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关键词： 隐私政策   自我表露   隐私风险记忆   社交媒体信任   隐私政策有效性感知   隐私政策内容理解  

摘要： 传播技术的每次飞跃都能给人类带来历史性的变革,电话改变了人们的通讯距离,网络诞生了“地球村”,社交媒体使得随时沟通变得可能。社交媒体因其便利性、即时性、趣味性特征突出,广受青睐。但看似充满了好处的社交媒体,却暗藏危机。社交媒体服务提供商既是服务提供者,同时也是数据搜集者。社交媒体依靠隐私政策与用户达成协议,使得用户在社交媒体所有的痕迹数据都将成为平台方的商业资源。“ZAO隐私协议被质疑”出来后,也使得用户对于隐私政策越来越重视,但此类新闻事件并非是首例。2018年支付宝账单活动默许勾选同意《芝麻服务协议》事件也曾引起热议。那么屡次发生的新闻事件或者其他隐私风险记忆对于用户对隐私政策的感知是否有影响呢?隐私风险记忆和隐私政策又是如何影响用户在社交媒体上的自我表露行为呢?本研究基于此进行研究,以社交媒体用户为研究对象,使用问卷调查法,探究用户的隐私风险记忆和对隐私政策的有效性感知和内容理解对自我表露的影响路径。并且提出研究模型,研究模型共包括7个变量和14条假设。研究发现:1)有隐私政策查看史的用户对隐私政策的内容理解更深和对其有效性感知也更深;2)社交媒体信任在隐私政策有效性感知和隐私政策内容理解对自我表露的影响路径中起到了中介效应作用;3)隐私计算在隐私政策内容理解与社交媒体信任、隐私政策有效性感知与社交媒体信任间起到了调节效应;4)隐私风险记忆直接影响自我表露,社交媒体信任在其中并不能起到中介效应作用;5)当隐私计算作用明显时,用户的感知收益也就越高,隐私风险记忆可对社交媒体信任产生正向影响。基于研究结果,本文针对社交媒体运营者、社交媒体用户、社交媒体监管者分别给出相关建议。

摘要： 文章结合民法典有关担保合同的法律条文的规定,对于担保合同的内容和形式进行深入解读,以期为经济主体降低法律风险提供帮助。上一篇文章我们详细介绍了担保合同在融资借贷中的广泛应用,解读了什么是担保合同、担保合同的主体,但这仅是对担保合同的初步认识。在实际的经济交往活动中,担保合同担保期限、担保方式、担保范围等条款的约定,对于担保人的利益和债权人的利益保护都息息相关。文章结合民法典有关担保合同法律条文的规定,对于担保合同的内容和形式进行深入解读,以期为经济主体降低法律风险提供帮助。

关键词： 生化检验   小儿支原体肺炎   并心肌损伤   及肝损伤   诊断价值  

摘要： 目的探讨生化检验对小儿支原体肺炎合并心肌损伤以及肝损伤的诊断作用。方法选取2017年1月～2019年1月我院收治的小儿支原体肺炎患儿90例作为观察组,所有患儿均合并有不同程度的肝损伤及心肌损伤,另选取同期收治的健康小儿50例作为对照组,分析两组受检小儿的生化检验结果,探究其临床诊断价值。结果观察组患儿各项检测指标均显著高于正常水平,差异有统计学意义(P<0.05)。结论生化检验针对小儿支原体肺炎效果显著,能够有效检测其心肌损伤以及肝损伤程度,判定其疾病发展状况,为临床诊疗提供更加完善的参考依据,值得推广。

关键词： 儿童   腹泻   粪便微生物检验   治疗方式  

摘要： 目的:探析儿童腹泻诊断中应用粪便微生物检验的临床效果,及其对治疗方式的指导作用。方法:将120例2018年10月至2020年1月在我院治疗的腹泻患儿选为研究对象,均给予粪便微生物检验,总结分析病原类型与治疗方式。结果:120例患儿中,共检出腹泻病原微生物91例(75.83%),其中肠道致病菌检出例数为13例(10.83%),腹泻病毒检出例数为77例(64.17%),寄生虫检出例数为1例(0.83%)。结论:在儿童腹泻诊断中,粪便微生物检验能够有效确定患儿感染类型与病原微生物种类,为患儿临床治疗方式的制定提供了可靠依据,值得临床推广应用。

关键词： 微生物检验   医院感染   控制作用  

摘要： 目的对微生物检验控制医院感染的临床有效性进行探讨,以减少医院感染事件发生。方法选择我院2018年03月～2019年03月收治的100例患者作为实验对象,数字奇偶法分组后探究各组干预效果。对照组(50例):未采取临床检验措施;实验组(50例):应用微生物检验。对比两组患者医院感染发生率与感染程度评分。结果实验组医院感染发生率为6%(3/50),远远低于对照组(20%,10/50),临床比较差异性显著(P<0.05);实验组感染程度评分为(15.48±2.21)分,比对照组低,差异具备统计学研究意义(P<0.05)。结论在控制医院感染方面,微生物检验的优势突出,在降低感染率的同时,也提高了临床用药的合理性。

关键词： Graphene  

摘要： Graphene films were exposed to low-pressure capacitively coupled (E-mode) and inductively coupled (H-mode) argon radio frequency plasmas to investigate damage formation by very-low-energy ion irradiation. In the H-mode, plasma parameters were assessed by a Langmuir probe and plasma sampling mass spectrometry to determine the conditions of fixed ion fluence but with different average ion energies. The populations of argon metastable and resonant argon atoms were also measured by optical absorption spectroscopy to determine their contribution to the total energy flux during plasma treatment. In the H-mode, in which plasma-graphene interactions are dominated by ion irradiation effects, Raman spectroscopy reveals a significant rise in the D/G ratio and full width at half maximum of the G peak as well as the onset of graphene amorphization, even at very low ion energies (between 7 and 13 eV). In the E-mode characterized by comparable ion energy but much lower ion density, significant damage is also observed, a feature ascribed to the additional energy flux linked to the de-excitation of metastable argon species on the graphene surface. Published under license by AIP Publishing.

关键词： Arabidopsis   Stress   Transcriptome   Time-series   Machine learning  

摘要： Background: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the stress response are available in databases. With the data, an integrated analysis of multiple stresses is possible, which identifies stress-responsive genes with higher specificity because considering multiple stress can capture the effect of interference between stresses. To analyze such data, a machine learning model needs to be built. Results: In this study, we developed StressGenePred, a neural network-based machine learning method, to integrate time-series transcriptome data of multiple stress types. StressGenePred is designed to detect single stress-specific biomarker genes by using a simple feature embedding method, a twin neural network model, and Confident Multiple Choice Learning (CMCL) loss. The twin neural network model consists of a biomarker gene discovery and a stress type prediction model that share the same logical layer to reduce training complexity. The CMCL loss is used to make the twin model select biomarker genes that respond specifically to a single stress. In experiments using Arabidopsis gene expression data for four major environmental stresses, such as heat, cold, salt, and drought, StressGenePred classified the types of stress more accurately than the limma feature embedding method and the support vector machine and random forest classification methods. In addition, StressGenePred discovered known stress-related genes with higher specificity than the Fisher method. Conclusions: StressGenePred is a machine learning method for identifying stress-related genes and predicting stress types for an integrated analysis of multiple stress time-series transcriptome data. This method can be used to other phenotype-gene associated studies.

关键词： Mapping  

摘要： Monitoring cropland dynamics is critical for water management and crop-yield estimation but cropland mapping is still a challenge because of its seasonality and human intervention. Both large-area mapping and change detection studies use images from certain or the same seasons;however, the uneven distribution of Landsat data within a year may affect accuracy. This study aimed to explore the accuracy and uncertainty of cropland mapping performance in different season and month by analyzing all available images in three Landsat footprints in Egypt, Ethiopia, and South Africa from 1984 to 2016. Three different combinations of training models (using yearly, seasonal, and monthly sample set) were used to compare the effect on cropland classification in different month and season through 10-fold cross-validation. There was a tendency to achieve better cropland mapping performance in the dry season and peak growth cycle in all three sites. We showed that monthly and seasonal cropland mapping accuracy was only slightly (similar to 2%) increased using training data in corresponded month. Therefore, we recommended transfer seasonal/yearly training data to fine temporal resolution (i.e., monthly and seasonal) cropland mapping for time and labor efficiency.

关键词： 建筑工程合同   合同保全制度   次债务人   债权债务关系   债权人   合法性   代位权   债的保全  

摘要： 建筑工程合同的保全作为合同保全制度的一种,是对债的保全。然而如何在实际工作中有效使用建筑工程合同保全制度,是每个建设工程相关单位必须考虑的问题。建筑工程合同的保全形式建筑工程合同的保全,也就是合同的保全,它是通过债权人行使代位权、撤销权的形式而实现的。(一)代位权的行使要件1.合法性。债权人对债务人的债权合法,是行使代位权的首要条件。即债权人与之债务人之间存在合法的债权债务关系,债权人对债务人享有合法的债权。同理,债务人对次债务人的债权也必须是合法的债权。