sj-dta-2-hpq-10.1177_13591053221124374 – Supplemental material for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators

Supplemental material, sj-dta-2-hpq-10.1177_13591053221124374 for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators by Mingqi Fu, Jing Guo and Qilin Zhang in Journal of Health Psychology</p

sj-pdf-3-hpq-10.1177_13591053221124374 – Supplemental material for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators

Supplemental material, sj-pdf-3-hpq-10.1177_13591053221124374 for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators by Mingqi Fu, Jing Guo and Qilin Zhang in Journal of Health Psychology</p

sj-smcl-4-hpq-10.1177_13591053221124374 – Supplemental material for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators

Supplemental material, sj-smcl-4-hpq-10.1177_13591053221124374 for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators by Mingqi Fu, Jing Guo and Qilin Zhang in Journal of Health Psychology</p

sj-do-1-hpq-10.1177_13591053221124374 – Supplemental material for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators

Supplemental material, sj-do-1-hpq-10.1177_13591053221124374 for The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators by Mingqi Fu, Jing Guo and Qilin Zhang in Journal of Health Psychology</p

Supplemental Material - Predictive Model of Chemotherapy-Induced Myelosuppression for Patients with Esophageal Cancer

Supplemental Material for Predictive Model of Chemotherapy-Induced Myelosuppression for Patients with Esophageal Cancer by Ziming Zheng, Qilin Zhang, Yong Han, Tingting Wu, and Yu Zhang in Cancer Control</p

Highly Efficient Conversion of Xylose Residues to Levulinic Acid over FeCl₃ Catalyst in Green Salt Solutions

The economically viable synthesis of levulinic acid (LA), a promising and valuable renewable biomass-derived platform for bioproducts, with high carbon efficiency is a challenge. A direct and highly effective catalytic system for conversion of xylose residues (XRs) into LA under mild conditions by using FeCl₃ as catalyst and cheaply available NaCl as promoter has been developed. The NaCl solution exhibits high carbon efficiency in LA (68.0 mol %) when compared with the non-NaCl systems (48.5 mol %) due to the moderate increase of the acidity and the higher viscosity of the NaCl system than water. The experimental results demonstrated that the presence of NaCl caused no distinctive changes on reaction pathways but increased the dissolution rate and the hydrolysis rate of XRs cellulose. Moreover, further integration of our degradation process with a reactive extraction step makes energy-efficient separation of LA. The NaCl solutions easily and efficiently extracted LA into LA-derived solvent 2-methyltetrahydrofuran from aqueous solutions. The efficiency and integration of the reaction process presented a great potential for LA production from renewable biomass with the aid of concentrated seawater

Lightning Optical Automatic Detection Method based on Deep Neural Network

In order to achieve automatic lightning image recognition, which cannot easily be handled by existing methods and still requires significant manpower consumption, we propose a lightning image dataset and a preprocessing method. At least 5 months of lightning image data is collected based on the two optical observation stations with camera, then a series of batch labeling methods is applied, which can greatly reduce the workload of subsequent manual labeling, and a dataset containing more than 30,000 labeled samples has been established. Considering that lightning varies rapidly over time, we propose a time sequence composite (TSC) preprocessing method that inputs lightning's time-varying characteristics into a model for better lightning image recognition. By using experiments, TSC is evaluated on four backbones, and it is found that this preprocess method significantly enhances the classification performance. The final trained model can successfully distinguish between "lightning" and "non-lightning" samples, and a recall rate of 86.5% and a false detection rate of 0.2% have been achieved.</p