Tetracosanuclear nickel complexes as effective catalysts for cycloaddition of carbon dioxide with epoxides.

A series of well-defined tetracosanuclear nickel complexes 3-7 facilely produced by one-pot synthesis were active catalysts for cycloaddition of CO2 and cyclohexene oxide (CHO). These nickel complexes were doughnut-like supramolecular coordination complexes involving eight repeating units, and each of them contains one Schiff base ligand and three nickel(II) ions. Notably, the 24-nuclear nickel cluster complex 3 in combination with nucleophilic additives was the most efficient catalyst to mediate CO2 coupling with CHO to generate CO2-based cis-cyclohexene carbonates. In addition to CO2/CHO cycloaddition, complex 3 was also found to effectively couple CO2 with other alicyclic epoxides, generating the corresponding cyclic carbonates. Additionally, kinetic investigations for CO2 cycloaddition of CHO using 3 were reported.

Deep Convolutional Neural Network Optimization for Defect Detection in Fabric Inspection.

This research is aimed to detect defects on the surface of the fabric and deep learning model optimization. Since defect detection cannot effectively solve the fabric with complex background by image processing, this research uses deep learning to identify defects. However, the current network architecture mainly focuses on natural images rather than the defect detection. As a result, the network architecture used for defect detection has more redundant neurons, which reduces the inference speed. In order to solve the above problems, we propose network pruning with the Bayesian optimization algorithm to automatically tune the network pruning parameters, and then retrain the network after pruning. The training and detection process uses the above-mentioned pruning network to predict the defect feature map, and then uses the image processing flow proposed in this research for the final judgment during fabric defect detection. The proposed method is verified in the two self-made datasets and the two public datasets. In the part of the proposed network optimization results, the Intersection over Union (IoU) of four datasets are dropped by 1.26%, 1.13%, 1.21%, and 2.15% compared to the original network model, but the inference time is reduced to 20.84%, 40.52%, 23.02%, and 23.33% of the original network model using Geforce 2080 Ti. Furthermore, the inference time is also reduced to 17.56%, 37.03%, 19.67%, and 22.26% using the embedded system AGX Xavier. After the image processing part, the accuracy of the four datasets can reach 92.75%, 94.87%, 95.6%, and 81.82%, respectively. In this research, Yolov4 is also trained with fabric defects, and the results showed this model are not conducive to detecting long and narrow fabric defects.

Caffeine Mitigates Lung Inflammation Induced by Ischemia-Reperfusion of Lower Limbs in Rats.

Reperfusion of ischemic limbs can induce inflammation and subsequently cause acute lung injury. Caffeine, a widely used psychostimulant, possesses potent anti-inflammatory capacity. We elucidated whether caffeine can mitigate lung inflammation caused by ischemia-reperfusion (IR) of the lower limbs. Adult male Sprague-Dawley rats were randomly allocated to receive IR, IR plus caffeine (IR + Caf group), sham-operation (Sham), or sham plus caffeine (n = 12 in each group). To induce IR, lower limbs were bilaterally tied by rubber bands high around each thigh for 3 hours followed by reperfusion for 3 hours. Caffeine (50 mg/kg, intraperitoneal injection) was administered immediately after reperfusion. Our histological assay data revealed characteristics of severe lung inflammation in the IR group and mild to moderate characteristic of lung inflammation in the IR + Caf group. Total cells number and protein concentration in bronchoalveolar lavage fluid of the IR group were significantly higher than those of the IR + Caf group (P < 0.001 and P = 0.008, resp.). Similarly, pulmonary concentrations of inflammatory mediators (tumor necrosis factor-α, interleukin-1ß, and macrophage inflammatory protein-2) and pulmonary myeloperoxidase activity of the IR group were significantly higher than those of the IR + Caf group (all P < 0.05). These data clearly demonstrate that caffeine could mitigate lung inflammation induced by ischemia-reperfusion of the lower limbs.