Static coupling effect of a two-degree-of-freedom direct drive induction motor

Two-degree-of-freedom motors are capable of producing linear, rotary, and helical motion, and thus have widespread applications in special industries. In this study, a new concept- static coupling effect is studied in the two-degree-of-freedom direct-drive induction motor (2DoFDDIM). The proposed approach is based on the image method and the three-dimensional (3D) finite-element method. The image method model is established to analyse its reasons and predict the main effects, which are then verified by the proposed 3D finite-element static coupling model and experiments. The induced voltages and currents are produced in the static part and induced torque or force is obtained, even though the static part is not energised. It is concluded that the static coupling effect increases with the supply frequency and is influenced by the stator winding configuration. Thus, the existence of the static coupling effect is confirmed, which must be taken into account in future optimisation and precise control of the 2DoFDDIM

Assessment of intrahepatic blood flow by Doppler ultrasonography: Relationship between the hepatic vein, portal vein, hepatic artery and portal pressure measured intraoperatively in patients with portal hypertension

<p>Abstract</p> <p>Background</p> <p>Abnormality of hepatic vein (HV) waveforms evaluated by Doppler ultrasonography has been widely studied in patients with chronic liver disease. We investigated the correlation between changes in HV waveforms and portal vein velocity (PVVel), the hepatic artery pulsatility index (HAPI), and also the extent of abnormal Doppler HV waveforms expressed as damping index (DI), severity of portal hypertension expressed as Child-Pugh scores and portal pressure (PP) measured directly from patients with portal hypertension (PHT) to evaluate the indicative value of abnormal HV waveforms and discuss the cause of abnormal HV waveform.</p> <p>Methods</p> <p>Sixty patients who had been diagnosed with PHT and accepted surgical therapy of portosystemic shunts were investigated. PP was measured intraoperatively. Thirty healthy volunteers with no history of chronic liver disease were enrolled as the control group. HV waveforms were categorized as triphasic, biphasic or monophasic. DI was compared as the quantitative indicator of abnormal HV waveforms. Another two Doppler parameters, PVVel and HAPI were also measured. These Doppler features were compared with PP, Child-Pugh scores and histological changes assessed by liver biopsy.</p> <p>Results</p> <p>In the patient group, the Doppler flow waveforms in the middle HV were triphasic in 31.6%, biphasic in 46.7%, and monophasic in 21.6% of subjects. These figures were 86.7%, 10.0%, and 3.3%, respectively, in healthy subjects. With the flattening of HV waveforms, the HAPI increased significantly (<it>r </it>= 00.438, <it>p </it>< 0.0001), whereas PVVel decreased significantly (<it>r </it>= -0.44, <it>p <</it>0.0001). Blood flow parameters, HAPI, PVVel and HV-waveform changes showed no significant correlations with Child-Pugh scores. The latter showed a significant correlation with PP (<it>r </it>= 0.589, <it>p </it>= 0.044). Changes of HV waveform and DI significantly correlated with PP (<it>r </it>= 0.579, <it>r </it>= 0.473, <it>p <</it>0.0001), and significant correlation between DI and Child-Pugh scores was observed (<it>r </it>= 0.411, <it>p = </it>0.001). PP was significantly different with respect to nodule size (<it>p </it>< 0.05), but HV-waveform changes were not significantly correlated with pathological changes.</p> <p>Conclusion</p> <p>In patients with PHT, a monophasic HV waveform indicates higher portal pressure. Furthermore, quantitative indicator DI can reflect both higher portal pressure and more severe liver dysfunction. Flattening of HV waveforms accompanied by an increase in the HAPI and decrease in PVVel support the hypothesis that histological changes reducing HV compliance be the cause of abnormality of Doppler HV waveforms from the hemodynamic angle.</p

Hypoglycemia and Death in Mice Following Experimental Exposure to an Extract of Trogia venenata Mushrooms

BACKGROUND: Clusters of sudden unexplained death (SUD) in Yunnan Province, China, have been linked to eating Trogia venenata mushrooms. We evaluated the toxic effect of this mushroom on mice. METHODS: We prepared extracts of fresh T. venenata and Laccaria vinaceoavellanea mushrooms collected from the environs of a village that had SUD. We randomly allocated mice into treatment groups and administered mushroom extracts at doses ranging from 500 to 3500 mg/kg and water (control) via a gavage needle. We observed mice for mortality for 7 days after a 3500 mg/kg dose and for 24 hours after doses from 500 to 3000 mg/kg. We determined biochemical markers from serum two hours after a 2000 mg/kg dose. RESULTS: Ten mice fed T. venenata extract (3500 mg/kg) died by five hours whereas all control mice (L. vinaceoavellanea extract and water) survived the seven-day observation period. All mice died by five hours after exposure to single doses of T. venenata extract ranging from 1500 to 3000 mg/kg, while the four mice exposed to a 500 mg/kg dose all survived. Mice fed 2000 mg/kg of T. venenata extract developed profound hypoglycemia (median= 0.66 mmol/L) two hours after exposure. DISCUSSION: Hypoglycemia and death within hours of exposure, a pattern unique among mushroom toxicity, characterize T. venenata poisoning

Exploration of natural phosphatidylcholine sources from six beans by UHPLC-Q-HRMS

International audienceBACKGROUND: Bean is a rich source of phosphatidylcholine (PC). This study aims to explore natural PC sources rich in polyunsaturated fatty acid (PUFA) with nutritional interest. PCs from six beans were purified (purity > 98.2%) by thin layer chromatography, and subsequently identified by UHPLC-Q-Exactive Orbitrap/MS.RESULTS: Results showed that chickpea and soybean contained the highest quantity of PC among the six beans, making up 50.0 mg/g and 34.0 mg/g, respectively. Gas chromatographic analysis showed that soybean fatty acids contained high proportion of polyunsaturated fatty acid (58.78%), and chickpea contained high proportion of DHA (22:6, 2.73%). A total of 49 molecular species were identified by UHPLC-Q-Exactive Orbitrap/MS. (18:2-18:2)PC was predominant in soybean, red bean, red kidney bean and white kidney bean. (16:0-18:1)PC was the major species of chickpea PC and many plasmanyl-PC species and DHA (22:6)-PC were identified. The Principal Component Analysis (PCA) analysis and hierarchical cluster analysis indicated that the molecular profiles of chickpea PC were significantly different compared to other beans studied.CONCLUSION: The findings suggest that chickpea appears to be an interesting plant source of DHA and ether lipids for dietary supplement.Keywords: Bean PC, UHPLC-Q-Exactive Orbitrap/MS, Molecular species, Identification, PC

Nanometer-Scale Heterogeneous Interfacial Sapphire Wafer Bonding for Enabling Plasmonic-Enhanced Nanofluidic Mid-Infrared Spectroscopy

10.1021/acsnano.0c05794ACS NANO14912159-1217

Deep Learning for Classification of Thyroid Nodules on Ultrasound: Validation on an Independent Dataset

Objectives: The purpose is to apply a previously validated deep learning algorithm to a new thyroid nodule ultrasound image dataset and compare its performances with radiologists. Methods: Prior study presented an algorithm which is able to detect thyroid nodules and then make malignancy classifications with two ultrasound images. A multi-task deep convolutional neural network was trained from 1278 nodules and originally tested with 99 separate nodules. The results were comparable with that of radiologists. The algorithm was further tested with 378 nodules imaged with ultrasound machines from different manufacturers and product types than the training cases. Four experienced radiologists were requested to evaluate the nodules for comparison with deep learning. Results: The Area Under Curve (AUC) of the deep learning algorithm and four radiologists were calculated with parametric, binormal estimation. For the deep learning algorithm, the AUC was 0.69 (95% CI: 0.64 - 0.75). The AUC of radiologists were 0.63 (95% CI: 0.59 - 0.67), 0.66 (95% CI:0.61 - 0.71), 0.65 (95% CI: 0.60 - 0.70), and 0.63 (95%CI: 0.58 - 0.67). Conclusion: In the new testing dataset, the deep learning algorithm achieved similar performances with all four radiologists. The relative performance difference between the algorithm and the radiologists is not significantly affected by the difference of ultrasound scanner.Comment: Clinical Imaging (2023