Quantifying co-creative writing experiences

Collaboration with artificial intelligence (AI) is a growing trend even in the field of creativity. This paper examines which quantitative metrics can be used to comparatively analyse human-computer co-creativity with children. To study this question, 24 schoolchildren of age 10–11 wrote a poem with three co-creative poetry writing processes: a human-computer, a human-human, and a human-human-computer process. The computational participant in the processes was an AI-based application called the Poetry Machine. The children were asked to evaluate their user experience with a 5-point Likert-type questionnaire after each writing process and a comparative questionnaire after finishing all processes. The metrics used in the evaluation were immediate fun, long-term enjoyment, creativity, self-expression, outcome satisfaction, ease of starting and finishing writing, quality of ideas and support from others, and ownership.

Significant differences were found in fun, long-term enjoyment, quality of ideas, support, and ownership. The high number of statistically relevant results was enabled by exposing all participants to all writing processes, and the comparative questionnaire. The human-human-computer process was evaluated the best in long-term enjoyment and the human-computer process the weakest in support and idea quality. Creativity and ease of finishing writing turned out to be outlining metrics for the co-creative processes.     

Simple Sequence Repeat Markers in Genetic Divergence and Marker-Assisted Selection of Rice Cultivars: A Review

Sequencing of rice genome has facilitated the understanding of rice evolution and has been utilized extensively for mining of DNA markers to facilitate marker-assisted breeding. Simple sequence repeat (SSR) markers that are tandemly repeated nucleotide sequence motifs flanked by unique sequences are presently the maker of choice in rice improvement due to their abundance, co-dominant inheritance, high levels of allelic diversity, and simple reproducible assay. The current level of genome coverage by SSR markers in rice is sufficient to employ them for genotype identification and marker-assisted selection in breeding for mapping of genes and quantitative trait loci analysis. This review provides comprehensive information on the mapping and applications of SSR markers in investigation of rice cultivars to study their genetic divergence and marker-assisted selection of important agronomic traits.     

Adventitial Tertiary Lymphoid Organs as Potential Source of MicroRNA Biomarkers for Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is an inflammatory disease associated with marked changes in the cellular composition of the aortic wall. This study aims to identify microRNA (miRNA) expression in aneurysmal inflammatory cells isolated by laser microdissection from human tissue samples. The distribution of inflammatory cells (neutrophils, B and T lymphocytes, mast cells) was evaluated in human AAA biopsies. We observed in half of the samples that adventitial tertiary lymphoid organs (ATLOs) with a thickness from 0.5 to 2 mm were located exclusively in the adventitia. Out of the 850 miRNA that were screened by microarray in isolated ATLOs (n = 2), 164 miRNAs were detected in ATLOs. The three miRNAs (miR-15a-3p, miR-30a-5p and miR-489-3p) with the highest expression levels were chosen and their expression quantified by RT-PCR in isolated ATLOs (n = 4), M1 (n = 2) and M2 macrophages (n = 2) and entire aneurysmal biopsies (n = 3). Except for the miR-30a-5p, a similar modulation was found in ATLOs and the two subtypes of macrophages. The modulated miRNAs were then evaluated in the plasma of AAA patients for their potential as AAA biomarkers. Our data emphasize the potential of miR-15a-3p and miR-30a-5p as biomarkers of AAA but also as triggers of ATLO evolution. Further investigations will be required to evaluate their targets in order to better understand AAA pathophysiology.     

APP软件性能效率研究

性能效率是APP软件的重要质量属性，但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征，基于ISO/IEC 25010标准提出了APP软件的性能效率模型，定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型，通过实验对APP软件的性能效率进行了度量及相关分析。     

中国省际绿色技术创新效率测度及影响因素研究

文章基于2011—2017年中国30个省份面板数据，运用super-SBM模型对绿色技术创新效率进行测算，并利用ML指数对绿色技术创新效率进行动态分析，最后通过空间滞后模型分析影响效率的关键因素。研究结果表明：中国绿色技术创新效率呈逐渐增长的趋势，但整体效率偏低，有较大进步空间；中国绿色技术创新效率存在明显区域差异，呈现由东部向西部递减的格局；绿色技术创新水平的提高是技术效率和技术进步共同贡献的结果；产业结构、区域开放程度和教育水平对绿色技术创新效率产生积极的正向影响，环境规制和研发投入强度对绿色技术创新效率影响不显著。     

应用API 581对输气站场进行定量风险评价

目前专门针对输气站场的风险评价方法还不多，现有的手段也只是根据国家法律法规得出定性的评价结果，然后按照评价结果对照得出整改方案。为此，对输气站场的定量风险评价工作提出了一套新方法，得到了定量的和更加客观的风险排序，为管道站场的完整性管理工作提供了有力的支持；并以陕京输气管道榆林压气站为例，应用美国石油学会标准API 581（基于风险检测的基本源文件）对站内设施进行了风险评价，计算了站内设备和管线的失效后果、失效概率，得到了定量风险值，进而分析了风险值产生差异的原因。最后，针对我国输气管道风险评估工作提出了看法和建议。     

分形方法对裂缝性储集层的定量预测研究和评价

隐蔽类油气藏同构造类油气藏一样，目前已成为我国油气勘探工作的重点领域，而且随着勘探工作的深入，隐蔽类油气藏必将是油气储量增长的主要来源。裂缝性油气藏是隐蔽类油气藏中最为复杂、勘探难度最大且产量较高的一类油气藏。为了提高裂缝性油气藏的勘探成功率。以辽河盆地火山岩裂缝油气藏的勘探为例，在分析和研究不同类型裂缝性油气藏的测井响应特征，利用电导率测井、声波测井、放射性测井和地层倾角测井等测井方法对裂缝性储层进行测井识别的基础上，引进分形模型方法对裂缝性储层的表征参数——裂缝发育程度和裂缝密度进行了定量预测，从而达到对裂缝性储层的孔隙度进行定量评价。     

医学超声图像处理系统

超声图像诊断是与X线CT、同位素扫描、核磁共振等一样重要的医学图像诊断手段。根据肝脏超声图像进行脂肪肝的诊断,是病变确诊的主要方法。但是,与CT和核磁共振等医学图像相比,超声图像的图像质量较差,目前的诊断以定性为主,受主观因素影响较大。以图像分割为基础,以VC语言为工具,建立了超声图像处理系统,对超声图像进行了二值化处理,并对处理结果进行了量化,为诊断提供了依据。