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Remote estimates of suspended particulate matter in global lakes using machine learning models

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International Soil and Water Conservation Research 2024年第1期12卷 200-216页

作者： Zhidan Wen Qiang wang Yue Ma Pierre Andre Jacinthe Ge Liu Sijia Li Yingxin Shang hui Tao Chong fang Lili Lyu Baohua Zhang Kaishan Song Northeast Institute of Geography and Agroecology CASChangchunJilin130102China Department of Geology Indiana University∼Purdue UniversityIndianapolisIN44602USA University of Chinese Academy of Sciences Beijing100100China College of Geography and Urban Planning Liaocheng UniversityLiaochengChina

Suspended particulate matter(SPM)in lakes exerts strong impact on light propagation,aquatic ecosystem productivity,which co-varies with nutrients,heavy metal and micro-pollutant in *** lakes,SPM exerts strong absorption and backscattering,ultimately affects water leaving signals that can be detected by satellite *** regression models based on specific band or hand ratios have been widely used for SPM estimate in the past with moderate *** are still rooms for model accuracy improvements,and machine learning models may solve the non-linear relationships between spectral variable and SPM in *** assembled more than 16,400 in situ measured SPM in lakes from six continents(excluding the Antarctica continent),of which 9640 samples were matched with Landsat overpasses within±7 *** machine learning algorithms and two simple regression methods(linear and partial least squares models)were used to estimate SPM in lakes and the performance were *** overcome the problem of imbalance datasets in regression,a Synthetic Minority Over-Sampling technique for regression with Gaussian Noise(SMOGN)was adopted in this *** comparison,we found that gradient boosting decision tree(GBDT),random forest(RF),and extreme gradient boosting(XGBoost)models demonstrated good spatiotemporal transferability with SMOGN processed dataset,and has potential to map SPM at different year with good quality of Landsat land surface reflectance *** all the tested modeling approaches,the GBDT model has accurate calibration(n=6428,R^(2)=0.95,MAPE=29.8%)from SPM collected in 2235 lakes across the world,and the validation(n=3214,R^(2)=0.84,MAPE=38.8%)also exhibited stable ***,the good performances were also exhibited by RF model with calibration(R^(2)=0.93)and validation(R^(2)=0.86,MAPE=24.2%)*** applied GBDT and RF models to map SPM of typical lakes,and satisfactory result was *** addition,the GBDT model was evaluated b

关键词： Landsat imagery Remote estimation SPM Transferability

Artificial intelligence for the detection of glaucoma with SD-OCT images:a systematic review and Meta-analysis

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International Journal of Ophthalmology(English edition) 2024年第3期17卷 408-419页

作者： Nan-Nan Shi Jing Li Guang-hui Liu Ming-fang Cao Department of Ophthalmology Affiliated People’s Hospital(Fujian Provincial People’s Hospital)Fujian University of Traditional Chinese MedicineFuzhou 350004Fujian ProvinceChina Eye Institute of Integrated Chinese and Western Medicine Fujian University of Traditional Chinese MedicineFuzhou 350004Fujian ProvinceChina

●AIM:To quantify the performance of artificial intelligence(AI)in detecting glaucoma with spectral-domain optical coherence tomography(SD-OCT)images.●METHODS:Electronic databases including PubMed,Embase,Scopus,ScienceDirect,ProQuest and Cochrane Library were searched before May 31,2023 which adopted AI for glaucoma detection with SD-OCT *** pieces of the literature were screened and extracted by two ***-analysis,Meta-regression,subgroup,and publication of bias were conducted by *** risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool.●RESULTS:Twenty studies and 51 models were selected for systematic review and *** pooled sensitivity and specificity were 0.91(95%CI:0.86–0.94,I2=94.67%),0.90(95%CI:0.87–0.92,I2=89.24%).The pooled positive likelihood ratio(PLR)and negative likelihood ratio(NLR)were 8.79(95%CI:6.93–11.15,I2=89.31%)and 0.11(95%CI:0.07–0.16,I2=95.25%).The pooled diagnostic odds ratio(DOR)and area under curve(AUC)were 83.58(95%CI:47.15–148.15,I2=100%)and 0.95(95%CI:0.93–0.97).There was no threshold effect(Spearman correlation coefficient=0.22,P>0.05).●CONCLUSION:There is a high accuracy for the detection of glaucoma with AI with SD-OCT *** application of AI-based algorithms allows together with“doctor+artificial intelligence”to improve the diagnosis of glaucoma.

关键词： artificial intelligence spectral-domain optical coherence tomography glaucoma Meta-analysis

Effects of acid-rock reaction on physical properties during CO_(2)-rich industrial waste gas(CO_(2)-rich IWG)injection in shale reservoirs

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Petroleum Science 2024年第1期21卷 272-285页

作者： Yi-Fan wang Jing wang hui-Qing Liu Xiao-Cong Lv Ze-Min Ji National Key Laboratory of Petroleum Resources and Engineering China University of PetroleumBeijing102249China MOE Key Laboratory of Petroleum Engineering China University of PetroleumBeijing102249China Research Institute of Exploration and Development PetroChinaBeijing100083China

"Carbon peaking and carbon neutrality"is an essential national strategy,and the geological storage and utilization of CO_(2)is a hot issue ***,due to the scarcity of pure CO_(2)gas sources in China and the high cost of CO_(2)capture,CO_(2)-rich industrial waste gas(CO_(2)-rich IWG)is gradually emerging into the public's ***_(2)has good adsorption properties on shale surfaces,but acidic gases can react with shale,so the mechanism of the CO_(2)-rich IWG-water-shale reaction and the change in reservoir properties will determine the stability of geological ***,based on the mineral composition of the Longmaxi Formation shale,this study constructs a thermodynamic equilibrium model of water-rock reactions and simulates the regularity of reactions between CO_(2)-rich IWG and shale *** results indicate that CO_(2)consumed 12%after reaction,and impurity gases in the CO_(2)-rich IWG can be dissolved entirely,thus demonstrating the feasibility of treating IWG through water-rock *** IWG inhibits the dissolution of CO_(2),the optimal composition of CO_(2)-rich IWG is 95%CO_(2)and 5%IWG when CO_(2)geological storage is the main *** contrast,when the main goal is the geological storage of total CO_(2)-rich IWG or impurity gas,the optimal CO_(2)-rich IWG composition is 50%CO_(2)and 50%*** the CO_(2)-rich IWG-water-shale reaction,temperature has less influence on the water-rock reaction,while pressure is the most important ***2 has the greatest impact on water-rock reaction in *** minerals,clay minerals such as illite and montmorillonite had a significant effect on water-rock *** overall reaction is dominated by precipitation and the volume of the rock skeleton has increased by 0.74 cm3,resulting in a decrease in shale porosity,which enhances the stability of CO_(2)geological storage to some *** the reaction between CO_(2)-rich IWG-water-shale at simulated temperatures and pressures,precipitation

关键词： CO_(2)-rich industrial waste gas Geological storage Acid-rock reaction Shale Geochemical modelling

Multi-scale data joint inversion of minerals and porosity in altered igneous reservoirs—A case study in the South China Sea

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Petroleum Science 2024年第1期21卷 206-220页

作者： Xin-Ru wang Bao-Zhi Pan Yu-Hang Guo Qing-hui wang Yao Guan College of Geo-exploration Science and Technology Jilin UniversityChangchun130046JilinChina Research Institute CNOOC Ltd.-ShenzhenShenzhen518000GuangdongChina

There are abundant igneous gas reservoirs in the South China Sea with significant value of research,and lithology classification,mineral analysis and porosity inversion are important links in reservoir ***,affected by the diverse lithology,complicated mineral and widespread alteration,conventional logging lithology classification and mineral inversion become considerably *** the same time,owing to the limitation of the wireline log response equation,the quantity and accuracy of minerals can hardly meet the exploration requirements of igneous *** overcome those issues,this study takes the South China Sea as an example,and combines multi-scale data such as micro rock slices,petrophysical experiments,wireline log and element cutting log to establish a set of joint inversion methods for minerals and porosity of altered igneous ***,we define the lithology and mineral characteristics through core slices and mineral data,and establish an igneous multi-mineral volumetric *** we determine element cutting log correction method based on core element data,and combine wireline log and corrected element cutting log to perform the lithology classification and joint inversion of minerals and ***,it is always difficult to determine the elemental eigenvalues of different minerals in *** paper uses multiple linear regression methods to solve this ***,an integrated inversion technique for altered igneous formations was *** results show that the corrected element cutting log are in good agreement with the core element data,and the mineral and porosity results obtained from the joint inversion based on the wireline log and corrected element cutting log are also in good agreement with the core data from X-ray *** results demonstrate that the inversion technique is applicable and this study provides a new direction for the mineral inversion research of altered igneous formation

关键词： Joint inversion Altered igneous rock Element correction method Lithology identification Multi mineral volume model

Achievement of a high-performance 30-tesla metal-as-insulated user superconducting magnet

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Science China(Technological Sciences) 2024年第6期67卷 1974-1978页

作者： ZHOU BenZhe DAI YinMing ZHANG ZiLi LIU hui wang Yaohui wang Lei wang hui CHEN ShunZhong wang KangShuai CHEN Yong LIU JianHua wang QiuLiang Institute of Electrical Engineering Chinese Academy of Sciences University of Chinese Academy of Sciences

Strong magnetic fields can be used to manipulate the states of matter and induce unique ***,they enable a thorough investigation of the intrinsic properties of matter through the application of the nuclear magnetic resonance(NMR)*** versatile nature of strong magnetic fields facilitates the discovery of novel phenomena and patterns.

关键词： effect NMR versatile

Knockout of C6orf120 in Rats Alleviates Concanavalin A-induced Autoimmune Hepatitis by Regulating Macrophage Polarization

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Biomedical and Environmental Sciences 2024年第6期37卷 594-606页

作者： Xin wang Yuqi wang hui Liu Yingying Lin Peng wang Yunyun Yi Xin Li Department of Center of Integrated Traditional Chinese and Western Medicine Peking University Ditan Teaching HospitalBeijing 100015China Department of Center of Integrated Traditional Chinese and Western Medicine Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China Department of Center of Infectious Disease Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China

Objective The effect of the functionally unknown gene C6orf120 on autoimmune hepatitis was investigated on C6orf120 knockout rats(C6orf120^(-/-))and THP-1 *** Six–eight-week-old C6orf120^(-/-)and wild-type(WT)SD rats were injected with Con A(16 mg/kg),and euthanized after 24 *** sera,livers,and spleens were ***-1 cells and the recombinant protein(rC6ORF120)were used to explore the mechanism in *** frequency of M1 and M2 macrophages was analyzed using flow *** blotting and PCR were used to detect macrophage polarization-associated *** C6orf120 knockout attenuated Con A-induced autoimmune *** cytometry indicated that the proportion of CD68^(+)CD86^(+)M1 macrophages from the liver and spleen in the C6orf120^(-/-)rats decreased.C6orf120 knockout induced downregulation of CD86 protein and the mRNA levels of related inflammatory factors TNF-α,IL-1β,and IL-6 in the liver.C6orf120 knockout did not affect the polarization of THP-1 ***,rC6ORF120 promoted the THP-1 cells toward CD68^(+)CD80^(+)M1 macrophages and inhibited the CD68^(+)CD206^(+)M2 *** C6orf120 knockout alleviates Con A-induced autoimmune hepatitis by inhibiting macrophage polarization toward M1 macrophages and reducing the expression of related inflammatory factors in C6orf120^(-/-)rats.

关键词： C6orf120 Autoimmune hepatitis Macrophage polarization M1 macrophages

Surface chemical microenvironment engineering of catalysts by organic molecules for boosting electrocatalytic reaction

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Chinese Chemical Letters 2024年第8期35卷 15-24页

作者： Xianxu Chu Lu wang Junru Li hui Xu Henan Key Laboratory of Biomolecular Recognition and Sensing College of Chemistry and Chemical EngineeringShangqiu Normal UniversityShangqiu 476000China Key Laboratory of Advanced Catalytic Materials and Technology Advanced Catalysis and Green Manufacturing Collaborative Innovation CenterChangzhou UniversityChangzhou 213164China

Electrocatalysis is a surface-sensitive process,in which the catalytic activity of electrocatalyst highly re-lates to the surface adsorption/desorption behaviors of the reactants/intermediates/products on the cat-alytically active *** chemical microenvironment engineering via organic molecules functional-ization is a promising strategy to tune the electrocatalytic activity since it can well modify the elec-trode/electrolyte interface and alter the reaction *** this review,we summarize the recent progress of surface microenvironment engineering of electrocatalysts induced by organic molecules func-tionalization,with the special focus on the organic molecule-assisted growth mechanism and unique electronic *** importantly,the applications of organic molecule functionalized catalysts in var-ious electrocatalytic reactions are also systematically summarized,along with a deep discussion on the conclusion and *** work will open a new avenue for the construction and modification of advanced electrocatalysts based on organic molecule-mediated interface engineering.

关键词： Chemical microenvironment engineering Organic molecules Electrocatalysis Functionalization Interface

Statistical QoS Provisioning Architecture for 6G Satellite-Terrestrial Integrated Networks

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Journal of Communications and Information Networks 2024年第1期9卷 34-42页

作者： Jingqing wang Wenchi Cheng Wei Zhang hui Liang School of Telecommunications Engineering Xidian UniversityXi’an 710071China School of Electrical Engineering and Telecommunications the University of New South WalesSydneyAustralia School of Electrical Engineering and Intelligentization Dongguan University of TechnologyDongguan 523808China Peng Cheng Laboratory Shenzhen 518055China.

The emergence of massive ultra-reliable and low latency communications (mURLLC) as a category of age/time/reliability-sensitive service over 6G wireless networks has received considerable research attention, which has presented unprecedented challenges. As one of the key enablers for 6G,satellite-terrestrial integrated networks (STIN) have been developed to offer more expansive connectivity and comprehensive 3D coverage in space-aerial-terrestrial domains for supporting 6G mission-critical mURLLC applications while fulfilling diverse and rigorous quality of service (QoS) requirements. In the context of these mURLLC-driven satellite services, data freshness assumes paramount importance, as outdated data may engender unpredictable or catastrophic *** effectively measure data freshness in satellite-terrestrial integrated communications,age of information(AoI)has recently surfaced as a new dimension of QoS metric to support time-sensitive applications. It is crucial to design new analytical models that ensure stringent and diverse QoS metrics bounded by different key parameters,including AoI,delay,and reliability,over 6G satellite-terrestrial integrated networks. However,due to the complicated and dynamic nature of satellite-terrestrial integrated network environments, the research on efficiently defining new statistical QoS provisioning schemes while taking into account varying degrees of freedom has still been in their infancy. To remedy these deficiencies, in this paper we develop statistical QoS provisioning schemes over 6G satellite-terrestrial integrated networks in the finite blocklength regime. Particularly, we firstly introduce and review key technologies for supporting ***,we formulate a number of novel fundamental statistical-QoS metrics in the finite blocklength ***,we conduct a set of simulations to validate and evaluate our developed statistical QoS provisioning schemes over satellite-terrestrial integrated networks.

关键词： statistical QoS provisioning mURLLC peak AoI satellite-terrestrial integrated networks QoS exponents hybrid automatic repeat request finite blocklength coding

Spatial Distribution Feature Extraction Network for Open Set Recognition of Electromagnetic Signal

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 279-296页

作者： hui Zhang Huaji Zhou Li wang Feng Zhou The Ministry Key Laboratory of Electronic Information Countermeasure and Simulation Xidian UniversityXi’an710071China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033China

This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction Network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution feature extraction layer in SDFEN replaces convolutional output neural networks with the spatial distribution features that focus more on inter-sample information by incorporating class center *** designed hybrid loss function considers both intra-class distance and inter-class distance,thereby enhancing the similarity among samples of the same class and increasing the dissimilarity between samples of different classes during ***,this method allows unknown classes to occupy a larger space in the feature *** reduces the possibility of overlap with known class samples and makes the boundaries between known and unknown samples more ***,the feature comparator threshold can be used to reject unknown *** signal open set recognition,seven methods,including the proposed method,are applied to two kinds of electromagnetic signal data:modulation signal and real-world *** experimental results demonstrate that the proposed method outperforms the other six methods overall in a simulated open ***,compared to the state-of-the-art Openmax method,the novel method achieves up to 8.87%and 5.25%higher micro-F-measures,respectively.

关键词： Electromagnetic signal recognition deep learning feature extraction open set recognition