The impact of the Rural Minimum Living Standard Guarantee(Rural Dibao)Program on child nutrition outcomes

The Rural Minimum Living Standard Guarantee(Rural Dibao)is an important unconditional cash transfer program to alleviate poverty in rural China.Despite the importance of children’s nutrition in breaking poverty cycles,little is known about the impact of Rural Dibao on child nutrition outcomes.Using China Family Panel Studies(CFPS),this paper examines the effects of Rural Dibao on child nutrition outcomes and investigates potential pathways and heterogeneous effects.We exploit propensity score matching and difference-in-differences techniques to evaluate the effects of the Rural Dibao program on child nutrition outcomes.Our results suggest that Rural Dibao significantly impacts the nutrition outcomes of children up to 15 years of age.Specifically,our results suggest that Rural Dibao improves child height-to-age z-scores by 1.05 standard deviations and lowers the probability of stunting by 11.9 percentage points.Additional analyses suggest that increased protein intake is the main pathway through which Rural Dibao participation contributes to better nutrition outcomes.We also find that the effect of the program is more pronounced among girls,children who are non-left-behind or live with highly educated mothers,and those from low-income families and poor areas.Our findings suggest that Rural Dibao participation helps improve child nutrition outcomes through improving diet quality.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Joint computation offloading and parallel scheduling to maximize delay-guarantee in cooperative MEC systems

The growing development of the Internet of Things(IoT)is accelerating the emergence and growth of new IoT services and applications,which will result in massive amounts of data being generated,transmitted and pro-cessed in wireless communication networks.Mobile Edge Computing(MEC)is a desired paradigm to timely process the data from IoT for value maximization.In MEC,a number of computing-capable devices are deployed at the network edge near data sources to support edge computing,such that the long network transmission delay in cloud computing paradigm could be avoided.Since an edge device might not always have sufficient resources to process the massive amount of data,computation offloading is significantly important considering the coop-eration among edge devices.However,the dynamic traffic characteristics and heterogeneous computing capa-bilities of edge devices challenge the offloading.In addition,different scheduling schemes might provide different computation delays to the offloaded tasks.Thus,offloading in mobile nodes and scheduling in the MEC server are coupled to determine service delay.This paper seeks to guarantee low delay for computation intensive applica-tions by jointly optimizing the offloading and scheduling in such an MEC system.We propose a Delay-Greedy Computation Offloading(DGCO)algorithm to make offloading decisions for new tasks in distributed computing-enabled mobile devices.A Reinforcement Learning-based Parallel Scheduling(RLPS)algorithm is further designed to schedule offloaded tasks in the multi-core MEC server.With an offloading delay broadcast mechanism,the DGCO and RLPS cooperate to achieve the goal of delay-guarantee-ratio maximization.Finally,the simulation results show that our proposal can bound the end-to-end delay of various tasks.Even under slightly heavy task load,the delay-guarantee-ratio given by DGCO-RLPS can still approximate 95%,while that given by benchmarked algorithms is reduced to intolerable value.The simulation results are demonstrated the effective-ness of DGCO-RLPS for delay guarantee in MEC.

Guarantee Strategy for the Safety of Agricultural Industry in Hunan Province

The safety of agricultural industry in Hunan Province shows an upward trend from"basically safe"to"very safe",but the state in the"safe"or"very safe"range is still unstable.In view of this,Hunan Province should guarantee the agricultural production ability,cultivate and enhance the core competitiveness of agriculture,firmly grasp the agricultural control power,attach importance to the export quality of agri-cultural products and other aspects to ensure the safety of agricultural industry.

Study on Urban Resilience Based on the Analysis of Supply Guarantee Facilities during Epidemic Closure—A Case Study of Shanghai in 2022

In the case of major public emergencies, the ability of cities to resist shocks becomes very important and reflects urban resilience. This paper selected the supply guarantee facilities during the city-wide lockdown of Shanghai during March-May 2022 due to COVID-19 pandemic as the research object. In this research, the per capita supply guarantee capacity and supply guarantee overlay intensity were analyzed based on the official list of facilities, and the actual role of the supply guarantee facilities was investigated through a public research questionnaire. The thermodynamic diagram map that was generated based on phone visits reflected the actual distribution of the population. Then the level of “supply guarantee resilience” was evaluated and graded for each district of Shanghai. It was concluded that the overall level of supply guarantee resilience was high in the central city, divergence in the near suburban districts, and generally low in the remote suburban districts. Based on this, the paper summarized the problems of supply guarantee revealed in Shanghai during the epidemic lockdown as well as proposed strategies to improve the resilience of similar scenarios in the future. With the help of big data and public research tools, this paper aimed to provide ways and methods to evaluate the resilience of cities under major public emergencies.

树立大农业观、大食物观构建整体性的国家重要农产品供给保障战略

构建一套整体性的农产品供给保障战略,是居民食物消费结构从“生存型”“温饱型”向“发展型”“享受型”转变的需要,是避免不同品类农产品保障任务相互冲突、顾此失彼的需要,是利用农产品品类间功能替代关系扩大政策选择空间的需要,是设置合理精准任务目标引导保供政策实施的需要。构建国家重要农产品供给保障战略应树立大农业观、大食物观,聚焦国家食物营养安全,根据不同农产品品类的功能作用差异,建立分层次的重要农产品供给保障体系,聚焦重点品类,强化要素支撑,完善市场机制,优化进口布局,保障重要农产品充足、持续、稳价、高效供给。

我国重要农产品供需变化趋势与供给保障能力提升策略

基于对我国重要农产品生产、消费和进口历史变化情况的分析,以及对2035年前变化趋势的预测,认为我国重要农产品供给保障面临国内增产边际效应递减和利用国际市场风险增大的双重挑战,应从统筹国内和国际两个大局、发展和安全两件大事出发,谋划好现代化新征程重要农产品供给保障思路。一方面,应从供需两侧入手扩产能、控消费,构建农业综合生产能力内在增长机制,针对农民务农种粮和地方重农抓粮逻辑采取差异化扶持政策,推进节粮减损、倡导节约消费;另一方面,应实施农产品进口多元化战略,提高海外供应链稳定性可靠性;此外,还应推动建立统一、联动的全国农产品大市场,完善农产品储备调节制度。

我国共同富裕评价指标体系及测度——基于省级行政区与区域层面的探讨

扎实推动共同富裕的重要基础是科学构建评价指标体系,并准确测度共同富裕水平。本文强调整体思维、多维思维、长线思维和底线思维,系统梳理共同富裕的理论内涵与统计含义,构建由富裕性、共享性与托底性三个一级指标组成的共同富裕评价指标体系,并采用政府统计部门宏观数据与中国家庭追踪调查(CFPS)的大样本微观调查数据,在省级与区域层面测度2010—2018年共同富裕的实现程度。研究发现,从省级层面看,共同富裕指数持续向好,省级行政区之间的共同富裕指数呈收敛趋势;从一级指标看,富裕性指数与托底性指数稳步提升,但共享性指数提升乏力;省际富裕性指数与共享性指数呈比较明显的倒U型关系。从区域层面看,东部、中部、西部、东北地区之间在共同富裕指数上呈现明显的收敛趋势;南方与北方地区之间在共同富裕指数上的差距则呈加速扩大态势,但北方地区共享性维度的指数却一直高于南方地区。本文丰富了构建共同富裕评价指标体系的理论与方法,并将共同富裕的测度细化到省级与区域层面,为刻画共同富裕指数的省际差异、区域差异与时序变动,找准共同富裕的着力点并优化相关政策提供重要借鉴。

碳中和目标下我国森林碳汇功能实现的困境检视与法治保障

森林是水库、钱库和粮库,同时森林生态系统固碳增汇功能在实现碳中和目标中的作用也愈发凸显,成为重要的“碳库”。然而,我国森林碳汇功能实现存在因法治化程度较低、法律体系不健全且位阶低而造成的法律困境,以及因存在产权、资金、技术、风险障碍而造成的事理积弊。因应之策在于:一方面要积极推进国家应对气候变化专门立法、推进森林碳汇相关法律修订与制定、加强森林碳汇司法保障以巩固提升森林碳汇能力;另一方面要明晰森林碳汇的产权与收益归属,建立健全森林碳汇金融服务体系,提升森林碳汇项目技术实现能力、发展森林碳汇项目风险分散机制以消弭森林碳汇功能实现的障碍。

中国式现代化背景下师德师风建设的关键路径

在全面推进中国式现代化背景下,大力加强师德师风建设是打造高质量教师队伍的重中之重。精神引领、文化涵养和制度保障是中国式现代化背景下师德师风建设的关键路径。精神引领是行动自觉,通过教师内在性的精神领悟与外在化的公共呈现,让教育家精神成为每一位教师的自觉追求;文化涵养是必由之路,立足中华文化传统,秉承“学以成人”的师德涵养理念,构建“时时觉察”的成长机制,追求“立己达人”的理想境界,激发教师的内在动力;制度保障是重要支撑,基于中华文化对人性的洞察,通过公正、合理和健全的制度保障,真正实现对每一位教师的真切关怀。三者相合共生、相辅相成,贯穿中国式现代化背景下师德师风建设的全过程。

幼儿园教师待遇保障的逻辑遵循、困境检视与立法保障

建设一支高素质善保教的幼儿园教师队伍,是新时期党和国家的重要战略。长期以来,我国幼儿园教师法律身份不明、整体工资收入水平低、五险一金缴纳不足、城乡地区待遇水平差距大等问题突出,严重影响队伍稳定性与职业吸引力,亟待立法破解。为此,完善幼儿园教师待遇保障的法律体系应进一步凸显幼儿园教师具有公共性的专业人员定位,制定、完善工资定价制度并明确最低工资标准,明确五险一金足额足项缴纳的立法规定与法律责任,完善农村幼儿园教师待遇保障机制。

大数据下企业供应链风险管理与竞争情报融合模型构建--以华为公司为例

[研究目的]国际经贸对抗环境下,中美贸易摩擦将持续升级,国家层面的技术创新竞争使得企业面临的供应链风险大幅提升。同时,大数据改变了供应链风险管理模式,而竞争情报可以从理论、技术和方法等方面提升大数据下企业供应链风险管理能力,因此大数据下企业供应链风险管理与竞争情报的融合研究具有重要意义。[研究方法]采用文献分析、案例研究等方法,分析供应链风险管理与竞争情报的异同点,继而论证大数据下供应链风险管理与竞争情报融合的可行性和必要性,再辅之以标杆企业华为的供应链中断风险事件验证,最终构建大数据下华为供应链风险管理与竞争情报融合模型,并分析运行维护此模型的保障要素。[研究结论]研究表明,基于战略、组织、制度、技术和资源五要素的共同保障,大数据下供应链风险管理与竞争情报的融合能够实现供应链风险管理的全面性、及时性和有效性。

中国稀散金属矿资源概况

中国稀散金属资源丰富,在全球占有重要的战略地位。对中国542处矿产地(包括759个矿床/点)的稀散金属资源调查数据分析表明,目前中国已查明稀散金属资源储量102.82万t,其中,镓矿44.65万t,锗矿1.39万t,铟矿2.52万t,铊矿2.96万t,镉矿47.12万t,硒矿2.56万t,碲矿1.53万t,铼矿893.00 t。中国稀散金属资源具有如下特征:①分布广泛,但主要集中在西南地区、中南地区和华北地区,云南、河南、广西、内蒙古、山西、贵州、广东等是稀散金属资源较丰富的省(区);②独立矿床极少,但资源储量占到全国稀散金属资源总量的6.64%;③矿床规模以中、小型为主,但大型矿床和超大型矿床资源储量占全国稀散金属资源总量的80%以上;④主要伴生在铅锌多金属矿、铝土矿和煤矿中,3类矿床中的稀散金属资源储量占全国稀散金属资源总量的80%左右;⑤总体综合利用率较低。中国镓、锗、铊资源的储备充足,但硒、碲、铼、铟、镉资源相对缺乏。

城投信仰与城投债的定价

探讨了如何估计地方政府融资平台发行的城投债的隐性担保问题。尽管新的《预算法》规定“地方政府不再为任何机构提供担保”,但城投债的市场价格表明,投资者仍然相信地方政府会为城投债提供隐性担保,即存在所谓的“城投信仰”。将城投信仰定义为市场价格中所隐含的“政府为城投债提供担保的概率”,分析了政府提供担保和无担保两种状态下的城投债价格。利用期权定价理论给出了考虑城投信仰的城投债定价公式,并给出利用城投债交易价格数据测算城投信仰的方法和实例。本文的方法基于城投债的产品层面而非行业层面,在城投信仰面临分化的情况下,可更深入地研究政府隐性担保对城投债价格的影响,有助于更理性地看待和评价城投债的隐性担保问题。

化工学科研究生创新能力培养模式及保障机制研究

当今时代,创新研究生培养在于培养具有创新能力与实践能力的高端人才。仲恺农业工程学院化学化工学院根据化工学科特点,以提高研究生的创新能力为目标,完善了研究生创新课程体系;更新了教师的教育观念;建立了严格健全的考核和评价制度;加强了导师队伍建设;建立了多方位、多层面的研究生奖助体系;加强了国际合作与交流,创新了化工学科研究生培养模式和保障机制,提升研究生学术创新能力。

中国金融稳定保障基金最优规模度量和配置研究--基于宏观经济部门非预期损失的分析

金融稳定保障基金是建设金融强国战略背景下维护和实现金融稳定的重要工具。通过编制2008—2020年中国31个省(区、市)金融部门、政府部门、非金融企业部门和家庭部门宏观或有权益资产负债表,运用宏观在险价值方法度量各地区、各部门资产和负债市场价值的非预期损失,估算能充分覆盖重大风险敞口的金融稳定保障基金最优规模和配置比例。研究发现,中国金融稳定保障基金的最优相对规模从大到小依次是:政府部门、非金融企业部门、家庭部门和金融部门。其中,非金融企业部门和家庭部门地区间规模差异显著,东部地区相对规模水平较低,西部地区较高。政府部门作为公共部门具有对其他经济主体的隐性担保责任,最终承担其他部门产生但未抵补的金融风险,是金融稳定的“最后一道防线”。为了更好地防范和化解金融风险,维护金融稳定,金融稳定保障基金应当确定风险适配的目标规模,并实现多层级分部门的有效配置,最终形成全方位、多层次的金融稳定保障基金配置体系。

区域协调发展与市场统一的法治保障

实现中国式现代化,需要统筹解决区域协调发展与市场统一问题,并加强相应的法治保障,对此有必要在“区域—市场—法治”的框架下展开分析。以东北地区为例,基于该地区在我国的重要地位及其存在的发展问题,应进一步推进市场化改革,并将其区域发展与区域市场建设有机结合,进而促进全国的区域协调发展和统一大市场建设。针对上述领域既往存在的法治问题,应明晰制度优化的重点,加强经济政策与经济法治的有效协调,从而在法治框架下推动区域协调发展与市场统一的相互促进,这有助于持续推进现代化经济体系建设和国家的整体现代化,深化区域经济学、经济法学、发展法学等领域的理论研究。

罕见病寻医找药多功能智慧化药学服务平台的建立与应用

目的加强罕见病患者合理用药管理,提高用药综合保障水平,以解决罕见病用药痛点问题。方法借助移动信息化技术,开发广东短缺药品咨询平台应用程序,并建立罕见病患者智慧化多功能的药学信息服务。结果作为中国首个整合省级罕见病医药资源的大数据平台,通过建立完善、专业的罕见病移动式药学服务体系,创新性实现线上线下“医+药+患”三方闭环。结论该药学服务平台为罕见病患者搭建起寻医找药的桥梁,助力健康中国高质量发展。

高校美育思政价值的彰显及其保障机制

高校美育所具有的独特思政价值源于美本身所具有的鲜明政治属性,体现在美的标准具有时代性、民族性和阶级性。审美能力培养是大学生社会化的重要内容,美育是引导学生树立科学信仰的过程。从功能上看,高校美育在塑造和引导大学生的崇高价值观、营造崇德向善的社会风尚、传承创新中华美育精神方面同样彰显了无可替代的思政价值。保障高校美育思政价值落地,须提高美育教师教学素养,增强思政引领自觉;美育与思政教育协同,构建育人共同体;加强审美实践引领,发挥美育教化作用,多措并举,提升高校美育立德树人成效。

教师作为有价值的专业人员——经合组织“教师教学国际调查”(TALIS)的生成与运行

“教师教学国际调查”(TALIS)作为经合组织开展的大型国际教师调查研究项目,其产生和发展与所处国际背景和经合组织自身理念密切相关。由于经合组织是一个不具有强制约束力的机构,“教师教学国际调查”的运行受经合组织的软性治理及竞争比较这两大非正式机制的影响。行政资源的有效利用、集聚知识的能力、过去的成功经验这三条路径保障了“教师教学国际调查”的成功运行,使之获得较大关注和影响力。“教师教学国际调查”有一定的局限性,要在认识其作用的基础上,考虑我国的现实国情和历史文化背景,改进和完善我国的教师发展政策。