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Objectives: This study aims to decrease the scan time and enhance image quality in pediatric total-body PET imaging by utilizing multimodal artificial intelligence techniques. Methods: A total of 270 pediatric patients who underwent total-body PET/CT scans with a uEXPLORER at the Sun Yat-sen University Cancer Center were retrospectively enrolled. 18F-fluorodeoxyglucose (18F-FDG) was administered at a dose of 3.7 MBq/kg with an acquisition time of 600 s. Short-term scan PET images (acquired within 6, 15, 30, 60 and 150 s) were obtained by truncating the list-mode data. A three-dimensional (3D) neural network was developed with a residual network as the basic structure, fusing low-dose CT images as prior information, which were fed to the network at different scales. The short-term PET images and low-dose CT images were processed by the multimodal 3D network to generate full-length, high-dose PET images. The nonlocal means method and the same 3D network without the fused CT information were used as reference methods. The performance of the network model was evaluated by quantitative and qualitative analyses. Results: Multimodal artificial intelligence techniques can significantly improve PET image quality. When fused with prior CT information, the anatomical information of the images was enhanced, and 60 s of scan data produced images of quality comparable to that of the full-time data. Conclusion: Multimodal artificial intelligence techniques can effectively improve the quality of pediatric total-body PET/CT images acquired using ultrashort scan times. This has the potential to decrease the use of sedation, enhance guardian confidence, and reduce the probability of motion artifacts. [ABSTRACT FROM AUTHOR]

Together, the Yinggehai and Qiongdongnan basins have received a large amount of terrigenous sediments, but the provenance evolution of Cenozoic sediments in the two basins remains disputable. Combined with previous studies in the Yinggehai and Qiongdongnan basins, the elemental geochemistry of Oligocene to Pliocene sediment samples in the junction area of the two basins were analyzed to explore the tectonic implications, parent rock characteristics, and provenance evolution of the two basins during the Cenozoic. The results reveal that all the sediment samples were derived from continental island arc to passive continental margin settings. The light REE enrichment and stable content of heavy REE with large negative Eu anomalies indicate that they were probably derived from Hainan Island. The reconstructed provenance evolution model showed that the Red River Source (RRS) provided sedimentary materials for the Central Depression of Yinggehai Basin from the Oligocene to the Pliocene, and Hainan Island Source (HIS) was also one of the sources for sediments deposited in the Central Depression of Yinggehai Basin during the Miocene. However, most of the sediments preserved in the Yingdong Slope and Qiongdongnan Basin were derived from the HIS from the Oligocene to the Pliocene, and sediments deposited in the Yingdong Slope were also derived from the RRS during the Miocene. Furthermore, the junction area of the two basins had a mixed source of the RRS and HIS during the Cenozoic. [ABSTRACT FROM AUTHOR]

Past meta-analyses in mental health interventions failed to use stringent inclusion criteria and diverse moderators, therefore, there is a need to employ more rigorous methods to provide evidence-based and updated results on this topic. This study presents an updated meta-analysis of interventions targeting anxiety or depression using more stringent inclusion criteria (e.g., baseline equivalence, no significant differential attrition) and additional moderators (e.g., sample size and program duration) than previous reviews. This meta-analysis includes 29 studies of 32 programs and 22,420 students (52% female, 79% White). Among these studies, 22 include anxiety outcomes and 24 include depression outcomes. Overall, school-based mental health interventions in grades K-12 are effective at reducing depression and anxiety (ES = 0.24, p = 0.002). Moderator analysis shows that improved outcomes for studies with anxiety outcomes, cognitive behavioral therapy, interventions delivered by clinicians, and secondary school populations. Selection modeling reveals significant publication and outcome selection bias. This meta-analysis suggests school-based mental health programs should strive to adopt cognitive behavioral therapy and deliver through clinicians at the secondary school level where possible. [ABSTRACT FROM AUTHOR]

Twin support vector machine (TSVM) has attracted much attention in the field of machine learning with good generalization ability and computational performance. However, the conventional grid search method is very time-consuming to obtain the optimal regularization parameter. To address this problem, we develop a novel fast regularization parameter tuning algorithm for TSVM, named TSVMPath. After transforming the models of two sub-optimization problems, we divide the two classes of samples into different sets. Lagrangian multipliers are then proved to be piecewise linear concerning the corresponding regularization parameters, greatly extending the search space of the solution. By proving that the Lagrangian multipliers of two sub-optimization models are 1 when the regularization parameters approach infinity, we design a simple yet effective initialization. As a result, the entirely regularized solution path can be obtained without solving quadratic programming problems. Four types of events are finally defined to update the solution path. Experiments on 8 UCI datasets show that the prediction accuracy of TSVMPath is superior to the best competing methods, with up to four orders of magnitude speed-up for the computational overhead compared with the grid search method. [ABSTRACT FROM AUTHOR]

International students continue to experience myriad of challenges, some of which further transpired disproportionately during the COVID-19 pandemic era. To this effect, this study investigated psychological capital (PsyCap), psychological distress, and well-being among 188 international students attending U.S universities. Results using Hayes PROCESS indicated that well-being mediated the relationship between PsyCap and psychological distress and in particular moderated the relationship between PsyCap and depression. When higher education institutions are considering steps to mitigate psychological distress experienced by international students during the COVID-19 pandemic and beyond, based on the findings of our study, we suggest investing efforts and resources into two aspects: (a) promotion of positive mental health and well-being and (b) identification and development of positive psychological capital. We further discuss these results and implications for mental health promotion of international students in light of its limitations and recommendations for future research. [ABSTRACT FROM AUTHOR]

We investigated the effect of supports based on ZrO2, TiO2, Al2O3, and SiO2 on the rate of propene formation in the metathesis of ethylene with 2-butene at 50 °C over Mo-containing catalysts possessing highly dispersed MoOx. Large improvements in this rate were achieved when using supports composed of mixed oxides (ZrO2–SiO2, ZrO2–PO4, TiO2–SiO2; Al2O3–SiO2) rather than of individual oxides (ZrO2, TiO2, Al2O3, SiO2). Although previous literature studies dealing with the metathesis reaction over Al2O3- or SiO2-suppported catalysts at higher temperatures suggest the importance of redox or acidic properties of supported MoOx species for catalyst activity, we were not able to establish any general direct correlation in this regard. Contrarily, the rate of propene formation can be significantly enhanced when promoting supports with an oxide promoter. We suggest that the created support lattice defects may facilitate the transformation of MoOx to Mo carbenes under reaction conditions or improve the intrinsic activity of the latter. [ABSTRACT FROM AUTHOR]