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Saint-Venant Model Analysis of Trapezoidal Open Channel Water Flow using Finite Difference Method

Procedia computer science 2019年 157卷 6-15页

作者： Gracia Natasha Suharjito Viska Noviantri Mathemathics Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

This study aims to compare the flow characteristics in rectangular and trapezoidal open channel by investigating the effects of Manning coefficient, channel bottom slope, channel width, and channel side slope which represented by modified Saint-Venant equation according to the channel cross section, which are rectangular and trapezoidal, and the slope of channel friction using the Manning coefficient. The equation is solved numerically by using finite difference methods with Forward Time Backward Space approach. The model is simulated by using python-based desktop application to show the flow characteristics. Computational results are displayed in the form of summaries, tables, two-dimensional graphics, and three-dimensional graphics. Validation is done by comparing computational results data with data from the other studies that have been done before and concluded that the simulation results have been valid and indicate compliance with the prior studies. The simulation results show that trapezoidal channel is better at minimizing the risk of flooding than rectangular channel in consideration of smaller discharge, smaller velocity, and lower water level.

关键词： Channel Water Flow Simulation Saint-Venant Equation Finite Difference Method

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The Mid-Infrared Region Absorption of Graphene-based Photodetector with Au-grating Structure

The Mid-Infrared Region Absorption of Graphene-based Photode...

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IEEE International Conference on Nano/Molecular Medicine and Engineering (NANOMED)

作者： Wei-Yu Long Kuan-Chou Lin Yu-Xuan Lu Chih-Ting Lin B.S. degree from the Department of Electrical Engineering from National Taiwan University. He is currently a Ph.D candidate in the Graduate School of Advanced Technology National Taiwan University B.S. degree in civil engineering from National Taiwan University and M.S. degree in Institute of Electronics Engineering National Taiwan University B.S. degree from the Department of Materials Science and Engineering from Central South University China B.S. degree in civil engineering from National Taiwan University the M.S. degree in Institute of Applied Mechanics from National Taiwan University and the Ph.D. degree in electrical engineering and computer science University of Michigan Ann Arbor MI USA

Graphene, a single layer of carbon atoms arranged in a two-dimensional honeycomb lattice, has garnered immense attention for its exceptional electrical conductivity, transparency, and mechanical strength. These properties make graphene an ideal candidate for photodetectors, as it can efficiently convert incident photons into electrical signals. The integration of graphene into surface plasmonic devices has opened up new avenues for photodetection technology. In our research, we combine graphene and surface plasmonic devices to realize a high responsivity mid-infrared graphene photodetector with a grating metal/graphene/SiO 2 structure. The Bruker Vertex70 Fourier-transform infrared spectroscopy (FTIR) was used for the mid-infrared spectrum measurement. With different linewidth of Au grating structure, the peak of absorption redshifts as the grating linewidth increases and the intensity is also different. Further, by adding graphene, the total absorption increases. Due to these advantages, the Au-grating graphene device can be used as infrared photodetectors.

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Non-linear optics at twist interfaces in h-BN/SiC heterostructures

arXiv

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arXiv 2023年

作者： Biswas, Abhijit Xu, Rui Alvarez, Gustavo A. Zhang, Jin Christiansen-Salameh, Joyce Puthirath, Anand B. Burns, Kory Hachtel, Jordan A. Li, Tao Iyengar, Sathvik Ajay Gray, Tia Li, Chenxi Zhang, Xiang Kannan, Harikishan Elkins, Jacob Pieshkov, Tymofii S. Vajtai, Robert Birdwell, A. Glen Neupane, Mahesh R. Garratt, Elias J. Ivanov, Tony Pate, Bradford B. Zhao, Yuji Zhu, Hanyu Tian, Zhiting Rubio, Angel Ajayan, Pulickel M. Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States Max Planck Institute for the Structure and Dynamics of Matter Center for Free-Electron Laser Science Luruper Chaussee 149 22761 Germany Department of Materials Science & Engineering University of Virginia CharlottesvilleVA22904 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States DEVCOM Army Research Laboratory RF Devices and Circuits AdelphiMD20783 United States Chemistry Division Naval Research Laboratory WashingtonDC20375 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Flatiron Institute New YorkNY10010 United States

Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here, we suggest an alternative, simple and scalable approach where nanocrystalline two-dimensional (2D) film on three-dimensional (3D) substrates yield twisted-interface-dependent properties. Ultrawidebandgap hexagonal boron nitride (h-BN) thin films are directly grown on high in-plane lattice mismatched wide-bandgap silicon carbide (4H-SiC) substrates to explore the twist-dependent structure-property correlations. Concurrently, nanocrystalline h-BN thin film shows strong nonlinear second-harmonic generation and ultra-low cross-plane thermal conductivity at room temperature, which are attributed to the twisted domain edges between van der Waals stacked nanocrystals with random in-plane orientations. First-principles calculations based on time-dependent density functional theory manifest strong even-order optical nonlinearity in twisted h-BN layers. Our work unveils that directly deposited 2D nanocrystalline thin film on 3D substrates could provide easily accessible twist-interfaces, therefore enabling a simple and scalable approach to utilize the 2D-twistronics integrated in 3D material devices for next-generation nanotechnology. © 2023, CC BY.

关键词： Harmonic generation

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Optimal parameter configurations for sequential optimization of the variational quantum eigensolver

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Physical Review Research 2023年第4期5卷 043136-043136页

作者： Katsuhiro Endo Yuki Sato Rudy Raymond Kaito Wada Naoki Yamamoto Hiroshi C. Watanabe Research Center for Computational Design of Advanced Functional Materials National Institute of Advanced Industrial Science and Technology (AIST) 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan Quantum Computing Center Keio University Hiyoshi 3-14-1 Kohoku-ku Yokohama 223-8522 Japan Toyota Central R & D Labs. Inc. Koraku Mori Building 10F 1-4-14 Koraku Bunkyo-ku Tokyo 112-0004 Japan IBM Quantum IBM Japan 19-21 Nihonbashi Hakozaki-cho Chuo-ku Tokyo 103-8510 Japan Department of Computer Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku-ku Yokohama 223-8522 Japan Department of Chemistry Graduate School of Science Kyushu University 744 Motooka Nishi-ku Fukuoka 819-0395 Japan

The variational quantum eigensolver (VQE) is a hybrid algorithm to find the minimum eigenvalue/vector of the given Hamiltonian by optimizing a parameterized quantum circuit (PQC) using a classical computer. Sequential optimization methods, which are often used in quantum circuit tensor networks, are popular for optimizing the parameterized gates of PQCs. In this paper, we focus on the case where the components to be optimized are single-qubit gates, in which the analytic optimization of a single-qubit gate is sequentially performed. The analytical solution is given by diagonalization of a matrix whose elements are computed from the expectation values of observables specified by a set of predetermined parameters, which we refer to as the parameter configurations. In this paper, we first show that the optimization accuracy significantly depends on the choice of parameter configurations owing to the statistical errors in the expectation values. We then identify a metric that quantifies the optimization accuracy of a parameter configuration for all possible statistical errors, named configuration overhead/cost or C-cost. We theoretically provide the lower bound of C-cost and show that, for the minimum size of parameter configurations, the lower bound is achieved if and only if the parameter configuration satisfies the so-called equiangular line condition. Finally, we provide numerical experiments demonstrating that the optimal parameter configuration exhibits the best result in several VQE problems. We hope that this general statistical methodology will enhance the efficacy of sequential optimization of PQCs for solving practical problems with near-term quantum devices.

关键词： Quantum algorithms & computation Quantum circuits Quantum computation Quantum information processing Quantum measurements Quantum parameter estimation

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An ALMA Glimpse of Dense Molecular Filaments Associated with High-mass Protostellar Systems in the Large Magellanic Cloud

arXiv

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arXiv 2023年

作者： Tokuda, Kazuki Harada, Naoto Tanaka, Kei E.I. Inoue, Tsuyoshi Shimonishi, Takashi Zhang, Yichen Sewilo, Marta Kunitoshi, Yuri Konishi, Ayu Fukui, Yasuo Kawamura, Akiko Onishi, Toshikazu Machida, Masahiro N. Department of Earth and Planetary Sciences Faculty of Science Kyushu University Fukuoka Nishi-ku819-0395 Japan National Astronomical Observatory of Japan National Institutes of Natural Sciences 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Earth and Planetary Sciences Tokyo Institute of Technology Meguro Tokyo152-8551 Japan Department of Physics Konan University Okamoto 8-9-1 Kobe Japan Environmental Science Program Faculty of Science Niigata University Ikarashi-ninocho 8050 Nishi-ku Niigata950-2181 Japan Department of Astronomy University of Virginia CharlottesvilleVA22904-4325 United States RIKEN Cluster for Pioneering Research Saitama Wako351-0198 Japan Exoplanets and Stellar Astrophysics Laboratory NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Astronomy University of Maryland College ParkMD20742 United States Center for Research and Exploration in Space Science and Technology NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Physics Graduate School of Science Osaka Metropolitan University 1-1 Gakuen-cho Naka-ku Sakai Osaka599-8531 Japan Department of Physics Nagoya University Furo-cho Chikusa-ku Nagoya464-8601 Japan

Recent millimeter/sub-millimeter facilities have revealed the physical properties of filamentary molecular clouds in relation to high-mass star formation. A uniform survey of the nearest, face-on star-forming galaxy, the Large Magellanic Cloud (LMC), complements the Galactic knowledge. We present ALMA survey data with a spatial resolution of ∼0.1 pc in the 0.87 mm continuum and HCO+(4–3) emission toward 30 protostellar objects with luminosities of 104–105.5 L☉ in the LMC. The spatial distributions of the HCO+(4–3) line and thermal dust emission are well correlated, indicating that the line effectively traces dense, filamentary gas with an H2 volume density of 105 cm−3 and a line mass of ∼103–104 M☉ pc−1. Furthermore, we obtain an increase in the velocity linewidths of filamentary clouds, which follows a power-law dependence on their H2 column densities with an exponent of ∼0.5. This trend is consistent with observations toward filamentary clouds in nearby star-forming regions withiin 1 kpc from us and suggests enhanced internal turbulence within the filaments owing to surrounding gas accretion. Among the 30 sources, we find that 14 are associated with hub-filamentary structures, and these complex structures predominantly appear in protostellar luminosities exceeding ∼5 ×104 L☉. The hub-filament systems tend to appear in the latest stages of their natal cloud evolution, often linked to prominent H ii regions and numerous stellar clusters. Our preliminary statistics suggest that the massive filaments accompanied by hub-type complex features may be a necessary intermediate product in forming extremely luminous high-mass stellar systems capable of ultimately dispersing the parent cloud. © 2023, CC BY.

关键词： Clouds

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Competitive Landscape and Industry Prospects of Techniques in the Intersection of computer science and Genomics: An Analysis Based on Patent Data 19

Competitive Landscape and Industry Prospects of Techniques i...

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Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence

作者： Juan He Hongying Zhang Lin Qiao Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen P R China Department of Computer Science and Technology Tsinghua University Beijing P R China

ISBN: (纸本)9781450372619

computer technology represented by artificial intelligence and big data has begun to combine with genetic technology, and has gradually played an increasingly important role in the fields of gene sequencing, disease diagnosis, and drug development. The intersection of computer science and genomics brings new opportunities for technological innovation in the medical field. In this context, this paper analyzes the published patents in the intersection of computer science and genomics, focusing on the comprehensive competitiveness of countries/regions, the R&D capability of major patent applicants, the content of patented technology and the industrial application of these technologies. Based on the above research, this paper points out China's competitive landscape and industry prospects in this field, and then puts forward relevant suggestions.

关键词： Artificial Intelligence

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Titania Nanosheets Generates Peroxynitrite for S-Nitrosylation and Enhanced p53 Function in Lung Cancer Cells

Research Square

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Research Square 2021年

作者： Soonnarong, Rapeepun Tungsukruthai, Sucharat Nutho, Bodee Rungrotmongkol, Thanyada Vinayanuwattikun, Chanida Maluangnont, Tosapol Chanvorachote, Pithi Interdisciplinary Program of Pharmacology Graduate School Chulalongkorn University Bangkok Thailand Cell-based Drug and Health Products Development Research Unit Chulalongkorn University Bangkok Thailand Departments of Pharmacology and Physiology Faculty of Pharmaceutical Sciences Bangkok Thailand Department of Pharmacology Faculty of Science Mahidol University Bangkok Thailand Biocatalyst and Environmental Biotechnology Reseach Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok Thailand Division of Medical Oncology Department of Medicine Chulalongkorn University Bangkok Thailand College of Materials Innovation and Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

Background: Metal oxide nanomaterials are increasingly being exploited in cancer therapy thanks to their unique properties, which can enhance the efficacy of current cancer therapies. However, the nanotoxicity and mechanism of Ti0.8O2 nanosheets for specific site-targeting strategies in NSCLC have not yet been investigated. Methods: The effects of Ti0.8O2 nanosheets on cytotoxicity in NSCLC cells and normal cells were examined. The apoptosis characteristics, including condensed and fragmented nuclei, as assessed by positive staining with annexin V. The cellular uptake of the nanosheets and the induction of stress fiber were assessed via transmission electron microscopy (TEM) and scanning electron microscopy (SEM) analyses, respectively. We also evaluated the expression of protein in death mechanism to identify the molecular mechanisms behind the toxicity of these cells. We investigated the relationship between S-nitrosylation and the increase in p53 stability by molecular dynamics. Results: Ti0.8O2 nanosheets caused cytotoxicity in several lung cancer cells, but not in normal cells. The nanosheets could enter lung cancer cells and exert an apoptosis induction. Results for protein analysis further indicated the activation of p53, increased Bax, decreased Bcl-2 and Mcl-1, and activation of caspase-3. The nanosheets also exhibited a substantial apoptosis effect in drug-resistant metastatic primary lung cancer cells, and it was found that the potency of the nanosheets was dramatically higher than that of cisplatin and etoposide. In terms of their mechanism of action, we found that the mode of apoptosis induction was through the generation of cellular ONOO− mediated the S-nitrosylation of p53 at C182. Molecular dynamics analysis further showed that the S-nitrosylation of one C182 stabilized the p53 dimer. Consequently, this nitrosylation of the protein led to an upregulation of p53 through its stabilization. Conclusions: Taking all the evidence together, we provided info

关键词： Molecular dynamics

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Forecasting Vegetation Health in the MENA Region by Predicting Vegetation Indicators with Machine Learning Models

Forecasting Vegetation Health in the MENA Region by Predicti...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Sachi Perera Wenzhao Li Erik Linstead Hesham El-Askary Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Schmid College of Science and Technology Chapman University Orange CA USA Fowler School of Engineering Chapman University Orange CA USA Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Machine learning (ML) techniques can be applied to predict and monitor drought conditions due to climate change. Predicting future vegetation health indicators (such as EVI, NDVI, and LAI) is one approach to forecast drought events for hotspots (e.g. Middle East and North Africa (MENA) regions). Recently, ML models were implemented to predict EVI values using parameters such as land types, time series, historical vegetation indices, land surface temperature, soil moisture, evapotranspiration etc. In this work, we collected the MODIS atmospherically corrected surface spectral reflectance imagery with multiple vegetation related indices for modeling and evaluation of drought conditions in the MENA region. These models are built by a total of 4556 and 519 normalized samples for training and testing purposes, respectively and with 51820 samples used for model evaluation. Models such as multilinear regression, penalized regression models, support vector regression (SVR), neural network, instance-based learning K-nearest neighbor (KNN) and partial least squares were implemented to predict future values of EVI. The models show effective performance in predicting EVI values (R 2 > 0.95) in the testing and (R 2 > 0.93) in the evaluation process.

关键词： Vegetation mapping MODIS Atmospheric modeling Remote sensing Predictive models Training Support vector machines

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Caco-2 Cell-Derived Biomimetic Electrochemical Biosensor for Cholera Toxin Detection

SSRN

引用

SSRN 2022年

作者： Kim, Yonghwan Lee, Dongtak Seo, Youngjun Jung, Hyo Gi Jang, Jae Won Park, Dongsung Kim, Insu Lee, Gyudo Hwang, Kyo Seon Kim, Seung-Hyun Lee, Sang Won Lee, Jeong Hoon Yoon, Dae Sung School of Biomedical Engineering Korea University Seoul02841 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02841 Korea Republic of Department of Clinical Pharmacology and Therapeutics College of Medicine Kyung Hee University Seoul02447 Korea Republic of Department of Biotechnology and Bioinformatics Korea University Sejong30019 Korea Republic of Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong30019 Korea Republic of School of Engineering Brown University ProvidenceRI02912 United States Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States Department of Electrical Engineering Kwangwoon University Seoul01897 Korea Republic of Astrion Inc Seoul02841 Korea Republic of

Cholera is a highly contagious and lethal waterborne disease induced by an infection with Vibrio cholerae (V. cholerae) secreting cholera toxin (CTx). Cholera toxin subunit B (CTxB) from the CTx specifically binds with monosialo-tetra-hexosyl-ganglioside (GM1) found on the exterior cell membrane of an enterocyte. Owing to the pathological process of CTx, a biomimetic electrochemical biosensor (CCB) was developed by applying GM1-expressing Caco-2 cell membrane (CCM) on the electrode surface of the biosensor for CTx detection. Briefly, the electrode surface was functionalized with CCM using the vesicle fusion method. The specific binding between GM1 and CTxB on the electrode surface was verified using confocal laser scanning microscopy and atomic force microscopy. The CTxB detection performances of the CCB, including sensitivity, selectivity, and long-term stability, were determined using electrochemical impedance spectroscopy (EIS). Based on the results, the CCB had an excellent limit of detection of ~11.46 nM and a detection range spanning 100 ng/mL - 1 mg/mL. Further, the CCB had high selectivity for the CTxB compared to different interfering molecules, which are abundant constituents of intestinal fluid and fecal matter in the human body. The long-term stability of the CCBs was also verified for 3 weeks using EIS. Overall, the CCB was found to have an excellent potential for application to point-of-care and cost-effective testing for CTxB detection in developing countries. © 2022, The Authors. All rights reserved.

关键词： Electrochemical impedance spectroscopy

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Transformer and multi-scale convolution for target-oriented sentiment analysis 3rd

Transformer and multi-scale convolution for target-oriented ...

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3rd APWeb and WAIM Joint Conference on Web and Big Data, APWeb-WAIM 2019

作者： Pan, Yinxu Song, Binheng Luo, Ningqi Chen, Xiaojun Cui, Hengbin Department of Computer Science and Technology Tsinghua University Beijing China Graduate School at ShenZhen Tsinghua University Beijing China Ant Financial Services Group Xihu China

ISBN: (纸本)9783030260743

Target-oriented sentiment analysis aims to extract the sentiment polarity of a specific target in a sentence. In this paper, we propose a model based on transformers and multi-scale convolutions. The transformer which is based solely on attention mechanisms generalizes well in many natural language processing tasks. Convolution layers with multiple filters can efficiently extract n-gram features at many granularities on each receptive field. We conduct extensive experiments on three datasets: SemEval ABSA challenge Restaurant and Laptop dataset, Twitter dataset. Our framework achieves state-of-the-art results, including improving the accuracy of Restaurant dataset to 84.20% (5.81% absolute improvement), improving the accuracy of the Laptop dataset to 78.21% (4.23% absolute improvement), and improving the accuracy of the Twitter dataset to 72.98% (0.87% absolute improvement). © 2019, Springer Nature Switzerland AG.

关键词： Sentiment analysis

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