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Biological sources, paleoenvironment, and organic matter enrichment in source rocks of the Ordovician Majiagou Formation, Ordos Basin, China:Evidence from biomarkers,microfossils, and inorganic geochemical analyses

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Journal of Palaeogeography 2024年第1期13卷 92-115页

作者： jing-jing cao Wen-Zhe Gang Shang-Ru Yang State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Bejing)Beijing 102249China College of Geosciences China University of Petroleum(Bejing)Beijing 102249China Oil and Gas Technology Research Institute PetroChina Changqing Oifield CompanyXi'an 710018Shaanxi ProvinceChina

Carbonate deposits in the Ordovivian Majiagou Formation are significant source rocks for natural gas generation in the Ordos Basin, northwestern China. Previous studies mainly focused on the organic matter enrichment mechanism of shales rather than carbonate rocks. The biological sources and paleoenvironment of carbonate source rocks, and the main controlling factors of organic matter enrichment in the carbonate source rocks were studied in this paper in combination with evidence from biomarkers, microfossils and inorganic geochemistry analysis. The results show that four types of microfacies were identified in the Majiagou Formation, respectively as: mud flat microfacies, mud-dolomite flat microfacies, dolomite flat microfacies, and open marine microfacies. The biological sources of organic matter are chiefly planktonic algae, followed by bacteria. The mud flat and mud-dolomite flat contain a high abundance of terrigenous detrital inputs, as indicated by the high content of Al_(2)O_(3), TiO_(2), Th, and Zr. The low Sr/Cu and high Rb/Sr values reveal warm and humid paleoclimate conditions in the mud flat and mud-dolomite flat, whereas the dolomite flat and open marine were likely formed in hot and arid paleoclimate conditions. The mud flat and mud-dolomite flat deposits were characterized by high paleoproductivity of the Majiagou Formation. Low Sr/Ba values were found in the mud flat samples, indicating fresh to brackish water condition, whereas samples of other facies have a relatively high degree of salinity. Based on U_(auth), Mo_(auth), Cr_(auth), Co_(auth), δCe, and δEu values, the mud flat microfacies was formed in a suboxic and anoxic environment, whereas the mud-dolomite flat, dolomite flat and open marine microfacies were within dysoxic to oxic conditions. A model of organic matter enrichment in the Majiagou Formation is thus established. The level of terrigenous detrital inputs is the principal factor of organic matter enrichment in the Majiagou Formation, secondly are redox condition and then paleoprod

关键词： Biological source Microfacies Trace elements Organic matter Majiagou Formation Ordos Basin

A Robust Framework for Multimodal Sentiment Analysis with Noisy Labels Generated from Distributed Data Annotation

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2965-2984页

作者： Kai Jiang Bin cao jing Fan School of Computer Science and Technology Zhejiang University of TechnologyHangzhou310023China

Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.

关键词： Distributed data collection multimodal sentiment analysis meta learning learn with noisy labels

Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1643-1655页

作者： Meng Zhou Zihao Wang jing Wang Zhengcai cao the School of Electrical and Control Engineering North China University of TechnologyBeijing 100144China IEEE the College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China

This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.

关键词： Dynamic obstacle avoidance multi-robot collaborative hunting obstacle-avoiding Voronoi cells task allocation

PURP: A Scalable System for Predicting Short-Term Urban TrafficFlow Based on License Plate Recognition Data

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Big Data Mining and Analytics 2024年第1期7卷 171-187页

作者： Shan Zhang Qinkai Jiang Hao Li Bin cao jing Fan School of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310000China

Accurate and efficient urban traffic flow prediction can help drivers identify road traffic conditions in real-time,consequently helping them avoid congestion and accidents to a certain extent.However,the existing methods for real-time urban traffic flow prediction focus on improving the model prediction accuracy or efficiency while ignoring the training efficiency,which results in a prediction system that lacks the scalability to integrate real-time traffic flow into the training procedure.To conduct accurate and real-time urban traffic flow prediction while considering the latest historical data and avoiding time-consuming online retraining,herein,we propose a scalable system for Predicting short-term URban traffic flow in real-time based on license Plate recognition data(PURP).First,to ensure prediction accuracy,PURP constructs the spatio-temporal contexts of traffic flow prediction from License Plate Recognition(LPR)data as effective characteristics.Subsequently,to utilize the recent data without retraining the model online,PURP uses the nonparametric method k-Nearest Neighbor(namely KNN)as the prediction framework because the KNN can efficiently identify the top-k most similar spatio-temporal contexts and make predictions based on these contexts without time-consuming model retraining online.The experimental results show that PURP retains strong prediction efficiency as the prediction period increases.

关键词： traffic flow prediction k-Nearest Neighbor(KNN) License Plate Recognition(LPR)data spatio-temporalcontext

Sustainable production of high-energy-density jet fuel via cycloaddition reactions

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Journal of Energy Chemistry 2024年第8期95卷 712-722页

作者： Yan-Cheng Hu Yingying Zhao Ning Li jing-Pei cao School of Chemical Engineering and Technology China University of Mining and Technology School of Education Science Jiangsu Normal University CAS Key Laboratory of Science and Technology on Applied Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences

Developing an energy supply-chain based on renewable biomass holds great potential to build a low carbon society. High-energy-density(HED) jet fuel, featuring unique fused/strained cycloalkanes, is of great significance for volume-limited military aircrafts, as their high density and combustion heat can extend flight duration and increase the payload. Therefore, the exploration of biomass-based routes towards HED fuel has drawn much attention over the past decade. Cycloaddition reaction features rapid construction of various carbocycles in an atom-and step-economical fashion. This elegant strategy has been widely applied in the manufacture of sustainable HED fuel. Here we carefully summarize the progress achieved in this fascinating area and the review is categorized by the cycloaddition patterns including [4+2], [2+2],[4+4], and [2+1] cycloadditions. Besides, the energy densities of the as-prepared biofuels and petroleumbased fuels(conventional Jet-A and advanced JP-10) are also compared. This review will provide important insights into rational design of new HED fuel with different ring-types/sizes and inspire the chemists to turn those literature studies into practical applications in military field.

关键词： Biomass-based chemicals Catalysis Cycloaddition Cycloalkanes High-energy-density fuel

Efficient construction of calcium fluoride nanoaggregates for enhanced water vapor adsorption

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Particuology 2024年第6期89卷 191-197页

作者： Dan-Lei Yang jing cao Rong-Kun Liu Jie-Xin Wang School of Life Sciences and Chemical Engineering Jiangsu Second Normal UniversityNanjing210013China State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029China Research Center of the Ministry of Education for High Gravity Engineering and Technology Beijing University of Chemical TechnologyBeijing100029China Petrochemical Research Institute PetroChinaBeijing102206China

Calcium fluoride(CaF_(2))is an ideal adsorbent for the dehydration of gaseous hydrogen fluoride(HF)containing water vapor.In this work,a novel CaF_(2)absorbent,spherical CaF_(2)nanoaggregates(NAs)with a closely packed structure,was proposed and efficiently fabricated by spray drying technology.As the building blocks of CaF_(2)NAs,the CaF_(2)nanoparticles(NPs)were prepared by the addition of excess calcium ions(Ca^(2+))or fluorine ions(F−)in the synthesis.The results indicated that the CaF_(2)NPs synthesized by excess Ca^(2+)and the corresponding NAs exhibited much better water vapor adsorption properties than their counterparts by excess F−,owing to higher zeta potentials.More importantly,whether excess Ca^(2+)or F^(−),CaF_(2)NAs had further enhanced water vapor adsorption capacity compared to primary CaF_(2)NPs,possibly owing to their unique nano-micro secondary structures and higher surface areas.This work has great potential in the development of high-performance absorbents for separating moisture from corrosive gas HF.

关键词： CaF_(2)nanoaggregates Water vapor adsorption Spray drying

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 images.All pieces of the literature were screened and extracted by two investigators.Meta-analysis,Meta-regression,subgroup,and publication of bias were conducted by Stata16.0.The 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 Meta-analysis.The 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 images.The 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

Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

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Tsinghua Science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang cao Peiyu Guan Fengshui jing Min Tan Junzhi Yu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot manipulation.Mainstream pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and efficiency.However,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are neglected.It is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains unsolved.Meanwhile,the channel information in high-level feature is also not well mined.Inevitably,the performance of grasp detection is degraded.To solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle residual.Both low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature fusion.Such a hierarchical fusion guarantees the quality of grasp prediction.Furthermore,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective branches.By such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the network.Besides,an information enhancement module is added before the encoder to reinforce input information.The proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

Rare earth fluorescent nanoprobes with minimal side effects enable tumor microenvironment activation for chemotherapy

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Journal of Rare Earths 2024年第2期42卷 256-262,I0001页

作者： Tianqi cao Yuxin Liu Qi Jia Xiaolu Wang Shouqiang Zhang jing Zhou Department of Chemistry Capital Normal UniversityBeijing100048China

Chemotherapy,the use of antitumor drugs to kill cancer cells,is currently one of the most effective treatments for cancer.However,serious toxic side effects caused by long-term drug accumulation can cause significant damage to the body,which limits the clinical application of antitumor drugs.In this study,a novel RENPs@DOX-Fe nanoprobe(NP) was constructed by coating the surface of rare earth nanomaterials(NaLuF_(4):Yb,Er) with a complex formed by doxorubicin(DOX) and iron ion(Ⅲ).Due to the low toxicity of anthracycline-metal complexes,the damage to normal cells is reduced.The unique acidic microenvironment in tumor cells facilitates the decomposition and gradual release of DOX from the DOX-Fe complex.In addition,the DOX-Fe complex can convert near-infrared(NIR) light into heat energy,which promotes the decomposition of the complex,further enhancing the release of DOX in the tumor environment.The change of ratio fluorescence of rare earth nanomaterials at 660 and 1550 nm after DOX release enables visual monitoring of drug release,which can potentially improve the chemotherapeutic effect.In vitro experiments established that RENPs@DOX-Fe NPs with NIR illumination had good therapeutic efficacy in tumors.This work provides new insights into designing tumor microenvironment-responsive nanoprobes for chemotherapy with minimal side effects.

关键词： Rare earth nanoprobes Fluorescence Ratiometric imaging DOX Chemotherapy