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arXiv 2022年

作者： Jiang, Enhua Chen, Rujun Wu, Xinming Liu, Jianxin Zhu, Debin Pitiya, Regean Liu, Weiqiang Changsha410083 China Key Laboratory of Non-ferrous Resources and Geological Hazard Detection Central South University Changsha410083 China School of Geoscience and Info-physics Central South University South Lushan Road Changsha410083 China School of Earth and Space Sciences University of Science and Technology of China Hefei230026 China Chinese Academy of Geological Sciences Beijing100037 China

The main signals from the field sources of audio-magnetotellurics (AMT) sounding generated by global lightning activities are called sferics. In data analysis, the absence of long-term and high-amplitude natural field signals will result in a lack of energy in the AMT dead-band, which may cause unreliable impedance estimate. The collected data itself is redundant, and most of the data segments are non-signal segments containing noise. To achieve reliable AMT data interpretation, professional and rigorous preprocessing methods such as cropping or selection are required. In order to efficiently extract AMT main signals, we propose a deep convolutional neural network (CNN) to automatically recognize sferic signals from time series. We train the CNN by using field time series data with different signal to noise rations (S/Ns) that were acquired from different regions in mainland China. To solve the potential overfitting problem due to the limited number of sferic labels, we propose a training strategy that randomly generates training samples (with random data augmentations) while optimizing the CNN model parameters. We stop the process of training and data generation until the training loss converges. In addition, we use a weighted binary cross-entropy loss function to solve the sample imbalance problem to better optimize the network, use multiple reasonable metrics to evaluate network performance, and carry out ablation experiments to optimally choose the model hyperparameters. Extensive field data applications show that our trained CNN can robustly recognize sferic signals from noisy time series for subsequent impedance estimation. The computed results show that our method can significantly improve S/N and effectively solve the problem of lack of energy in AMT dead-band. We obtained a smoother and more reasonable apparent resistivity-phase curves and depolarized phase tensor in the dead-band. corrected the estimation error of sudden drop/abrupt change of high-frequenc

关键词： Magnetotellurics

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Development of colorimetric immunochromatographic assay based on different morphologies of gold nanoparticles for the detection of triadimefon

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Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy 2025年 343卷 126544页

作者： Dong, Sa Zhang, Yu Shi, Qiuyun Zhu, Zixin Wang, Yulong Luo, Ruifeng Feng, Jianguo College of Plant Protection Yangzhou University Jiangsu Yangzhou 225009 China Key Lab of Food Quality and Safety of Jiangsu Province-State Key Laboratory Breeding Base Key Laboratory of Control Technology and Standard for Agro-product Safety and Quality Ministry of Agriculture Institute of Food Safety and Nutrition Jiangsu Academy of Agricultural Sciences Jiangsu Nanjing 210014 China Food Quality Supervision and Testing Center of Ministry of Agriculture Xinjiang Academy of Agricultural and Reclamation Science Xinjiang Shihezi 832000 China

Triadimefon (TDF) is a highly effective, low toxicity, broad-spectrum triazole fungicide with strong systemic absorption. Excessive residues in tobacco and vegetables can affect human health. Therefore, it is urgent to establish a simple, rapid, and sensitive detection method for residual analysis of TDF in tobacco and vegetables. In this study, colloidal gold nanoparticles (Au NPs), gold nanoflowers (Au NFs), and gold nanorods (Au NRs) were synthesized and combined with anti-TDF monoclonal antibodies (mAb) to prepare probes for immunochromatographic strips (ICS). The lowest visual detection limits (vLODs) of the test strips using AuNPs-mAb, AuNFs-mAb, and AuNRs-mAb as probes were 7.8, 15.6, and 15.6 ng/mL, respectively. The three test strips showed no significant cross reactivity with the four structural analogues of tebuconazole, hexaconazole, myclobutanil, and difenoconazole, indicating that all three test strips have good specificity. To assess the presence of 0 and 62.5 ng/mL of TDF, ten test strips were used, and the results showed perfect accuracy with no false positives or false negatives. In addition, three test strips (same batch) were utilized to detect TDF (0 and 62.5 ng/mL) after storage for three months, and the results were still accurate, indicating that all three kinds of test strips have good repeatability and stability. The addition and recovery tests of TDF were conducted on cucumber and tobacco leaf samples (0, 2.5, 17.5, and 65 μg/kg), and the test results revealed that the strips performed with high accuracy. This study established three colorimetric test strips based on three different morphologies of gold nanoparticles, which possess the benefits of quick processing times, high cost-effectiveness, and minimal technical requirements, making them suitable for rapid on-site qualitative detection of TDF. © 2025 Elsevier B.V.

关键词： Gold nanoflowers Gold nanoparticles Gold nanorods Immunochromatographic strip Monoclonal antibody Triadimefon

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Effect of long-acting polyethylene glycol recombinant human growth hormone dosages in pediatric practice:A pooled analysis of two phase IV randomized controlled trials

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Chinese Medical Journal 2024年第17期137卷 2125-2127页

作者： Ling Hou Xuefeng Chen Hongwei Du Jianping Zhang Xinran Cheng Jiayan Pan Hui Pan Wei Liao Xiaoping Luo Junfen Fu on Behalf of the 045 Study Group Department of Pediatrics Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei 430030China Department of Endocrinology Children’s Hospital of Zhejiang University School of MedicineNational Clinical Research Center for Child HealthZhejiang University School of MedicineHangzhouZhejiang 310052China Department of Paediatrics First Hospital of Jilin UniversityChangchunJilin 130021China Department of Pediatrics Ningbo Women&Children’s HospitalNingboZhejiang 315012China Department of Pediatric Endocrine Genetics and Metabolism Chengdu Women’s and Children’s Center HospitalChengduSichuan 610074China Department of Pediatrics Wuhu First People’s HospitalWuhuAnhui 241000China Department of Endocrinology Key Laboratory of Endocrinology of National Health CommissionState Key Laboratory of Complex Severe and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Science and Peking Union Medical CollegeBeijing 100730China Department of Pediatrics The First Affiliated Hospital of Army Medical University(Third Military Medical University)Chongqing 400038China 不详

To the Editor:Growth hormone deficiency(GHD)impairs growth and development,affecting approximately 1 in 4000 children worldwide.[1]Recombinant human growth hormone(rhGH)has been standard practice since 1985.[2]However,compliance has been challenged by the need for frequent *** glycol rhGH(PEG-rhGH)was developed,improving protein stability and extending *** studies suggested that a weekly dosage of 0.20 mg/kg of PEG-rhGH offers improved growth rates and increased insulin-like growth factor-1 standard deviation score(IGF-1 SDS)without novel toxicities.[3]Here,we present a pooled analysis of two phase IV trials evaluating the efficacy and safety of various PEG-rhGH dosages in GHD.

关键词： dosage analysis glycol

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An atomic-scale investigation of structural transitions in ruthenium induced by x-ray free-electron lasers

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Journal of Applied Physics 2025年第20期137卷

作者： Hai, Xue Yin, Ya-Ru Tong, Ya-Jun Zhang, Xiao-Feng Wang, Han Zhang, Fei-Fei Wen, A-Li Ren, Cui-Lan Huai, Ping Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201800 China School of Nuclear Science and Technology University of Chinese Academy of Sciences Beijing100049 China Center for Transformative Science ShanghaiTech University Shanghai201210 China ShanghaiTech University Shanghai201210 China Key Laboratory of Thorium Energy Shanghai Institute of Applied Physics Chinese Academy of Science Shanghai201800 China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai201210 China

The surface thermodynamic properties of ruthenium (Ru) targets were systematically investigated under different laser energy fluences to elucidate the irradiation damage mechanisms of the grazing incidence mirror in x-ray free-electron laser (XFEL) facilities, by combining the two-temperature model and molecular dynamics method. Initially, the 50 nm Ru thin film was irradiated by a 20 fs laser pulse at an absorbed laser fluence of 40 mJ cm−2, and surface dynamic processes with rapid heating and homogeneous melting lasting picosecond-timescale were observed. However, the ultra-short laser-induced surface dynamic responses in 600 nm Ru thick film were lasting much longer time. With the increasing energy fluence of the laser pulse, the intensified irradiation effects characterized by the surface morphology changes were observed, followed by homogeneous melting of the Ru thick film. As the laser fluence approaches the damage threshold, an unconventional ablation effect was observed in the irradiated thick film, featuring the formation of point defects, voids, and subsequent nanometer-scale splitting in the front surface (approximately 5 nm). It indicates that, at laser fluences ranging from 20 to 320 mJ cm−2, the surface morphology undergoes expansion at angstrom to nanometer scales, accompanied by nanoscale splitting. The results provide valuable insights into the irradiation damage mechanism of the high-Z coating materials for x-ray optics in XFELs. © 2025 Author(s).

关键词： Point defects

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Neuroimaging epicenters as potential sites of onset of the neuroanatomical pathology in schizophrenia

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science Advances 2024年第24期10卷 eadk6063页

作者： Jiang, Yuchao Palaniyappan, Lena Luo, Cheng Chang, Xiao Zhang, Jie Tang, Yingying Zhang, Tianhong Li, Chunbo Zhou, Enpeng Yu, Xin Li, Wei An, Dongmei Zhou, Dong Huang, Chu-Chung Tsai, Shih-Jen Lin, Ching-Po Cheng, Jingliang Wang, Jijun Yao, Dezhong Cheng, Wei Feng, Jianfeng Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China Ministry of Education Shanghai China Douglas Mental Health University Institute Department of Psychiatry McGill University MontréalQC Canada Robarts Research Institute University of Western Ontario LondonON Canada Lawson Health Research Institute LondonON Canada Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of life Science and Technology University of Electronic Science and Technology of China Chengdu China High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province Center for Information in Medicine University of Electronic Science and Technology of China Chengdu China Chinese Academy of Medical Sciences Chengdu China Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine Shanghai200030 China Beijing China Department of Neurology West China Hospital Sichuan University Chengdu610041 China School of Psychology and Cognitive Science East China Normal University Shanghai China Shanghai Changning Mental Health Center Shanghai China Department of Psychiatry Taipei Veterans General Hospital Taipei Taiwan Institute of Neuroscience National Yang Ming Chiao Tung University Taipei Taiwan Department of MRI First Affiliated Hospital of Zhengzhou University Zhengzhou China Department of Neurology Huashan Hospital Fudan University Shanghai China Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence Zhejiang Normal University Jinhua China MOE Frontiers Center for Brain Science Fudan University Shanghai China Zhangjiang Fudan International Innovation Center Shanghai China School of Data Science Fudan University Shanghai China Department of Computer Science University of Warwick CoventryCV 4 7AL United Kingdom

Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca’s area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia. These epicenters can predict an individual’s response to treatment for psychosis. In addition, cross-diagnostic similarities based on epicenter mapping over of 4000 individuals diagnosed with neurological, neurodevelopmental, or psychiatric disorders appear to be limited. When present, these similarities are restricted to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. We provide a comprehensive framework linking schizophrenia-specific epicenters to multiple levels of neurobiology, including cognitive processes, neurotransmitter receptors and transporters, and human brain gene expression. Epicenter mapping may be a reliable tool for identifying the potential onset sites of neural pathophysiology in schizophrenia. © 2024 the Authors, some rights reserved

关键词： Mapping

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Towards artificial general intelligence via a multimodal foundation model

arXiv

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arXiv 2021年

作者： Fei, Nanyi Lu, Zhiwu Gao, Yizhao Yang, Guoxing Huo, Yuqi Wen, Jingyuan Lu, Haoyu Song, Ruihua Gao, Xin Xiang, Tao Sun, Hao Wen, Ji-Rong Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China School of Information Renmin University of China Beijing China Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Electrical and Electronic Engineering University of Surrey Guildford United Kingdom

The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods have only single-cognitive ability. To overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks. To achieve this goal, we propose to pre-train our foundation model by self-supervised learning with weak semantic correlation data crawled from the Internet and show that promising results can be obtained on a wide range of downstream tasks. Particularly, with the developed model-interpretability tools, we demonstrate that strong imagination ability is now possessed by our foundation model. We believe that our work makes a transformative stride towards AGI, from our common practice of "weak or narrow AI" to that of "strong or generalized AI". © 2021, CC BY.

关键词： Semantics

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Learning Network-Invariant and Label-Discriminative Representations for Cross-Network Node Classification

Learning Network-Invariant and Label-Discriminative Represen...

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Chinese Automation Congress (CAC)

作者： Linyao Yang Yancai Xu Jiachen Hou Yuxin Dai Chen Lv The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Institute of Systems Engineering Macau University of Science and Technology Macau China School of Electrical Engineering and Automation Wuhan University Wuhan China China Electric Power Research Institute Beijing China

ISBN: (纸本)9781665426480

Networks are ubiquitous data structures in the real world. The accurate and efficient analysis of networks is critical to realizing many intelligent network-based services. However, most existing network analysis methods are developed for single networks and require a lot of labeled data, which is costly and time-consuming to acquire. Transfer learning has been widely accepted as an effective paradigm for tackling this problem by reusing the model trained on a supervised task. However, transfer learning on the non-euclidean network data has been investigated by no more than a few studies. To realize accurate node classification based on the knowledge learned from the labeled source network, this paper proposes to learn network-invariant and label-discriminative representations based on graph embedding and linear discriminant analysis. Specifically, we embed the source and target networks into adjacent vector spaces based on the graph attention network by minimizing the Sinkhorn distributional distances between their embeddings. To obtain label-discriminative features for learning better classification models, we then utilize a transferable linear discriminative analysis method to project the embeddings into label-discriminative subspaces. In the end, a support vector machine model trained on the labeled source network is utilized to classify the target nodes. Experiments on two pairs of networks illustrate that our method achieves the best performance and evaluates the effectiveness of the proposed modules.

关键词： Support vector machines Knowledge engineering Analytical models Automation Transfer learning Network analyzers Data structures

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Production of avermectins by Streptomyces avermitilis through solid-state fermentation using agro-industrial waste

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Bioresource technology 2025年 431卷 132625页

作者： Du, Guozhong Dong, Zhuoxu Wang, Zhengduo Pan, Minghui Zhang, Yanyan Xiang, Wensheng Li, Shanshan State Key Laboratory for Biology of Plant Diseases and Insect Pests Institute of Plant Protection Chinese Academy of Agricultural Sciences Beijing100193 China School of Life Science Northeast Agricultural University No. 59 Mucai Street Xiangfang District Harbin150030 China State Key Laboratory of Bioreactor Engineering and School of Biotechnology East China University of Science and Technology Shanghai200237 China

The natural products (NPs) avermectins from Streptomyces show exceptional insecticidal activity and become the most widely produced and used biopesticides in the world. Avermectins are produced by submerged fermentation (SmF), generating significant amount of effluent, exhaust gas and solid waste. We therefore endeavored to establish a green and sustainable alternative through solid-state fermentation (SSF) using agro-industrial waste. We determined the optimal culture medium composition and fermentation style through SSF. The maximum concentration of avermectin B1a (3.83 mg/gds) was obtained with a substrate mixture containing wheat bran, corn cob, earthworm cast, sugarcane bagasse, cane molasses, ammonium sulfate and CoCl2 in shallow trays cultivated for 14 days at 28 °C by repeated-batch SSF, and the initial moisture content and inoculum size was set as 78.5 % and 25 %, respectively. Economic analysis demonstrated that avermectin production cost generated from the fermentation process by SSF was 8.38 % lower than that by SmF. Moreover, avermectin SSF products could be directly used as microbial pesticides for biological control of underground pests and nematodes. This is the first report on avermectin production via SSF, demonstrating great potential in industrial and agricultural applications. Our work also provides guidance to produce other NPs through SSF in other Streptomyces species. © 2025

关键词： Sugar cane

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analysis of pore characteristics of reservoir rock based on CT scanning—taking the tazhong block of tarim basin as an example 8th

Analysis of pore characteristics of reservoir rock based on ...

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8th International Field Exploration and Development Conference, IFEDC 2018

作者： Guo, Ying Yang, Yong Ren, Guangying Ni, Jinlong Cheng, Hanlie Institute of Geology and Paleontology Linyi University LinyiShandong276000 China Shandong Provincial Key Laboratory of Depositional Mineralization & Sedimentary Minerals Shandong University of Science and Technology ShandongQingdao266590 China Institute of Geomechanics Chinese Academy of Geological Sciences Beijing100081 China LandOcean Energy Services Co. Ltd Beijing100084 China

ISBN: (纸本)9789811371264

At present, the research methods of micropore structure mainly include mercury pressure method, scanning electron microscope, casting thin film, laser confocal, and nuclear magnetic resonance. Mercury porosimetry is a fast and accurate method with high pressure. It is the main method to measure capillary pressure at present, but this method can only measure pore throat characteristics and can not quantitatively get the microscopicpore characteristics and rock images. Scanning electron microscopy, casting thin film, and laser coke can only obtain two-dimensional local pore characteristics and cannot obtain three-dimensional images and quantitative characteristics. For the fractured vuggy carbonate complicated pore structure, hole and crack connectivity in Ordovician in Tazhong fractured vuggy carbonate reservoir was chosen forfurther evaluation. The core CT scanning image is processed by two values. After processing, the number of pore pixels in core samples is different from those of the sample particles. According to the number of pixels in pores, the total area of all pores and the area of CT image are calculated, and then, porosity is determined. Finally, the three-dimensional reconstruction of the digital core is formed to analyze the characteristics of the core hole. The face rate of CT scanning is close to that of the conventional casting sheet analysis, which proves the reliability of the CT scanning results. It can be realized that the scanning and quantitative analysis of the full diameter and plunger sample accurately obtain the physical parameters of the rock. © Springer Nature Singapore Pte Ltd 2020.

关键词： Computerized tomography

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Validation of Sentinel-1-derived sea ice cover data in the Arctic 1

Validation of Sentinel-1-derived sea ice cover data in the A...

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1st China Digital Earth Conference, CDEC 2019

作者： Zhang, Qiang Guo, Shibo Sun, Yan Dou, Jianping Li, Xiao-Ming College of Geomatics and Geoinformation Guilin University of Technology Guangxi Guilin541006 China Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Ecology and Environment Quality Control and Service Center of Zibo City Zibo ShanDong255000 China

The Sentinel-1 synthetic aperture radar (SAR) instrument can image the polar regions with a large area and high temporal and spatial resolutions, which is particularly suitable for sea ice monitoring in the Arctic. In a previous study, a support vector machine (SVM)-based method was developed to automatically extract the sea ice cover from Sentinel-1 SAR Extra Wide (EW) swath mode data in cross-polarization (horizontal-vertical, HV, or vertical-horizontal, VH). For validation, 468 Sentinel-1 EW HV-polarized images acquired in the Arctic are used to derive the sea ice cover with a spatial resolution of 0.96 km. We then compared the SAR-derived sea ice cover with the Ice Mapping System (IMS) dataset, which has a resolution of 1.0 km, and the AMSR-2 sea ice concentration (SIC, 15% is used as a threshold for deriving sea ice cover) dataset, which has a resolution of 3.125 km, based on pixel-by-pixel matching. The accuracies of the comparisons with the IMS and SIC data are 85.01% and 88.69%, respectively. The comparison shows that the IMS dataset is mostly overestimates the sea ice cover, while the AMSR2 dataset is relatively underestimates the sea ice extent. On the other hand, the sea ice cover information derived from the Sentinel-1 images by using the proposed method well characterizes the details of the marginal ice zone (MIZ). Furthermore, through the analysis of individual cases, the main factors that affect accuracy are drift (or pack) ice and a high land proportion in some areas. © Published under licence by IOP Publishing Ltd.

关键词： Synthetic aperture radar

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