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The importance of data assimilation components for initial conditions and subsequent error growth

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Science China Earth Sciences 2024年第1期67卷 105-116页

作者： Zhongrui WANG Haohao SUN Lili LEI zhe-min TAN Yi ZHANG Key Laboratory of Mesoscale Severe Weather Ministry of Educationand School of Atmospheric SciencesNanjing UniversityNanjing 210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjing 210023China

Despite a specific data assimilation method,data assimilation(DA)in general can be decomposed into components of the prior information,observation forward operator that is given by the observation type,observation error covariances,and background error *** a classic Lorenz model,the influences of the DA components on the initial conditions(ICs)and subsequent forecasts are systematically investigated,which could provide a theoretical basis for the design of DA for different scales of *** forecast errors undergo three typical stages:a slow growth stage from 0 h to 5 d,a fast growth stage from 5 d to around 15 d with significantly different error growth rates for ensemble and deterministic forecasts,and a saturation stage after 15 *** strategies that provide more accurate ICs can improve the *** assimilation is superior to offline assimilation,and a flow-dependent background error covariance matrix(Pf)provides better analyses than a static background error covariance matrix(B)for instantaneous observations and frequent time-averaged observations;but the opposite is true for infrequent time-averaged observations,since cycling simulation cannot construct informative priors when the model lacks predictive skills and the flow-dependent Pf cannot effectively extract information from low-informative observations as the static *** observations contain more information than time-averaged observations,thus the former is preferred,especially for infrequent observing ***,ensemble forecasts have advantages over deterministic forecasts,and the advantages are enlarged with less informative observations and lower predictive-skill model priors.

关键词： Data assimilation Atmospheric predictability Background error covariances Ensemble forecasts

Experimental and numerical study on protective effect of RC blast wall against air shock wave

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Defence Technology（防务技术） 2024年第1期31卷 567-579页

作者： Xin-zhe Nian Quan-min Xie Xin-li Kong Ying-kang Yao Kui Huang State Key Laboratory of Precision Blasting Jianghan UniversityWuhan430056China Hubei Key Laboratory of Blasting Engineering Jianghan UniversityWuhan430056China Hubei(Wuhan)Institute of Explosion and Blasting Technology Jianghan UniversityWuhan430056China College of Defense Engineering Army Engineering University of PLANanjing210007China Institute of Defense Engineering AMSPLALuoyang471023China

Prototype experiments were carried out on the explosion-proof performance of the RC blast *** mass of TNT detonated in the experiments is 5 kg and 20 kg *** shock wave overpressure was tested in different *** above experiments were numerically simulated,and the simulated shock wave overpressure waveforms were compared with that tested and given by CONWEP *** results show that the numerically simulated waveform is slightly different from the test waveform,but similar to CONWEP *** dimensional analysis and numerical simulation under different working conditions,the equation for the attenuation rate of the diffraction overpressure behind the blast wall was *** to the corresponding standards,the degree of casualties and the damage degree of the brick concrete building at a certain distance behind the wall can be determined when parameters are *** above results can provide a reference for the design and construction of the reinforced concrete blast wall.

关键词： Blast wall Shock wave Diffraction Overpressure Protection

Hemoglobin loss method calculates blood loss during pancreaticoduodenectomy and predicts bleeding-related risk factors

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World Journal of Gastrointestinal Surgery 2024年第2期16卷 419-428页

作者： Chao Yu Yi-min Lin Guo-zhe Xian Department of Hepatobiliary Surgery Shandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinan 250021Shandong ProvinceChina

BACKGROUND The common clinical method to evaluate blood loss during pancreaticoduoden-ectomy(PD)is visual inspection,but most scholars believe that this method is extremely subjective and ***,there is no accurate,objective me-thod to evaluate the amount of blood loss in PD *** retrospectively analyzed the clinical data of 341 patients who underwent PD in Shandong Provincial Hospital from March 2017 to February *** to different surgical methods,they were divided into an open PD(OPD)group and a laparoscopic PD(LPD)*** differences and correlations between the in-traoperative estimation of blood loss(IEBL)obtained by visual inspection and the intraoperative calculation of blood loss(ICBL)obtained using the Hb loss method were ***,IEBL and perioperative calculation of blood loss(PCBL)were compared between the two groups,and single-factor regression analysis was *** There was no statistically significant difference in the preoperative general patient information between the two groups(P>0.05).PD had an ICBL of 743.2(393.0,1173.1)mL and an IEBL of 100.0(50.0,300.0)mL(P200μmol/L(95%CI:7.09-644.26;P=0.045)were independent risk factors for *** ICBLs of the LPD group and OPD group were 767.7(435.4,1249.0)mL and 663.8(347.7,1138.2)mL,respectively(P>0.05).The IEBL of the LPD group 200.0(50.0,200.0)mL was slightly greater than that of the OPD group 100.0(50.0,300.0)mL(P>0.05).PCBL was greater in the LPD group than the OPD group[1061.6(612.3,1632.3)mL vs 806.1(375.9,1347.6)mL](P<0.05).CONCLUSION The ICBL in patients who underwent PD was greater than

关键词： Pancreaticoduodenectomy Hemoglobin loss Calculated blood loss Estimated blood loss

A hybrid deep learning and data assimilation method for model error estimation

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Science China Earth Sciences 2024年

作者： Ziyi PENG Lili LEI zhe-min TAN Key Laboratory of Mesoscale Severe Weather Ministry of Education and School of Atmospheric Sciences Nanjing University Department of Atmospheric and Oceanic Sciences Fudan University

Forecast errors of numerical weather prediction consist of model errors and the growth of initial condition errors,while the initial condition is often optimized based on short-term forecasts. Thus it is difficult to untangle the initial condition error and model error, but it is essential to infer model errors not just for prediction but also for data assimilation (DA). A hybrid deep learning (DL) and DA method is proposed here, aiming to correct model errors. It uses a convolutional neural network(CNN) to extract characteristics of initial conditions and forecast errors, and then provides estimations for model errors. The CNN-based model error estimation method can consider the model error resulted from inaccurate model parameters, or simultaneously consider the model error and initial condition error. Based on the Lorenz05 model, offline and online experiments demonstrate that the CNN-based model error estimation method can effectively correct model errors resulted from inaccurate model parameters, including the forcing F, coupling coefficient c, and relative scale b. For both online and offline model error estimations, simultaneously considering model errors and initial condition errors are beneficial to infer the model errors,compared to considering model errors only. Moreover, using the observations to verify the forecasts has advantages over using the analyses, to estimate the model errors. Using observations can also achieve a faster convergence of model error estimation with online DA than using analyses.

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Gut microbiota affects the estrus return of sows by regulating the metabolism of sex steroid hormones

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Journal of Animal Science and Biotechnology 2024年第2期15卷 578-599页

作者： min Liu Jia Zhang Yunyan Zhou Shuqi Xiong Mengqing Zhou Lin Wu Qin Liu zhe Chen Hui Jiang Jiawen yang Yuxin Liu Yaxiang Wang Congying Chen Lusheng Huang National Key Laboratory of Swine Genetic Improvement and Germplasm Innovation Jiangxi Agricultural UniversityNanchang 330045China

Background Sex hormones play important roles in the estrus return of post-weaning *** studies have demonstrated a complex and bi-directional regulation between sex hormones and gut ***,the extent to which the gut microbiota affects estrus return of post-weaning sows is largely *** In this study,we first screened 207 fecal samples from well-phenotyped sows by 16S rRNA gene sequencing and identified significant associations between microbes and estrus return of post-weaning *** metagenomic sequencing data from 85 fecal samples,we identified 37 bacterial species that were significantly associated with estrus *** returning sows were characterized by increased abundances of *** and *** and decreased abundances of ***,***,and *** changes in gut microbial composition significantly altered the functional capacity of steroid hormone biosynthesis in the gut *** results were confirmed in a validation *** changes in sex steroid hormones and related compounds were found between normal and non-return sows via metabolome *** integrated analysis of differential bacterial species,metagenome,and fecal metabolome provided evidence that normal return-associated bacterial species *** and Prevotella *** in the degradation of pregnenolone,progesterone,and testosterone,thereby promoting estrogen ***,the microbial metabolites related to sow energy and nutrient supply or metabolic disorders also showed relationships with sow estrus *** An integrated analysis of differentially abundant bacterial species,metagenome,and fecal metabolome revealed the involvement of *** and Prevotella *** sow estrus *** findings provide deep insight into the role of gut microbiota in the estrus return of post-weaning sows and the complex cross-talk between gut microbiota and sex hormones,suggesting that the manipulatio

关键词： Estrus return Fecal metabolome Gut microbiota Metagenomics Sex steroid hormones Sow

Collembolans maintain a core microbiome responding to diverse soil ecosystems

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Soil Ecology Letters 2024年第1期6卷 33-46页

作者： zhe-Lun Liu Dong Zhu Yi-Fei Wang Yong-Guan Zhu min Qiao State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China Key Lab of Urban Environment and Health Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China

The unique gut habitat led to a core intestinal micro-biome in diverse soil *** collembolan guts may help eliminate soil ***-selection carried more weight on community assembly of gut *** invertebrates are widely distributed in the ecosystem and are essential for soil ecological ***-brate gut microbiome plays an important role in host health and has been considered as a hidden microbial ***,little is known about how gut microbiome in soil invertebrates respond to diverse soil *** on a laboratory microcosm experiment,we characterized the assembling of microbiome of soil collembolans(Folsomia candida)from six representative regions of the soil ecosystem which they *** showed that collembolan gut microbial communities differed significantly from their surrounding soil microbial communities.A dominant core gut microbiome was identified in gut *** analyses indicated that deterministic process dominated in the community assembly of collembolan gut *** results further demonstrate a dominant contribution of host selection in shaping gut *** is also worthy to mention that pathogens,such as common agricultural phytopathogenic fungi Fusarium,were involved in core microbiome,indicating that collembolans could act as vectors of *** results unravelled the existence of gut core microbiome of collembolans in soil ecosystems and provided new insights for under-standing the crucial role of gut microbiome of soil fauna in maintaining microbial biodiversity and stability of soil ecosystems.

关键词： gut microbiome collembolan core microbiome community assembly

Beam based alignment using a neural network

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Nuclear Science and Techniques 2024年第4期35卷 108-118页

作者： Guan-Liang Wang Ke-min Chen Si-Wei Wang zhe Wang Tao He Masahito Hosaka Guang-Yao Feng Wei Xu National Synchrotron Radiation Laboratory University of Science and Technology of ChinaHefei 230029China Diamond Light Source Oxfordshire OX110DEUK

Beams typically do not travel through the magnet centers because of errors in storage *** beam deviating from the quadrupole centers is affected by additional dipole fields due to magnetic field ***-based alignment(BBA)is often performed to determine a golden orbit where the beam circulates around the quadrupole center *** storage rings with many quadrupoles,the conventional BBA procedure is time-consuming,particularly in the commissioning phase,because of the necessary iterative *** addition,the conventional BBA method can be affected by strong coupling and the nonlinearity of the storage ring *** this study,a novel method based on a neural network was proposed to determine the golden orbit in a much shorter time with reasonable *** golden orbit can be used directly for operation or adopted as a starting point for conventional *** method was demonstrated in the HLS-II storage ring for the first time through simulations and online *** results of the experiments showed that the golden orbit obtained using this new method was consistent with that obtained using the conventional *** development of this new method and the corresponding experiments are reported in this paper.

关键词： Golden orbit Beam-based alignment Neural network Storage ring

Encoding risk decision-making with neuron spikes in prefrontal cortex

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Encoding risk decision-making with neuron spikes in prefront...

Prefrontal Dopaminergic Modulations of Risk Decision Making

中国神经科学学会第十二届全国学术会议

作者： Xu HU min-zhe yang Fei LUO Bao-ming LI Chao-Lin MA Laboratory of Cognitive Functions and Disorders Nanchang University School of Life Science Nanchang University

Objective Decision making is a mental process when people faced multiple options to weigh the trade-offs, while those behaviors which decision makers are intent to choose risk actions for high yield with knowing the estimated probability is called risk decision-making（RDM）. Previous studies indicated that there are differences in risk preference among different individuals when rats carrying RDM task, and the prefrontal cortex（PFC） is involved in the regulation of this process, but its specific mechanism is unclear. Methods In this study, we used the behavioral electrophysiological method to train rats to learn the RDM task, applied the multi-channel microelectrode to record the firing pattern of PFC neurons when rats were performing the task. Results（1） SD rats successfully learned the risk decision making task and most of them prefer the risky option when the amount of total reward is equal.（2） Under the situation of changing reward probability, rats’ selection of risk option was positively correlated with reward probability and more sensitive for low probability alterations.（3） We identified different types of neurons that were related to different events of the task performance, such as choice and reward. Conclusion PFC is essential for encoding the planning or organization of the RDM task performance.

关键词： Prefrontal Cortex Risk Decision-making Neural Decoding Firing Pattern Multi-channel Microelectrode

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Prefrontal Dopaminergic Modulations of Risk Decision Making