Foodborne doping and supervision in sports

Cases of foodborne doping are frequently reported in sports events and can cause severe consequences for athletes.The foodborne doping can be divided into natural endogenous and artifi cially added foods according to the sources,including anabolic agents,stimulants,diuretics,β-blockers,β2 agonists and others.In order to control foodborne doping,chromatographic technique,immunoassay,nuclear magnetic resonance,biosensor technology,pyrolytic spectroscopy,comprehensive analysis and electrochemical analysis have usually used as analytical and inspection strategies.Meanwhile,the legislation of anti-doping,the improvement of testing standard and technology,and the prevention and control of food safety,as well as the improvement of risk perception of athletes are highly necessary for achieving the effective risk control and supervision of foodborne doping,which will be benefi cial for athletes,doctors and administrators to avoid the risks of foodborne doping test and reduce foodborne doping risks for the health of athletes.

Research on the intelligent supervision and operation platform of railway real estate

Railway real estate is the fundamental element of railway transportation production and operation.Effective management and rational utilization of railway real estate is essential for railway asset operation.Based on the investigation of the requirements of railway real estate management and operation,combined with Beidou positioning,GIS(Geographic Information System),multi-source data fusion and other cutting-edge technologies,this paper puts forward the multi-dimensional dynamic statistical method of real estate information,the identification method of railway land occupation and the comprehensive evaluation method of real estate development and utilization potential,and build the railway real estate supervision and operation platform,design the function of the platform,so as to provide intelligent solutions for the railway real estate operation.

Routine Supportive Supervision and Management of Medicines and Other Health Products and Technologies in Vihiga County, Kenya

Health Products and Technologies (HPTs) are pivotal for an efficient health system. Availability and accessibility to affordable health products are critical indicators towards achieving universal health coverage. Routine supportive supervision, performance monitoring, recognition of efforts and client feedback are vital activities toward health supply chain system strengthening. This is a descriptive paper that describes a model of integrated commodity supportive supervision, and mentorship and its impact on various outcomes of health commodity management. Data were abstracted from the standardized scored checklists used during integrated commodity supportive supervision and supply chain audit in public health facilities in Vihiga County. Scores for the period 2020 to 2022 were analyzed on the eight key areas of interest. The analysis was done using Statistical Package for Social Sciences (SPSS version 26). Results are interpreted at 95% Confidence interval. This paper also shares findings from both quantitative and qualitative data from client exit and facility managers’ interviews. Six complete rounds of supervisions, three clients and service providers’ interviews, and three annual award events have been conducted. We observed trends across six data collections points and compared the results at first point or baseline (January-June 2020) to the results at the last point or end line (April-June 2022). Findings show significant improvements on the eight parameters in terms of mean scores as follows: resolution of issues from previous visits by 35.06% (46.75% - 81.81%);storage of HPTs by 17.41% (68.72% - 86.13%);inventory management by 28.16% (42.67% - 70.83%);availability and use of commodity data management information systems (MIS) tools by 22.39% (74.40% - 96.79%);verification of commodity data by 25.61% (65.56% - 91.17%);availability of guidelines and job aids for commodity management by 46.28% (36.65% - 82.93%). There was an improvement on the mean score on accountability by 20.22% (58.58% - 83.51%). The composite (final) score improved by 28.33% (56.19% - 84.52%). There was progressive narrowing of the standard deviations on all the indicators across the study period. This demonstrates that there is standardization of practices and positive competition among all the public health facilities. There were significant improvements on all the eight indicators. Routine integrated commodity supportive supervision has proven to be an effective high impact intervention in improving management of health products and technologies in Vihiga County, Kenya.

Model-constrained and data-driven double-supervision acoustic impedance inversion

Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.

Human-pose estimation based on weak supervision

Background In computer vision,simultaneously estimating human pose,shape,and clothing is a practical issue in real life,but remains a challenging task owing to the variety of clothing,complexity of de-formation,shortage of large-scale datasets,and difficulty in estimating clothing style.Methods We propose a multistage weakly supervised method that makes full use of data with less labeled information for learning to estimate human body shape,pose,and clothing deformation.In the first stage,the SMPL human-body model parameters were regressed using the multi-view 2D key points of the human body.Using multi-view information as weakly supervised information can avoid the deep ambiguity problem of a single view,obtain a more accurate human posture,and access supervisory information easily.In the second stage,clothing is represented by a PCA-based model that uses two-dimensional key points of clothing as supervised information to regress the parameters.In the third stage,we predefine an embedding graph for each type of clothing to describe the deformation.Then,the mask information of the clothing is used to further adjust the deformation of the clothing.To facilitate training,we constructed a multi-view synthetic dataset that included BCNet and SURREAL.Results The Experiments show that the accuracy of our method reaches the same level as that of SOTA methods using strong supervision information while only using weakly supervised information.Because this study uses only weakly supervised information,which is much easier to obtain,it has the advantage of utilizing existing data as training data.Experiments on the DeepFashion2 dataset show that our method can make full use of the existing weak supervision information for fine-tuning on a dataset with little supervision information,compared with the strong supervision information that cannot be trained or adjusted owing to the lack of exact annotation information.Conclusions Our weak supervision method can accurately estimate human body size,pose,and several common types of clothing and overcome the issues of the current shortage of clothing data.

Strategic interaction between institutional investors and supervision department:a theoretical analysis of low‑price collusion in SBIC

We introduce evolutionary game method to analyze low-price collusion in inquiry market of Sci-Tech Innovation Board of China(SIBC)from the perspective of strategic interaction between large institutional investors(LIIs),small and medium-sized institutional investors(SMIIs),and supervision department(SD).The results show that supervision behaviors of SD,and quotation behaviors of institutional investors,are subject to supervision conditions.Under the condition that benefits of tough supervision are lower a lot than minimum benefits of light supervision(light supervision condition),SD will choose light supervision and institutional investors will turn to illegal quotation in response.Finally,a steady-state equilibrium with low-price collusion will form in SIBC’s inquiry market even with a large supervision penalty for illegal quotation.On the contrary,under the condition that benefits of tough supervision are higher a lot than maximum benefits of light supervision(tough supervision condition)and with a large penalty for illegal quotation,SD and institutional investors will choose tough supervision and legal quotation.Further numerical simulations under light supervision condition show that:(1)High-price culling rule will become a booster for low-price collusion and accelerate SMIIs’evolutionary process to imitative quotation.(2)Blindly increasing penalties for illegal quotation or reducing the culling rate is not an appropriate approach to solve the problem of low-price collusion since it cannot shift supervision condition from light into tough and make SD supervise toughly.(3)Institutional investors’choices of quotation strategies are more volatile and highly susceptible to supervision behaviors of SD when facing exogenous uncertainty.Therefore,the keys to solving the problem of low-price collusion are shifting supervision condition from light into tough through increasing incremental benefits of tough supervision,and providing institutional investors with a stable and predictable supervision policy.In conclusion,the creation of a fair inquiry market doesn’t only depend on restraint and punishment to institutional investors,but also requires the establishment of supervision mechanism those are compatible with market-based inquiry.

On the Expansion and Realization of the Right to Environmental Information in Environmental Protection Supervision

As an innovation in the environmental governance system that breaks the traditional hierarchical structure,environmental protection supervision has not only played a significant role in protecting tangible environmental rights but also expanded the basic scope of the right to environmental information—part of procedural environmental rights.In the supervision of environmental protection,the objects of the right to environmental information and the subjects of the obligation to provide environmental information have been both expanded,with the focus shifting from government information to Party information and from administrative organs to Party organs.This vividly demonstrates the Communist Party of China’s concrete efforts to protect human rights in the field of the endeavor to build an ecological civilization.At present,the realization of the right to environmental information in environmental protection supervision still faces problems such as insufficient standards and norms,disordered practice and operation,and lack of liability guarantee.In this context,based on renewing relevant subjects’cognition of the right to know in environmental protection supervision,we should further improve and specify the rule for disclosing information about environmental protection supervision,rationally distribute the obligations for information disclosure in environmental protection supervision,and clarify the accountability rules for violating relevant requirements for information disclosure,so as to promote the overall development of the environmental protection supervision system while guaranteeing the realization of the right to environmental information.

Supervision of Public Opinion under the Background of Social Co-governance-Take the Changsheng Vaccine Incident as an Example

Objective To provide reference for the news media to give play to the role of public opinion supervision in time based on the background of drug safety and social co-governance.Methods The method of case analysis was used to make a retrospective study on the Changsheng vaccine incident in 2018.Then the role of mainstream media,pharmaceutical media,and self-media in the supervision of public opinion was investigated.Results and Conclusion Both mainstream and pharmaceutical media played an excellent role in supervising the Changchun Changsheng vaccine incident.However,the content published by some pharmaceutical media was hard to understand by ordinary people.Besides,the role of self-media in public opinion supervision was polarized.Some self-media closely kept pace with mainstream media in public opinion supervision.Other self-media unilaterally pursued the click rate,publishing false information to guide wrong public opinion.The news media should optimize the supervision efficiency of drug safety.On the one hand,pharmaceutical media should pay attention to the fact that readers may not understand the difficult terms because they are not professional.On the other hand,self-media practitioners should improve their professional quality so that they will not publish some fake news to mislead public opinion.

迈向智能监察:人工智能赋能国家监察的逻辑与进路

新一代人工智能的兴起为国家治理注入新动能,为国家监察工作的数字化、智能化指明方向。人工智能赋能国家监察具有以“数据全覆盖”实现“监察全覆盖”、从人力监督到智能监督等现实价值。受限于国家监察的初创性与人工智能的局限性,国家监察智能化呈现阶段性特征。国家监察的智能化发展围绕数据、算法、算力三大核心要素,实现监察“块数据”构建、面向国家监察的语言模型嵌入及算力资源的优化供给。针对人工智能存在的数据隐私、数据安全等技术性风险,可从人工智能政府采购的制度化与规范化、建构监察对象数据隐私与安全保护机制和人工智能监察应用的纠错与救济机制等方面予以防范和化解。

公共数据授权运营数据要素流通监管的理念、模式与发展策略

[目的/意义]加强授权运营公共数据要素流通全生命周期的监管是其安全、高质量、平等和包容创新利用的重要保障。[方法/过程]文章采用了文献研究法和案例分析法,阐述了公共数据授权运营数据要素流通监管的含义、相关研究以及监管理念,重点构建和分析了其监管模式和发展策略。[结果/结论]提出公共数据授权运营需要建立全生命周期的数据质量管控机制,构建可用不可见与全程可追溯的科技监管模式,促进授权运营公共数据多元共享、严格规制算法垄断行为以及以监管沙盒优化与促进“包容审慎”监管模式的发展策略。

如何实现“黑箱”下的算法治理?——平台推荐算法监管的测量实验与策略探索

近年来,平台推荐算法的快速发展和广泛应用深刻改变了互联网信息内容的供给方式,同时也引发了一系列算法风险与现实问题。平台推荐算法治理与监管成为政府规范算法应用的重点内容之一,无论是算法备案制度的探索,还是实现算法透明化的设想,均面临着一定的困难和挑战。在不打开算法“黑箱”的前提下,平台推荐算法规制与监管是否有可行之道?论文基于机器行为学思想,采用实验方法,以用户视角对推荐结果进行跟踪记录,通过实验数据的对比分析,验证了平台推荐算法结果差异的可测性。基于实验结果,论文提出了通过对不同平台推荐结果进行大规模数据测试和检验,测量平台推荐算法运行逻辑与推荐效果,从而实现“黑箱”下有效的逆向监管,以期丰富未来算法治理的选择。

纪检监察学科话语体系的百年构建:历史演进与原创贡献

构建中国特色纪检监察学科话语体系是中国共产党矢志不渝的奋斗目标。在革命、建设和改革开放实践中,中国共产党根据执政历史方位、肩负主要任务和面临突出问题的变化,坚持把马克思主义政党学说与中华优秀传统监察文化结合起来,以纪检监察理论创新推动制度创新和实践创新,构建了纪检监察学科话语体系的“四梁八柱”,奠定了纪检监察学科发展的坚实基础。中国共产党纪检监察话语体系的百年构建作出了原创性贡献,这就是开辟了纪检监察学科话语构建的中国道路,积累了纪检监察学科话语体系构建的中国经验,形成了纪检和监察合署办公的中国方案,赢得了与资产阶级政党理论竞争的中国优势。

融合大数据的校园公权力监督机制研究与模型构建

通过运用大数据技术,构建了一种校园公权力监督模型(CPASM),旨在提升教育资源配置的透明度和公平性,以及优化教学与行政决策。利用案例分析法,聚焦于A学院计算机应用技术专业,探讨了大数据在财务管理、教学质量评估和行政决策过程中的应用。CPASM模型结合时间序列分析和外部因素分析,应用自回归积分滑动平均(ARIMA)模型处理数据,同时将校园公权力动态变化纳入考量。CPASM模型的拟合与验证结果表明,其预测的均方误差(MSE)、均方根误差(RMSE)较低,确定系数(R^(2))接近1,准确地描绘了财务趋势,有助于管理层进行财务规划和资源配置。

潜在内分泌干扰风险防晒剂的监管及其使用情况分析

欧盟对具有潜在内分泌干扰风险的化妆品原料进行筛查并建立了化妆品原料优先评估清单,该清单包含了4个欧盟化妆品指令准用防晒剂。文章以优先评估清单中的防晒剂为研究对象,对其在欧盟、美国等国家(地区)的监管情况和在我国的使用情况进行概述和分析,并汇总欧盟消费者安全科学委员会的再评估结果。经研究调查发现,优先评估清单中防晒剂在我国的法规限值与美国、日本和韩国规定基本一致,但部分防晒剂限值较欧盟新修订限值高,可能存在安全风险。建议监管部门综合评估上述防晒剂的安全风险、实际使用情况和行业发展等因素,通过进一步评估和细化法规限值,以期更好地保障民众用妆安全。

弱监督场景下的支持向量机算法综述

支持向量机(Support Vector Machine,SVM)是一种建立在结构风险最小化原则上的统计学习方法,以其在非线性、小样本以及高维问题中的独特优势被广泛应用于图像识别、故障诊断以及文本分类等领域.但SVM是一种监督学习算法,它旨在利用大量的、唯一且明确的真值标记样本来训练学习器,在不完全监督、不确切监督以及多义监督等弱监督场景下难以取得较好的效果.本文首先阐述了弱监督场景的概念和SVM的相关理论,然后从弱监督场景角度出发,系统地梳理了目前SVM算法的研究现状和发展,包括基于半监督学习、多示例学习以及多标记学习的方法;其中基于半监督学习的方法根据数据假设可细分为基于聚类假设和基于流形假设的方法,基于多标记学习的方法根据解决方案可细分为基于示例水平空间、基于包水平空间以及基于嵌入空间的方法,基于多标记学习的方法根据处理思路可细分为基于问题转换和基于算法自适应的方法;随后,本文总结了部分代表性算法在公开数据集上的实验结果;最后,探讨并展望了未来可能的研究方向.

商业银行设立理财子公司能够实现风险隔离吗?

本文以中国商业银行设立理财子公司为准自然实验,基于2018—2021年84家银行的季度财务数据,采用渐进双重差分模型(DID)考察商业银行设立理财子公司的风险隔离效应。研究发现:设立理财子公司显著降低了母公司商业银行的风险承担,能够实现理财业务与其他业务的风险隔离,且设立时间越长,风险隔离效应越显著。异质性检验和机制分析表明,这种风险隔离效应在城商行与农商行中最弱;“去嵌套、降杠杆”和“去池化、缓错配”是实现风险隔离的主要机制。对母公司商业银行和理财子公司并表的进一步分析发现,设立理财子公司不能降低银行控股集团的整体风险承担,仅能实现风险隔离。这些研究发现对于完善商业银行内部控制和外部监管具有重要启示。

因“需”督导:挥好本科教育教学“督”和“导”的指挥棒

随着我国进入新时代,国家对高等教育人才的培养质量提出更高的要求。如何建立科学有效的教学质量评价体系是每个高校都要解决的紧迫问题。《深化新时代教育评价改革总体方案》中指出,教育评价事关教育发展方向,有什么样的评价指挥棒,就有什么样的办学导向。各高校要深刻理解并深入贯彻落实习近平总书记关于教育的重要论述,努力完善教学质量评价体制机制,扭转不科学的教育评价导向。该文分析“督”和“导”的含义、属性、职能,并结合其内在规律,系统阐述本科教育教学督导工作的职责、理念、督与导的辩证关系,认为要以导为主,督导结合,因“校”制宜做好本科教育教学督导工作。

基于半监督学习的网络异常检测研究综述

网络流量数据的获取较为容易,而对流量数据进行标记相对困难。半监督学习利用少量有标签数据和大量无标签数据进行训练,减少了对有标签数据的需求,能较好适应海量网络流量数据下的异常检测。文章对近年来的半监督网络异常检测领域的论文进行深入调研。首先,介绍了一些基本概念,并深入剖析了网络异常检测中使用半监督学习策略的必要性;然后,从半监督机器学习、半监督深度学习和半监督学习结合其他范式三个方面,分析和比较了半监督网络异常检测领域近年来的论文,并进行归纳和总结;最后,对当前半监督网络异常检测领域进行了现状分析和未来展望。

基于血站管理信息系统的业务全流程监督管理体系构建

目的 血站管理者可以实时对血站全流程关键业务运行态势进行全流程掌握,实现对血站业务全流程的监督管理,提升业务工作效率和保障血液质量。方法 从编制依据、血站业务范围、岗位监督管理内容、总体框架设计、管理系统和监督管理界面设计、物理数据库设计、程序开发和上线调试等多个方面,建立业务全流程监督管理体系,并将其与血站管理信息系统进行对接,及时、全面地记录从采血到供血全过程的业务流程关键指标信息,通过手机APP的方式进行展示和管理,于2023年投入血站使用后对2023年和2022年总采集量、总制备量、总供应量,以及检验不合格报废率和非检验不合格报废率(不含乳糜)进行统计分析。结果 建立了基于血站管理信息系统的业务全流程监督管理体系的手机APP,实现了“移动办公”式监督管理,2023年正式投入使用后,2023年总采集量、总制备量和总供应量均高于2022年,分别增长5.88%(13 247/225 454 U)、4.73%(24 156/510 698 U)、6.70%(34 814/519 914 U),检验报废率(0.54%,2 868/534 854 U)显著低于2022年(0.60%,3 047/510 698 U)(P<0.01),非检验报废率(不含乳糜)(0.12%,649/534 854 U)显著低于2022年(0.19%,991/510 698 U)(P<0.01)。结论 基于血站管理信息系统的业务全流程监督管理体系的构建,可以满足血站不同管理者不限时间和地点的标准化管理服务需求,实现对业务全流程的监督管理,还可以持续提升血站业务工作和血站管理的规范化、科学化水平,保障血液资源供应。

努力构建党内全过程监督体系

长期以来,我们重视自上而下的监督,不够重视自下而上的监督,没有构建起全过程监督体系。造成领导干部特别是“一把手”贪腐问题屡禁不止。要解决这个问题,必须构建并不断完善党内全过程监督体系。全过程监督体系,坚持党中央的集中统一领导,坚持纪委监委专门监督责任,坚持民主监督与集中监督的有机结合,坚持自上而下监督与自下而上监督相结合。当务之急,是要建立健全党内全过程监督制度,进一步明确监督主体、监督对象、监督体制机制。发挥同级党组织相互监督的作用。改进自下而上的民主监督。积极推进对“一把手”和领导班子的监督。加强领导班子成员之间相互监督。加强各级党委对监督工作的领导。强化对干部管理工作的监督,完善干部选举和任用工作监督、“一把手”和领导班子决策监督。加强对党内全过程监督体系构建的领导与管理。