Subjects: Digital Publishing >> New Media submitted time 2023-10-08 Cooperative journals: 《中国传媒科技》
Abstract：自工业革命以来,科学技术逐渐呈高速发展的状态,信息化和数字化的发展成为时代发展的主流,促进了数字媒体技术的进步,逐渐在发展的过程中崭露头角。在近年的发展中,数字媒体技术在影视行业中逐渐被推广应用,该技术的应用对传统影视技术产生了较大的影响,这对传统影视技术而言,形成一种挑战和机会并存的局面。在这种背景下,如何有效融合传统影视技术和全新数字媒体技术,进而有效调节二者的关系,便成为影视行业的热门话题。如何采用数字媒体技术进行影视艺术创作,进而有效将交互性和代入性表达出来,成为影视创作的棘手问题。因此,本文主要对数字媒体时代影视行业的相关创作工作进行有效分析,有效探索传统影视艺术以及全新数字媒体技术之间存在的冲突和交融,进而寻求改善二者的关系,以便促进影视艺术高效发展。
Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2023-05-12 Cooperative journals: 《中国全科医学》
Abstract： Obstructive sleep apnea（OSA） is a common sleep-related respiratory disorder that can easily induce or aggravate a variety of diseases，often causing different levels of decline in the patient's quality of life. Patient-reported outcome（PRO） assessment tools provide effective means for evaluating both quality of life and clinical efficacy. There are numerous OSA-PRO assessment tools available，primarily developed in foreign countries，mainly covering domains such as symptoms，daily activities，social activities，and psychological emotions，with items ranging in number from one to 84，and Likert scale as the main type of response scale. The development and evaluation of these tools employ the Classical Test Theory（CTT）. We provide the following recommendations for future research: evaluating the psychometric properties and methodological quality of OSA-PRO assessment tools；combining CTT with Modern Test Theory to develop，revise，and evaluate OSA-PRO assessment tools；strengthening the research on the minimal clinically important difference of OSA-PRO assessment tools；developing OSA-PRO assessment tools highlighting the clinical efficacy of traditional Chinese medicine.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Background: P-value is the most widely used statistical index for inference in science. A p-value greater than 0.05, i.e., nonsignificant results, however, cannot distinguish the two following cases: the absence of evidence or the evidence of absence. Unfortunately, researchers in psychological science may not be able to interpret p-values correctly, resulting in wrong inference. For example, Aczel et al (2018), after surveying 412 empirical studies published in Psychonomic Bulletin & Review, Journal of Experimental Psychology: General, and Psychological Science, found that about 72% of nonsignificant results were misinterpreted as evidence in favor of the null hypothesis. Misinterpretations of nonsignificant results may lead to severe consequences. One such consequence is missing potentially meaningful effects. Also, in matched-group clinical trials, misinterpretations of nonsignificant results may lead to false “matched” groups, thus threatening the validity of interventions. So far, how nonsignificant results are interpreted in Chinese psychological literature is unknown. Here we surveyed 500 empirical papers published in five mainstream Chinese psychological journals, to address the following questions: (1) how often are nonsignificant results reported; (2) how do researchers interpret nonsignificant results in these published studies; (3) if researchers interpreted nonsignificant as “evidence for absence,” do empirical data provide enough evidence for null effects? Method: Based on our pre-registration (https://osf.io/czx6f), we first randomly selected 500 empirical papers from all papers published in 2017 and 2018 in five mainstream Chinese psychological journals (Acta Psychologica Sinica, Psychological Science, Chinese Journal of Clinical Psychology, Psychological Development and Education, Psychological and Behavioral Studies). Second, we screened abstracts of these selected articles to check whether they contain negative statements. For those studies which contain negative statements in their abstracts, we searched nonsignificant statistics in their results and checked whether the corresponding interpretations were correct. More specifically, all those statements were classified into four categories (Correct-frequentist, Incorrect-frequentist: whole population, Incorrect-frequentist: current sample, Difficult to judge). Finally, we calculated Bayes factors based on available t values and sample sizes associated with those nonsignificant results. The Bayes factors can help us to estimate to what extent those results provided evidence for the absence of effects (i.e., the way researchers incorrectly interpreted nonsignificant results). Results: Our survey revealed that: (1) out of 500 empirical papers, 36% of their abstracts (n = 180) contained negative statements; (2) there are 236 negative statements associated with nonsignificant statistics in those selected studies, and 41% of these 236 negative statements misinterpreted nonsignificant results, i.e., the authors inferred that the results provided evidence for the absence of effects; (3) Bayes factor analyses based on available t-values and sample sizes found that only 5.1% (n = 2) nonsignificant results could provide strong evidence for the absence of effects (BF01 > 10). Compared with the results from Aczel et al (2019), we found that empirical papers published in Chinese journals contain more negative statements (36% vs. 32%), and researchers made fewer misinterpretations of nonsignificant results (41% vs. 72%). It worth noting, however, that there exists a categorization of ambiguous interpretations of nonsignificant results in the Chinese context. More specifically, many statements corresponding to nonsignificant results were “there is no significant difference between condition A and condition B”. These statements can be understood either as “the difference is not statistically significant”, which is correct, or “there is no difference”, which is incorrect. The percentage of misinterpretations of nonsignificant results raised to 64% if we adopt the second way to understand these statements, in contrast to 41% if we used the first understanding. Conclusion: Our results suggest that Chinese researchers need to improve their understanding of nonsignificant results and use more appropriate statistical methods to extract information from nonsignificant results. Also, more precise wordings should be used in the Chinese context.
Subjects: Psychology >> Statistics in Psychology submitted time 2020-10-17
Abstract： P-value is the most widely used statistical index for inference in science. Unfortunately, researchers in psychological science may not be able to interpret p-value correctly, resulting in possible mistakes in statistical inference. Our specific goal was to estimate how nonsignificant results were interpreted in the empirical studies published in Chinese Journals. Frist, We randomly selected 500 empirical research papers published in 2017 and 2018 in five Chinese prominent journals (Acta Psychological Sinica, Psychological Science, Chinese Journal of Clinical Psychology, Psychological Development and Education, Psychological and Behavioral Studies). Secondly, we screened the abstracts of the selected articles and judged whether they contained negative statements. Thirdly, we categorized each negative statement into 4 categories (Correct-frequentist, Incorrect-frequentist: whole population, Incorrect-frequentist: current sample, Difficult to judge). Finally, we calculated Bayes factors based on the t values and sample size associated with the nonsignificant results to investigate whether empirical data provide enough evidence in favor of null hypothesis. Our survey revealed that: (1) 36% of these abstracts (n = 180) mentioned nonsignificant results; (2) there were 236 negative statements in the article that referred to nonsignificant results in abstracts, and 41% negative statements misinterpreted nonsignificant results; (3) 5.1% (n = 2) nonsignificant results can provide strong evidence in favor of null hypothesis (BF01 > 10). The results suggest that Chinese researchers need to enhance their understanding of nonsignificant results and use more appropriate statistical methods to extract information from non-significant results.
Peer Review Status:
Awaiting Review
Subjects: Biology >> Bioengineering submitted time 2018-01-16 Cooperative journals: 《中国生物工程杂志》
Abstract：纤维二糖可有效诱导丝状真菌产纤维素酶，前期研究表明匍枝根霉Rhizopus stolonifer TP-02具有纤维二糖合成酶（CBS），可以尿苷二磷酸葡萄糖（UDPG）为糖基供体合成纤维二糖，从而开启纤维素酶的自诱导合成途径。为研究R. stolonifer中纤维二糖的胞内合成途径，通过重叠PCR在GDP-葡糖焦磷酸化酶基因ggp中引入硫胺吡啶抗性基因ptrA，分别转化原菌TP-02和△ugp突变株，构建△ggp和△ugp/△ggp突变株。利用液质联用（LC-MS）检测突变株的胞内糖组分，发现ggp的缺失对胞内纤维二糖合成的影响较弱，而同时缺失ugp则将直接导致二糖合成受阻。RT-qPCR结果显示△ggp突变株中纤维素酶基因转录水平较原株TP-02下调20%左右，而△ugp/△ggp突变株中被测基因的转录水平则出现了高达80%左右的下调。同时对突变株纤维素酶表达水平进行研究，发现△ugp/△ggp突变株中几乎检测不到纤维素酶活力。结果显示，UDPG为R. stolonifer胞内合成纤维二糖的主要糖基供体，而GDPG可能是UDPG的替代物，在UDPG不足时维持胞内二糖合成。此外，利用生物信息学方法对CBS结构功能深入分析，经丙氨酸扫描确定其合成纤维二糖的关键作用残基为Asp210和Asp300，为后续进一步研究及理性改造提供方向和理论依据。
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