财政扶持何以提升返乡创业者创新精神?

本文选取2019年全国2139家返乡创业企业的调查数据,运用有序评定模型和中介效应模型,研究财政扶持对返乡创业者创新精神的影响和作用机制。研究结果表明,财政扶持能够促进返乡创业者创新精神的产生,其中技能培训可以培育返乡创业者的创新精神,税收减免、土地优惠和产业扶贫可以激发返乡创业者的创新精神。机制分析结果表明,财政扶持能够通过优化外部营商环境,有效激发返乡创业者的创新精神。异质性分析结果表明,相较于东西部地区、第一二产业、中低端第三产业和生存型返乡创业者,财政扶持对中部地区、高端第三产业及发展型返乡创业者创新精神的激发效果更明显。因此,加大对返乡创业者的扶持力度、优化外部营商环境、制定差异化的扶持政策,将有利于进一步激发返乡创业者的创新精神。

Litter Productivity and Nutrient Return Characteristics of Three Typical Forest Stands in Golden Mountain

Objective: The paper aims to analyze the dynamic characteristics of litter production and nutrient return of the forest ecosystems in subtropical areas, and provide a theoretical basis for the nutrient cycling study in southwest Hubei Province and carbon sink function of the whole forest ecosystem. Methods: Three typical forest stands (Chinese fir plantation, Cryptomeria fortunei plantation and evergreen and deciduous broad-leaved mixed forest) in Golden Mountain Forest Farm in southwest Hubei Province were investigated and monitored continuously for the litter types and productivity and nutrient return. Results: The annual litter productivity of the three forest stands ranged from 161.77 to 396.26 kg·hm-2;Litters of branches, leaves and reproductive organs accounted for 14.14% - 20.85%, 33.26% - 78.33%, 7.52% - 42.18% of the total, respectively;The litter productivity and total litter productivity of each composition in the three forest stands show unimodal or bimodal changes over months, and the total litter productivity reached the highest value in January, April and October respectively. For different nutrient contents of the three forest stands, the common feature is C > N. The order of nutrient return amount from greatest to least is evergreen and deciduous broad-leaved mixed forest, Cryptomeria fortunei plantation and Chinese fir plantation. For different nutrient return amounts, the common feature is C > N, and the nutrient return amounts are 76.51-180.69 kg·hm-2 and 2.3 - 5.71 kg·hm-2 respectively. Conclusion: The annual litter productivity and nutrient return amount of the evergreen and deciduous broad-leaved mixed forest are the highest among the three forest stands. Therefore, protecting the evergreen and deciduous broad-leaved mixed forest and studying the litter changes of Chinese fir plantation and Cryptomeria fortunei plantation are of far-reaching significance for the development of sustainable forest management in this region and the further improvement of the carbon sequestration function of the whole forest ecosystem.

基于fsQCA的国产服装品牌忠诚提升路径研究

为探究中国服装企业维护和提升消费者品牌忠诚的方式,以京东平台上30个国产服装品牌为案例,在收集商品评论并对其进行文本分析的基础上,运用模糊集定性比较分析(fsQCA)方法,探究国产服装企业维护和提升品牌忠诚的多种因素组合路径。研究结果表明,国产服装企业品牌忠诚的提升是多因素组态作用的结果,产生高品牌忠诚的7条路径可以归纳为5种模式,分别为质量领先+影响力型、质量领先+情感驱动型、情感驱动+社会责任感型、质量领先+在线社群运营型、品牌形象+价值让渡型。在此结论的基础上提出服装企业应注重生产制造能力提升、积极履行社会责任以及要以满足消费者需求为中心等建议,为国产服装企业提供了理论和实践启示。

脆性X综合征遗传学诊断方法研究进展

脆性X综合征(FXS)是导致智力障碍和发育障碍的主要单基因病之一,呈X连锁不完全显性遗传。FXS的病因是FMR1基因内(CGG)n重复序列的不稳定扩展及其上游CpG岛的异常甲基化,进而导致脆性X智力低下蛋白(FMRP)减少或缺乏,FMRP的水平直接关系到临床表型的严重程度。临床表现和基因检测是诊断FXS的主要依据。然而,FMR1基因分子结构和遗传模式的特殊性使得FXS的分子诊断和遗传咨询面临挑战。因此,如何简便而准确地进行FMR1基因检测一直是临床关注的焦点。文章针对FXS遗传学诊断方法的研究进展进行综述,旨在促进FXS的规范诊断,为临床提供帮助。

液态空气储能耦合综合能源系统热电联储联供优化配置研究

液态空气储能(LAES)在多能耦合的综合能源系统中极具应用前景,合理的储能容量配置更有利于综合能源系统低碳经济运行,但目前研究未充分考虑LAES热电联储联供强相关的特性和优势。因此,本文提出了一种LAES耦合综合能源系统的热电联储联供优化配置方法,针对综合能源系统的基本架构,构建了各组成单元的热电联储/供调度约束模型,并以设备初始投资成本、设备运维成本、购能成本、弃风弃光成本等为目标函数,考虑了系统能量平衡约束、设备容量约束、设备出力约束、外网交互功率约束以及储能约束,建立了相应的优化配置模型,并基于混合整数线性规划方法进行模型求解。以某实际园区为例,设置了5种场景进行优化结果对比分析,结果表明:考虑LAES热电联储联供特性的综合能源系统能实时有效地满足系统用能需求,同时能实现更好的经济效益和环境效益,相较于传统分供系统,系统总经济成本下降37.1%,实现碳减排71.50%,并在消纳可再生能源和减少弃光弃风方面更具潜力。本研究可为LAES耦合系统热电联储联供优化模型的有效性提供理论依据,有助于推动LAES在综合能源系统中的商业化应用。

电压的量子基准发展历程及其现况研究

以对电压量子基准发展及其现况的讨论为核心,阐述了约瑟夫森效应以及由此诞生的约瑟夫森结及约瑟夫森结阵列的原理,描述了随着测量需求从直流扩展到交流,从传统约瑟夫森电压基准过渡到可编程约瑟夫森电压基准的过程。着重探究了作为当下前沿研究领域的基于二进制划分阵列与脉冲驱动阵列的可编程电压基准这两大重要电学计量课题的发展历程、研究成果及其应用。最后概括了电压量子基准多年来的发展成果并对其未来发展方向加以展望。

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023?

In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter.In this report,as shown in the multi-model ensemble mean(MME)prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences,a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months,which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection,thus serving to modulate the winter climate in East Asia and North America.Despite some uncertainty due to unpredictable internal atmospheric variability,the global mean surface temperature(GMST)in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend.Specifically,the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter,and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991.Moreover,the necessary early warnings are still reliable in the timely updated mediumterm numerical weather forecasts and sub-seasonal-to-seasonal prediction.

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

胎儿视网膜母细胞瘤超声表现

目的观察胎儿视网膜母细胞瘤(RB)超声表现。方法回顾性分析7胎接受产前超声检查的单胎单侧RB胎儿资料,观察眼内病变二维、三维超声和血流成像表现。结果7胎眼内RB病灶均形态不规则、边缘不光整;6胎呈实性偏高回声,1胎呈无回声;6胎可见钙化,其中5胎点状钙化伴声影、1胎未伴声影;6胎呈分支状血流,与视网膜动脉连续,收缩期最高血流速度15.78~19.68 cm/s,阻力指数0.82~1.01,1胎呈稀疏点状;三维断层超声成像(TUI)显示4胎偏高回声肿块位于眼眶内,其余3胎未获得满意TUI。结论胎儿RB主要超声表现为眼内实性肿块伴钙化斑及高速高阻血流。

数字经济及技术创新与纺织业高质量发展

为探究数字经济和技术创新对纺织业高质量发展产生的影响并分析其中的作用机制和区域异质性,基于2013—2020年的省际面板数据,构建纺织业高质量发展的指标体系,计算数字经济以及纺织业高质量发展的程度,利用stata软件对数据进行回归分析和稳健性检验。回归结果表明:数字经济对纺织业高质量发展有显著促进作用;技术创新在数字经济驱动纺织业高质量发展的过程中产生部分中介作用,且数字经济对于我国东部和中部地区纺织业的高质量发展影响效果更为显着。

“三维”视角的财政专项转移支付资金审计研究

财政专项转移支付主要用于办理特定事项,引导地方贯彻落实党中央重大决策部署。作为实现特定经济和社会发展目标的重要政策工具,财政专项转移支付在实现国家重大战略和激励地方政府层面发挥着不可或缺的作用。然而,财政专项转移支付资金在实际运行过程中存在着目标偏离、政策悬浮和效能弱化等问题,且尚未形成完善的审计实务框架,亟待通过改进治理考核机制,形成治理效能合力。本文以合规审计与绩效审计相结合为视角展开专题化审计研究,借助形式、事实和价值维度的“三维”财政专项转移支付资金审计框架,探索财政专项转移支付资金在政策制定、规范实施和效益提升的治理路径,以期为今后财政专项转移支付资金审计工作的顺利开展提供理论依据与实践启示。

果蔬用冷库相变材料研制及其系统应用

相变蓄冷技术应用于冷库中,不仅可以利用谷电蓄冷产生经济效益,同时可以有效控制冷库温度,减少温度波动对果蔬造成的损失。本工作研制了一种相变温度可调、安全无害的麦芽糖醇/水低温相变材料。该材料根据麦芽糖醇配比的不同(质量分数1%~5%),可实现相变温度和相变潜热在0.73~1.62℃和281.43~325.82 J/g的范围可调。鉴于该材料存在的过冷问题,通过添加质量分数为1.2%的四硼酸钠作为成核剂,可将过冷度缓解至1.09℃。通过数值模拟研究蓄冷板的布置形式对冷库内温度分布和蓄冷时长的影响,发现顶置+侧置的蓄冷板布置形式相比顶置式和侧置式具有更好的储冷保鲜效果。此外,底部架空的货物布置方式可进一步延长对果蔬的保鲜时间。本工作结合材料研发和模拟研究表明,相变蓄冷技术可有效转移峰电时期的用能负荷,实现16 h的离网保鲜运行。

基于毛细管电泳的单基因病扩展性携带者筛查技术的建立及临床评估

目的建立并评估一种基于毛细管电泳技术的单基因病扩展性携带者筛查方法.方法采用多个基于毛细管电泳的技术检测1099例样本中24个基因相关的20种疾病中的448个致病变异并进行验证.结果毛细管电泳检测结果与其他方法验证的结果完全一致.在1099例受检者中,检出190例携带者,总体携带率为17.3%(190/1099),检出变异个数最多的是GJB2基因.在检测的1075例女性样本中,共检出8例为X连锁遗传病致病基因的携带者,携带率为7.4‰(8/1075).结论成功建立了一种基于毛细管电泳的扩展性携带者筛查技术.

膜下咸水滴灌水肥盐调控对棉花生长及产量的影响

【目的】研究膜下咸水滴灌条件下利用咸水资源高效的水肥盐综合管理模式。【方法】设置不同淡咸水混合比例和施氮量,观测不同生育期棉花生长指标,通过最终产量分析水氮利用效率,分析适宜的淡咸水混合比例和施氮量。【结果】棉花各项生长指标和产量受灌溉水矿化度和施氮量影响显著(P<0.05);随着灌溉水矿化度的增加,棉花各生长指标和籽棉产量显著降低(P<0.01),而增施氮肥能显著提高棉花各生长指标和籽棉产量(P<0.05)。将淡水与咸水混合灌溉,灌溉淡水利用效率显著提高(P<0.01);增施氮肥可以显著提高灌溉淡水利用效率(P<0.01)和水分利用效率(P<0.05),而偏肥生产力降低(P<0.01);再利用咸水与淡水混合灌溉时,除需控制混合灌溉水矿化度外,在增施氮肥提高产量的同时还需控制施氮量保证氮肥利用效率。【结论】淡咸比例4∶1灌溉合理的增施氮肥在减少20%淡水使用的情况下,产量(6829.80 kg/hm^(2))和水分利用效率(0.97 kg/m^(3))达到了对照处理水平。

超声心动图诊断先天性心耳瘤

目的 观察超声心动图诊断先天性心耳瘤(AAA)的价值。方法 回顾性分析2013年8月—2023年2月经手术确诊的3例AAA患儿,记录超声心动图所示AAA位置、大小、形态及与左心房连通情况,以及临床、心电图表现及CTA所见。结果 3例中,左AAA(LAAA)2例(序号1、2)、双侧AAA 1例(序号3)。序号1于孕38周经产前超声心动图诊断LAAA,出生后瘤体持续增大,9岁时见左心室壁受压、窦性心动过速,左心室射血分数(LVEF)55%。序号2于孕30周产前诊断LAAA,之后至生后1个月瘤体持续增大,伴窦性心动过速,LVEF 60%。序号3于2月龄时经超声心动图检出双侧AAA压迫双侧心室壁,伴频发短阵房性心动过速,LVEF 42%。3例均接受手术切除AAA,术后心率下降、LVEF提高。结论 超声心动图可用于诊断先天性AAA,对于评估瘤体大小、形态、血栓形成及周围组织受压等具有重要价值。

单侧肺动脉异常起源于动脉导管的产前超声心动图特征分析

目的总结单侧肺动脉异常起源于动脉导管的产前超声心动图特征。方法回顾性分析我院经产前胎儿超声心动图检查发现的4例单侧肺动脉异常起源于动脉导管胎儿的声像图资料,随访新生儿超声心动图、心脏CTA检查资料及引产儿尸检报告,总结其产前超声心动图特征。结果4例单侧肺动脉异常起源于动脉导管胎儿中,左位主动脉弓、右肺动脉起源于动脉导管3例,右位主动脉弓、左肺动脉起源于动脉导管1例。产前超声心动图示肺动脉分叉切面仅见一侧肺动脉,另一侧缺如;无名动脉冠状切面显示患侧远端肺动脉通过动脉导管连接无名动脉根部。3例继续妊娠,出生后超声心动图未显示患侧肺动脉,心脏CTA示肺动脉缺如、无名动脉根部囊状憩室;1例终止妊娠,引产后尸检显示左位主动脉弓、右肺动脉通过动脉导管连接无名动脉根部。结论应用产前超声心动图可准确诊断单侧肺动脉异常起源于动脉导管,患儿出生后患侧动脉导管即收缩、闭锁。

Another Year of Record Heat for the Oceans

Changes in ocean heat content(OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum.According to IAP/CAS data, the 0–2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ(1 Zetta Joules = 1021Joules);and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins(the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier–fresh gets fresher” pattern, also reached its highest level on record in 2022,implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Ni?a event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.

Will the Historic Southeasterly Wind over the Equatorial Pacific in March 2022 Trigger a Third-year La Niña Event?

Based on the updates of the Climate Prediction Center and International Research Institute for Climate and Society(CPC/IRI)and the China Multi-Model Ensemble(CMME)El Niño-Southern Oscillation(ENSO)Outlook issued in April 2022,La Niña is favored to continue through the boreal summer and fall,indicating a high possibility of a three-year La Niña(2020-23).It would be the first three-year La Niña since the 1998-2001 event,which is the only observed three-year La Niña event since 1980.By examining the status of air-sea fields over the tropical Pacific in March 2022,it can be seen that while the thermocline depths were near average,the southeasterly wind stress was at its strongest since 1980.Here,based on a quaternary linear regression model that includes various relevant air-sea variables over the equatorial Pacific in March,we argue that the historic southeasterly winds over the equatorial Pacific are favorable for the emergence of the third-year La Niña,and both the anomalous easterly and southerly wind stress components are important and contribute~50%of the third-year La Niña growth,respectively.Additionally,the possible global climate impacts of this event are discussed.