Dynamic mechanical properties of nonirradiated and irradiated blends of polyethylene (PE) and ethylene vinylacetate (EVA) copolymer have been determined. Effect of addition of EVA and radiational crosslinking on loss and storage modulus, tan ␦, and transition temperatures were determined. Increase in transition temperatures on exposure to radiation and decrease in transition temperatures with addition of EVA is observed. Peak broadening is observed on exposure to radiation. Values of the storage modulus increase while that of loss modulus and tan ␦ decrease on crosslinking
Analyzing gender is critical to study mental health (MH) support in CVD (cardiovascular disease). The existing studies on using social media for extracting MH symptoms consider symptom detection and tend to ignore user context, disease, or gender. The current study aims to design and evaluate a system to capture how MH symptoms associated with CVD are expressed differently with the gender on social media. We observe that the reliable detection of MH symptoms expressed by persons with heart disease in user posts is challenging because of the co-existence of (dis)similar MH symptoms in one post and due to variation in the description of symptoms based on gender. We collect a corpus of 150k items (posts and comments) annotated using the subreddit labels and transfer learning approaches. We propose GeM, a novel task-adaptive multi-task learning approach to identify the MH symptoms in CVD patients based on gender. Specifically, we adopt a knowledge-assisted RoBERTa based bi-encoder model to capture CVD-related MH symptoms. Moreover, it enhances the reliability for differentiating the gender language in MH symptoms when compared to the state-of-art language models. Our model achieves high (statistically significant) performance and predicts four labels of MH issues and two gender labels, which outperforms RoBERTa, improving the recall by 2.14% on the symptom identification task and by 2.55% on the gender identification task.
X-ray photoelectron spectroscopy study of low-temperature molybdenum oxidation process J. Appl. Phys. 85, 8415 (1999); 10.1063/1.370690 X-ray photoelectron spectroscopy and x-ray diffraction study of the thermal oxide on gallium nitrideThe authors present the application of synchrotron Bragg diffraction, x-ray reflectance ͑XRR͒, and x-ray photoelectron spectroscopy ͑XPS͒ to study silicon loss in the low temperature plasma oxidation of silicon-on-insulator ͑SOI͒ wafers. The Laue oscillations of the Si͑004͒ Bragg peak provide a direct measure of the number of lattice planes that are consumed in the silicon device layer during processing, while the Fourier transform of the XRR data provides a model-independent determination of the increase in the combined thickness of the silicon and surface oxide. XPS measurements provide complementary information concerning changes in thickness, chemical composition, and the bonding of the surface oxide. These methods were applied to samples processed in an oxidizing plasma system at temperatures below 250°C. The authors find that 2.7Ϯ 1 Å of silicon, corresponding to two lattice planes, is consumed while the combined thickness increases by 2.7Ϯ 0.8 Å, corresponding to a net increase in the oxide thickness of 5.4Ϯ 1.3 Å. Thus, the ratio of oxide growth to silicon loss is about 2.0Ϯ 0.9, somewhat lower than the bulk ratio of 2.2, but within experimental error. The XPS measurements show the increase to be 5.5 Å. Additionally, XPS shows clearly the consumption of silicon to form Si 2 O and SiO 2 and the net oxidation of Si 2 O 3 to SiO 2 .
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