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How will climate change affect the sources of global irrigation water withdrawal?

Science Bulletin 2024年第21期69卷 3361-3364页

作者： Zhipin Ai Xin Zhao Julien Boulange Fadong Li Rashid Mahmood Qiuying Zhang Yonghui Yang Jun Xia Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 101408China Earth System Division National Institute for Environmental StudiesTsukuba 305-8506Japan United Graduate School of Agricultural Science Tokyo University of Agriculture and TechnologyTokyo 183-8509Japan Water Engineering and Management Asian Institute of TechnologyPathumthani 12120Thailand Chinese Research Academy of Environmental Sciences Beijing 100012China Center for Agricultural Resources Research Institute of Genetics and Developmental BiologyChinese Academy of SciencesShijiazhuang 050021China State Key Laboratory of Water Resources Engineering and Management Wuhan UniversityWuhan 430072China

Irrigation plays a vital role in global food production,contributing approximately 40%of the total production[1],although the contribution varies by crop type[2,3].However,irrigation water withdrawal constitutes 65%–70%of total global anthropogenic water withdrawal[4,5],making it the largest water-use sector *** irrigation water demand,sources,and availability,particularly in the context of climate change,is crucial for identifying potential threats to crop production and ensuring future global food *** studies have focused extensively on the impacts of climate change on irrigation water demand and withdrawal[6–9];however,it remains unclear how climate change will affect the sources of irrigation water withdrawal.

关键词： irrigation withdrawal sources

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Development and Implementation of a Holistic Flexibility Market Architecture

Development and Implementation of a Holistic Flexibility Mar...

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Innovative Smart Grid Technologies (ISGT)

作者： Oliver Kraft Oliver Pohl Ulf Hä ger Kai Heussen Nils Mü ller Zeeshan Afzal Mathias Ekstedt Hossein Farahmand Dmytro Ivanko Ankit Singh Sasiphong Leksawat Andreas Kubis Institute of Energy Systems Energy Efficiency and Energy Economics TU Dortmund University Dortmund Germany Department of Electrical Engineering Technical University of Denmark Kongens Lyngby Denmark Division of Network and System Engineering KTH Royal Institute of Technology Stockholm Sweden Department of Electric Power Engineering Norwegian University of Science and Technology Trondheim Norway Research and Development Department Electrical Energy Division PSI Software AG Dortmund Germany

The demand for increasing flexibility use in power systems is stressed by the changing grid utilization. Making use of largely untapped flexibility potential is possible through novel flexibility markets. Different approaches for these markets are being developed and vary considering their handling of transaction schemes and relation of participating entities. This paper delivers the conceptual development of a holistic system architecture for the realization of an interregional flexibility market, which targets a market based congestion management in the transmission and distribution system through trading between system operators and flexibility providers. The framework combines a market mechanism with the required supplements like appropriate control algorithms for emergency situations, cyber-physical system monitoring and cyber-security assessment. The resulting methods are being implemented and verified in a remote-power-hardware-in-the-loop setup coupling a real world low voltage grid with a geographically distant real time simulation using state of the art control system applications with an integration of the aforementioned architecture components.

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Protocol for the fabrication of self-standing (nano)cellulose-based 3D scaffolds for tissue engineering

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STAR Protocols 2025年第1期6卷 103583页

作者： Mohan, Tamilselvan Bračič, Matej Bračič, Doris Lackner, Florian Nagaraj, Chandran Štiglic, Andreja Dobaj Kargl, Rupert Kleinschek, Karin Stana Graz University of Technology Institute for Chemistry and Technology of Biobased System (IBioSys) Stremayrgasse 9 Graz 8010 Austria University of Maribor Faculty of Mechanical Engineering Laboratory for Characterization and Processing of Polymers Smetanova Ulica 17 Maribor 2000 Slovenia Department of Internal Medicine Division of Pulmonology Medical University of Graz Graz Austria Institute of Automation Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Members of the European Polysaccharide Network of Excellence (EPNOE) Austria

Three-dimensional (3D) and porous scaffolds made from nanocellulosic materials hold significant potential in tissue engineering (TE). Here, we present a protocol for fabricating self-standing (nano)cellulose-based 3D scaffolds designed for in vitro testing of cells from skin and cartilage tissues. We describe steps for preparation of nanocellulose ink, scaffold formation using 3D printing, and freeze-drying. We then detail post-processing procedures to enhance mechanical properties, stability, and biocompatibility. This protocol offers researchers a framework for developing versatile and sustainable biomaterials for regenerative medicine. For complete details on the use and execution of this protocol, please refer to Mohan et al.¹ and Štiglic et al.² © 2025 The Authors

关键词： Biotechnology and bioengineering Chemistry Material sciences Tissue engineering

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iGEM: a model system for team science and innovation

arXiv

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arXiv 2023年

作者： Santolini, Marc Blondel, Leo Palmer, Megan J. Ward, Robert N. Jeyaram, Rathin Brink, Kathryn R. Krishna, Abhijeet Barabási, Albert-László Université Paris Cité Inserm System Engineering and Evolution Dynamics ParisF-75004 France Learning Planet Institute ParisF-75004 France Network Science Institute Department of Physics Northeastern University BostonMA02115 United States Department of Bioengineering Stanford University StanfordCA United States Center for International Security and Cooperation Stanford University StanfordCA United States School of Public Policy Georgia Institute of Technology AtlantaGA United States Channing Division of Network Medicine Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Network and Data Science Central European University Budapest Hungary

Teams are a primary source of innovation in science and technology. Rather than examining the lone genius, scholarly and policy attention has shifted to understanding how team interactions produce new and useful ideas. Yet the organizational roots of innovation remain unclear, in part because of the limitations of current data. This paper introduces the international Genetically Engineered Machine (iGEM) competition, a model system for studying team science and innovation. By combining digital laboratory notebooks with performance data from 2,406 teams over multiple years of participation, we reveal shared dynamical and organizational patterns across teams and identify features associated with team performance and success. This dataset makes visible organizational behavior that is typically hidden, and thus understudied, creating new opportunities for the science of science and innovation. © 2023, CC BY.

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Opportunistic Wiretapping/Jamming: A New Attack Model in Millimeter-Wave Wireless networks

arXiv

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arXiv 2022年

作者： Zhang, Yuanyu Zheng, Zhumeng He, Ji Zhao, Shuangrui Qu, Qianyue Shen, Yulong Jiang, Xiaohong School of Computer Science and Technology Xidian University Shaanxi Xi’an China Shannxi Key Laboratory of Network and System Security China Beijing Sunwise Information Technology Ltd Beijing Institute of Control Engineering Beijing China Division of Information Science Graduate School of Science and Technology Nara Institute of Science and Technology Nara Ikoma Japan School of Systems Information Science Future University Hakodate Hokkaido Hakodate Japan

While the millimeter-wave (mmWave) communication is robust against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an eavesdropper can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack. © 2022, CC BY.

关键词： Millimeter waves

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Opportunistic Wiretapping/Jamming: A New Attack Model in Millimeter-Wave Wireless networks

TechRxiv

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TechRxiv 2022年

作者： Zhang, Yuanyu Zheng, Zhumeng He, Ji Zhao, Shuangrui Qu, Qianyue Shen, Yulong Jiang, Xiaohong School of Computer Science and Technology Xidian University Shaanxi Xi’an China Shannxi Key Laboratory of Network and System Security China The Beijing Sunwise Information Technology Ltd Beijing Institute of Control Engineering Beijing China The Division of Information Science Graduate School of Science and Technology Nara Institute of Science and Technology Nara Ikoma Japan School of Systems Information Science Future University Hakodate Hokkaido Hakodate Japan

关键词： Millimeter waves

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A Comparison of Machine and Statistical Time Series Learning for Encrypted Traffic Prediction

A Comparison of Machine and Statistical Time Series Learning...

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International Conference on Computing, networking and Communications (ICNC)

作者： Qing He Georgios P. Koudouridis György Dán Division of Network and Systems Engineering KTH Royal Institute of Technology Stockholm Sweden RAN System Lab Stockholm Research Center Huawei Technologies Stockholm Sweden

ISBN: (数字)9781728149059

ISBN: (纸本)9781728149066

This paper studies the utilization of machine and statistical learning methods for predicting encrypted user traffic. To this end, a reference system model and performance metrics for traffic prediction have been defined for enabling on-line training. Based on a collection of representative traffic data sets including various video and web traffic, two different classes of predictors have been evaluated. Our results show that very good prediction performance can be achieved using long short-term memory (LSTM) recurrent neural networks at the price of a significant computational cost for training.

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Semi-Persistent Scheduling for 5G Downlink based on Short-Term Traffic Prediction

Semi-Persistent Scheduling for 5G Downlink based on Short-Te...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Qing He György Dán Georgios P. Koudouridis Division of Network and Systems Engineering KTH Royal Institute of Technology Stockholm Sweden RAN System Lab. Stockholm Research Center Huawei Technologies Stockholm Sweden

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

Efficient communication and computing resource allocation is becoming a fundamental issue in wireless networks. Efficiency is most often defined in terms of throughput, utilization and spectral efficiency, while the required computational effort is often overlooked. In this paper, we focus on efficient and computationally lightweight downlink scheduling, and we propose a semi-persistent scheduler based on adaptive short term traffic prediction. We evaluate the performance of the proposed scheduler in terms of throughput, fairness, latency, and scheduling complexity. Our numerical results show that scheduling with prediction is a promising approach in improving network performance. The proposed semi-persistent scheduler performs equally well in terms of throughput, fairness, and latency as traditional proportional-fair scheduling, but at a significantly reduced computational cost.

关键词： Processor scheduling Throughput Downlink Dynamic scheduling Prediction algorithms Computational efficiency Wireless networks

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High-pressure synthesis of Ba2RhO4, a rhodate analog of the layered perovskite Sr-ruthenate

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Physical Review Materials 2021年第1期5卷 015001-015001页

作者： I. Kurata José A. Flores-Livas H. Sugimoto H. Takahashi H. Sagayama Y. Yamasaki T. Nomoto R. Arita S. Ishiwata Division of Materials Physics Graduate School of Engineering Science Osaka University Osaka 560-8531 Japan Department of Applied Physics University of Tokyo Tokyo 113-8656 Japan Dipartimento di Fisica Università di Roma La Sapienza Piazzale Aldo Moro 5 I-00185 Roma Italy RIKEN Center for Emergent Matter Science 2-1 Hirosawa Wako 351-0198 Japan Center for Spintronics Research Network (CSRN) Graduate School of Engineering Science Osaka University Osaka 560-8531 Japan Institute of Materials Structure Science High Energy Accelerator Research Organization Tsukuba Ibaraki 305-0801 Japan Research and Services Division of Materials Data and Integrated System (MaDIS) National Institute for Materials Science (NIMS) Ibaraki Tsukuba 305-0047 Japan

A layered perovskite-type oxide Ba2RhO4 was synthesized by a high-pressure technique with the support of convex-hull calculations. The crystal and electronic structure were studied by both experimental and computational tools. Structural refinements for powder x-ray diffraction data showed that Ba2RhO4 crystallizes in a K2NiF4-type structure, isostructural to Sr2RuO4 and Ba2IrO4. Magnetic, resistivity, and specific-heat measurements for polycrystalline samples of Ba2RhO4 indicate that the system can be characterized as a correlated metal. Despite the close similarity to its Sr2RuO4 counterpart in the electronic specific-heat coefficient and the Wilson ratio, Ba2RhO4 shows no signature of superconductivity down to 0.16 K. Whereas the Fermi surface topology has reminiscent pieces of Sr2RuO4, an electronlike eg−(dx2−y2) band descends below the Fermi level, making this compound unique also as a metallic counterpart of the spin-orbit coupled Mott insulator Ba2IrO4.

关键词： Electrical conductivity Fermi surface Spin-orbit coupling Transition metal oxides Density functional theory Resistivity measurements Specific heat measurements X-ray powder diffraction

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Biomedical data and AI

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Science China Life Sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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