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Objective In the context of intelligent operation-maintenance, existing algorithm exhibits low accuracy, resulting in high false alarm rates, hence it is necessary to conduct analysis of data coupling and independent consistency in train operation data. Method The definition of coupling and independent consistency are established from both statistical and data-driven perspectives. Train operation states are divided into four stages based on the absolute value change rate of acceleration: stationary, stable operation, start-up acceleration, and brake deceleration. Corresponding data slices are generated, and comprehensive quantile plots and correlation coefficients are utilized to analyze the cumulative mainline operation data of traction and braking systems, quantifying the coupling relationship between systems. Linear regression, support vector machine, LightGBM, and K nearest neighbors models are constructed to decouple the data, rendering the traction and braking system data normal, with related variables conforming to independence and consistency, so as to meet the prerequisites of a joint conditional probability distribution. Result & Conclusion The research findings indicate that data decoupling enhances the independent consistency of raw data between systems. From an engineering perspective, the LightGBM model exhibits optimal performance in both real time and offline states, achieving no less than 50% optimization rates across all quantitative analyses. By utilizing decoupled data, it becomes feasible to issue early warnings for potential faults even in cases of limited or missing fault samples, effectively reducing false alarm rates in intelligent operation-maintenance while enhancing fault prediction accuracy.

At present, the traditional linear regression model is mainly used to predict the calorific value of coal. But it is difficult to express the complex relationship between independent variables and dependent variables. The model needs data to obey specific distribution assumptions. And the model is sensitive to abnormal values. In view of the above problems, a prediction method of coal calorific value based on quantile regression is proposed. The method selects the coal industry analysis indicators that are easy to measure, such as total moisture, ash and volatile matter. The method uses two quantile regression methods, linear quantile regression and quantile regression forest, to predict the calorific value of coal. The results are compared with that of the traditional linear regression method. The results show that the predicted value of calorific value of coal given by linear regression is only a conditional mean value. But the range of predicted value of calorific value of coal can be given by quantile regression. The prediction effect of quantile regression is better than linear regression and linear quantile regression. The importance of total moisture for the prediction of calorific value of coal is much greater than that of ash and volatile matter. Total moisture has great influence on the prediction of calorific value of low calorific value coal. But total moisture has little influence on the prediction of calorific value of high calorific value coal. Volatile matter and ash have little influence on the prediction of calorific value of low calorific value coal. But volatile matter and ash have a great influence on the prediction of calorific value of high calorific value coal.

Carbonate cementation is one of the significant tightness factors in Chang 6 reservoir of the western Jiyuan (WJY) area. Based on the observation of core and thin sections, connecting-well profile analysis as well as carbon and oxygen isotope analysis, it is found that ferrocalcite is the main carbonate cements in the Chang 6 reservoir of the WJY area. The single sand body controls the development of carbonate cements macroscopically. Both carbonate cements and calcite veins hold similar diagenetic conditions: the dissolution of plagioclase is the main calcium source and the de-acidification of organic acids is the main carbon source. The diagenetic stage is identified as the mesogenetic A stage. The sedimentary environment is of low salinity. Accordingly, the development model of carbonate cementation in Chang 6 reservoir is summarized into three types: “eggshell pattern,” “cutting pattern,” and “favorable reservoir pattern.” The development degree of carbonate cementation affects the physical properties of reservoir.

The magnetic gear has the advantages of no friction between the rotor,simple manufacturing and installation,low cost and so on,it is an excellent transmission mechanism. The development history of magnetic gears from time to time is briefly described,and the research status of magnetic gears at home and abroad is compared. The topological structure of several kinds of common magnetic gears are introduced,and the advantages and disadvantages of these kinds of magnetic gears are compared. Its future development direction and research questions are summarized.

BackgroundCancer is the leading cause of death among Asian Americans, who often face barriers to cancer care. Cancer supportive care needs among Asian Americans remain understudied.AimsWe examined cancer supportive care needs and participant factors correlated with these needs, identified profiles of supportive care needs, and examined whether needs profiles are associated with quality of life among Asian American adults.Methods and resultsWe recruited 47 Asian American adults with colorectal, liver, or lung cancer who spoke Chinese, English, or Vietnamese, and were starting or undergoing cancer treatment. We assessed cancer supportive care needs in four domains: cancer information, daily living, behavioral health, and language assistance. Hierarchical cluster analysis was used to identify clusters of participants based on their supportive need profiles to further examine the association between need profiles and quality of life (QoL) assessed by the Functional Assessment of Cancer Therapy. Participants (mean age = 57.6) included 72% males and 62% spoke English less than very well. Older participants (age ≥ 65) and those with annual income

Plagiarism is prevalent all over the world, especially in higher education. This quantitative-descriptive study investigated the reasons and gender differences for plagiarism among undergraduate students at Wenzhou-Kean University (WKU). To collect quantitative data, the random sample of 102 undergraduates at WKU answered questions about plagiarism in the online questionnaire. The results revealed that the development of technology and the Internet is the main reason for plagiarism. Surprisingly, the study found that students are confident with their citation skills. The participants reported that using additional materials to help with their online testing is easy during the COVID-19 pandemic. The COVID-19 pandemic has become another significant reason for plagiarism. In terms of gender differences, the results showed no significant difference in attitudes and behaviors toward plagiarism among WKU undergraduate students by gender. The study advises educational institutions like WKU should use both traditional solutions (e.g., failing the plagiarized assignment, giving suspension to student) and new solutions (e.g., using plagiarism tracking system) to deal with plagiarism.

PurposeCancer is the leading cause of death for Asian Americans. However, few studies have documented supportive care needs from the perspective of Asian American cancer patients. This study describes the needs reported by Asian American patients with colorectal, liver, or lung cancer over a 6-month period during their treatment.MethodsParticipants were recruited through the Greater Bay Area Cancer Registry and from cancer care providers in San Francisco. Participants self-identified as Asian or Asian American; were age 21 or older; spoke English, Chinese, or Vietnamese; and had stage I-III colon, rectum, liver, or lung cancer. Participants were matched with a language concordant patient navigator who provided support during a 6-month period. Needs were assessed by surveys at baseline, 3, and 6 months.ResultsAmong 24 participants, 58% were 65 years or older, 42% did not complete high school, and 75% had limited English proficiency (LEP). At baseline, the most prevalent needs were cancer information (79%), nutrition and physical activity (67%), language assistance (54%), and daily living (50%). At the 3- and 6-month follow-up surveys, there was a higher reported need for mental health resources and healthcare access among participants.ConclusionIn this pilot study of Asian American cancer patients who predominantly had LEP, participants reported many needs, with cancer information and language assistance as the most prominent. The findings highlight the importance of culturally and linguistically appropriate patient navigators in addressing supportive care needs among cancer patients with LEP.Trial registrationClinicalTrials.gov identifier: NCT03867916.