Effect of lens surgery on health-related quality of life in preschool children with congenital ectopia lentis

AIM:To evaluate the effect of lens surgery on health-related quality of life(HRQoL)of preschool children with congenital ectopia lentis(CEL).METHODS:A prospective self-controlled study was conducted in Zhongshan Ophthalmic Center.Children aged from 5 to 7y whom were diagnosed with CEL and underwent phacoemulsification with scleral-fixated posterior chamber intraocular lens implantation and their parents were enrolled in this study.All of them completed the child and proxy(parental)PedsQL™4.0 before and after the surgery.Their preoperative scores were compared to their postoperative ones.Subgroup analyses were performed based on gender and preoperative bilateral presenting visual acuity of the children.RESULTS:Thirty-two children with CEL successfully underwent surgery without any complications,among whom 8 had monocular surgery and 24 had binocular surgery.Preoperative and postoperative questionnaires were completed by 32 child-parent pairs.Surgical intervention could significantly improve the vision of affected children(P<0.001).The medians of physical,psychosocial and total health scores self-reported by the children were 68.75(62.50,81.25),65.00(60.00,80.00)and 67.39(60.87,78.26)preoperatively and were 93.75(87.50,100.00),90.00(83.33,96.67)and 89.13(85.32,95.65)postoperatively.The preoperative scores of the affected children were significantly lower in all scales than age-matched healthy children(P<0.001).All the postoperative scores were significantly higher than the preoperative scores in affected children and their parents(P<0.001).In the physical functioning evaluation,the preoperative score reported by parents of girls was higher than parents of boys(P=0.041),and the postoperative score of girls was higher than that of boys(P=0.036).CONCLUSION:CEL is associated with significantly worse quality of life in preschool children.Surgical intervention can significantly improve the HRQoL in affected children from both personal and family perspective.

Analyzing topics in social media for improving digital twinning based product development

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product development.Previous efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital spaces.This work mines real-world consumer feedbacks through social media topics,which is significant to product development.We specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a product.The primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset distribution.Therefore,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse topics.To this end,this work combines deep learning and survival analysis to predict the prevalent time of topics.We propose a specialized deep survival model which consists of two modules.The first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network structure.Moreover,a specific loss function different from regular survival models is proposed to achieve a more reasonable prediction.Extensive experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

Health-related quality of life and coping strategies of patients on hemodialysis in selected hospitals in Ilorin,Kwara state,Nigeria

Objective:The study assessed the quality of life(QoL)and coping strategies of patients on hemodialysis in selected hospitals in Ilorin,Kwara State.Methods:The study was a descriptive cross-sectional design using a quantitative strategy.A multistage sampling technique was adopted to select 80 participants.The data were collected using an adapted questionnaire including four sections:sociodemographic characteristics,hemodialysis stressor scale consisting of four stressors,Jaloweic Coping Scale consisting of eight coping strategies,and QoL consisting of four items.The data were analyzed using SPSS version 23.Results:Findings from the study revealed that 50%of the participants were between the ages of 18 and 39 years,40%of the participants have been on hemodialysis for 1-2 years,whereas 52.5%had hypertension as a comorbidity.A total of 12.5%,63.8%,and 23.8%of the respondents were categorized as experiencing low,moderate,and high stress due to hemodialysis,respectively.QoL of the respondents revealed that 49.4%had no problem in self-care dimension.Average monthly income(χ^(2)=16.36,P=0.04)was observed to be significantly associated with coping strategies,whereas religion(χ^(2)=11.14,P=0.03)and frequency of hemodialysis(χ^(2)=10.26,P=0.04)were significantly associated with coping helpfulness.Conclusion:All participants experienced stress at varying degrees.Hemodialysis results in marked changes in the quality of patients’life,since it includes a number of modifications and restrictions,which affects patients’health functioning.This study revealed a wide range of information on the psychological and physiological stressors of people under hemodialysis.

基于BERTopic模型的国外信息资源管理研究进展分析

[目的/意义]文章从已有研究成果中提取主题,梳理主要研究方向,展示主题热度变化趋势,为了解和评估国外信息资源管理(IRM)研究发展现状与趋势提供参考。[方法/过程]采用新兴BERTopic模型对2013—2022年期间WoS数据库中IRM相关文献进行主题提取与识别,结合相关主题词及主题距离划分研究方向,并利用动态主题模型揭示国外IRM领域的演变过程。[结果/结论]国外IRM近10年的研究可分为59个主题,可归纳为信息技术及应用、企业信息管理、图书馆管理与服务、健康信息管理、信息用户与服务、IRM基本理论与方法、文献计量与评价7个方向。大多数主题的研究热度变化偏向稳定的趋势,数字化建设、开放数据等部分主题热度逐渐上涨,而外包、知识管理等少数主题热度退却。

Research on the Chinese Path to Modernization in History,Key Topics,and Outlook:A Cite Space-based Bibliometric Analysis

In the speech delivered at the centenary celebration of the Communist Party of China(CPC),Xi Jinping,general secretary of the Communist Party of China(CPC)Central Committee,made important remarks on the“Chinese path to modernization.”This term represents the latest achievement China has scored in adapting Marxism to the Chinese context and the needs of the times.It has set the course as China embarks on a new journey of building a strong socialist country with Chinese characteristics and achieving national rejuvenation.Drawing on CiteSpace,we conducted a visualized bibliometric analysis of literature on the Chinese path to modernization by searching the CNKI database using subject terms such as“Chinese modernization,Chinese path to modernization,and Chinese-style modernization.”The findings reveal that:(a)Research on the Chinese path to modernization has gone through three stages:initial establishment,pioneering exploration,and comprehensive in-depth development.(b)Existing literature has covered the four key topics associated with the Chinese path to modernization,namely its essence,goal,methodology,and pioneering achievements.(c)Future research may focus on building up China’s strength in agriculture,developing the digital economy,modernizing China’s system and capacity for governance,and establishing a unique socialist discourse system for Chinese modernization.

Medium-term surgical outcomes and health-related quality of life after laparoscopic vs open colorectal cancer resection: SF-36 health survey questionnaire

BACKGROUND Previous studies that compared the postoperative health-related quality of life(HRQoL)outcomes after receiving laparoscopic resection(LR)or open resection(OR)in patients with colorectal cancer(CRC)have different conclusions.AIM To explore the medium-term effect of postoperative HRQoL in such patients.METHODS This study randomized 567 patients undergoing non-metastatic CRC surgery managed by one surgeon to the LR or OR groups.HRQoL was assessed during the preoperative period and 3,6,and 12 mo postoperative using a modified version of the 36-Item Short Form(SF-36)Health Survey questionnaire,emphasizing eight specific items.RESULTS This cohort randomly assigned 541 patients to receive LR(n=296)or OR(n=245)surgical procedures.More episodes of postoperative urinary tract infection(P<0.001),wound infection(P<0.001),and pneumonia(P=0.048)were encountered in the OR group.The results demonstrated that the LR group subjectively gained mildly better general health(P=0.045),moderately better physical activity(P=0.006),and significantly better social function recovery(P=0.0001)3 mo postoperatively.Only the aspect of social function recovery was claimed at 6 mo,with a significant advantage in the LR group(P=0.001).No clinical difference was found in HRQoL during the 12 mo.CONCLUSION Our results demonstrated that LR resulted in better outcomes,including intra-operative blood loss,surgery-related complications,course of recovery,and especially some health domains of HRQoL at least within 6 mo postoperatively.Patients should undergo LR if there is no contraindication.

基于BERTopic模型的网络暴力事件衍生舆情探测

[研究目的]在海量用户生成内容中及时探测和剖析网络暴力事件的衍生舆情能够为舆情事件链的演化分析、同类舆情的研判介入、衍生事件的监测预警提供理论支持。[研究方法]使用BERTopic模型对短文本内容主题建模并采用聚类的方式展示主题的潜在层次结构。根据词向量余弦相似度设计主题衍生度的计量算法,同时融合词共现网络在文档-词语层面信息捕捉的优势以及桑基图直观演示舆情演化过程的特点,衡量主题间的影响力与衍生关系。[研究结论]在开源数据集下多组主题模型的对照实验中,BERTopic模型在短文本建模以及下游任务的平均得分提高2.13%。在网络暴力热点事件的应用实例中,多维细粒度分析与交互式可视化方法可达到直观展示暴力事件的主题聚类、词义关联与演化态势的效果,实现网络暴力事件衍生舆情的探测与分析。

基于BERTopic算法的引文主题实证分析——以一篇高被引诺贝尔生理学或医学奖论文为例

[目的/意义]引文主题识别/分析(CTR/CTA)是引文内容分析(CCA)的一项重要研究议题,通过对引文语料中蕴涵主题信息的识别和提取,可望为论文学术贡献评价、知识扩散及演化分析等问题的解决提供新的研究思路。[过程/方法]以一篇高被引诺贝尔生理学或医学获奖关键论文为例,采用BERTopic算法对其引文句语料进行主题识别,并对识别出的引文主题展开多个维度的分析与讨论。[结果/结论]对高被引论文开展引文主题识别分析,有助于更全面细致地揭示其学术贡献内容及演化趋势;BERTopic算法能较好识别案例文献的多个引文主题,且不同引文主题的施引文献特征分布不尽相同;对引文主题重要性、演化趋势及其与原文主题差异性的分析,能多维度刻画研究同行对案例文献学术贡献的认识,表明CTR/CTA研究对学术论文评价具有深入探索价值。

A Video Captioning Method by Semantic Topic-Guided Generation

In the video captioning methods based on an encoder-decoder,limited visual features are extracted by an encoder,and a natural sentence of the video content is generated using a decoder.However,this kind ofmethod is dependent on a single video input source and few visual labels,and there is a problem with semantic alignment between video contents and generated natural sentences,which are not suitable for accurately comprehending and describing the video contents.To address this issue,this paper proposes a video captioning method by semantic topic-guided generation.First,a 3D convolutional neural network is utilized to extract the spatiotemporal features of videos during the encoding.Then,the semantic topics of video data are extracted using the visual labels retrieved from similar video data.In the decoding,a decoder is constructed by combining a novel Enhance-TopK sampling algorithm with a Generative Pre-trained Transformer-2 deep neural network,which decreases the influence of“deviation”in the semantic mapping process between videos and texts by jointly decoding a baseline and semantic topics of video contents.During this process,the designed Enhance-TopK sampling algorithm can alleviate a long-tail problem by dynamically adjusting the probability distribution of the predicted words.Finally,the experiments are conducted on two publicly used Microsoft Research Video Description andMicrosoft Research-Video to Text datasets.The experimental results demonstrate that the proposed method outperforms several state-of-art approaches.Specifically,the performance indicators Bilingual Evaluation Understudy,Metric for Evaluation of Translation with Explicit Ordering,Recall Oriented Understudy for Gisting Evaluation-longest common subsequence,and Consensus-based Image Description Evaluation of the proposed method are improved by 1.2%,0.1%,0.3%,and 2.4% on the Microsoft Research Video Description dataset,and 0.1%,1.0%,0.1%,and 2.8% on the Microsoft Research-Video to Text dataset,respectively,compared with the existing video captioning methods.As a result,the proposed method can generate video captioning that is more closely aligned with human natural language expression habits.

Pain perception enhancement in consecutive secondeye phacoemulsification cataract surgeries under topical anesthesia

Cataract is the main cause of visual impairment and blindness worldwide while the only effective cure for cataract is still surgery.Consecutive phacoemulsification under topical anesthesia has been the routine procedure for cataract surgery.However,patients often grumbled that they felt more painful during the second-eye surgery compared to the first-eye surgery.The intraoperative pain experience has negative influence on satisfaction and willingness for second-eye cataract surgery of patients with bilateral cataracts.Intraoperative ocular pain is a complicated process induced by the nociceptors activation in the peripheral nervous system.Immunological,neuropsychological,and pharmacological factors work together in the enhancement of intraoperative pain.Accumulating published literatures have focused on the pain enhancement during the secondeye phacoemulsification surgeries.In this review,we searched PubMed database for articles associated with pain perception differences between consecutive cataract surgeries published up to Feb.1,2024.We summarized the recent research progress in mechanisms and interventions for pain perception enhancement in consecutive secondeye phacoemulsification cataract surgeries.This review aimed to provide novel insights into strategies for improving patients’intraoperative experience in second-eye cataract surgeries.

InCites中Citation Topics功能应用于科技期刊选题策划的实证研究——以热带医学研究领域为例

以热带医学研究领域为例,探索InCites数据库中的Citation Topics功能在选题策划中的应用。选取Web of Science数据库中热带医学领域近5年SCIE收录的论文,利用Citation Topics,对个别发文量多或被引频次高的研究方向、区域、研究人员、机构进行微观主题举例分析。疟疾微观主题下表现最活跃的区域为USA,机构为University of London,研究人员为Drakeley,Chris,出版物为Malaria Journal,United States Department of Health&Human Services为疟疾微观主题提供的基金资助最多;血吸虫病、疟疾、登革热、包虫囊肿和冠状病毒是中国热带医学领域的研究重点,冠状病毒、血吸虫病、隐孢子虫、登革热和疟疾微观主题的论文影响力相对较高;研究人员Zhou,Xiao-Nong的重点研究方向为血吸虫病、疟疾和包虫囊肿,疟疾、登革热、轮状病毒、犬弓首线虫和莱姆病研究主题的论文质量和关注度高;University of London热带医学领域的研究重点为疟疾、血吸虫病和登革热。InCites中Citation Topics功能可以实现对研究主题、人员、机构、国家/地区等模块进行更精细的分析,有助于科技期刊编辑更高效地制定选题方案。

基于BERTopic模型的数字政府治理领域的主题识别与内容分析

[目的/意义]在信息技术创新、政府数字化转型的背景下,中国学术界输出的“数字政府治理”相关研究体量较大,现阶段亟待对其进行科学整理和综述概览,以回应“政府治理现代化”目标对理论研究的新要求。[方法/过程]以2011-2023年间中国知网数据库收录的有关数字政府治理研究的1829篇文献为数据来源,借助深度学习模型BERTopic和文献计量法CiteSpace相互验证分析数字政府治理领域的研究阶段、研究关键词、研究热点主题及内容等,使得结果具有高准确性和强解释性,以科学有效地探测主题取向及特征,展望数字政府治理领域的未来研究方向。[结果/结论]中国数字政府治理研究在过去的10年间发展迅猛,已成为学者探索的热点论域;现有文献研究热点整体上聚焦于价值导向、治理模式进化、技术工具嵌入;重点主题关注的是“政府数据开放共享研究”“基于数字技术的政务服务改革研究”“城乡场域下的数字化治理研究”“数字政府治理水平的评估研究”及“数字化转型下具体治理领域的实践研究”。未来,数字政府治理仍然是一个具有持续性拓展空间的研究领域,将逐步实现数字政府治理的更广场域触达、精准滴灌、多项学科融合和技术实用主义。

基于Citation Topic的领域期刊主题演化研究——以行为医学为例

基于论文层面的Citation Topic分类体系,通过测度行为医学领域SCI及SSCI期刊引文主题变动情况,展现国际行为医学领域研究重点以及相关支撑学科的演化。

基于BERTopic的中药治疗眼科疾病的处方用药规律分析

目的分析中医药治疗眼科疾病的处方用药规律,探讨治疗眼科疾病的更多潜在配伍组合。方法收集眼科专家门诊的中医处方并整理筛选,采用Python 3.9.10中BERTopic算法对复发性虹膜睫状体炎的所有处方进行分析,得到药物关键词聚类组合;采用SPSS 25.0对中药处方数据进行层次聚类,比较两种方法的优劣和药物配伍组合的挖掘效果。结果采用BERTopic算法得到核心药物关键词组合累计2种,包括酒地龙、土茯苓、大青叶、葎草等;应用层次聚类得到的药物组合包括葎草、土茯苓、菝葜等。应用BERTopic技术的算法具有不易受噪声数据影响、提高聚类效率、增强对于处方文本语义理解等诸多优势。结论使用基于BERTopic技术的算法在寻找疾病潜在中药配伍中表现良好,潜力较大,能为眼科疾病的中药配伍组合提供更多参考方向。

基于BERTopic主题建模的延时现场救护研究趋势与热点分析

目的分析2009~2024年间国际延时现场救护领域的文献,探究主要研究主题及其发展趋势,以期为未来救护策略提供理论支持。方法系统检索PubMed、Embase、Web of Science和中国知网等数据库,筛选并纳入283篇相关文献。运用BERTopic主题建模技术对文献进行主题识别和关键词分析,并进行可视化展示。结果当前研究主要聚焦在“急救策略研究”“智能技术与信息管理”“实战应用”与“政策与理论研究”等4个方面,预测这些领域将持续成为研究热点。结论国际延时现场救护研究正处于快速发展阶段,建议未来研究深入重点领域,开发有效的救护策略,以提升救治效率和伤员生存率。

基于BERTopic模型的组织成员工作投入研究的主题提取

[目的/意义]旨在通过科学计量方法,挖掘“组织成员工作投入”文献资源中蕴藏的主题,为后续研究提供参考和启示。[方法/过程]搜集中国知网学术期刊数据库中2002-2023年相关文献的摘要和发表年份,经过文本预处理,使用BERTopic模型进行主题提取和可视化分析。[结果/结论]国内现有的关于组织成员工作投入的研究可以分为研究内容和研究方法两大主题集群,均表现出多样化态势。主题时序演化分析揭示了组织成员工作投入研究正逐步转向对个体差异和心理健康的关注。未来研究可从新技术的影响、工作投入动态变化以及跨学科合作等方面进行拓展。

基于BERTopic模型的公众心理应激信息表征分析

[目的/意义]在后疫情时代的背景下,探讨心理应激的信息表征对公众的心理健康建设及社会发展具有重要意义。[方法/过程]使用BERTopic模型对问答数据进行匹配和热度分析,探究不同主题下用户的关注内容和关注程度。[结果/结论]用户心理应激信息表征主要集中在生理反应、认知反应、情感反应、行为反应4种类型。本研究从后疫情时代的视角出发探讨心理应激的信息表征,能够以常态化心理应激干预为目标为决策者提出长期心理支持服务建议,推进线上线下并举的心理服务。

Identification and Prediction of Interdisciplinary Research Topics: A Study Based on the Concept Lattice Theory

Purpose: Formal concept analysis(FCA) and concept lattice theory(CLT) are introduced for constructing a network of IDR topics and for evaluating their effectiveness for knowledge structure exploration.Design/methodology/approach: We introduced the theory and applications of FCA and CLT, and then proposed a method for interdisciplinary knowledge discovery based on CLT. As an example of empirical analysis, interdisciplinary research(IDR) topics in Information & Library Science(LIS) and Medical Informatics, and in LIS and Geography-Physical, were utilized as empirical fields. Subsequently, we carried out a comparative analysis with two other IDR topic recognition methods.Findings: The CLT approach is suitable for IDR topic identification and predictions.Research limitations: IDR topic recognition based on the CLT is not sensitive to the interdisciplinarity of topic terms, since the data can only reflect whether there is a relationship between the discipline and the topic terms. Moreover, the CLT cannot clearly represent a large amounts of concepts.Practical implications: A deeper understanding of the IDR topics was obtained as the structural and hierarchical relationships between them were identified, which can help to get more precise identification and prediction to IDR topics.Originality/value: IDR topics identification based on CLT have performed well and this theory has several advantages for identifying and predicting IDR topics. First, in a concept lattice, there is a partial order relation between interconnected nodes, and consequently, a complete concept lattice can present hierarchical properties. Second, clustering analysis of IDR topics based on concept lattices can yield clusters that highlight the essential knowledge features and help display the semantic relationship between different IDR topics. Furthermore, the Hasse diagram automatically displays all the IDR topics associated with the different disciplines, thus forming clusters of specific concepts and visually retaining and presenting the associations of IDR topics through multiple inheritance relationships between the concepts.

Motor competence and health-related fitness in children:A cross-cultural comparison between Portugal and the United States

Background: Motor competence and health-related fitness are important components for the development and maintenance of a healthy lifestyle in children. This study examined cross-cultural performances on motor competence and health-related fitness between Portuguese and U.S.children.Methods: Portuguese(n = 508; 10.14 § 2.13 years, mean § SD) and U.S.(n = 710; 9.48 § 1.62 years) children performed tests of cardiorespiratory fitness(Progressive Aerobic Cardiovascular Endurance Run), upper body strength(handgrip), locomotor skill performance(standing long jump), and object projection skill performance(throwing and kicking). Portuguese and U.S. children were divided into 2 age groups(6à9 and 10à13 years) for data analysis purposes. A twoàfactor oneàway analysis of covariance(ANOVA) was conducted with the Progressive Aerobic Cardiovascular Endurance Run, handgrip, standing long jump scores, kicking, and throwing speed(km/h) as dependent variables.Results: Results indicated that Portuguese children, irrespective of sex, presented better performances in locomotor and cardiorespiratory performance(standing long jump and Progressive Aerobic Cardiovascular Endurance Run) than U.S. children in both age bands. U.S. children outperformed Portuguese children during throwing and handgrip tests. Kicking tests presented gender differences: Portuguese boys and U.S. girls outperformed their internationally matched counterparts.Conclusion: Cultural differences in physical education curricula and sports participation may impact differences in motor competence and fitness development in these countries.

Detecting Dynamics of Hot Topics with Alluvial Diagrams:A Timeline Visualization

Purpose： In this paper, we combined the method of co-word analysis and alluvial diagram to detect hot topics and illustrate their dynamics. Design/methodology/approach： Articles in the field of scientometrics were chosen as research cases in this study. A time-sliced co-word network was generated and then clustered. Afterwards, we generated an alluvial diagram to show dynamic changes of hot topics, including their merges and splits over time. Findings： After analyzing the dynamic changes in the field of scientometrics from 2011 to 2015, we found that two clusters being merged did not mean that the old topics had disappeared and a totally new one had emerged. The topics were possibly still active the following year, but the newer topics had drawn more attention. The changes of hot topics reflected the shift in researchers＇ interests. subdivided and re-merged. For example, several topics as research progressed. Research topics in scientometrics were constantly a cluster involving ＂industry＂ was divided into Research limitations： When examining longer time periods, we encounter the problem of dealing with bigger data sets. Analyzing data year by year would be tedious, but if we combine, e.g. two years into one time slice, important details would be missed. Practical implications： This method can be applied to any research field to illustrate the dynamics of hot topics. It can indicate the promising directions for researchers and provide guidance to decision makers. Originality/value： The use of alluvial diagrams is a distinctive and meaningful approach to detecting hot topics and especially to illustrating their dynamics.