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Gold nanoparticles (AuNPs) decorated CNTs are promising materials for photocatalytics and biosensors. However, the synthesis of AuNPs chemically linked to the walls of MWCNTs is challenging and toxic products such as thionylchloride (SOCl 2 ) or [1-ethyl-3(dimethyl-amino) propyl] carbodiimide hydrochloride (EDAC) need to be used. This work reports a new approach to prepare gold nanoparticles decorated multiwalled carbon nanotubes (MWCNTs) by using cysteaminium chloride via the formation of a Zwitterionic acide-base bond. The grafting process consists of 3 mains steps: oxidation, thiolation and decoration of AuNPs on the surface of MWCNTs. The completion of each step has been verified out by both spectroscopic (Raman, UV-Vis, FT-IR) and Scanning Electron Miscroscopy (SEM). The chemical bonding states of synthesized products have been proven by X-ray photoelectron spectroscopy (XPS).

We report a superspreading event of severe acute respiratory syndrome coronavirus 2 infection initiated at a bar in Vietnam with evidence of symptomatic and asymptomatic transmission, based on ministry of health reports, patient interviews, and whole-genome sequence analysis. Crowds in enclosed indoor settings with poor ventilation may be considered at high risk for transmission.

Jet precession is sometimes invoked to explain asymmetries in radio galaxy (RG) jets and “X/S/Z-shaped” RGs, caused by the presence of a binary black hole companion to the source active galactic nucleus or by accretion instabilities. We present a series of simulations of RG jet precession to examine how these sources would evolve over time, including a passive distribution of cosmic-ray electrons so we can model radio synchrotron emissions and create synthetic radio maps of the sources. We find that a single source viewed from different angles can result in differing RG morphological classifications, confusing physical implications of these classifications. Additionally, the jet trajectories can become unstable due to their own self-interactions and lead to “reorientation events” that may look like the effects of external dynamics such as shocks, winds, or cold fronts in the medium. Finally, something akin to an “Odd Radio Circle” may be observed in the case of viewing the radio remnant of such a precessing source from a line of sight near the precession axis.

Background Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression. Methods We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds. Results We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions. Conclusion If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering.

We present an auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of local shape descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a study comparing several existing methods across various specimen, imaging techniques, and resolutions, auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinity-based segmentation methods to be on par with the current state of the art for neuron segmentation (flood-filling networks), while being two orders of magnitudes more efficient—a critical requirement for the processing of future petabyte-sized datasets. During segmentation of neurons in electron microscopy datasets, auxiliary learning via the prediction of local shape descriptors increases efficiency, which is important for the processing of datasets of ever-increasing size.

Randomisation is often believed to lead to baseline comparability of treatment groups in controlled trials. This study aims to challenge this popular belief, which is relevant in expectation– but not necessarily in realisation. After presenting an overview of methods for assessing baseline comparability of treatment groups in randomised controlled trials (RCTs), we reviewed RCTs published over 1 year in three high-impact medical journals. We extracted data regarding the methods used to evaluate baseline comparability. To quantify baseline balance, we calculated post hoc standardised mean differences (SMDs) in baseline characteristics reported in these trials. Amongst 142 RCTs, 120 (84.5%) claimed that baseline comparability was achieved. However, 81 RCTs (57%) did not report how they assessed this balance. The rest (61 RCTs, 43%) used traditional statistical tests, which are deemed inappropriate for balance checking. Our post hoc calculation of SMDs showed that 49 (34.5%) RCTs had at least one baseline variable, which might have been strongly unbalanced (i.e., SMD ≥25%) across treatment groups. Baseline incomparability of treatment groups in RCTs is often blindly ignored. We suggest it be thoroughly evaluated and transparently reported, using the standardised mean difference or other proper balance metrics.

The research goal is to identify the essential components of visitor satisfaction that influence future return intentions. The quantitative method and the deductive approach were implemented with a sample size of 300 tourists in Can Tho city, Vietnam after sending the survey questionnaire to 15 experts and receiving positive feedback within two weeks. The researchers used the main method to evaluate the data, which was structural equation modeling. The findings illustrated those three factors including cultural contact, perceived value, and green practices noticeably impact visitor satisfaction leading to their intention to visit again, with cultural contact being the most significant influence. At the same time, this helps researchers better understand the intention of tourists to return. Service quality and novelty seeking have negligible influence on tourists’ willingness to revisit the location. The valuable data of this study can inform tourism and hotel managers about their customer groups by encouraging visitors to engage in value-creating activities, cultural exposure and promotion of ideas related to green tourism. On the other side, this study contributes hospitality-related material resources for the following research and provides recommendations to create strategies for tourism regulators and hospitality businesses to promote visitor satisfaction and return.This study aims to identify the essential components of tourist satisfaction that encourage repeat visits. The questionnaire was reviewed and received good feedback from more than ten experts after which the survey was conducted with 300 tourists coming to Can Tho city, Vietnam. Through structural equation modelling, the findings illustrated those three factors including cultural contact, perceived value, and green practices noticeably impact visitor satisfaction leading to their intention to visit again, with cultural contact being the most significant influence. This also helps academics understand visitor return intentions. Tourists’ inclination to return is unaffected by service quality and novelty. This study’s findings can help tourism and hotel management understand their customers by encouraging value-creating events, cultural exposure, and green tourism initiatives. This study provides necessary resources for future research and recommends strategies for tourism regulators and hospitality firms to increase tourist happiness and repeat visits.

Pregnant women with twins and a short cervical length (CL) are at greater risk of preterm birth (PTB). The comparative efficacy of cervical cerclage and cervical pessary with or without additional progesterone to prevent PTB is unknown. We aimed to assess, in women with twin pregnancies and a short CL, the effectiveness of cerclage versus pessary and the additional treatment with 400 mg vaginal progesterone versus no progesterone in preventing PTB. This multicenter, two-by-two factorial randomised trial was conducted in 2 hospitals in Ho Chi Minh City, Vietnam. Asymptomatic women with twin pregnancies and a CL ≤28 mm at 16 to 22 gestational weeks were recruited. Between March 2019 and July 2023, we randomised 219 participants (64.4% of the planned sample size) to cerclage plus progesterone (n = 55), Arabin pessary plus progesterone (n = 56), cerclage alone (n = 54) or Arabin pessary alone (n = 54). Primary outcome was any PTB <34 weeks. Following the second interim analysis, the study was terminated due to significantly lower rates of perinatal deaths and deliveries <28 weeks in the cerclage group. The primary outcome occurred in 20 (19.8%) participants receiving cerclage versus 20 (19%) participants receiving pessary (relative risk [RR] 1.04; 95% confidence interval [CI], 0.60 to 1.8). Delivery <28 weeks occurred in 1% versus 8.6% (RR 0.12; 95% CI, 0.01 to 0.52) and perinatal death occurred in 1% versus 5.8% (RR 0.17; 95% CI, 0.05 to 0.62) in the cerclage group and the pessary group, respectively. However, PTB <24 weeks, <32 weeks, and other neonatal outcomes were not significantly different between the 2 groups. For maternal side effects, vaginal discharge was significantly less frequent in the cerclage group. In participants allocated to progesterone, PTB <34 weeks occurred in 19 (18.4%) versus 21 (20.4%) participants who did not have progesterone (RR 0.90; 95% CI, 0.52 to 1.6). In this prematurely halted study on pregnant women with twins and a CL ≤28 mm, cerclage and cervical pessary were comparably effective on PTB <34 weeks prevention. However, compared to pessary, cerclage was associated with significantly lower rates of PTB <28 weeks and perinatal mortality. ClinicalTrials.gov Registration: NCT03863613 (https://clinicaltrials.gov/study/NCT03863613).

In the current era of e-commerce, users are overwhelmed with countless products, making it difficult to find relevant items. Recommendation systems generate suggestions based on user preferences, to avoid information overload. Collaborative filtering is a widely used model in modern recommendation systems. Despite its popularity, collaborative filtering has limitations that researchers aim to overcome. In this paper, we enhance the K-nearest neighbor (KNN)-based collaborative filtering algorithm for a recommendation system, by considering the similarity of user cognition. This enhancement aimed to improve the accuracy in grouping users and generating more relevant recommendations for the active user. The experimental results showed that the proposed model outperformed benchmark models, in terms of MAE, RMSE, MAP, and NDCG metrics.

In this study, we focus on dynamic traffic routing of connected vehicles with various origins and destinations; this is referred to as a multi-source multi-destination traffic routing problem. Ant colony optimization (ACO)-based routing method, together with the idea of coloring ants, is proposed to solve the defined problem in a distributed manner. Using the concept of coloring ants, traffic flows of connected vehicles to different destinations can be distinguished. To evaluate the performance of the proposed method, we perform simulations on the multi-agent NetLogo platform. The simulation results indicate that the ACO-based routing method outperforms the shortest path-based routing method (i.e., given the same simulation period, the average travel time decreases by 8% on average and by 11% in the best case, whereas the total number of arrived vehicles increases by 13% on average and by 23% in the best case).