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Background The past nearly 20-year period has seen a sudden increase in the use of artificial intelligence (AI) in esophageal cancer research, and an emergence of many systematic reviews and meta-analyses of the research. However, most of the reviews and meta-analyses only address a single aspect in summary, making it difficult for researchers to gain a comprehensive understanding of the latest developments and research hotspots in the field. Objective To perform a bibliometric analysis of the use of AI in esophageal cancer research, and the development, hotspots and emerging trend in this field. Methods All literature in English regarding esophageal cancer research using AI included in the Science Citation Index Expanded database of the Web of Science Core Collection was searched from 2000-01-01 to 2022-04-06. Microsoft Excel 2019, CiteSpace (5.8R3-64bit) and VOSviewer (1.6.18) were used to analyze the literature for annual number of publications, country, author, institution, co-citation and keywords. Results Nine hundred and eighteen studies were retrieved, with a total of 23 490 times of being cited. The number of studies published between 2000 and 2016 grew slowly (from 6 to 40), but increased rapidly between 2017 and 2022 (from 62 to 216). Sixty countries, 118 institutions and 5 979 authors were involved in the studies. China (306 articles), the United States (238 articles) and the United Kingdom (113 articles) ranked the top three in terms of number of studies published. The top three institutions in terms of intensity of cooperation were University of Amsterdam (TLS=72), Catherine Hospital (TLS=64) and Eindhoven University of Technology (TLS=53). The top three authors in terms of number of publications were Jacques J G H M Bergman from the Netherlands (n=16), Tomohiro Tada from Japan (n=12), and Fons Van Der Sommen from the Netherlands (n=12). There were 39 962 co-cited authors and 42 992 co-cited studies. Thirty-three burst keywords were identified: the major burst keywords were p53 and mutations in 2001-2008 (early stage), and were esophageal cancer classification, new examination techniques (tomography), differentiation, identification and comparison between esophageal cancer and other cancers in 2013-2018 (middle stage), and were deep learning, convolutional neural network, and machine learning in esophageal cancer examination and diagnosis applications in 2019-2022 (late stage). Among which deep learning had the highest burst intensity (burst intensity of 13.89) . Conclusion AI application in esophageal cancer research has entered a new phase, moving gradually from genes and mutations toward accurate examination, diagnosis, and treatment. The latest major burst keywords in recent years (2019-2022) are deep learning, convolutional neural network, and machine learning in esophageal cancer examination and diagnosis. The future challenges to the use of AI in esophageal cancer research may include individual data collection, data quality assurance, data processing specifications, AI code reproduction, and reliability assurance of AI-assisted diagnostic decision-making.

This study investigated gender differences in the relationship between creativity and academic achievement. A sample of 1082 primary students participated in this study in Beijing, China. Their age ranged between 8 and 15 years old (M = 10.41, SD = 0.99). Students' creativity was measured by the Chinese version of the Torrance Test of Creative Thinking Figural Form A, and academic achievement was based on students' self-reported grades of last semester. Results revealed that there was a significantly positive relationship between creativity and academic achievement, ranging from r = 0.07 to r = 0.21. Gender differences regarding which aspects of creativity were related to academic achievement were also found. Plausible explanations and implications of the findings in creativity research and education are discussed.

Reliable measurements are key to social science research. Multiple measures of reliability of the total score have been developed, including coefficient alpha, coefficient omega, the greatest lower bound reliability, and others. Among these, the coefficient alpha has been most widely used, and it is reported in nearly every study involving the measure of a construct through multiple items in social and behavioral research. However, it is known that coefficient alpha underestimates the true reliability unless the items are tau-equivalent, and coefficient omega is deemed as a practical alternative to coefficient alpha in estimating measurement reliability of the total score. However, many researchers noticed that the difference between alpha and omega is minor in applications. Since the observed differences in alpha and omega can be due to sampling errors, the purpose of the present study, therefore, is to propose a method to evaluate the difference of coefficient alpha (alpha-hat and omega-hat statistically. In particular, the current article develops a procedure to estimate the "SE" of (omega-hat - alpha-hat) and consequently the confidence interval (CI) for (omega-alpha). This procedure allows us to test whether the observed difference (omega-hat - alpha-hat) is due to sample error or omega-hat is significantly greater than alpha-hat. The developed procedure is then applied to multiple real data sets from well-known scales to empirically verify the values of (omega-hat - alpha-hat) in practice. Results showed that in most of the comparisons the differences are significantly above zero but cases also exist where the CIs contain zero. An R program for calculating omega-hat, alpha-hat, and the "SE" of (omega-hat - alpha-hat) is also included in the present study so that the developed procedure is easily accessible to applied researchers.

Biochar is currently used as a phosphate adsorbent in water and subsequently as a soil amendment. In this study, modified biochar was prepared directly by co‐pyrolysis of MgO and rice straw, and a preliminary ecotoxicological assessment was performed before the application of modified biochar to soil. The effects of single factors, such as pyrolysis temperature, dosage, pH, and coexisting ions, on phosphate adsorption performance were investigated. In addition, after phosphate adsorption, the effects of modified biochar leachate on the germination of corn and rice seeds were examined. The results showed that phosphate adsorption by the modified biochar first increased and then decreased as the pyrolysis temperature increased, with modified biochar prepared at 800 °C showing the greatest adsorption. In addition, a comprehensive cost analysis showed that the best phosphate adsorption effect of modified biochar was achieved at a dosage of 0.10 g and a solution pH of 3. In contrast, the presence of competitive coexisting ions, Cl−, NO3−, CO32−, and SO42−, reduced the phosphate adsorption capacity of the modified biochar. The adsorption kinetics results revealed that the process of phosphate adsorption by the modified biochar was more in line with the pseudo‐second‐order model and dominated by chemisorption. Moreover, the adsorption isotherm results indicated that the process was more in line with the Langmuir model and dominated by monomolecular layer adsorption, with a maximum adsorption of 217.54 mg/g. Subsequent seed germination tests showed that phosphate‐adsorbed modified biochar leachate had no significant effect on the germination rate of corn seeds, whereas it improved the germination rate of rice seeds. Together, these results provide guidance for the application of modified biochar firstly as an adsorbent of phosphate and subsequently as a soil remediator. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore how environmental factors (family environment and school education) and individual characteristics (personality, creative attitudes, and divergent thinking) collectively affect creative achievement of American and Chinese college students. Data were collected from 378 college students in the United States (N = 193) and China (N = 185). Results showed that the US sample had significantly higher means in home resources, high-school education, Conscientiousness, creative achievement, and all four dimensions of the Abbreviated Torrance Test for Adults (ATTA) than the China sample. In contrast, the China sample scored significantly higher in understanding the importance of creativity. Results indicated creative attitudes and divergent thinking sequentially mediated the effects of parental values on creative achievement for the US sample, whereas Openness mediated the effect of high-school education on creative achievement for the China sample. For both samples, creative attitudes mediated the effect of Openness on divergent thinking. The results suggested cultural differences in the effects of environmental factors on creativity, yet more similar findings in the effects of individual characteristics on creativity between the two samples. The results and implications are discussed.

Certain diversity among team members is beneficial to the growth of an organization. Multiple measures have been proposed to quantify diversity, although little is known about their psychometric properties. This article proposes several methods to evaluate the unidimensionality and reliability of three measures of diversity. To approximate the interval scale required by the measures of diversity, a transformation on the Likert-item scores is proposed. Ridge maximum likelihood is used to deal with the issue of small sample size, and methods for evaluating the significance of the difference of two reliability estimates with correlated samples are also developed. Results with a real data set on entrepreneurial teams indicate that different measures of diversity may correspond to significantly different estimates of reliability. Results also indicate that diversity measures obtained with the transformed data tend to be more unidimensional than their counterparts obtained from Likert data. However, diversity measures obtained from Likert data tend to yield greater reliability estimates. Among the three examined measures of diversity, the standard deviation is found to yield greater and more efficient reliability estimates than the others and is thus recommended.

Much effort has been devoted to the synthesis of novel nanostructured MnO2 materials because of their unique properties and potential applications as cathode catalyst in Microbial fuel cell. Hybrid MnO2 nanostructures were fabricated by a simple hydrothermal method in this study. Their crystal structures, morphology, and electrochemical characters were carried out by FESEM, N2-adsorption-desorption, and CV, indicating that the hydrothermally synthesized MnO2 (HSM) was structured by nanorods of high aspect ratio and multivalve nanoflowers and more positive than the naturally synthesized MnO2 (NSM), accompanied by a noticeable increase in oxygen reduction peak current. When the HSM was employed as the cathode catalyst in air-cathode MFC which fed with leachate, a maximum power density of 119.07 mW/m2 was delivered, 64.68% higher than that with the NSM as cathode catalyst. Furthermore, the HSM via a 4-e pathway, but the NSM via a 2-e pathway in alkaline solution, and as 4-e pathway is a more efficient oxygen reduction reaction, the HSM was more positive than NSM. Our study provides useful information on facile preparation of cost-effective cathodic catalyst in air-cathode MFC for wastewater treatment.

This is a follow-up reply to "Structural parameters under partial least squares and covariance-based structural equation modeling: A comment on Yuan and Deng (2021)" by Schuberth et al. (2023). In this reply, explanations are provided on why the messages in the comment article are mostly from a lack of a coherent understanding of the results in Yuan and Deng (2021, YD21). Implications of the results in YD21 are explicated to facilitate proper comparison between covariance-based structural equation modeling (SEM) and partial least-squares SEM. The meaning of bias and mean-squared errors for parameter estimates is also elaborated for models involving latent variables that have no predefined scales. [ABSTRACT FROM AUTHOR]