Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

Spatiotemporal Evaluation and Future Projection of Diurnal Temperature Range over the Tibetan Plateau in CMIP6 Models

The diurnal temperature range(DTR) serves as a vital indicator reflecting both natural climate variability and anthropogenic climate change. This study investigates the historical and projected multitemporal DTR variations over the Tibetan Plateau. It assesses 23 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6) using CN05.1 observational data as validation, evaluating their ability to simulate DTR over the Tibetan Plateau. Then, the evolution of DTR over the Tibetan Plateau under different shared socioeconomic pathway(SSP) scenarios for the near,middle, and long term of future projection are analyzed using 11 selected robustly performing models. Key findings reveal:(1) Among the models examined, BCC-CSM2-MR, EC-Earth3, EC-Earth3-CC, EC-Earth3-Veg, EC-Earth3-Veg-LR,FGOALS-g3, FIO-ESM-2-0, GFDL-ESM4, MPI-ESM1-2-HR, MPI-ESM1-2-LR, and INM-CM5-0 exhibit superior integrated simulation capability for capturing the spatiotemporal variability of DTR over the Tibetan Plateau.(2) Projection indicates a slightly increasing trend in DTR on the Tibetan Plateau in the SSP1-2.6 scenario, and decreasing trends in the SSP2-4.5, SSP3-7.0, and SPP5-8.5 scenarios. In certain areas, such as the southeastern edge of the Tibetan Plateau, western hinterland of the Tibetan Plateau, southern Kunlun, and the Qaidam basins, the changes in DTR are relatively large.(3) Notably, the warming rate of maximum temperature under SSP2-4.5, SSP3-7.0, and SPP5-8.5 is slower compared to that of minimum temperature, and it emerges as the primary contributor to the projected decrease in DTR over the Tibetan Plateau in the future.

Establishment of a humanized ST6GAL1 mouse model for influenza research

Background:This study aimed to construct and characterize a humanized influenza mouse model expressing hST6GAL1.Methods:Humanized fragments,consisting of the endothelial cell-specific K18 promoter,human ST6GAL1-encoding gene,and luciferase gene,were microinjected into the fertilized eggs of mice.The manipulated embryos were transferred into the oviducts of pseudopregnant female mice.The offspring were identified using PCR.Mice exhibiting elevated expression of the hST6GAL1 gene were selectively bred for propagation,and in vivo analysis was performed for screening.Expression of the humanized gene was tested by performing immunohistochemical(IHC)analysis.Hematologic and biochemical analyses using the whole blood and serum of humanized hST6GAL1 mice were performed.Results:Successful integration of the human ST6GAL1 gene into the mouse genome led to the overexpression of human SiaT ST6GAL1.Seven mice were identified as carrying copies of the humanized gene,and the in vivo analysis indicated that hST6GAL1gene expression in positive mice mirrored influenza virus infection characteristics.The IHC results revealed that hST6GAL1 was expressed in the lungs of humanized mice.Moreover,the hematologic and biochemical parameters of the positive mice were within the normal range.Conclusion:A humanized influenza mouse model expressing the hST6GAL1 gene was successfully established and characterized.

The bio-active components of the Mongolian medicine Horcha-6 and therapeutic mechanism in the rat migraine model

Background:The active components of Horcha-6 were identified using liquid chromatography with tandem mass spectrometry.Also,we investigated the potential mechanisms that explain why Horcha-6 may be effective in treating migraines through the use of network pharmacology and a rat migraine model.Methods:After identifying the active components of Horcha-6,the corresponding genes of the active components’target were obtained from the Universal Protein database,and a“compound-target-disease”network was constructed using Cytoscape 3.9.0 software.For the in vivo experiments,nitroglycerin was injected intraperitoneally into rats to create a migraine model.Pre-treatment with Horcha-6 was administered orally for 14 days,and rats were subjected to migraine-related behavior tests.RNA sequencing was performed to identify the gene expression regulated by Horcha-6 in the trigeminal nerve.Results:A total of 903 chemical components of Horcha-6 have been collected in the liquid chromatography with tandem mass spectrometry.We discovered 55 of the Horcha-6 bio-active components that were evaluated based on their Percent Human Oral Absorption(≥30%)and DL values(≥0.185)on the traditional Chinese medicine systems pharmacology database.The“compound-target-disease”network contained 163 intersection targets with the migraine state.Gene Ontology analysis indicated that these components significantly regulated the immune response,vascular function,oxidative stress,etc.When Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed,we observed that most of the target genes were significantly enriched in the inflammation and neuro-related signaling pathway,toll-like receptor signaling pathway,neuroactive ligand-receptor interaction,etc.These predictions were further demonstrated via in vivo animal model experiments.The RNA sequencing results showed that 41 genes were down-regulated(P<0.05)and 86 genes were up-regulated(P<0.05)in the Horcha-6 treated group compared with the untreated group.Those genes were mainly involved in neuromodulation,vascular function,and hormone metabolism.Conclusion:The 55 bio-active components in Horcha-6 regulate inflammation,hormone metabolism,and neurotransmitters and have potential as a therapy to treat migraines.

A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.

Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6

Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

Variability of the Pacific subtropical cells under global warming in CMIP6 models

The Pacific subtropical cells(STCs)are shallow meridional overturning circulations connecting the tropics and subtropics,and are assumed to be an important driver of the tropical Pacific decadal variability.The variability of STCs under global warming is investigated using multimodal outputs from the latest phase of the Coupled Model Inter-comparison Project(CMIP6)and ocean reanalysis products.Firstly,the volume transport diagnostic analysis is employed to evaluate how coupled models and ocean reanalysis products reproduce interior STC transport.The variation of heat transport by the interior STC under the high-emissions warming scenarios is also analyzed.The results show that the multimodal-mean linear trends of the interior STC transport along 9°S and 9°N are-0.02 Sv/a and 0.04 Sv/a under global warming,respectively,which is mainly due to the combined effect of the strengthened upper oceanic stratification and the weakening of wind field.There is a compensation relationship between the interior STC and the western boundary transport in the future climate,and the compensation relationship of 9°S is more significant than that of 9°N.In addition,compared with ocean reanalysis products,the coupled models tend to underestimate the variability of the interior STC transport convergence,and thus may lose some sea surface temperature(SST)driving force,which may be the reason for the low STC-SST correlation simulated by the model.The future scenario simulation shows that the heat transport of interior STC is weakened under global warming,with a general agreement across models.

CMIP 6 models simulation of the connection between North/South Pacific Meridional Mode and ENSO

The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relationship experienced an interdecadal transition.Changes in this connection can be attributed mainly to the phase change of the Pacific decadal oscillation(PDO).During the positive phase of PDO,a shallower thermocline in the central Pacific is responsible for the stronger trade wind charging(TWC)mechanism,which leads to a stronger equatorial subsurface temperature evolution.This dynamic process strengthens the connection between NPMM and ENSO.Associated with the negative phase of PDO,a shallower thermocline over southeastern Pacific allows an enhanced wind-evaporation-SST(WES)feedback,strengthening the connection between SPMM and ENSO.Using 35 Coupled Model Intercomparison Project Phase 6(CMIP6)models,we examined the NPMM/SPMM performance and its connection with ENSO in the historical runs.The great majority of CMIP6 models can reproduce the pattern of NPMM and SPMM well,but they reveal discrepant ENSO and NPMM/SPMM relationship.The intermodal uncertainty for the connection of NPMM-ENSO is due to different TWC mechanism.A stronger TWC mechanism will enhance NPMM forcing.For SPMM,few models can simulate a good relationship with ENSO.The intermodel spread in the relationship of SPMM and ENSO owing to SST bias in the southeastern Pacific,as WES feedback is stronger when the southeastern Pacific is warmer.

白细胞介素-6对胰腺癌小鼠癌组织的细胞增殖及上皮间质转化的影响

目的 探讨白细胞介素-6(IL-6)在胰腺癌裸鼠模型癌组织增殖与上皮间质化中的作用,并分析其分子机制。方法 将18只成功构建胰腺癌细胞荷瘤的BALB/c裸鼠模型随机分为模型对照组、IL-6过表达组和免疫球蛋白G(IgG)抗体组,每组6只。模型对照组于肿瘤部位注射生理盐水进行干预,IL-6过表达组于肿瘤部位注射IL-6过表达质粒进行干预,IgG抗体组予肿瘤部位注射IgG抗体进行干预。3组均于末次给药24 h后处死小鼠,并收集胰腺肿瘤组织。对各组肿瘤组织进行离体称重并计算抑瘤率。通过苏木精-伊红(HE)染色观察胰腺组织的病理学改变。采用酶联免疫吸附试验(ELISA)检测各组裸鼠肿瘤组织中IL-6、p-STAT3、NF-κB p65和VEGF蛋白的表达水平。采用蛋白质印迹法(Western blot)检测各组肿瘤组织中E-cadherin、Vimentin、MMP-9蛋白的表达水平。采用实时荧光定量聚合酶链反应(qRT-PCR)检测各组IL-6、p-STAT3、SOCS3基因的表达水平。结果 3组裸鼠胰腺肿瘤组织的平均瘤重及抑瘤率比较,差异均无统计学意义(P>0.05)。HE染色结果显示,模型对照组肿瘤组织细胞体积增大,癌细胞排列呈巢状;IL-6过表达组可见肿瘤组织轻度纤维化,少量炎症浸润;IgG抗体组可见核分裂象,大量肿瘤细胞坏死,局灶组织纤维化。IL-6过表达组E-cadherin蛋白、SOCS3基因表达水平低于模型对照组和IgG抗体组,而Vimentin、MMP-9、IL-6、p-STAT3、NF-κB p65、VEGF蛋白的表达水平及IL-6、NF-κB p65基因的表达水平高于模型对照组和IgG抗体组,差异均有统计学意义(P<0.05);IgG抗体组Vimentin、MMP-9、IL-6、p-STAT3、NF-κB p65、VEGF蛋白的表达水平及IL-6、NF-κB p65基因的表达水平低于模型对照组,而E-cadherin和SOCS3基因水平高于模型对照组,差异均有统计学意义(P<0.05)。结论 IL-6可以通过p-STAT3和(或)NF-κB p65信号通路调节胰腺癌裸鼠模型肿瘤组织中的相关细胞因子,影响肿瘤组织的增殖及上皮间质化。

外圆磨削18CrNiMo7-6力模型及表面完整性研究

为了准确和有效地控制磨削参数对磨削力及表面完整性的影响,通过解析法,以磨粒与材料间的塑性变形、压痕理论以及剪切应变效应为理论依据,建立了三阶段的磨削力理论模型。选定棕刚玉砂轮进行磨削试验,探究了磨削参数对磨削力的影响以及磨削参数和磨削力对表面完整性的影响,通过外圆横向磨削正交试验获得了外圆磨削最优工艺参数。结果表明,外圆磨削力模型法向磨削力和切向磨削力的预测平均误差分别为5.56%和7.08%;砂轮径向进给速度f_(r)对磨削力的影响最大,磨削宽度b次之,工件转速n_(w)和砂轮粒度的影响较小;f_(r)和b对残余应力的影响较大,砂轮粒度对表面粗糙度的影响最大;随着磨削力的增大,表面粗糙度值一直增大,残余应力先减小后增大,沿深度方向残余应力最大值先增大后减小,在试验所取参数条件下,影响残余应力的深度分布范围基本在20~40μm;最优工艺参数组合如下:f_(r)=0.15 mm/min,n_(w)=120 r/min,b=10 mm,砂轮粒度80。

鄂尔多斯盆地蟠龙地区长6储层四性关系研究

针对蟠龙地区长6储层四性关系的研究与认识不足,利用蟠龙地区的测井数据、录完井数据、岩心分析和化验资料等资料进行整理与分析,对研究区储层岩性、物性、电性与含油性特征及其相互间的关系进行了研究。研究结果表明,①蟠龙地区长6油层组以长石砂岩为主;②储层平均孔隙度为8%,平均渗透率为0.79×10-3μm 2,属于低孔特低渗至低孔超低渗储层;③录井中岩心以油迹含油级别为主;④结合岩心测试资料建立了储层参数测井解释模型,并最终确定有效储层物性下限为:渗透率0.15×10^(-3)μm^(2),孔隙度5.5%,电阻率20Ω·m,声波时差215μs/m。研究了储层四性基本特征及其关系,并得出了蟠龙地区储层物性和含油性的电性解释图版,为后续蟠龙地区油层解释以及探明储量参数的确定提供了依据。

CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment

The outputs of the Chinese Academy of Sciences(CAS)Flexible Global Ocean-Atmosphere-Land System(FGOALSf3-L)model for the decadal climate prediction project(DCPP)of the Coupled Model Intercomparison Project Phase 6(CMIP6)are described in this paper.The FGOALS-f3-L was initialized through the upgraded,weakly coupled data assimilation scheme,referred to as EnOI-IAU,which assimilates observational anomalies of sea surface temperature(SST)and upper-level(0–1000-m)ocean temperature and salinity profiles into the coupled model.Then,nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year over the period of 1960–2021,based on initial conditions produced by three initialization experiments.The hindcast and forecast experiments follow the experiment designs of the Component-A and Component-B of the DCPP,respectively.The decadal prediction output datasets contain a total of 44 monthly mean atmospheric and oceanic variables.The preliminary evaluation indicates that the hindcast experiments show significant predictive skill for the interannual variations of SST in the north Pacific and multi-year variations of SST in the subtropical Pacific and the southern Indian Ocean.

Projected Regional 1.50℃and 2.00℃Warming Threshold-crossing Time Worldwide Using the CMIP6 Models

The Paris Agreement aims to limit global warming to well below 2.00℃and pursue efforts to limit the temperature increase to 1.50℃.However,the response of climate change to unbalanced global warming is affected by spatial and temporal sensitivities.To better understand the regional warming response to global warming at 1.50℃and 2.00℃,we detected the 1.50℃and 2.00℃warming threshold-crossing time(WTT)above pre-industrial levels globally using the Coupled Model Intercomparison Project phase 6(CMIP6)models.Our findings indicate that the 1.50℃or 2.00℃WTT differs substantially worldwide.The warming rate of land would be approximately 1.35–1.46 times that of the ocean between 60°N–60°S in 2015–2100.Consequently,the land would experience a 1.50℃(2.00℃)warming at least 10–20 yr earlier than the time when the global mean near-surface air temperature reaches 1.50℃(2.00℃)WTT.Meanwhile,the Southern Ocean between 0°and 60°S considerably slows down the global 1.50℃and 2.00℃WTT.In 2040–2060,over 98.70%(77.50%),99.70%(89.30%),99.80%(93.40%),and 100.00%(98.00%)of the land will have warmed by over 1.50℃(2.00℃)under SSP(Shared Socioeconomic Pathway)1–2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5,respectively.We conclude that regional 1.50℃(2.00℃)WTT should be fully considered,especially in vulnerable high-latitude and high-altitude regions.

Spatial Inhomogeneity of Atmospheric CO_(2) Concentration and Its Uncertainty in CMIP6 Earth System Models

This paper provides a systematic evaluation of the ability of 12 Earth System Models(ESMs)participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)to simulate the spatial inhomogeneity of the atmospheric carbon dioxide(CO_(2))concentration.The multi-model ensemble mean(MME)can reasonably simulate the increasing trend of CO_(2) concentration from 1850 to 2014,compared with the observation data from the Scripps CO_(2) Program and CMIP6 prescribed data,and improves upon the CMIP5 MME CO_(2) concentration(which is overestimated after 1950).The growth rate of CO_(2) concentration in the northern hemisphere(NH)is higher than that in the southern hemisphere(SH),with the highest growth rate in the mid-latitudes of the NH.The MME can also reasonably simulate the seasonal amplitude of CO_(2) concentration,which is larger in the NH than in the SH and grows in amplitude after the 1950s(especially in the NH).Although the results of the MME are reasonable,there is a large spread among ESMs,and the difference between the ESMs increases with time.The MME results show that regions with relatively large CO_(2) concentrations(such as northern Russia,eastern China,Southeast Asia,the eastern United States,northern South America,and southern Africa)have greater seasonal variability and also exhibit a larger inter-model spread.Compared with CMIP5,the CMIP6 MME simulates an average spatial distribution of CO_(2) concentration that is much closer to the site observations,but the CMIP6-inter-model spread is larger.The inter-model differences of the annual means and seasonal cycles of atmospheric CO_(2) concentration are both attributed to the differences in natural sources and sinks of CO_(2) between the simulations.

基于GF-6/WFV卫星遥感的大田冬小麦叶片氮素含量估测

为对大田冬小麦叶片氮素含量(LNC)进行快速、准确及无损监测,通过在江苏省泰州泰兴市、盐城大丰区和南通如皋市布设冬小麦遥感监测大田试验,在获取试验样点冬小麦冠层红光波段反射率(REDref)、近红外波段反射率(NIRref)和计算的十个光谱指数(RVI、NDVI、DVI、SAVI、OSAVI、MSR、RDVI、EVI2、NLI和SVI)基础上,将12个遥感光谱指标与冬小麦LNC进行相关分析,选出与LNC相关性较好的作为模型输入变量,构建基于BP神经网络的冬小麦LNC估测模型,并利用GF-6/WFV卫星遥感影像对县域冬小麦LNC的空间分布开展监测。结果表明,12个遥感光谱指标与冬小麦LNC之间存在不同程度的相关性,其中NDVI、RVI、MSR、OSAVI和NLI与冬小麦LNC的相关性较好(相关系数不低于0.65)。将优选的5个遥感光谱指标作为模型输入变量,构建基于BP神经网络的冬小麦LNC估测模型(LNC-BPEM),模型的估测精度r^(2)=0.866,RMSE=0.246%,ARE=12.9%。将冬小麦LNC-BPEM估测模型和GF-6/WFV影像结合对县域冬小麦LNC的空间信息监测,获得了如皋县域冬小麦LNC的空间分布特征,该区域冬小麦LNC范围在0.9%~2.0%(长势正常)的种植面积为29 693.3 hm^(2),占冬小麦总种植面积的74%。这说明利用GF-6/WFV卫星的多个遥感光谱指标与神经网络结合建模可有效估测县域大田冬小麦叶片氮素含量。

安塞油田黑山梁区长6油层组单砂体构型分析及平面展布特征

安塞油田黑山梁区块位于延安市安塞区,三叠系延长组长6油层组是其主力产油层。目前该区已进入注水开发阶段,但砂体展布、非均质性、砂体叠置规律等认识不清,导致开发过程中存在注水受效程度不均衡,整体水驱效果差等问题。为此,本次研究依托丰富的测井、录井资料,以及岩心、镜下薄片资料和分析测试数据,开展地层精细刻画、沉积微相、砂体平面分布及单砂体叠置规律的综合研究。结果表明:黑山梁地区长6时期主要发育三角洲前缘亚相,岩性以细粒长石砂岩为主,分选性中等-好,磨圆度中等,水下分流河道和分流间湾微相较为多见,河口坝微相发育较少;水下分流河道为优势相,砂岩分布广、厚度大,沿河道方向延伸,早期形成的河口坝由于波浪作用和分流河道侵蚀作用被破坏,河口坝无法保存完整,仅有部分痕迹。砂体类型包括水下分流河道砂和河口坝砂两种,单砂体垂向叠置可分为孤立型、叠加型和切叠型3种;侧向拼接样式可分为孤立式、对接式和侧切式3种。研究区内砂体沿北东-南西方向呈长条状展布,由于河道频繁摆动和分叉,砂体切叠现象明显,顺物源方向砂体连通性较好,垂直物源方向砂体被分流间湾泥隔开,砂体连通性较差,并结合生产动态数据,认为砂体连通程度越高,水驱动用效果越好。基于该研究成果建立了研究区曲流河三角洲沉积模式,为后期油藏完善注采井网、分层注水开发方案调整提供地质依据。

一种6-DOF小行星着陆轨迹序列凸优化方法

针对6自由度的小行星动力着陆多约束轨迹优化问题,提出了一种基于序列凸优化的小行星着陆轨迹优化算法。首先采用多面体引力场模型计算小行星的引力场,其可用于描述任意形状的小行星引力场,且比质点群法和球谐函数展开法等方法计算精度更高。为了在凸约束下解决小行星着陆过程燃料消耗最优问题,通过对探测器动力学模型及其约束进行线性化和离散化,将原来的非凸连续时间优化问题转化为凸化的子问题,即二阶锥规划问题(SOCP);然后引入了虚拟控制项和信赖域,以增强算法的鲁棒性。通过在形状不规则小行星上的着陆模拟,验证了所提出算法的有效性,仿真结果满足各项约束条件,可实现高精度着陆和燃料消耗最优的目标。

B7-H6在宫颈上皮内瘤变、宫颈癌组织中表达差异及与肿瘤浸润T淋巴细胞、预后的相关性

目的探究宫颈上皮内瘤变、宫颈癌组织中B7同源体6(B7-H6)表达差异与肿瘤浸润T淋巴细胞、预后相关性。方法选取2019年6月—2021年3月60例经病理检查确诊为宫颈癌的手术患者作为研究组,另选同期同年龄段60例宫颈上皮内瘤变作为对照组。比较2组组织B7-H6表达情况(H-score评分)及血清B7-H6水平,并比较研究组不同肿瘤浸润T淋巴细胞浸润程度患者H-score评分、血清B7-H6水平,分析研究组H-score评分、血清B7-H6水平与肿瘤浸润T淋巴细胞浸润程度的相关性。研究组术后随访1年,比较不同预后患者一般资料、H-score评分、血清B7-H6水平,探讨预后影响因素,并分析H-score评分和血清B7-H6水平预测患者预后的价值。结果研究组H-score评分和血清B7-H6水平高于对照组(P<0.01)。研究组肿瘤浸润T淋巴细胞浸润程度0级患者H-score评分、血清B7-H6水平高于1级、2级患者,且1级患者高于2级患者(P<0.05)。研究组H-score评分、血清B7-H6水平与肿瘤浸润T淋巴细胞浸润程度呈负相关(P<0.01)。多因素Logistic回归分析显示,肿瘤直径、国际妇产科协会(FIGO)分期、淋巴结转移、间质浸润深度、H-score评分、血清B7-H6水平均为宫颈癌手术患者预后不良的独立危险因素(P<0.01)。肿瘤直径、FIGO分期、淋巴结转移、间质浸润深度、H-score评分和血清B7-H6水平预测宫颈癌手术患者预后不良的曲线下面积(AUC)分别为0.736、0.726、0.714、0.712、0.842和0.840,H-score评分和血清B7-H6水平预测的AUC分别大于肿瘤直径、FIGO分期、淋巴结转移、间质浸润深度预测的AUC(P<0.05)。H-score评分和血清B7-H6水平在预测宫颈癌手术患者预后不良方面拥有良好的临床效用。结论宫颈癌组织B7-H6表达高于宫颈上皮内瘤变,且宫颈癌组织B7-H6表达、血清B7-H6水平与肿瘤浸润T淋巴细胞浸润程度呈负相关,也是宫颈癌手术患者预后不良的独立危险因素,在预测预后方面具有一定临床价值。

Inhibition of Bcl-6 Expression Ameliorates Asthmatic Characteristics in Mice

Objective The function of Bcl-6 in T follicular helper(Tfh)cell maturation is indispensable,and Tfh cells play a pivotal role in asthma.This study investigated the impact of Bcl-6 on asthmatic traits.Methods The microscopic pathological alterations,airway resistance(AR),and lung compliance(LC)were determined in asthmatic mice and Bcl-6 interference mice.The surface molecular markers of Tfh cells and the Bcl-6 mRNA and protein expression were determined by flow cytometry,RT-qPCR,and Western blotting,respectively.The relationships between the Tfh cell ratio and the IgE and IgG1 concentrations in peripheral blood mononuclear cells(PBMCs)and bronchoalveolar lavage fluid(BALF)were determined.Results Asthmatic inflammatory changes were observed in the lung tissue and were attenuated by Bcl-6 siRNA and dexamethasone(DXM).Asthmatic mice exhibited an increased AR and a decreased LC,while Bcl-6 siRNA or DXM mitigated these changes.The percentages of Tfh cells and eosinophils were significantly increased in the asthmatic mice,and they significantly decreased after Bcl-6 inhibition or DXM treatment.RT-qPCR and Western blotting analyses revealed that the Bcl-6 expression level in PBMCs was significantly higher in asthmatic mice,and it decreased following Bcl-6 inhibition or DXM treatment.The IgE expression in the serum and BALF and the B cell expression in PBMCs exhibited a similar trend.In asthmatic mice,the ratio of Tfh cells in the peripheral blood showed a strong positive correlation with the IgE levels in the serum and BALF,but not with the IgG1 levels.Conclusion The amelioration of airway inflammation and airway hyper-responsiveness is achieved through Bcl-6 suppression,which effectively hinders Tfh cell differentiation,ultimately resulting in a concurrent reduction in IgE production.

Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.