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recent Ventures in Interdisciplinary Arctic research:The ArCPATH Project

Advances in Atmospheric Sciences 2024年第8期41卷 1559-1568页

作者： Astrid E.J.OGILVIE Leslie A.KING Noel KEENLYSIDE François COUNILLON Brynhildur DAVIÐSDÓTTIr Níels EINArSSON Sergey GULEV Ke FAN Torben KOENIGK james r.mcgoodwin Marianne H.rASMUSSON Shuting YANG Institute of Arctic and Alpine research(INSTAAr) University of ColoradoBoulder CO 80303USA Stefansson Arctic Institute AkureyriÍS-600Iceland royal roads University BC V9B 5Y2Canada University of Bergen Bergen N-5007Norway Nansen Environmental and remote Sensing Centre Bergen N-5007Norway University of Iceland Reykjavík 102Iceland Shirshov Institute of Oceanology Moscow 117218Russia Moscow State University Moscow 11991Russia Chinese Academy of Sciences Beijing 100045China Swedish Meteorological and Hydrological Institute SE-60176 NorrköpingSweden Danish Meteorological Institute CopenhagenØ2100Denmark Obukhov Institute of Atmospheric Physics RAS119017MoscowRussia

This paper celebrates Professor Yongqi GAO's significant achievement in the field of interdisciplinary studies within the context of his final research project Arctic Climate Predictions: Pathways to resilient Sustainable Societies-ArCPATH(https://***/en/projects/finished-projects/arcpath). The disciplines represented in the project are related to climatology, anthropology, marine biology, economics, and the broad spectrum of social-ecological studies. Team members were drawn from the Nordic countries, russia, China, the United States, and Canada. The project was transdisciplinary as well as interdisciplinary as it included collaboration with local knowledge holders. ArCPATH made significant contributions to Arctic research through an improved understanding of the mechanisms that drive climate variability in the Arctic. In tandem with this research, a combination of historical investigations and social, economic, and marine biological fieldwork was carried out for the project study areas of Iceland, Greenland, Norway, and the surrounding seas, with a focus on the joint use of ocean and sea-ice data as well as social-ecological drivers. ArCPATH was able to provide an improved framework for predicting the near-term variation of Arctic climate on spatial scales relevant to society, as well as evaluating possible related changes in socioeconomic realms. In summary, through the integration of information from several different disciplines and research approaches, ArCPATH served to create new and valuable knowledge on crucial issues, thus providing new pathways to action for Arctic communities.

关键词： recent Ventures in Interdisciplinary Arctic research:The ArCPATH Project

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Facilitated Prediction of Micropollutant Degradation via UV-AOPs in Various Waters by Combining Model Simulation and Portable Measurement

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Engineering 2024年第6期37卷 87-95页

作者： Yanyan Huang Mengkai Li Zhe Sun Wentao Li james r.Bolton Zhimin Qiang Key Laboratory of Drinking Water Science and Technology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China Department of Civil and Environmental Engineering University of AlbertaEdmontonAB T6G 1H9Canada State Key Laboratory of Environmental Aquatic Chemistry Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China

The degradation of micropollutants in water via ultraviolet(UV)-based advanced oxidation processes(AOPs)is strongly dependent on the water *** reactive radicals(rrs)formed in UV-AOPs have different reaction selectivities toward water matrices and degradation efficiencies for target ***,process selection and optimization are *** study developed a facilitated prediction method for the photon fluence-based rate constant for micropollutant degradation(K′_(p,MP))in various UV-AOPs by combining model simulation with portable *** methods for measuring the scavenging capacities of the principal rrs(rrSCs)involved in UV-AOPs(i.e.,HO^(·),SO_(4)^(·-),and Cl^(·))using a mini-fluidic photoreaction system were *** simulation models consisted of photochemical,quantitative structure–activity relationship,and radical concentration steady-state approximation *** rrSCs were determined in eight test waters,and a higher rrSC was found to be associated with a more complex water ***,by taking sulfamethazine,caffeine,and carbamazepine as model micropollutants,the k′_(p,MP) values in various UV-AOPs were predicted and further verified experimentally.A lower k′_(p,MP) was found to be associated with a higher rrSC for a stronger rr competition;for example,k′_(p,MP) values of 130.9 and 332.5 m^(2) einstein^(–1),respectively,were obtained for carbamazepine degradation by UV/H_(2)O_(2) in the raw water(rrSC=9.47×10^(4) s^(-1))and sand-filtered effluent(rrSC=2.87×10^(4) s^(-1))of a drinking water treatment *** developed method facilitates process selection and optimization for UV-AOPs,which is essential for increasing the efficiency and cost-effectiveness of water treatment.

关键词： UV-AOPs Micropollutant degradation reactive radicals Water matrix Model simulation

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ranking environmental and edaphic attributes driving soil microbial community structure and activity with special attention to spatial and temporal scales

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mLife 2024年第1期3卷 21-41页

作者： Vadakattu V.S.r.Gupta james M.Tiedje CSIrO Agriculture&Food UrrbraeSouth AustraliaAustralia Centre for Microbial Ecology Michigan State UniversityEast LansingMichiganUSA

The incredibly complex soil microbial communities at small scales make their analysis and identification of reasons for the observed structures *** community structure is mainly a result of the inoculum(dispersal),the selective advantages of those organisms under the habitat-based environmental attributes,and the ability of those colonizers to sustain themselves over *** soil is protective,and its microbial inhabitants have long adapted to varied soil conditions,significant portions of the soil microbial community structure are likely ***,a substantial portion of the community will not correlate to often measured soil *** suggest that the drivers be ranked on the basis of their importance to the fundamental needs of the microbes:(i)those that supply energy,i.e.,organic carbon and electron acceptors;(i)environmental effectors or stressors,i.e.,pH,salt,drought,and toxic chemicals;(ii)macro-organism associations,i.e.,plants and their seasonality,animals and their fecal matter,and soil fauna;and(iv)nutrients,in order,N,P,and probably of lesser importance,other micronutrients,and *** relevance of drivers also varies with spatial and time scales,for example,aggregate to field to regional,and persistent to dynamic populations to transcripts,and with the extent of phylogenetic difference,hence phenotypic differences in organismal *** present a summary matrix to provide guidance on which drivers are important for particular studies,with special emphasis on a wide range of spatial and temporal scales,and illustrate this with genomic and population(rrNA gene)data from selected studies.

关键词： abundance community structure diversity functional microbiome microorganisms

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Time-Aware LSTM Neural Networks for Dynamic Personalized recommendation on Business Intelligence

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Tsinghua Science and Technology 2024年第1期29卷 185-196页

作者： Xuan Yang james A.Esquivel Graduate School Angeles University FoundationAngeles City 2009Philippines Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 262700China

Personalized recommendation plays a critical role in providing decision-making support for product and service analysis in the field of business ***,deep neural network-based sequential recommendation models gained considerable ***,existing approaches pay litle attention to users'dynamically evolving interests,which are influenced by product attributes,especially product *** overcome these challenges,we propose a dynamic personalized recommendation model:***,we first embed product information and attribute information into a unified data ***,we exploit long short-term memory(LsTM)networks to characterize sequential behavior over multiple time periods and seize evolving interests by hierarchical LSTM ***,similarity values between users are measured through pairwise interest features,and personalized recommendation lists are generated.A series of experiments reveal the superiority of the proposed method compared withotheradvanced methods.

关键词： personalized recommendations evolving interests embedding LsTM networks

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Probing turbulence in galaxies with fast radio burst scintillation

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Science China(Physics,Mechanics & Astronomy) 2024年第1期67卷 177-178页

作者： james M.Cordes Department of Astronomy the Cornell Center for Astrophysics and Planetary ScienceCornell UniversityIthaca NY 14853USA

Interstellar scintillation(ISS)is a well-known phenomenon observed from pulsars in the Milky *** comprises intensity variations *** and frequency caused by constructive and destructive interference from multipath propagation,which is due to diffraction from fluctuations in electron density in the interstellar medium(ISM)on scales as small as~100 *** density fluctuations appear to be part of a turbulence process combined with discrete structures in electron density from other astrophysical processes;together these fluctuations extend to scales of pc or larger.

关键词： scales galaxies turbulence

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LSTM Network-Based Adaptation Approach for Dynamic Integration in Intelligent End-Edge-Cloud Systems

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Tsinghua Science and Technology 2024年第4期29卷 1219-1231页

作者： Xuan Yang james A.Esquivel Graduate School Angeles University FoundationAngeles City 2009Philippinesand also with Shandong Provincial University Laboratory for Protected HorticultureWeifang University of Science and TechnologyWeifang 262700China Graduate School Angeles University FoundationAngeles City 2009Philippines

Edge computing, which migrates compute-intensive tasks to run on the storage resources of edge devices, efficiently reduces data transmission loss and protects data privacy. However, due to limited computing resources and storage capacity, edge devices fail to support real-time streaming data query and processing. To address this challenge, first, we propose a Long Short-Term Memory (LSTM) network-based adaptive approach in the intelligent end-edge-cloud system. Specifically, we maximize the Quality of Experience (QoE) of users by automatically adapting their resource requirements to the storage capacity of edge devices through an event mechanism. Second, to reduce the uncertainty and non-complete adaption of the edge device towards the user’s requirements, we use the LSTM network to analyze the storage capacity of the edge device in real time. Finally, the storage features of the edge devices are aggregated to the cloud to re-evaluate the comprehensive capability of the edge devices and ensure the fast response of the user devices during the dynamic adaptation matching process. A series of experimental results show that the proposed approach has superior performance compared with traditional centralized and matrix decomposition based approaches.

关键词： quality of experience data query end-edge-cloud Long Short-Term Memory(LSTM)networks

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Analysis of the Oscillatory Flows of Multiple Shock Waves in a Constant Area Duct

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Journal of Thermal Science 2024年第3期33卷 794-806页

作者： K james Jintu KIM Heuy Dong Department of Mechanical Engineering Andong National UniversityAndong36729Republic of Korea CAD-IT Korea Co. Ltd.Seoul08591Republic of Korea

The oscillatory response of multiple shock waves to downstream perturbations in a supersonic flow is studied numerically in a rectangular *** shock waves are formed inside the duct at a shock Mach number of *** duct has an exit height of H,and the effect of duct resonance on multiple shock oscillations is investigated by attaching exit ducts of lengths 0H,50H,and *** downstream disturbance frequency varied from 10 Hz to 200 Hz to explore the oscillation characteristics of the multiple shock *** oscillatory response of shock waves under self-excited and forced oscillation conditions are analyzed in terms of wall static pressure,shock train leading-edge location,shock train length,and the size of the separation *** extent of the initial shock location increases with an increase in exit duct length for the self-excited oscillation *** analysis of the shock train leading edge and the spectral analysis of wall static pressure variations are *** variation in the shock train length is analyzed using the pressure ratio method for self-excited as well as forced *** rMS amplitude of the normalized shock train length(ζ_(ST))increases with an increase in the exit duct length for the self-excited oscillation *** the downstream perturbation frequency is increased,ζ_(ST)is decreased for exit duct *** all exit duct designs and downstream forcing frequencies,the size of the separation bubble grows and shrinks during the shock oscillations,demonstrating the dependence on duct resonance and forced oscillations.

关键词： shock train downstream disturbance supersonic flow shock wave boundary layer interaction duct resonance flow separation

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risk factors for hepatocellular carcinoma associated with hepatitis C genotype 3 infection:A systematic review

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World Journal of Gastrointestinal Oncology 2024年第4期16卷 1596-1612页

作者： Hamzah Z Farooq Michael james Jane Abbott Patrick Oyibo Pip Divall Naheed Choudhry Graham r Foster Blizard Institute Queen Mary University of LondonLondon E12ATUnited Kingdom School of Health and Psychological Sciences University of LondonLondon EC1V 0HBUnited Kingdom University Hospitals of Leicester Library University Hospitals of Leicester NHS TrustLeicester LE39QPUnited Kingdom

BACKGrOUND Hepatitis C virus(HCV)is a blood-borne virus which globally affects around 79 million people and is associated with high morbidity and *** infection leads to cirrhosis in a large proportion of patients and often causes hepatocellular carcinoma(HCC)in people with *** the 6 HCV genotypes(G1-G6),genotype-3 accounts for 17.9%of *** genotype-3 responds least well to directly-acting antivirals and patients with genotype-3 infection are at increased risk of HCC even if they do not have *** To systematically review and critically appraise all risk factors for HCC secondary to HCV-G3 in all ***,we studied possible risk factors for HCC due to HCV-G3 in the literature from 1946 to *** This systematic review aimed to synthesise existing and published studies of risk factors for HCC secondary to HCV genotype-3 and evaluate their strengths and *** searched Web of Science,Medline,EMBASE,and CENTrAL for publications reporting risk factors for HCC due to HCV genotype-3 in all settings,*** Four thousand one hundred and forty-four records were identified from the four databases with 260 records removed as *** thousand eight hundred and eighty-four records were screened with 3514 *** hundred and seventy-one full-texts were assessed for eligibility with seven studies included for *** the seven studies,three studies were retrospective case-control trials,two retrospective cohort studies,one a prospective cohort study and one a cross-sectional study *** were based in hospital settings with four in Pakistan,two in South Korea and one in the United *** total number of participants were 9621 of which 167 developed HCC(1.7%).All seven studies found cirrhosis to be a risk factor for HCC secondary to HCV genotype-3 followed by higher age(five-studies),with two studies each showing male sex,high alpha feto-protein,directly-acting antivirals trea

关键词： Hepatocellular carcinoma Hepatitis C Genotype 3 Systematic review Blood-borne viruses Liver cancer

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Event-triggered sliding mode control of linear repetitive processes and its application in metal rolling process

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Science China(Information Sciences) 2024年第3期67卷 167-181页

作者： Xinyu LV Yugang NIU james LAM Key Laboratory of Smart Manufacturing in Energy Chemical Process (East China University of Science and Technology) Ministry of Education Department of Mechanical Engineering The University of Hong Kong

This paper investigates the design problem of a sliding mode controller for linear repetitive processes(LrPs) with a finite pass length on each pass. Under limited communication resources, an eventtriggered mechanism is implemented from the sensors to the controller, whose triggered sequence is consistent with the evolution direction of LrPs. To periodically orchestrate communication between the controller and actuator, a round-robin scheduling mechanism is established based on the pass length. A sliding function involving the state and pass profile is constructed, and the sliding mode controller is designed using triggered states and pass profile signals. Feasible controller gains are attained to ensure the stability of the resultant closed-loop system. Finally, the proposed strategy is implemented for a multi-roll metal rolling process.

关键词： event-triggered mechanism linear repetitive processes metal rolling process round-robin scheduling sliding mode control

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Learning physically based material and lighting decompositions for face editing

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Computational Visual Media 2024年第2期10卷 295-308页

作者： Qian Zhang Vikas Thamizharasan james Tompkin Brown University ProvidenceRhode Island 02906USA

Lighting is crucial for portrait photography,yet the complex interactions between the skin and incident light are expensive to model computationally in graphics and difficult to reconstruct analytically via computer ***,to allow fast and controllable reflectance and lighting editing,we developed a physically based decomposition through deep learned priors from path-traced portrait *** approaches that used simplified material models or low-frequency or low-dynamic-range lighting struggled to model specular reflections or relight directly without intermediate ***,we estimate the surface normal,skin albedo and roughness,and high-frequency HDrI maps,and propose an architecture to estimate both diffuse and specular reflectance *** our experiments,we show that this approach can represent the true appearance function more effectively than simpler baseline methods,leading to better generalization and higher-quality editing.

关键词： intrinsic decomposition portrait relighting inverse rendering deep learning

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