Sulfur‐Decorated Ni−N−C Catalyst for Electrocatalytic CO2 Reduction with Near 100 % CO Selectivity

Developing highly efficient electrocatalysts for electrochemical CO2 reduction (ECR) to value-added products is important for CO2 conversion and utilization technologies. In this work, a sulfur-doped Ni−N−C catalyst is fabricated through a facile ion-adsorption and pyrolysis treatment. The resulting Ni−NS−C catalyst exhibits higher activity in ECR to CO than S-free Ni−N−C, yielding a current density of 20.5 mA cm−2 under −0.80 V versus a reversible hydrogen electrode (vs. RHE) and a maximum CO faradaic efficiency of nearly 100 %. It also displays excellent stability with negligible activity decay after electrocatalysis for 19 h. A combination of experimental investigations and DFT calculations demonstrates that the high activity and selectivity of ECR to CO is due to a synergistic effect of the S and Ni−NX moieties. This work provides insights for the design and synthesis of nonmetal atom-decorated M−N−C-based ECR electrocatalysts.publishedVersio

An Evaluation Framework for Online Courses Based on Sentiment Analysis Using Machine Learning

Online course evaluation is critical to both course selection and teaching effectiveness for students and teachers. However, the current online course evaluation methods have been criticized for neglecting learners’ needs and their inefficiency. Therefore, a course evaluation framework based on sentiment analysis using machine learning is proposed in this study to analyze a large number of online course review comments from learners. Initially, massive open online course review comments were collected through web crawling. Then, sentence- and aspect-based sentiment analyses were performed. Finally, a list of aspect terms that reflected the learners’ requirements was compiled based on the model-generated outcomes. The model was utilized to evaluate an online intellectual property law online course. Results demonstrate that the training models built in this study achieve over 90% accuracy and that 90%–95% of learners are satisfied with the intellectual property law online course. The learners are particularly satisfied with the teacher’s teaching style and course schedule. However, the models also highlight the insufficient interactivity in the class and the scarcity of novel course cases. The proposed framework provides a learner-centric approach to evaluating online courses, thereby enhancing the credibility of online course evaluation. This framework also serves as a practical reference for online course recommendation and construction

Knowledge structure and global trends of machine learning in stroke over the past decade: A scientometric analysis

Objective: Machine learning (ML) models have been widely applied in stroke prediction, diagnosis, treatment, and prognosis assessment. We aimed to conduct a comprehensive scientometrics analysis of studies related to ML in stroke and reveal its current status, knowledge structure, and global trends. Methods: All documents related to ML in stroke were retrieved from the Web of Science database on March 15, 2023. We refined the documents by including only original articles and reviews in the English language. The literature published over the past decade was imported into scientometrics software for influence detection and collaborative network analysis. Results: 2389 related publications were included. The annual publication outputs demonstrated explosive growth, with an average growth rate of 63.99 %. Among the 90 countries/regions involved, the United States (729 articles) and China (636 articles) were the most productive countries. Frontiers in Neurology was the most prolific journal with 94 articles. 234 highly cited articles, each with more than 31 citations, were detected. Keyword analysis revealed a total of 5333 keywords, with a predominant focus on the application of ML models in the early diagnosis, classification, and prediction of “acute ischemic stroke” and “atrial fibrillation-related stroke”. The keyword “classification” had the first and longest burst, spanning from 2013 to 2018. ‘Upport vector machine’ got the strongest burst strength with 6.2. Keywords such as ‘mechanical thrombectomy’, ‘expression’, and 'prognosis' experienced bursts in 2022 and have continued to be prominent. Conclusion: The applications of ML in stroke are increasingly diverse and extensive, with researchers showing growing interest over the past decade. However, the clinical application of ML in stroke is still in its early stages, and several limitations and challenges need to be addressed for its widespread adoption in clinical practice

The Prescription trends and dosing appropriateness analysis of novel oral anticoagulants in ischemic stroke patients: a retrospective study of 9 cities in China

Background: Novel oral anticoagulants (NOACs) have been recommended by guidelines as the first-line drugs for preventing cardiogenic stroke. We aimed to provide an overview of the prescription trends and dosing appropriateness of NOACs in China.Methods: We conducted a retrospective analysis of NOAC prescriptions using the Hospital Prescription Analysis Cooperation Project data from 2016 to 2022. Various patient features, such as gender, age, city, year, source, department visited, original diagnosis, dosing, cost, and insurance type, were collected and analyzed to examine the trends and dosing appropriateness of NOAC usage in ischemic stroke patients.Results: 62,014 NOAC prescriptions were analyzed, including 16,602 for dabigatran, 45,253 for rivaroxaban, and 159 for apixaban. 85.14% of the patients were aged 65 or above, and tertiary hospitals accounted for 95.97% of NOAC prescriptions. NOAC prescriptions rose from 1828 in 2016 to 13,998 in 2021 but dropped to 13,166 in 2022. The percentage of annual prescriptions for NOACs among stroke patients has increased from 0.05% in 2016 to 0.37% in 2022. Total drug cost increased from ¥704541.18 in 2016 to ¥4128648.44 in 2021, then decreased to ¥1680109.14 in 2022. Prescriptions were divided into 48,321 appropriate and 11,262 inappropriate dosing groups, showing significant differences in medications, age, year, city type, hospital level, source, insurance type, and department visited (all p < 0.001). The median drug cost for inappropriate dosing was higher than for appropriate dosing (¥55.20 VS ¥83.80). The top comorbidities in ischemic stroke patients were atrial fibrillation (35.30%), hypertension (32.75%), and coronary heart disease (16.48%).Conclusion: The application of NOACs in the Chinese population is increasing. Our findings highlight the frequent deviation from labeled dosing of NOACs in clinical practice. Continued efforts are necessary to promote the appropriate use of NOACs according to the standard dosage in the drug insert

A Visual Discrimination of Existing States of Virus Capsid Protein by a Giant Molybdate Cluster

We report a unique phenomenon, the opposite color response of a giant polyoxometalate, (NH4)42[Mo132O372(CHCOO)30] (H2O)72 ([Mo132]), to the existing states of human papillomavirus (HPV) major capsid protein, L1-pentamer (L1-p), and virus-like particles (VLPs). The color responses originate from the different assembly forms between [Mo132] and the capsid protein. The latter were inspected and separated by using CsCl gradient centrifugation, and validated in detail by sodium dodecyl sulfate-polyacrylamide gel-electrophoresis (SDS-PAGE), dynamic light scattering (DLS), and transmission electron microscopy (TEM) imaging. Furthermore, the intrinsic mechanisms were investigated in-depth by using XPS-based semi-quantitative analysis and well-designed peptides, revealing the critical points of L1 that determine the charge–transfer ratio between Mo(V) to Mo(VI), and consequently, the levels of [Mo132] hypochromic in different assemblies. Such a unique phenomenon is significant as it supplies a colorimetry approach to distinguish the existing states of the HPV capsid protein and would be significant in the quality assay of the HPV vaccine and existing states of other viruses in the future

Cross‐domain state‐of‐health estimation of Li‐ion batteries based on transfer neural network with soft‐dynamic time warping

Abstract The success of deep learning in the field of state‐of‐health (SOH) estimation relies on a large amount of battery data and the fact that all data possess the same probability distribution. While in real situations, a model based on one working condition data set may not be valid for another working condition data set due to distribution differences. Therefore, this article proposes a transfer learning method using soft‐dynamic time warping (soft‐DTW) as the statistical feature in the feature transfer method, called soft‐DTW domain adaptation network (SDDAN). By combining the prediction error with the time‐series gap in the model training process, the feature transformation can make the obtained prediction results more similar to the source domain results, which can help us to obtain better prediction results in the target domain. Experimental results show that SDDAN can effectively predict the SOH of Li‐ion batteries and significantly improve the performance of feature learning and knowledge transfer

The association of very low-density lipoprotein receptor (VLDLR) haplotypes with egg production indicates VLDLR is a candidate gene for modulating egg production

Abstract The very low-density lipoprotein receptor (VLDLR) transports egg yolk precursors into oocytes. However, our knowledge of the distribution patterns of VLDLR variants among breeds and their relationship to egg production is still incomplete. In this study, eight single nucleotide polymorphisms (SNPs) that account for 87% of all VLDLR variants were genotyped in Nick Chick (NC, n=91), Lohmann Brown (LohB, n=50) and Lueyang (LY, n=381) chickens, the latter being an Chinese indigenous breed. Egg production by NC and LY chickens was recorded from 17 to 50 weeks. Only four similar haplotypes were found in NC and LohB, of which two accounted for 100% of all NC haplotypes and 92.5% of LohB haplotypes. In contrast, there was considerable haplotypic diversity in LY. Comparison of egg production in LY showed that hens with NC-like haplotypes had a significantly higher production (p < 0.05) than those without the haplotypes. However, VLDLR expression was not significantly different between the haplotypes. These findings indicate a divergence in the distribution of VLDLR haplotypes between selected and non-selected breeds and suggest that the near fixation of VLDLR variants in NC and LohB is compatible with signature of selection. These data also support VLDLR as a candidate gene for modulating egg production

Comprehensive Quality and Bioactive Constituent Analysis of Celery Juice Made from Different Cultivars

Celery juice is rich in bioactive constituents, has good health properties, and is becoming much more popular, with its demand continuing to rise. The results of this study show that celery juice from Chinese cultivars contains more bioactive constituents, whereas celery cultivars from the United States and European countries have a higher juice yield. Compared with the other juices, the juices of five cultivars may taste sweeter, and the juices of three cultivars had a higher antioxidant capacity. The juices of six cultivars (three with the highest antioxidant capacity and three with the lowest antioxidant capacity) were selected to analyze bioactive constituents by LC/MS and GC/MS. A total of 71 phenolic acids, 38 flavonoids, 18 coumarins, 41 terpenoids, and 11 phthalides were detected in the juices of the six celery cultivars. The contents of 14 compounds had a more than 10-fold difference among these celery juices. This study first evaluated the comprehensive quality of the juices made from 26 celery cultivars and then analyzed the differences in bioactive constituents in the juices of6 celery cultivars. These findings provide information for the further study on the health functions of celery juice and can also guide celery juice production and celery breeding