检索结果-内蒙古大学图书馆

Sustainable Chemistry for the Environment 2023年 2卷

作者： Naveed, Sahar Oladoye, Peter Olusakin Alli, Yakubu Adekunle NIAB College Pakistan Institute of Engineering and Applied Sciences (PIEAS) Jhang Road P.O. Box 128 Faisalabad 38000 Pakistan Department of Chemistry and Biochemistry Florida International University 11200 SW 8th St Miami 33199 FL United States Department of Pure and Applied Chemistry Ladoke Akintola University of Technology P.M.B Ogbomoso 4000 Nigeria CNRS LCC (Laboratoire de Chimie de Coordination) UPR8241 université de Toulouse UPS INPT Toulouse cedex 4 F-31077 France Department of Chemical Sciences Faculty of Science and Computing Ahman Pategi University Patigi-Kpada Road Kwara State Patigi Nigeria Department of Manufacturing and Materials Engineering Kulliyyah of Engineering International Islamic University Malaysia Kuala Lumpur Jalan Gombak 53100 Malaysia

Heavy metal contamination of soil is becoming a life-threatening issue causing serious threat to our ecosystem. These metals reduce the potency of soil and affect the entire environment negatively. In plants, these metals inhibit the rate of photosynthesis, production of major proteins and enzymes. Decrease in the trend of seed germination, premature- growth have also been observed. Phytoremediation is a modern strategy that is used for treatment of contaminated soil using various methods, including phytoextraction, phytostabilization, phytovolatilization and phytofiltration. Phytoremediation has gained importance over different physical and chemical methods like soil replacement, washing policies and solidification as it is cost-effective and easy to adopt technology. The utilization of this green technology has benefited mankind via the reduction of heavy metal accumulation in plant parts, specifically non-edible plants. In view of the several merits of the green technology, this review paper discussed several literatures published on heavy metal toxicity, their risk assessment and phytoremediation method, while various research gaps were suggested to tackle some challenges inherent in phytoremediation approach for the treatment of heavy-metal contaminated soils. © 2023 The Authors

关键词： Contamination Heavy metal Hyperaccumulator Soil Treatment

来源：评论

学校读者我要写书评

暂无评论

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7248 LNCS卷 VI-XI页

作者： Di Chio, Cecilia Agapitos, Alexandros Cagnoni, Stefano Cotta, Carlos De Vega, F. Fernández Di Caro, Gianni Drechsler, Rolf Ekárt, Anikó Esparcia-Alcázar, Anna I. Farooq, Muddassar Langdon, William B. Merelo-Guervós, Juan-J. Preuss, Mike Richter, Hendrik Silva, Sara Simões, Anabela Squillero, Giovanni Tarantino, Ernesto Tettamanzi, Andrea G.B. Togelius, Julian Urqhart, Neil Uyar, A. Şima Yannakakis, Georgios N. University College Dublin Ireland Dept. of Computer Engineering University of Parma Italy Dept. Lenguajes Y Ciencias de la Computación University of Málaga Spain University of Extremadura Spain Lugano Switzerland Cyber-Physical Systems DFKI Bremen Germany Computer Science Aston University Birmingham United Kingdom S2 Grupo Spain National University of Computer and Emerging Sciences Islamabad Pakistan University College London United Kingdom Departamento de Arquitectura Y Tecnología de Computadores Universidad de Granada Spain TU Dortmund University Germany Faculty of Electrical Engineering and Information Technology HTWK Leipzig University of Applied Sciences Germany INESC-ID Lisboa Portugal Coimbra Institute of Engineering Coimbra Polytechnic Coimbra Portugal Politecnico di Torino Italy Institute for High Performance Computing and Networking Italy Università degli Studi di Milano Italy Center for Computer Games Research IT University of Copenhagen Denmark Centre for Emergent Computing Edinburgh Napier University United Kingdom Dept. of Computer Engineering Istanbul Technical University Turkey

来源：评论

学校读者我要写书评

暂无评论

Preface

SpringerBriefs in Applied Sciences and Technology

引用

SpringerBriefs in applied Sciences and technology 2024年 Part F2025卷 v页

作者： Ismail, Azman Zulkipli, Fatin Nur Daril, Mohd Amran Mohd Öchsner, Andreas Centre for Women Advancement and Leadership Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Technology Perak Lumut Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Kelantan Machang Malaysia Malaysian Institute of Industrial Technology Universiti Kuala Lumpur Johor Masai Malaysia Faculty of Mechanical Engineering Esslingen University of Applied Sciences Esslingen am Neckar Baden-Württemberg Germany

来源：评论

学校读者我要写书评

暂无评论

Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

引用

Science China(Life Sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A Sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong Soojin Jang Haruo Suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick K H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu Shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3S-Instituto de Investiga玢o e Inova玢o em Saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological Sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur Korea Seoul 13488Republic of Korea Faculty of Environment and Information Studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA School of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta SUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters

来源：评论

学校读者我要写书评

暂无评论

Towards improving Alzheimer's intervention: a machine learning approach for biomarker detection through combining MEG and MRI pipelines

arXiv

引用

arXiv 2024年

作者： Ahmad, Alwani Liyana Sanchez-Bornot, Jose Sotero, Roberto C. Coyle, Damien Idris, Zamzuri Faye, Ibrahima Department of Fundamental and Applied Sciences Faculty of Science and Information Technology Universiti Teknologi PETRONAS Perak Malaysia Department of Neurosciences Hospital Universiti Sains Malaysia Kelantan Malaysia Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Kelantan Malaysia Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Magee campus Derry~Londonderry BT48 7JL United Kingdom Department of Radiology Hotchkiss Brain Institute University of Calgary CalgaryAB Canada The Bath Institute for the Augmented Human University of Bath BathBA2 7AY United Kingdom Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Kelantan Malaysia Universiti Teknologi PETRONAS Perak Malaysia

Background: Magneto/eletro-encephalography (MEG/EEG) are non-invasive neuroimaging techniques that offer excellent temporal and spatial resolution that can be used to study brain functioning. It has been proven effective in research on dementia and Alzheimer's disease (AD), where MEG/EEG analyses can identify changes in brain activity at various stages of AD progression, including preclinical and prodromal. Research has shown differences in the power spectrum properties among healthy controls (HC) and individuals with mild cognitive impairment (MCI) or AD. It has also been conjectured that MEG/EEG analyses have the capability to identify pathological changes before first clinical symptoms and may provide biomarkers for interventions designed to reverse or slow the progression of AD. Objective: To conduct a comprehensive analysis by evaluating the performance of various classification techniques using features extracted by following different MEG methodologies. This study will focus on selecting MEG-based biomarkers/features that enhance performance in distinguishing between healthy control (HC) and mild cognitive impairment (MCI) participants from the BioFIND study. Furthermore, we will compare this with the effectiveness of using MRI-based anatomical features extracted from same participants, independently or in combination with the MEG features;thus, extending from previous study where similar analyses were performed using ADNI and OASIS-3 datasets. Methods: MEG and MRI data are obtained from the BioFIND dataset, comprising 324 participants with 158 individuals diagnosed as MCI and 166 HC. Sensor and source-based MEG analyses are performed using custom MATLAB code based on SPM12 and OSL toolboxes, for co-registration, preprocessing including filtering, and automatic artifact rejection. Source-based analyses were applied through different source localization methods as implemented in SPM12 and DAiSS toolboxes. We conducted analogous machine learning analyses on sen

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

Leveraging hardware-control imperfections for error mitigation via generalized quantum subspace

arXiv

引用

arXiv 2023年

作者： Ohkura, Yasuhiro Endo, Suguru Satoh, Takahiko Van Meter, Rodney Yoshioka, Nobuyuki Graduate School of Media and Governance Keio University SFC Kanagawa Fujisawa252-0882 Japan NTT Computer and Data Science Laboratories NTT Corporation Musashino180-8585 Japan Keio University Quantum Computing Center Kanagawa Yokohama223-8522 Japan Graduate School of Science and Technology Keio University Kanagawa Yokohama223-8522 Japan Faculty of Environment and Information Studies Keio University SFC Kanagawa Fujisawa252-0882 Japan Department of Applied Physics University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Wako-shi Saitama351-0198 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan

In the era of quantum computing without full fault-tolerance, it is essential to suppress noise effects via the quantum error mitigation techniques to enhance the computational power of the quantum devices. One of the most effective noise-agnostic error mitigation schemes is the generalized quantum subspace expansion (GSE) method, which unifies various mitigation algorithms under the framework of the quantum subspace expansion. Specifically, the fault-subspace method, a subclass of GSE method, constructs an error-mitigated quantum state with copies of quantum states with different noise levels. However, from the experimental aspect, it is nontrivial to determine how to reliably amplify the noise so that the error in the simulation result is efficiently suppressed. In this work, we explore the potential of the fault-subspace method by leveraging the hardware-oriented noise: intentional amplification of the decoherence, noise boost by insertion of identity, making use of crosstalk, and probabilistic implementation of noise channel. We demonstrate the validity of our proposals via both numerical simulations with the noise parameters reflecting those in quantum devices available via IBM Quantum, and also experiments performed therein. Copyright © 2023, The Authors. All rights reserved.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

A Systematic review of Multi-Mode Fiber based on Dimensional Code in Optical-CDMA

引用

Journal of Physics: Conference Series 2021年第1期1860卷

作者： Alaan Ghazi S.A. Aljunid Syed Zulkarnain Syed Idrus C.B.M Rashidi Aras Al-dawoodi Baban A. Mahmood Alaa Fareed Mohammed U. Zaenal Nameer Hashim Qasim Ranjdr M. Rafeeq Faculty of Applied and Human Sciences University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Technical Engineering Al-Qalam university College Iraq Computer Science Department College of Computer Science and Information Technology Kirkuk University Kirkuk Iraq School of Computing University Utara Malaysia Malaysia

This paper deals with optical code division multiple access (optical-CDMA) and provides a general analysis of multi-mode fiber (MMF). The purpose of this work is to classify the works in the literature that are related to Optical-CDMA based on MMF and to find the limitation of the researches done in this field. Several challenges that occur in the medium such as multiple-access interference (MAI), pulse dispersion (PD) and nonlinearity in optical fibers deteriorate system performances and become a major performance-limiting factor.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Correction: Extremely boosted neural network for more accurate multi-stage Cyber attack prediction in cloud computing environment

引用

Journal of Cloud computing 2023年第1期12卷 1-1页

作者： Dalal, Surjeet Manoharan, Poongodi Kumar, Lilhore Umesh Seth, Bijeta alsekait, Deema Mohammed Simaiya, Sarita Hamdi, Mounir Raahemifar, Kaamran Department of Computer Science and Engineering Amity University Haryana Gurugram India Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar School of Computing University of Louisiana Lafayette USA Department of Computer Science and Engineering Chandigarh University Mohali India Department of Computer Science and Engineering B. M. Institute of Engineering & Technology Sonipat India Department of Computer Science and Information Technology Applied College Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia College of Information Sciences and Technology Data Science and Artificial Intelligence Program State College USA School of Optometry and Vision Science Faculty of Science University of Waterloo Waterloo Canada Faculty of Engineering University of Waterloo Waterloo Canada

来源：评论

学校读者我要写书评

暂无评论

Preface

Advanced Structured Materials

引用

Advanced Structured Materials 2023年 193卷 v页

作者： Ismail, Azman Zulkipli, Fatin Nur Yaakup, Syajaratunnur Öchsner, Andreas Centre for Women Advancement and Leadership Malaysian Institute of Marine Engineering Technology Universiti Kuala Lumpur Perak Lumut Malaysia Information Science Studies College of Computing Informatics and Mathematics Universiti Teknologi MARA Kelantan Branch Machang Malaysia Malaysian Institute of Marine Engineering Technology Universiti Kuala Lumpur Perak Lumut Malaysia Faculty of Mechanical Engineering Esslingen University Applied Sciences Esslingen am Neckar Germany

来源：评论

学校读者我要写书评

暂无评论

Anonymization of labeled TOF-MRA images for brain vessel segmentation using generative adversarial networks

arXiv

引用

arXiv 2020年

作者： Kossen, Tabea Subramaniam, Pooja Madai, Vince I. Hennemuth, Anja Hildebrand, Kristian Hilbert, Adam Sobesky, Jan Livne, Michelle Galinovic, Ivana Khalil, Ahmed A. Fiebach, Jochen B. Frey, Dietmar CLAIM - Charité Lab for AI in Medicine Charité Universitätsmedizin Berlin Germany Department of Computer Engineering and Microelectronics Computer Vision & Remote Sensing Technical University Berlin Berlin Germany Department of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany School of Computing and Digital Technology Faculty of Computing Engineering and the Built Environment Birmingham City University Birmingham United Kingdom Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine Charité Universitätsmedizin Berlin Berlin Germany Fraunhofer MEVIS Bremen Germany Department VI Computer Science and Media Beuth University of Applied Sciences Berlin Germany Johanna-Etienne-Hospital Neuss Germany Centre for Stroke Research Berlin Charité Universitätsmedizin Berlin Berlin Germany Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany Mind Brain Body Institute Berlin School of Mind and Brain Humboldt University Berlin Berlin Germany Berlin Institute of Health Berlin Germany

Anonymization and data sharing are crucial for privacy protection and acquisition of large datasets for robust medical image analysis. This represents a major challenge, especially for brain imaging research. Here, the unique structure of brain images allows for potential re-identification and thus requires anonymization beyond conventional methods. Generative adversarial networks (GANs) have the potential to provide anonymous images while maintaining their predictive properties. Analyzing brain vessel segmentation as a use case, we trained 3 GAN architectures on time-of-flight (TOF) magnetic resonance angiography (MRA) patches of patients with cerebrovascular disease for image-label pair generation: 1) Deep convolutional GAN, 2) Wasserstein-GAN with gradient penalty (WGAN-GP) and 3) WGAN-GP with spectral normalization (WGAN-GP-SN). First, the synthesized image-labels from each GAN architecture were used to train a U-net for vessel segmentation. The U-nets were then tested on real patient data. In total, 66 patients were used for this analysis. In a second step, we simulated the application of our synthetic patches in a transfer learning approach using a second, independent dataset. Here, for an increasing number of up to 15 patients we evaluated vessel segmentation model performance on real data with and without pre-training on generated patches. Finally, performance for all models was assessed by the Dice Similarity Coefficient (DSC) and the 95th percentile of the Hausdorff Distance (95HD). Comparing the 3 GAN architectures, the U-net model trained on synthetic data generated by the WGAN-GP-SN showed the highest performance to predict brain vessels (DSC/95HD 0.82/28.97) benchmarked by the U-net trained on real data (0.89/26.61). The transfer learning approach showed superior performance for the same GAN architecture compared to no pre-training, especially for one labeled patient only (DSC/95HD 0.91/25.68 compared to DSC/95HD 0.85/27.36). In a brain imaging segment

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：