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arXiv 2022年

作者： Tian, Chunwei Yuan, Yixuan Zhang, Shichao Lin, Chia-Wen Zuo, Wangmeng Zhang, David School of Software Northwestern Polytechnical University Shaanxi Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Xi’an710129 China Department of Electrical Engineering City University of Hong Kong Hong Kong School of Computer Science and Engineering Central South University Hunan Changsha410083 China Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu Taiwan School of Computer Science and Technology Harbin Institute of Technology Heilongjiang Harbin150001 China Peng Cheng Laboratory Guangdong Shenzhen518055 China Guangdong Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image super-resolution, which may increase computational cost in general. In this paper, we present an enhanced super-resolution group CNN (ESRGCNN) with a shallow architecture by fully fusing deep and wide channel features to extract more accurate low-frequency information in terms of correlations of different channels in single image super-resolution (SISR). Also, a signal enhancement operation in the ESRGCNN is useful to inherit more long-distance contextual information for resolving long-term dependency. An adaptive up-sampling operation is gathered into a CNN to obtain an image super-resolution model with low-resolution images of different sizes. Extensive experiments report that our ESRGCNN surpasses the state-of-the-arts in terms of SISR performance, complexity, execution speed, image quality evaluation and visual effect in SISR. Code is found at https://***/hellloxiaotian/ESRGCNN. Copyright © 2022, The Authors. All rights reserved.

关键词： Convolution

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Marine collagen-driven synthesis of one-dimensional silver nanoparticles

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Materials Letters 2025年 397卷

作者： Nor Farida Retno Purbowati Nur Karimah Ade Irma Rozafia Wahyu Prasetyo Utomo Imam Susilo Hoi Ying Chung Afifah Rosyidah Adi Soeprijanto Djoko Hartanto Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember (ITS) Sukolilo Surabaya 60111 East Java Indonesia Department of Pharmacy Faculty of Pharmacy Universitas Airlangga Mulyorejo Surabaya 60115 East Java Indonesia Faculty of Medicine Universitas Airlangga Surabaya 60132 East Java Indonesia School of Energy and Environment City University of Hong Kong Kowloon 999077 Hong Kong China Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Sukolilo Surabaya 60111 East Java Indonesia

This study reported the development of one-dimensional silver nanoparticles (AgNPs) using marine collagen derived from shark fins as a reducing and stabilizing agent. The optimization of reaction parameters is performed to lead to the formation of 1D rod-shaped AgNPs, which includes concentration of AgNO 3 solution, reaction temperature, and pH. Based on the UV–vis measurements, XRD, and FESEM-EDX analysis, the 1D rod-shaped AgNPs are obtained in the concentration of 7.5 mM AgNO 3 , at a temperature of 70 °C, and a pH of 11. PSA analysis shows an average hydrodynamic diameter of 132.3 nm with good particle stability. The facile synthesis and the dual function of collagen as a reducing and stabilizing agent enhance the efficiency in producing one-dimensional silver nanoparticles.

关键词： Green Synthesis

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Research and Implementation of Anti-occlusion Algorithm for Vehicle Detection in Video data 16th

Research and Implementation of Anti-occlusion Algorithm for ...

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16th Web Information Systems and Applications Conference, WISA 2019

作者： Wu, Yongqi Zhou, Zhichao Yao, Lan Yu, Minghe Yan, Yongming College of Computer Science and Engineering Northeastern University Shenyang110819 China College of Software Northeastern University Shenyang110819 China Department of Video Big Data DIXN Technology Co. Ltd. Shenyang110004 China

ISBN: (纸本)9783030309510

Object detection is an important branch of image processing and computer vision, which has become a hot research issue in recent years. Accurate target detection in a video is the foundation of intelligent surveillance system. Since the background scenario is dynamic and even especially complicated when vehicles occlude, the target detection accuracy is declined. Therefore, based on the bounding box regression algorithm, this paper constructs adjacent punishment mechanism to make the bounding box clear off other objects. The proposal weak confidence suppression is leveraged for the robustness of the detector when occlusion happens. Experiments show that the proposed method outperforms traditional methods on three different datasets. © 2019, Springer Nature Switzerland AG.

关键词： Object detection

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Lessons learned from the 1st ariel machine learning challenge: correcting transiting exoplanet light curves for stellar spots

arXiv

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arXiv 2020年

作者： Nikolaou, Nikolaos Waldmann, Ingo P. Tsiaras, Angelos Morvan, Mario Edwards, Billy Yip, Kai Hou Tinetti, Giovanna Sarkar, Subhajit Dawson, James M. Borisov, Vadim Kasneci, Gjergji Petković, Matej Stepišnik, Tomaž Al-Ubaidi, Tarek Bailey, Rachel Louise Granitzer, Michael Julka, Sahib Kern, Roman Ofner, Patrick Wagner, Stefan Heppe, Lukas Bunse, Mirko Morik, Katharina Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom School of Physics and Astronomy Cardiff University The Parade CardiffCF24 3AA United Kingdom Department of Computer Science University of Tuebingen Tuebingen Germany Jožef Stefan Institute Ljubljana Slovenia DCCS Austria Space Research Institute Austrian Academy of Sciences Austria Chair of Data Science University of Passau Germany Know-Center GmbH Research Center for Data-Driven Business & Big Data Analytics Austria Commission for Astronomy Austrian Academy of Sciences Graz Austria Artificial Intelligence Group TU Dortmund University Germany

The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed using machine learning methodology. For instance, the most prolific method for detecting exoplanets and inferring several of their characteristics, transit photometry, is very sensitive to the presence of stellar spots. The current practice in the literature is to identify the effects of spots visually and correct for them manually or discard the affected data. This paper explores a first step towards fully automating the efficient and precise derivation of transit depths from transit light curves in the presence of stellar spots. The methods and results we present were obtained in the context of the 1st Machine Learning Challenge organized for the European Space Agency’s upcoming Ariel mission. We first present the problem, the simulated Ariel-like data and outline the Challenge while identifying best practices for organizing similar challenges in the future. Finally, we present the solutions obtained by the top-5 winning teams, provide their code and discuss their implications. Successful solutions either construct highly nonlinear (w.r.t. the raw data) models with minimal preprocessing –deep neural networks and ensemble methods– or amount to obtaining meaningful statistics from the light curves, constructing linear models on which yields comparably good predictive performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Extrasolar planets

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Investigating Prime Minister Narendra Modi’s Usage of Pathos in the Cyber-Physical Society – A Case of Public Relations Campaign

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Procedia Computer science 2019年 162卷 400-404页

作者： Shalini Upadhyay Nitin Upadhyay Department of Humanities and Social Sciences BITS Pilani K K Birla Goa Campus Goa India Nitin Upadhyay Big Data and Analytics Goa Institute of Management Goa India

The paper investigates the usage of pathos by Prime Minister Narendra in the Cyber-Physical Society. A unique public relations campaign was initiated by the prime minister Modi which was aired on All India Radio from October 2014 till March 2019. Typically, initial 100 days for a leader after joining the critical position are considered to be significant, and thus we aimed to understand the critical rhetorical appeal- pathos used by Prime Minister’s public relations campaign – Mann Ki Baat . An analytical framework is also proposed to accomplish the investigation. The public relations scholars, practitioners, and academia will be the primary beneficiary and can utilize the proposed framework to explore the pathos in the unstructured data.

关键词： Pathos Cyber-physical society unstructured data text analysis sentiment analysis pathos framework public relations

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Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images 23rd

Learning High-Resolution and Efficient Non-local Features fo...

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23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Jia, Haozhe Xia, Yong Cai, Weidong Huang, Heng Research and Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518057 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xian710072 China School of Computer Science University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States JD Finance America Corporation Mountain ViewCA94043 United States

ISBN: (纸本)9783030597184

Brain glioma segmentation using multi-parametric magnetic resonance (MR) imaging has significant clinical value. Although 3D convolutional neural networks (CNNs) have become increasingly prevalent in delivering this segmentation task, these models still suffer from an insufficient ability to high-resolution feature representation for small and irregular regions, limited local receptive fields, and poor long-range dependencies. In this paper, we propose a 3D High-resolution and Non-local Feature Network (HNF-Net) for brain glioma segmentation using multi-parametric MR imaging. We construct HNF-Net based mainly on the parallel multi-scale fusion (PMF) module, which helps produce strong high-resolution feature representation and aggregate multi-scale contextual information. We also introduce the expectation-maximization attention (EMA) module to HNF-Net, aiming to capture the long-range dependent contextual information and reduce the feature redundancy in a lightweight fashion. We evaluated our HNF-Net on the BraTS 2019 Challenge dataset against eight top-ranking methods listed on the challenge leaderboard. Our results suggest that the proposed HNF-Net achieves improved overall performance over these methods, and our ablation study demonstrates the effectiveness of the PMF module and EMA module. © 2020, Springer Nature Switzerland AG.

关键词： Magnetic resonance imaging

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Modelling excess zeros in count data: A new perspective on modelling approaches

arXiv

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arXiv 2020年

作者： Haslett, John Parnell, Andrew C. Hinde, John de Andrade Moral, Rafael School of Computer Science and Statistics Trinity College Dublin Ireland Hamilton Institute Insight Centre for Data Analytics Maynooth University Ireland School of Mathematics Statistics and Applied Mathematics NUI Galway Ireland Department of Mathematics and Statistics Maynooth University Ireland

We consider the analysis of count data in which the observed frequency of zero counts is unusually large, typically with respect to the Poisson distribution. We focus on two alternative modelling approaches: Over-Dispersion (OD) models, and Zero-Inflation (ZI) models, both of which can be seen as generalisations of the Poisson distribution;we refer to these as Implicit and Explicit ZI models, respectively. Although sometimes seen as competing approaches, they can be complementary;OD is a consequence of ZI modelling, and ZI is a by-product of OD modelling. The central objective in such analyses is often concerned with inference on the effect of covariates on the mean, in light of the apparent excess of zeros in the counts. Typically the modelling of the excess zeros per se is a secondary objective and there are choices to be made between, and within, the OD and ZI approaches. The contribution of this paper is primarily conceptual. We contrast, descriptively, the impact on zeros of the two approaches. We further offer a novel descriptive characterisation of alternative ZI models, including the classic hurdle and mixture models, by providing a unifying theoretical framework for their comparison. This in turn leads to a novel and technically simpler ZI model. We develop the underlying theory for univariate counts and touch on its implication for multivariate count data. Copyright © 2020, The Authors. All rights reserved.

关键词： Poisson distribution

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Partial (neighbourhood) singleton arc consistency for constraint satisfaction problems 31

Partial (neighbourhood) singleton arc consistency for constr...

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31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018

作者： Wallace, Richard J. Insight Centre for Data Analytics Department of Computer Science University College Cork Cork Ireland

ISBN: (纸本)9781577357964

Algorithms based on singleton arc consistency (SAC) show considerable promise for improving backtrack search algorithms for constraint satisfaction problems (CSPs). The drawback is that even the most efficient of them is still comparatively expensive. Even when limited to preprocessing, they give overall improvement only when problems are quite difficult to solve with more typical procedures such as maintained arc consistency (MAC). The present work examines a form of partial SAC and neighbourhood SAC (NSAC) in which a subset of the variables in a CSP are chosen to be made SAC-consistent or neighbourhood-SAC-consistent. These consistencies are well-characterized in that algorithms have unique fixpoints and there are well-defined dominance relations. Heuristic strategies for choosing an effective subset of variables are described and tested, in particular a strategy of choosing by constraint weight after random probing. Experimental results justify the claim that these methods can be nearly as effective as full (N)SAC in terms of values discarded while significantly reducing the effort required. Copyright © 2018, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Constraint satisfaction problems

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Spent bleaching earth as a source of oil and catalyst for renewable hydrocarbon conversion

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Journal of Environmental Chemical Engineering 2025年第3期13卷

作者： Ainnur Rusydina Ab Halim Zeni Rahmawati Mohamad Nasir Mohamad Ibrahim Chua Yong Shen Gnanasikamani Balaji Soh Kheang Loh Nuryono Nuryono Wan Nazwanie Wan Abdullah School of Chemical Sciences Universiti Sains Malaysia 11800 Penang Malaysia Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Sukolilo Surabaya 60111 Indonesia Department of Mechanical Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu 603203 India Energy and Environment Unit Engineering and Processing Division Malaysian Palm Oil Board 6 Persiaran Institusi Bandar Baru Bangi Kajang Selangor 43000 Malaysia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Bulaksumur Yogyakarta 55281 Indonesia

Spent bleaching earth (SBE) is a solid waste generated by the vegetable oil refining industries. It contains entrapped crude oil, making its disposal challenging for industries. In this study, valorization of SBE for catalytic biodiesel conversion using alginate-SBE catalyst was explored. The alginate-SBE catalyst was synthesized using a simple impregnation method. It was characterized by Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), field emission scanning electron microscopy with energy dispersive X-ray (FESEM- EDX) and temperature programmed desorption of carbon dioxide (CO 2/ TPD) to assess its structural and morphological properties. The recovered bleached oil was optimally transesterified at temperature of 80 °C, oil-to-methanol ratio of 1:22, and catalyst loading of 9 wt% within 2 h production, achieving a maximum biodiesel yield of 93.35 %. Reusability tests demonstrated that the alginate-SBE catalyst can retain > 90 % of initial activity after five cycles, highlighting its potential for practical applications. Gas chromatography-mass spectrometry (GC-MS) results indicated potential conversion of biodiesel to renewable hydrocarbons (C8-C15). This study highlights the dual benefits of utilizing industrial waste for both feedstock and catalyst support, promoting a cleaner and economically viable approach for biofuel generation.

关键词： Alginate Biodiesel Hydrocarbon Spent bleaching earth (SBE) Waste oils

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Inhibition of colorectal cancer targets IL-6, CTLA-4, & B7-2 by Tislelizumab: molecular docking, dynamics, & STRING protein-protein network analysis

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Informatics in Medicine Unlocked 2023年 41卷

作者： Elkazzaz, Mahmoud Ullah, Shahid Gao, Tianshun Shamkh, Israa M. Ahmed, Amr Wu, Ted X. Elsharayidi, Maii S. Khan, Mohammad Shahbaz Rehman, Aziz-ur Lotfy, Marwa M. Haikal, Abdullah Abdalrahman, Mahmoud Department of Chemistry and Biochemistry Faculty of Science Damietta University Damietta 7952567 Egypt S Khan Lab Mardan Khyber Pakhtunkhwa Pakistan Big Data Center The Seventh Affiliated Hospital of Sun Yat-sen University Shenzhen 518107 China Botany and Microbiology Department Faculty of Science Cairo University Cairo 12613 Egypt Chemo and Bioinformatics Lab Bio Search Research Institution BSRI Giza 12613 Egypt Public Health Department First Health Cluster Ministry of Health Riyadh 966-11 Saudi Arabia Science Department Milton Academy Milton 02186 MA United States Central Public Health Laboratories Egyptian Ministry of Health Egypt Children's National Hospital Washington DC United States Keystone Pharmacogenomics LLC Bensalem 19020 PA United States Faculty of Pharmacy Zagazig University Zagazig 44511 Egypt Department of Pharmacognosy Faculty of Pharmacy Mansoura University Mansoura 35516 Egypt Lowell Institute CPS Northeastern University 360 Huntington Ave Boston 02115 MA United States

As a DNA mismatch repair deficit (dMMR) anticancer medication, and a humanized monoclonal antibody (hmAb), Tislelizumab has attracted significant interest in recent years. The programmed cell death protein-1 (PD-1) and its ligands (PD-L1/CD274/B7-H1 and PDL2/CD273) may bind to each other with great affinity. This binding prevents activated T-cells from continuing to proliferate, produce cytokines, and engage in cytotoxic action. The B7:PD-1 inhibitory immunological checkpoint receptor binds to the B7-2(CD86) B-lymphocyte activation antigen. This paper presents Tislelizumab's molecular docking and dynamics simulations with the receptor B7-2(CD86) and its downstream signaling proteins CTLA-4 and IL-6. When docked to B cell stimulatory factor-2 soluble IL-6 receptor alpha (sIL6Ra/CD126), Tislelizumab had a strong binding affinity of 329 kcal/mol and provided an excellent quality model with an LGscore of 4.54. The type I membrane protein B7-2(CD86), a member of the immunoglobulin superfamily, responded to docking with an affinity of −332.35 kcal/mol and LGscore of 2.54. Docking to the immune checkpoint protein receptor cytotoxic T-lymphocyte-associated protein-4 (CTLA-4/CD152) had a binding affinity of −305.91 kcal/mol, facilitating immunological control and cellular dissociation. Tislelizumab and these target proteins exhibited persistent and advantageous interactions in molecular dynamics studies. The STRING functional protein-protein network analysis supported our in silico docking and dynamic simulation results. This analysis also included comparisons of the binding modes of mAbs to protein receptors involved in the cancer hallmark mechanism(s), demonstrating that IL-6, B7-2, and CTLA-4 act and are inhibited in group-mode. Functional enrichment analysis and molecular modelling supported the relationship between the hallmarks of the tumor microenvironment that link inflammation to immunity. Tislelizumab may therefore be able to prevent these three proteins from actin

关键词： B7-2 Colorectal Cancer CTLA-4 Dostarlimab IL-6 Immunotherapy PD-1 Tislelizumab

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