edinburgh EH9 3JG United Kingdom Center for Safe and Improved Food SRUC Kings Buildings West Mains Road Edinburgh EH9 3JG United Kingdom NanoBioTech Laboratory Health System Engineering Department of Natural Sciences Florida Polytechnic University Lakeland FL 33805 United States

Optimized therapeutic bio-compounds supported by bio-acceptable nanosystems (i.e., precise nanomedicine) have ability to promote health via maintaining body structure, organ function, and controlling chronic and acute effects. Therefore, nano-nutraceuticals (designed to neutralize virus, inhibit virus bindings with receptors, and support immunity) utilization can manage COVID-19 pre/post-infection effects. To explore these approaches well, our mini-review explores optimized bio-active compounds, their ability to influence SARS-CoV-2 infection, improvement in performance supported by precise nanomedicine approach, and challenges along with prospects. Such optimized pharmacologically relevant therapeutic cargo not only affect SARS-CoV-2 but will support other organs which show functional alternation due to SARS-CoV-2 for example, neurological functions. Hence, coupling the nutraceuticals with the nano-pharmacology perspective of higher efficacy via targeted delivery action can pave a novel way for health experts to plan future research needed to manage post COVID-19 infection effect where a longer efficacy with no side-effects is a key requirement. © 2022

关键词： COVID-19 infection Immunity Nanoparticles Nutraceuticals Phytochemicals SARS-CoV-2 Therapeutics

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Clinical text mining of the performance status and progression-free survival to facilitate data collection in cancer research: an exploratory study

ESMO Real World Data and Digital Oncology

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ESMO Real World Data and Digital Oncology 2024年 5卷 100059-100059页

作者： L. Lin M. Singer-van den Hout L.F.A. Wessels A.J. de Langen J.H. Beijnen A.D.R. Huitema Department of Pharmacy & Pharmacology Department of Biometrics The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital Amsterdam Division of Molecular Carcinogenesis The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital Amsterdam Oncode Institute Utrecht Department of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Department of Thoracic Oncology The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital Amsterdam Department of Pharmaceutical Sciences Utrecht University Utrecht Department of Pharmacology Princess Máxima Center for Pediatric Oncology Utrecht Department of Clinical Pharmacy University Medical Center Utrecht Utrecht University Utrecht The Netherlands

Background Modern electronic medical records (EMRs) contain a valuable amount of data. These data can be unlocked for research by manual data collection, which is highly labor intensive. Therefore, we explored whether automated text mining (TM) could be used to extract the performance status (PS) and progression-free survival (PFS) in a cohort of 328 non-small-cell lung cancer patients. Materials and methods Unstructured Dutch text data were derived from different EMR fields containing mainly information recorded during outpatient visits. A rule-based TM approach using regular expressions was used to extract PS and PFS in the R programming language. For PS, quantitative evaluation metrics, such as the weighted F1-score, were used to determine the accuracy of the TM-extracted data. For PFS, the median PFS was compared between the two approaches using the Kaplan–Meier method. In addition, the C-index was determined. Results A PS was obtained for 196 patients (60%) using the TM approach. In 189 (96%) patients, the TM-curated PS matched the manually curated PS. The weighted F1-score was 96.5%. The median PFS was 7.42 months for the manually curated data ( n = 328) and 8.00 months for the TM-curated data ( n = 301). The C-index was 0.916. Conclusions The developed TM approach is able to extract PS and PFS from the EMR with a very good performance. Therefore, this approach increases the efficiency of reliable data collection from EMRs, facilitating the use of real-world data (RWD) in clinical research.

关键词： text mining natural language processing real-world data progression-free survival performance status

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Syntax-enhanced Pre-trained model

arXiv

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arXiv 2020年

作者： Xu, Zenan Guo, Daya Tang, Duyu Su, Qinliang Shou, Linjun Gong, Ming Zhong, Wanjun Quan, Xiaojun Jiang, Daxin Duan, Nan School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Microsoft Research Asia Beijing China Microsoft Search Technology Center Asia Beijing China Guangdong Key Laboratory Big Data Analysis and Processing Guangzhou China Key Lab. of Machine Intelligence and Advanced Computing Ministry of Education China

We study the problem of leveraging the syntactic structure of text to enhance pre-trained models such as BERT and RoBERTa. Existing methods utilize syntax of text either in the pre-training stage or in the fine-tuning stage, so that they suffer from discrepancy between the two stages. Such a problem would lead to the necessity of having human-annotated syntactic information, which limits the application of existing methods to broader scenarios. To address this, we present a model that utilizes the syntax of text in both pre-training and fine-tuning stages. Our model is based on Transformer with a syntax-aware attention layer that considers the dependency tree of the text. We further introduce a new pre-training task of predicting the syntactic distance among tokens in the dependency tree. We evaluate the model on three downstream tasks, including relation classification, entity typing, and question answering. Results show that our model achieves state-of-the-art performance on six public benchmark datasets. We have two major findings. First, we demonstrate that infusing automatically produced syntax of text improves pre-trained models. Second, global syntactic distances among tokens bring larger performance gains compared to local head relations between contiguous tokens. Copyright © 2020, The Authors. All rights reserved.

关键词： Syntactics

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Viscous flow properties and hydrodynamic diameter of phenothiazine-based redox-active molecules in different supporting salt environments

arXiv

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arXiv 2020年

作者： Wang, Yilin Kaur, Aman Preet Harsha Attanayake, N. Yu, Zhou Suduwella, Thilini M. Cheng, Lei Odom, Susan A. Ewoldt, Randy H. Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61820 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61820 United States Joint Center for Energy Storage Research UrbanaIL61820 United States Joint Center for Energy Storage Research LexingtonKY40506 United States Department of Chemistry University of Kentucky LexingtonKY40506 United States Materials Science Division Joint Center for Energy Storage Research Argonne National Laboratory LemontIL60439 United States Materials Research Laboratory University of Illinois at Urbana-Champaign UrbanaIL61820 United States

We report viscous flow properties of a redox-active organic molecule, N-(2-(2methoxyethoxy)ethyl)phenothiazine (MEEPT), a candidate for non-aqueous redox flow batteries, and two of its radical cation salts. A microfluidic viscometer enabled the use of small sample volumes in determining viscosity as a function of shear rate and concentration in the non-aqueous solvent, acetonitrile, both with and without supporting salts. All solutions tested show Newtonian behavior over shear rates of up to 30,000 s-1, which is rationalized by scaling arguments for the diffusion-based relaxation time of a single MEEPT molecule without aggregation. Neat MEEPT is flowable but with a large viscosity (412 mPas at room temperature), which is approximately 1,000 times larger than acetonitrile. When dissolved in acetonitrile, MEEPT solutions have low viscosities;at concentrations up to 0.5 M, the viscosity increases by less than a factor of two. From concentration-dependent viscosity measurements, molecular information is inferred from intrinsic viscosity (hydrodynamic diameter) and the Huggins coefficient (interactions). Model fit credibility is assessed using the Bayesian Information Criterion (BIC). It is found that the MEEPT and its charged cation are "flowable" and do not flocculate at concentrations up to 0.5 M. MEEPT has a hydrodynamic diameter of around 8.5 Å, which is largely insensitive to supporting salt and state of charge. This size is comparable to molecular dimensions of single molecules obtained from optimized structures using density function theory calculations. The results suggest that MEEPT is a promising candidate for redox flow batteries in terms of its viscous flow properties. Copyright © 2020, The Authors. All rights reserved.

关键词： Viscosity

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Graph classification with the hypernetwork, a molecule interaction based evolutionary architecture

Graph classification with the hypernetwork, a molecule inter...

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IEEE International Conference on Big Data

作者： Jose Segovia-Juarez Silvano Colombano Alex Flores-Mamani Daniel Hidalgo-Chavez Miguel Mejia-Puma Computer Science Department National University of Engineering Lima Peru Intelligent Systems Division NASA Ames Research Center Moffett Field CA USA

ISBN: (数字)9781728108582

ISBN: (纸本)9781728108599

A novel architecture for information processing, called the hypernetwork architecture is described here. This model is based on the hierarchical organization and principles of biological information processing. The hypernetwork model has a representation of the molecular, cellular, and organismic levels of biological organization. Molecules are enzyme-like structures, and interactions are typical activation and inhibition processes. The representation of molecules and their interactions is comprised of binary strings and string matching respectively. Molecules are placed in cells, modeled by cellular automata. An organized group of cells forms an organism. Cell to cell interactions are produced by the effector-receptor molecules of the cells. The hypernetwork receives environmental influences at its input cells, creates cascades of molecular interactions inside the cells, passing through internal cells, and delivers an output from its output cells. Hypernetwork organisms learn classification tasks, including graph classification, by an adaptive algorithm based on molecular evolution. An organism is reproduced with random molecular mutation and the selection chooses the organism with the best structure for the problem to be solved. With its molecule based variation-selection learning algorithm, the hypernetwork is able to learn fairly complex classification tasks. Besides learning, the hypernetwork exhibits mutation buffering capabilities, intracellular feedback regulation, and can be used as a tool for understanding how hierarchies work, for studying evolutionary strategies, and as a model for building molecular computers.

关键词： Organisms computer architecture Receptor (biochemistry) Computational modeling Biological system modeling computer science Information processing

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An Artificial Electrode/Electrolyte Interface for CO2 Electroreduction by Cation Surfactant Self-Assembly

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Angewandte Chemie 2020年第43期132卷

作者： Zhong Y. Xu Y. Ma J. Wang C. Sheng S. Cheng C. Li M. Han L. Zhou L. Cai Z. Kuang Y. Liang Z. Sun X. State Key Laboratory of Chemical Resource Engineering Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing University of Chemical Technology Beijing 100029 China Electrical Engineering and Automation Shandong University of Science and Technology Tsingtao 266590 China Institute of Water Environmental Research Chinese Research Academy of Environmental Sciences Beijing 100012 China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 China Materials Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 United States

In this work, an artificial electrode/electrolyte (E/E) interface, made by coating the electrode surface with a quaternary ammonium cation (R4N+) surfactant, was successfully developed, leading to a change in the CO2 reduction reaction (CO2RR) pathway. This artificial E/E interface, with high CO2 permeability, promotes CO2 transportation and hydrogenation, as well as suppresses the hydrogen evolution reaction (HER). Linear and branched surfactants facilitated formic acid and CO production, respectively. Molecular dynamics simulations show that the artificial interface provided a facile CO2 diffusion pathway. Moreover, density-functional theory (DFT) calculations revealed the stabilization of the key intermediate, OCHO*, through interactions with R4N+. This strategy might also be applicable to other electrocatalytic reactions where gas consumption is involved. © 2020 Wiley-VCH GmbH

关键词： carbon dioxide cations electrodes reduction surfactants

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Synthesis of hydrochar from empty fruit bunches (EFB) and oil palm trunks (OPT) Via wet torrefaction: A parametric study

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AIP Conference Proceedings 2024年第1期3073卷

作者： Frederick Jit Fook Phang Megan Soh Jiuan Jing Chew Aqsha Aqsha Deni Shidqi Khaerudini Gerald Ensang Timuda Bing Shen How Soh Kheang Loh Suzana Yusup Jaka Sunarso Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga 93350 Kuching Sarawak Malaysia Department of Bioenergy and Chemurgy Faculty of Industrial Technology Institut Teknologi Bandung Bandung 40132 Jawa Barat Indonesia Research Center for Advanced Materials National Research and Innovation Agency (BRIN) Bld. 440 Kawasan Puspiptek Serpong South Tangerang 15314 Banten Indonesia Energy and Environmental Unit Engineering and Processing Division Malaysian Palm Oil Board 6 Persiaran Institusi Bandar Baru Bangi 43000 Kajang Selangor Malaysia Generation Unit (Fuel and Combustion Section) TNB Research Sdn. Bhd. No. 1 Kawasan Institusi Penyelidikan Jalan Ayer Hitam 43000 Kajang Selangor Malaysia

With the rising popularity of the oil palm industry driven by global demand, an abundance of oil palm biomass waste is expected. Wet torrefaction is an appealing method for converting oil palm biomass waste into fuel. Empty fruit bunches (EFB) with a particle size range of 0.5 to 1.0 mm were treated via wet torrefaction at 180 to 220 °C with 20 °C intervals and 3 to 9 hours with 3 hours intervals. The wet torrefied EFB, termed EFB hydrochar, was evaluated for its mass yield and higher heating value (HHV). The energy yield of the hydrochar was assessed as well, as it represents the fuel potential of the hydrochar. Ensuring that the mass yield is relatively high whilst HHV is favourable is desirable. The HHV of hydrochar increased with increasing temperature and residence times whilst mass yield followed an opposite trend. For instance, hydrochar obtained at 220 °C and 9 hours had the highest HHV and the lowest mass yield, at 23.74 MJ kg−1 and 42.86 wt. %, respectively. Despite its highest HHV, its energy yield was relatively low, at only 60 %. On the contrary, hydrochar obtained at 180 °C and 3 hours had the lowest HHV (17.37 MJ kg−1) among all treated EFB; however, it had the highest energy yield, at 76 %. The higher value of energy yield was due to its relatively higher mass yield when compared to the hydrochar with the highest HHV (i.e. 73.78 wt. % to 42.86 wt. %, respectively). Similar trends were observed for OPT hydrochar subjected to the same wet torrefaction condition. Nevertheless, EFB hydrochar generally had a higher mass yield and HHV, offering a higher energy yield than OPT hydrochar. This disparity is likely attributed to the higher lignin content in EFB compared to OPT.

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Improved U-Net for guidewire tip segmentation in X-ray fluoroscopy images 3

Improved U-Net for guidewire tip segmentation in X-ray fluor...

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3rd International Conference on Advances in Image Processing, ICAIP 2019

作者： Guo, Shuai Tang, Songyuan Zhu, Jianjun Fan, Jingfan Ai, Danni Song, Hong Liang, Ping Yang, Jian Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Electronics Beijing Institute of Technology Beijing100081 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Department of Interventional Ultrasound Chinese PLA General Hospital 28 Fuxing Road Beijing100853 China

ISBN: (纸本)9781450376754

In percutaneous coronary intervention (PCI), physicians use a guidewire tip to implant stents in vessels with stenosis. Given the small scale and low signal-to-noise ratio of guidewire tips in X-ray fluoroscopy images, physicians experience difficulty in recognizing and locating the tip. The automatic segmentation of the guidewire tip can ease navigation when the physicians implant stents for PCI. In this paper, we propose an end-to-end convolutional neural network-based method for guidewire tip segmentation. The network framework is derived from U-Net, and two specific designs involving reduced dense block and connectivity supervision are embedded in the framework to improve the accuracy and robustness of guidewire tip segmentation. Experiments are performed on clinical data. The proposed method achieves mean sensitivity, F1-score, Jaccard index, Hausdorff distance of 92.95%, 91.35%, 84.14%, and 0.531 mm on testing data, respectively. In addition, the segmentation time is 0.02 s/frame, which can satisfy the requirements for clinical intra-practice. © 2019 Association for Computing Machinery.

关键词： Stents

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Detecting out-of-distribution samples via variational auto-encoder with reliable uncertainty estimation

arXiv

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arXiv 2020年

作者： Ran, Xuming Xu, Mingkun Mei, Lingrui Xu, Qi Liu, Quanying Shenzhen Key Laboratory of Smart Healthcare Engineering Department of Biomedical Engineering Southern University of Science and Technology Shenzhen518055 China Center for Brain Inspired Computing Research Department of Precision Instrument Tsinghua University Beijing100084 China China Automotive Engineering Research Institute Chongqing401122 China School of Artifical Intelligence Electronic and Electrical Engineering School of Artifical Intelligence Dalian University of Technology Dalian116024 China College of Mathematics and Statistics Chongqing Jiaotong University Chongqing400074 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China

Variational autoencoders (VAEs) are influential generative models with rich representation capabilities from the deep neural network architecture and Bayesian method. However, VAE models have a weakness that assign a higher likelihood to out-of-distribution (OOD) inputs than in-distribution (ID) inputs. To address this problem, a reliable uncertainty estimation is considered to be critical for in-depth understanding of OOD inputs. In this study, we propose an improved noise contrastive prior (INCP) to be able to integrate into the encoder of VAEs, called INCPVAE. INCP is scalable, trainable and compatible with VAEs, and it also adopts the merits from the INCP for uncertainty estimation. Experiments on various datasets demonstrate that compared to the standard VAEs, our model is superior in uncertainty estimation for the OOD data and is robust in anomaly detection tasks. The INCPVAE model obtains reliable uncertainty estimation for OOD inputs and solves the OOD problem in VAE models. © 2020, CC BY.

关键词： Bayesian networks

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