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Lignite, as one of the coal materials, has been considered a promising precursor for hard carbon anodes in sodium-ion batteries (SIBs) owing to its low cost and high carbon yield. Nevertheless, hard carbon directly derived from lignite pyrolysis typically exhibits highly ordered microstructure with narrow interlayer spacing and relatively unreactive interfacial properties, owing to the abundance of polycyclic aromatic hydrocarbons and inert aromatic rings within its molecular composition. Herein, an innovative demineralization activating strategy is established to simultaneously modulate the interfacial properties and the microstructure of lignite-derived carbon for the development of high-performance SIBs. Demineralization process not only creates numerous void spaces in the matrix of lignite precursor to assist aromatic hydrocarbon rearrangement, thereby reducing the ordering and expanding interlayer spacing, but also exposes more interfacial oxygen-containing functional groups to effectively increasing the sodium storage active sites. As a result, the optimal demineralized lignite-derived hard carbon (DLHC 1300) delivers a high reversible capacity of 335.6 mAh g-1 at 30 mA g-1, superior rate performance of 246.3 mAh g-1 at 6 A g-1 and nearly 100 % capacity retention after 1100 cycles at 1A g-1. Furthermore, the optimized DLHC 1300 material functions as an outstanding anode in sodium ion full cells. This work significantly advances the development of low-cost, high-performance commercial hard carbon anodes for SIBs.
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Objective: To validate the Chinese version of the Quality of Life (QoL) Patient/Cancer Survivor Version (QOLCSV-C) for measuring QoL in Chinese cancer survivors. Methods: The study followed a seven-step research practice guideline for cross-cultural research instrument validation study including translation, adaptation, and psychometric assessment. A forward- and backward-translation procedure was approached, followed by cultural adaptation and acceptability assessment. For its psychometric properties, its concurrent validity with the Functional Assessment of Cancer Therapy-General (FACT-G) was examined with correlation analysis. The internal consistency (Cronbach's alpha) and item-total and item-subtotal correlations of the QOLCSV-C were obtained. Factor analyses were conducted. Floor and ceiling effects and the discriminant performance of the selected variables on QOLCSV-C score were also examined. Results: The QOLCSV-C was translated from the 41-item QOLCSV with four domains: psychological, physical, spiritual and social well-being. The content validity was excellent (CVI â= â1.00). Time spent to complete the QOLCSV-C was about 10 âmin. The QOLCSV-C was found easy to use, appropriate in length, and reflective of their QoL. The strong correlation between QOLCSV-C and FACT-G indicates a satisfactory concurrent validity (Spearman's rho â= â0.765, P â< â0.001, n â= â205). The overall internal consistency of the QOLCSV-C (Cronbach's alpha â= â0.888) and the split-half reliability (Spearman-Brown r â= â0.918) were excellent. Most of the items show moderate to strong item-total correlation. The exploratory factor analysis revealed a four-factor solution, and confirmatory factor analysis has a satisfactory model fit with indicative items. None of the total scores of QOLCSV-C reveal the floor or ceiling effect. For discriminant performance, variables demonstrating significant between-group differences include sleep quality, pain, fatigue, nausea, physical health, and financial burden. Conclusions: The QOLCSV-C is a reliable and valid instrument for measuring the QoL in Chinese cancer survivors. Future studies can explore the factor structure, gender universal or specific items, and significant predictors of QoL of cancer survivors in different cultures.
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Purpose: To perform a bibliometric analysis of the 100 most-cited articles (T100 articles) on COVID-19 vaccine hesitancy to characterize current trends. Methods: The data of the bibliometric analysis were retrieved from the Web of Science Core Collection (WoSCC) database on January 29, 2023, and the results were sorted in descending order by citations. Two researchers independently extracted the characteristics of the top 100 cited articles, including title, author, citations, publication year, institution, country, author keywords, Journal Cited Rank, and impact factor. Excel and VOSviewer were used to analyze the data. Results: The T100 articles ranged from 79 to 1125 citations, with a mean of 208.75. The T100 articles were contributed by 29 countries worldwide, of which the USA ranked first with 28 articles and 5417 citations. The T100 articles were published in 61 journals; the top three citations were VACCINES, NATURE MEDICINE, and EUROPEAN JOURNAL OF EPIDEMIOLOGY, and the number of citations was 2690, 1712, and 1644, respectively. Professor Sallam, M(n=4) from Jordan, is the author who participated in the most published articles. Catholic University of the Sacred Heart (n=8) had the most T100 articles. Conclusion: It is the first bibliometric analysis of the T100 articles in the field of COVID-19 vaccine hesitancy. We carefully analyzed and described the characteristics of these T100 articles, which provide ideas for further strengthening COVID-19 vaccination and fighting against the epidemic in the future.
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1,3-Dinitrobenzene (1,3-DNB) is listed by the USEPA as a priority pollutant. 1,3-DNB has two nitro functional groups (-NO2) bound to the benzene ring, with a +III nitrogen oxidation states, and strong electronegativity, and therefore can be reductively degraded by gaining electrons. Weeds that contain a high proportion of polyphenols can supply electrons and act as natural reducing agents. This study investigated the potential of various weeds to reductively remove 1,3-DNB from aqueous phase. The Taguchi L9 Orthogonal experimental design method was used to explore the optimum operational parameters. According to the analyzed characteristics of weeds, including total phenol content, antioxidant capacity, metal chelating capacity, reducing capacity, and environmental adaptability, the weed Sphagneticola trilobata, containing 11.93 mg of gallic acid equivalent per gram of weed (mg-GAE/g-weed), was selected for 1,3-DNB degradation experiments. The results showed that the optimum reaction conditions for the degradation of 1,3-DNB in the aqueous phase using Sphagneticola trilobata were: pH 3, a weed dose of 10 g/L, reaction time of 14 day, and initial 1,3-DNB concentration of 0.5 mM. According to ANOVA analysis, the weed dose was the most significant factor in the experiment, and each 1 mg of 1,3-DNB degraded required 120 mg of dry weeds.