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Rolling element bearing (REB) vibration signals under variable speed (VS) have non-stationary characteristics. Order tracking (OT) and time-frequency analysis (TFA) are two widely used methods for REB fault diagnosis under VS. However, the effect of OT methods is affected by resampling errors and close-order harmonic interference, while the accuracy of TFA methods is mainly limited by time-frequency resolution and ridge extraction algorithms. To address this issue, a novel method based on envelope spectrum fault characteristic frequency band identification (FCFBI) is proposed. Firstly, the characteristics of the bearing fault vibration signal’s envelope spectrum under VS are analyzed in detail and the fault characteristic frequency band (FCFB) is introduced as a new and effective representation of faults. Then, fault templates based on FCFB are constructed as reference for fault identification. Finally, based on the calculation of the correlation coefficients between the envelope spectrum and fault templates in the extended FCFB, the bearing fault can be diagnosed automatically according to the preset correlation coefficient criterion. Two bearing VS experiments indicate that the proposed method can achieve satisfactory diagnostic accuracy. The comparison of OT and TFA methods further demonstrates the comprehensive superiority of the proposed method in the overall consideration of accuracy, diagnostic time, tachometer dependency, and automatic degree.

Background As e-cigarette use rates continue to increase globally, people in different countries have developed varying perceptions of e-cigarette use. Understanding these perceptions could potentially help policymakers develop regulations that align with their tobacco control objectives. Existing research on the reasons for not using e-cigarettes among adults who smoke cigarettes has been limited to specific countries. This study broadens the scope and reports reasons for not using e-cigarettes among adults who smoke cigarettes in 20 leading nicotine markets worldwide. Methods We performed a secondary analysis of data from the 2019–2021 Euromonitor International’s Voice of Consumer: Nicotine Survey. The study sample consisted of adults who had never used e-cigarettes or had used them more than one year ago, and who currently smoked combustible cigarettes monthly or more often in 20 leading nicotine-consuming countries, including Canada, China, Czech Republic, France, Germany, Greece, Israel, Italy, Japan, Kazakhstan, Netherlands, Poland, Romania, Russia, Slovakia, South Korea, Spain, Ukraine, the United Kingdom, and the United States. Reasons for not using e-cigarettes were measured with a multiple-response question. Weighted percentages for each reason overall and by age, sex, and country were reported. Results The top reasons for not using e-cigarettes among adults who smoked cigarettes across the 20 countries were “never considered/not enough information,” “inauthentic/not ‘the real thing,’” and “too expensive,” closely followed by “safety concerns.” The top reasons were similar in most countries, with some variations. Greece had “do not want to quit smoking” and France had “prolonging addiction/substituting to another format” among the top reasons. In Poland, South Korea, Romania, and Slovakia, “unaware of the product” was one of the top reasons. Conclusions Tobacco control practitioners and policymakers can use the findings on reasons for not using e-cigarettes both domestically and globally to inform public health campaigns and policies that align with the specific tobacco control objectives in each country to ultimately reduce the burden of tobacco-related disease.

In recent years, Sporosarcina pasteurii (S . pasteurii) has become one of the most popular bacteria in microbially induced calcium carbonate precipitation (MICP). Various applications have been developed based on the efficient urease that can induce the precipitation of calcium carbonate. However, the metabolic mechanism related to biomineralization of S . pasteurii has not been clearly elucidated. The process of bacterial culture and biomineralization consumes a large amount of urea or ammonium salts, which are usually used as agricultural fertilizers, not to mention probable environmental pollutions caused by the excessive use of these raw materials. Therefore, it is urgent to reveal the mechanism of nitrogen utilization and metabolism of S . pasteurii . In this paper, we compared the growth and gene expression of S . pasteurii under three different culture conditions through transcriptome analyses. GO and KEGG analyses revealed that both ammonium and urea were direct nitrogen sources of S . pasteurii , and the bacteria could not grow normally in the absence of ammonium or urea. To the best of our knowledge, this paper is the first one to reveal the nitrogen utilization mechanism of S . pasteurii through transcriptome methods. Furthermore, the presence of ammonium might promote the synthesis of intracellular ATP and enhance the motility of the bacteria. There should be an ATP synthesis mechanism associated with urea hydrolysis catalyzed by urease in S . pasteurii .

The Taipei Basin (TPB) and the Lanyang Plain (LYP) are geographically similar, both situated in northern Taiwan. However, significant differences in heat transfer processes arise between the two regions due to local terrain influences under the Northeast Monsoon. Precipitation patterns in the TPB and LYP, especially during the case study of 26 November 2021, differ markedly due to the distinctive dustpan-shaped terrain of the LYP. Our study, based on the WRF model, reveals that while both the TPB and LYP are characterized by downward cold air transfer, the TPB exhibits stronger atmospheric boundary layer mixing and a higher mixing layer height compared to the LYP. Turbulent kinetic energy (TKE) in the TPB is higher during the morning and evening, while vertical heat flux is more pronounced in the LYP. The average sensible heat flux is greater in the TPB, whereas latent heat flux is higher in the LYP. In addition, the amount of water vapor transported into the LYP by the Northeast Monsoon is greater than in the TPB. In the TPB, the wind field, influenced by the terrain, shifts predominantly from northeast to northeasterly and southeasterly. However, upon entering the LYP, the same environmental wind field is affected by the dustpan-shaped terrain, resulting in a counterclockwise near-surface wind pattern. The wind field transitions from northeasterly in the north to westerly, southwesterly, or northwesterly in the south. This difference in wind field causes precipitation in the TPB to be confined mainly to the windward side of the mountainous areas whereas, in the LYP, precipitation occurs both on the windward side and, more abundantly, in the plains. The effect of different types of terrain under the Northeast Monsoon is quite obvious.

This study explored the effects of online academic help-seeking (OAHS) and flipped learning (FL) on students' development of involvement, self-efficacy, and self-directed learning. A quasi-experiment was conducted to investigate whether students' involvement, self-efficacy, and self-directed learning increases over time with intervention by OAHS, FL, and their combination. Three classes of first-year university students in a one-semester course were chosen for this empirical research. The 102 students were divided into three groups. The first group (G1, which received online OAHS and FL), and the second group (G2, which received online FL only), were the experimental groups. The last group (G3), which received the traditional teaching method in a blended course, served as the control group. The results indicate that G1 students' involvement, self-efficacy, and self-directed learning all improved under the condition of simultaneously applying OAHS and FL. In addition, this study also reveals that the application of FL alone could be helpful in G2 students' development of their involvement, self-efficacy, and self-directed learning. However, G3 students, who learned with traditional teaching method in a blended learning environment, did not have better development in their involvement, self-efficacy, and self-directed learning. Finally, the authors further discuss the implications for teachers, scholars, and schools engaged in online education.

Vibration signal analysis is an important means for bearing fault diagnosis. Affected by the vibration of other machine parts, external noise and the vibration transmission path, the impulses induced by a bearing defect in the measured vibrations are very weak. Blind deconvolution (BD) methods can counteract the effect of the transmission path and enhance the fault impulses. Most BD methods highlight fault features of the filtered signals by impulse-featured objective functions (OFs). However, residual noise in the filtered signals has not been well tackled. To overcome this problem, a fuzzy entropy-assisted deconvolution (FEAD) method is proposed. First, FEAD takes advantage of the high noise sensitivity of fuzzy entropy (FuzzyEn) and constructs a weighted FuzzyEn–kurtosis OF to enhance the fault impulses while suppressing noise interference. Then, the PSO algorithm is used to iteratively solve the optimal inverse deconvolution filter. Finally, envelope spectrum analysis is performed on the filtered signal to realize bearing fault diagnosis. The feasibility of FEAD was first verified by the bearing fault simulation signals at constant and variable speeds. The bearing test signals from Case Western Reserve University (CWRU), the railway wheelset and the test bench validated the good performance of FEAD in fault feature enhancement. A comparison with and quantitative results for the other state-of-the-art BD methods indicated the superiority of the proposed method.

Background Extensive‐stage small cell lung cancer (ES‐SCLC) is deemed as a fatal malignancy with a poor prognosis. Although immunotherapy has gradually played an important role in the treatment of ES‐SCLC since 2018, ES‐SCLC treatment data and patient outcome before 2018, when chemotherapy served as a fundamental therapeutic strategy, is still meaningful as a summary of the situation regarding previous medical treatment and is a baseline for comparative data. In addition, the prognostic factors of ES‐SCLC have failed to reach a consensus until now. Therefore, this study aimed to evaluate survival and identify the prognostic factors in an ES‐SCLC population. Methods We retrospectively collected the detailed medical records of 358 patients with ES‐SCLC from January 1, 2011 to December 31, 2018 in a Chinese top‐level cancer hospital. The prognostic factors were evaluated by Cox univariate and multivariate analysis. Results The median overall survival (OS) of ES‐SCLC patients (N = 358) was 14.0 months, the one‐ and two‐year OS rates were 56.2% and 21.7%, respectively. Moreover, we identified two demographic characters (age ≥ 70, smoking index ≥ 400), one tumor burden factor (bone multimetastasis), two tumor biomarkers (cyfra211, CA125) and two laboratory indexes (decreased Na, PLR < 76) as independent prognostic factors for OS in this patient population. Progression‐free survival (PFS) data of 238 patients was obtained for further analysis, and the median PFS was 6.2 months, and six‐month and one‐year PFS rates were 51.7% and 14.3%, respectively. Elevated cyfra211, decreased Hb and Na were identified as independent prognostic factors for PFS. Conclusions This study provides real‐world evidence of the survival and prognosis of ES‐SCLC patients which will enable better evaluation and clinical decision‐making in the future. This study provides real‐world evidence of survival and prognosis of untreated extensive stage small cell lung cancer (ES‐SCLC). We retrospectively collected the detailed medical records of 358 patients with ES‐SCLC from 2011 to 2018 in a Chinese top‐level cancer hospital. The median overall survival (OS) of all patients was 14.0 months, and the one‐ and two‐year OS rates were 56.2% and 21.7%, respectively. The median progression‐free survival (PFS) of 238 patients was 6.2 months, and the six‐month and one‐year PFS rates were 51.7% and 14.3%, respectively. Moreover, several independent prognostic factors for OS and PFS of ES‐SCLC were identified.

Objectives To determine whether contrast-enhanced ultrasonography (CEUS) can be used for selecting lesions and assessing the ablative effects of MRgFUS ablation on uterus fibroids, compared with MR imaging. Methods This retrospective study was approved by the institutional review board of our hospital. From April 2018 to November 2019, a total of 44 symptomatic fibroids in 38 patients who underwent MRgFUS ablation were included. The association between pre-ablation characteristics on CEUS/MR imaging and the non-perfusion volume (NPV) after ablation was analyzed using multivariable linear regression analysis. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve values was compared between the CEUS and MR imaging regression models. NPV after ablation was compared between CEUS and enhanced MR imaging. Results On CEUS, entangled branch vessels, fast-in, and fast-out patterns were significantly associated with NPV, with an AUC of 0.95 (95% CI; 0.88, 1.00). On MR imaging, hyper-intensity on T2-weighted images (T2WI), hyper-intense ring-like signal on T2WI images, and hyper-enhancement on contrast-enhanced T1WI images were correlated with NPV, with an AUC of 0.86 (95% CI; 0.70, 1.00). After ablation, no differences in NPV were noted between contrast-enhanced T1WI (84.13 ± 75.42 cm 3 ) and CEUS (80.22 ± 76.49 cm 3 ). Conclusions Some pre-ablation characteristics of uterine fibroids on CEUS were associated with NPV after MRgFUS. CEUS may contribute to the evaluation of ablative outcomes and patient selection, similar to MR imaging. Key Points • Contrast-enhanced ultrasonography (CEUS) is effective for selecting the appropriate uterine fibroids before MR-guided focused ultrasound (MRgFUS) ablation and evaluating non-perfusion volumes (NPV) after ablation, as a potential alternative to MR imaging. • Before ablation, entangled branch vessels, fast-in, and fast-out patterns on CEUS were significantly associated with NPV after MRgFUS. • No significant differences in NPV were detected between contrast-enhanced T1WI and CEUS after ablation.

Background Early prediction of treatment response is crucial for the optimal treatment of advanced breast cancer. We aimed to explore whether monitoring early changes in plasma human epidermal growth factor receptor 2 (HER2) levels using digital PCR (dPCR) could predict the treatment response in advanced breast cancer. Methods This was a multicenter, prospective, noninterventional clinical study of patients with advanced breast cancer. All enrolled patients underwent blood testing to measure the HER2 levels by digital PCR before treatment initiation and once every 3 weeks during the study. The primary endpoints werea the diagnostic value of dPCR for detecting HER2 status in the blood andb the relevance of potential changes in the plasma HER2 level at 3 weeks from baseline for predicting treatment response. Results Overall, 85 patients were enrolled between October 9, 2018, and January 23, 2020. dPCR had a specificity of 91.67% (95% CI: 80.61% to 97.43%) for detecting HER2 amplification, and the area under the receiver operating characteristic (ROC) curve was 0.84 (p < 0.01). A clinically relevant specificity threshold of approximately 90%, which was equivalent to a ≥15% decrease in the plasma HER2 ratio at 3 weeks from baseline, showed a positive predictive value of 97.37% (95% CI: 77.11% to 98.65%) in terms of predicting clinical benefit. Patients whose plasma HER2 ratio was reduced by ≥15% had a longer median progression‐free survival (PFS) than those whose ratio was reduced by <15% (9.20 months vs. 4.50 months, p < 0.01). Conclusions Early changes in the plasma HER2 ratio may predict the treatment response in patients with advanced breast cancer and could facilitate optimal treatment selection. Early prediction of treatment response is crucial for the optimal treatment of advanced breast cancer. This study found monitoring early changes in plasma human epidermal growth factor receptor 2 (HER2) levels using digital PCR (dPCR) could predict the treatment response in advanced breast cancer.

The complex and harsh working environment of rolling bearings cause the fault characteristics in vibration signal contaminated by the noise, which make fault diagnosis difficult. In this paper, a feature enhancement method of rolling bearing signal based on variational mode decomposition with K determined adaptively (K-adaptive VMD), and radial based function fuzzy entropy (RBF-FuzzyEn), is proposed. Firstly, a phenomenon called abnormal decline of center frequency (ADCF) is defined in order to determine the parameter K of VMD adaptively. Then, the raw signal is separated into K intrinsic mode functions (IMFs). A coefficient En for selecting optimal IMFs is calculated based on the center frequency bands (CFBs) of all IMFs and frequency spectrum for original signal autocorrelation operation. After that, the optimal IMFs of which En are bigger than the threshold are selected to reconstruct signal. Secondly, RBF is introduced as an innovative fuzzy function to enhance the feature discrimination of fuzzy entropy between bearings in different states. A specific way for determination of parameter r in fuzzy function is also presented. Finally, RBF-FuzzyEn is used to extract features of reconstructed signal. Simulation and experiment results show that K-adaptive VMD can effectively reduce the noise and enhance the fault characteristics; RBF-FuzzyEn has strong feature differentiation, superior noise robustness, and low dependence on data length.