Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-11-23 Cooperative journals: 《中国全科医学》
Abstract： Background The occurrence of postoperative complications in lumbar degenerative disease（LDD） is closely related to malnutrition，and currently there is a lack of nutritional evaluation methods that can effectively，objectively，and comprehensively assess the nutritional status of LDD patients and predict the occurrence of postoperative complications. Objective To compare the predictive value of four nutritional evaluation methods of prognostic nutritional index（PNI），controlling nutritional status（CONUT），Naples prognostic score（NPS） and high-sensitivity modified glasgow prognostic score（HS-mGPS） for postoperative complications in patients with LDD，so as to formulate a precise nutritional intervention plan and effectively prevent complications. Methods A total of 201 patients diagnosed with LDD and underwent open surgery in spine surgery department of Xiangya Hospital of Central South University from December 2021 to July 2022 were selected as the study subjects，four nutritional evaluation methods of PNI，CONUT，NPS and HS-mGPS were applied to assess the preoperative nutritional status of the patients，respectively，and occurrence of postoperative complications from postoperative period to hospital discharge were observed. The patients were divided into the complication group and non-complication group according to the occurrence of postoperative complications to analyze and compare the difference in clinical characteristics between the two groups；the optimal cut-off values of different nutritional evaluation methods were calculated by plotting the receiver operating characteristic（ROC） curve，and the prediction efficiency of different evaluation methods was compared，the area under curve（AUC） was compared by using MedCalc software. Multivariate Logistic regression model was used to analyze the correlation between different nutritional evaluation methods and postoperative complications. Results Postoperative complications occurred in 60 patients with an incidence rate of 29.85%. The comparison of clinical characteristics data showed statistically significant differences in age，gender，intraoperative bleeding，surgical segment，PNI，CONUT，and NPS scores between the complication group and non-complication group（P<0.05）. The optimal cut-off values of PNI，CONUT，NPS，and HS-mGPS for predicting postoperative complications of LDD were calculated by using ROC curve were 47.5，2，1，and 1 points，respectively，and the different nutritional evaluation methods were compared within the group based on the cut-off values，showing that low PNI score，high CONUT score，and high NPS score were associated with postoperative complications（P<0.01），while high HS-mGPS score was not associated with postoperative complications （P=0.815）. The comparison of AUC showed statistically significant differences（P<0.05） between CONUT and HS-mGPS（Z=4.961，P<0.000 1），CONUT and NPS （Z=2.534，P=0.011 3），CONUT and PNI（Z=3.455，P=0.000 6），HS-mGPS and NPS（Z=3.349，P=0.000 8），NPS and PNI（Z=2.025，P=0.042 9）；there was no statistically significant difference between HS-mGPS and PNI（Z=1.594，P=0.110 9）（P>0.05）. Multivariate Logistic regression analysis showed that CONUT score（OR=2.431，95%CI：1.376-4.295，P=0.002），surgical segment（OR=11.924，95%CI：5.491-25.893，P<0.001） were independent influencing factors for postoperative complications after LDD. Conclusion Among the four nutritional evaluation methods used to predict postoperative complications of LDD patients，CONUT score is the most effective and can be used as an independent predictor of postoperative complications of LDD.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/Significance] Emerging industrial technologies have a major role in creating or changing the economic structure and development direction of traditional industries. It has important strategic and practical guiding significance for industrial development and reform to identify emerging industrial technologies in a timely and accurate manner and clarify the appropriate development direction. [Method/Process] According to the patent IPC classification information, this paper built an IPC node network, used the structural clustering algorithm for networks (SCAN) to identify industrial clusters and emerging technologies, and analyzed them in detail; then based on the time-series data of the five identified emerging technology patents, it constructed a patent node network and performed CPM to realize critical path analysis under the field of different emerging technologies, making the recognition results more microscopic and refined. Finally, taking the new energy automobile industry as an example, it obtained patent information from INCOPAT patent database for empirical analysis. [Result/Conclusion] Analysis based on SCAN-CPM is a useful supplement to the traditional emerging technology identification method. It displays the technology evolution path from large to small, from coarse to detailed, and provides a new perspective and technical means for comprehensively identifying emerging technologies and detecting technology evolution paths. The empirical analysis finds that: the internal design and external layout of charging piles for new energy vehicles are still the top priority for the development of the industry. Thermal management technology has increasingly become a relatively independent technical field. It is an important technical support for the new energy automobile industry to achieve overtaking on a curve. The evolution and diffusion path is clear. The technical issues such as battery pack environment, motor heat dissipation, battery liquid cooling technology, and heat exchanger materials are important breakthroughs and innovation points in the future. The motor drive control system currently forms a relatively high patent barrier.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： This paper investigated the structure and function of interactive naturalness through three studies. After command-line interaction and graphic interaction, natural interactions have increased and become mainstream. In measuring interactive experience, the traditional usability standard is not enough to measure the usability and naturality of product interaction. The possible reason is that natural interaction is no longer limited to the product's features but is more concerned with the human experience (the perceived naturalness) or natural experience. A direct, reliable measurement tool is urgently needed to evaluate the natural experience. Most studies used traditional usability dimensions such as visibility and ease of use to simply measure naturalness. But if naturalness simply equals usability, then many traits beyond product usability cannot be measured. Some studies directly measured naturalness with a single item or synonyms of naturalness, but the reliability of these measurements is not enough. This paper aimed to develop and verify a conceptually solid and quantitatively validated scale to measure the naturalness of interaction. In Study 1, a comprehensive item set related to the concept of natural interaction was established by using qualitative methods including dictionary retrieval, literature review, and expert interviews. In Study 2, participants (n = 353) were recruited to evaluate the experience of different intelligent connected vehicles. In addition to the interactive naturalness scale, several key consumer behaviors and traditional usability criteria, including drive intention, satisfaction, and usability, were also collected. In Study 3, new samples (n = 349) and more criterion-related variables (two key consumption behaviors were added, namely perceived loyalty and recommendation intention) were used to further verify the validity and reliability of the developed measurement tool. We used SPSS 25.0 and Jamovi 1.2.27 to analyze the data. According to Study 1, the naturalness of the interactive experience scale of 9 items was developed based on the qualitative research. In Study 2, the exploratory factor analysis found that the two-dimensional model (six items for joyful fluency and three items for universal awareness) best suited the data. Confirmatory factor analysis verified the stability of the two-factor model. Correlation analysis and hierarchical regression analysis suggested that these two components had good criterion-related validity and joyful fluency played a crucial role in predicting satisfaction and drive intention. In Study 3, a new sample (n = 349) was used to validate the validity of the scale further. And the validity of the scale was further verified in Study 3. The criterion-related variables used in Study 2 also obtained the same correlation and regression results in Study 3. Two factors of interactive naturalness had a significant predictive effect on the newly included variables, namely recommendation intention and perceived loyalty. In addition, joyful fluency was more related to basic vehicle functions, while universal awareness was more related to advanced intelligent interaction functions. This study explored the structure and function of interactive naturalness. A psychometrically sound tool was obtained to measure the interactive naturalness experience of intelligent products in two dimensions: joyful fluency and universal awareness. We found that interactive naturalness is strongly linked to key experiential and post-purchase dimensions and has an additional contribution to predicting these variables that traditional usability dimensions cannot include. This finding was also supported by the difference of correlation between two factors in different vehicle functions. These results indicate that the scale developed in this study can measure the natural interaction experience of intelligent products reliably and effectively. This tool can be used in future human-computer interaction research and guidance for interface and product design.
Subjects: Psychology >> Applied Psychology submitted time 2022-01-30
Abstract：
This paper investigated the structure and function of interactive naturalness through three studies. After command-line interaction and graphic interaction, natural interactions have increased and become mainstream. In measuring interactive experience, the traditional usability standard is not enough to measure the usability and naturality of product interaction. The possible reason is that natural interaction is no longer limited to the product's features but is more concerned with the human experience (the perceived naturalness) or natural experience. A direct, reliable measurement tool is urgently needed to evaluate the natural experience. Most studies used traditional usability dimensions such as visibility and ease of use to simply measure naturalness. But if naturalness simply equals usability, then many traits beyond product usability cannot be measured. Some studies directly measured naturalness with a single item or synonyms of naturalness, but the reliability of these measurements is not enough. This paper aimed to develop and verify a conceptually solid and quantitatively validated scale to measure the naturalness of interaction.
在研究1中，通过使用定性方法（包括字典检索，文献综述和专家访谈）建立了与自然相互作用概念相关的综合项目集。在研究2中，招募了参与者（n = 353）来评估不同智能网联汽车的经验。除了交互式自然性量表外，还收集了几个关键的消费者行为和传统的可用性标准，包括驱动意图，满意度和可用性。在研究3中，使用新样本（n = 349）和更多与标准相关的变量（增加了两个关键的消费行为，即感知忠诚度和推荐意图）来进一步验证所开发测量工具的有效性和可靠性。我们使用SPSS 25.0和Jamovi 1.2.27来分析数据。
根据研究1，基于定性研究开发了9个项目的互动体验量表的自然性。在研究2中，探索性因素分析发现二维模型（六项用于快乐流利度，三项用于普遍意识）最适合数据。验证因素分析验证了双因素模型的稳定性。相关性分析和分层回归分析表明，这两个组成部分具有良好的标准相关有效性，快乐流畅性在预测满意度和驱动意图方面起着至关重要的作用。在研究3中，使用新样本（n = 349）进一步验证量表的有效性。该研究3进一步验证了量表的有效性。研究2中使用的标准相关变量在研究3中也获得了相同的相关性和回归结果。互动自然性的两个因素对新纳入的变量具有显着的预测作用，即推荐意图和感知忠诚度。此外，快乐流畅性更多地与车辆的基本功能相关，而通用意识更多地与先进的智能交互功能相关。
本研究探讨了互动自然性的结构和功能。获得一种心理测量合理的工具，在两个维度上测量智能产品的互动自然体验：快乐的流畅性和普遍的意识。我们发现，互动的自然性与关键的体验和购买后维度密切相关，并且对预测传统可用性维度无法包含的这些变量有额外的贡献。这一发现也得到了不同车辆功能中两个因素之间相关性差异的支持。这些结果表明，本研究开发的量表能够可靠、有效地测量智能产品的自然交互体验。该工具可用于未来的人机交互研究和指导界面和产品设计。
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2020-01-20
Abstract： As for violent behaviors, previous researches mostly focused on actual violent behaviors. With the development of social networks, more and more attention has been paid to verbal attacks on the Internet. According to the frustration-aggression hypothesis, we believed that in addition to the "outward verbal violence" in the popular sense, there is also "inward verbal violence". This study aimed to explore the relationship between life satisfaction and verbal attack in different orientations by text analysis based on big data of Weibo. Results showed that the “inward verbal violence” was negatively related to life satisfaction (r = -0.167, p <0.001), and the correlation coefficient between “outward verbal violence” and life satisfaction was 0.031, however which was not significant (p = 0.089). Lower “inward verbal violence” and higher “outward verbal violence” can significantly predict life satisfaction. "
Peer Review Status:Awaiting Review
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