368 research outputs found
sj-docx-2-tag-10.1177_17562848221101722 – Supplemental material for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study
No full textSupplemental material, sj-docx-2-tag-10.1177_17562848221101722 for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study by Yubin Cao, Jiaming Feng, Shihao Duan, Yi Yang and Yan Zhang in Therapeutic Advances in Gastroenterology</p
sj-docx-1-tag-10.1177_17562848221101722 – Supplemental material for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study
No full textSupplemental material, sj-docx-1-tag-10.1177_17562848221101722 for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study by Yubin Cao, Jiaming Feng, Shihao Duan, Yi Yang and Yan Zhang in Therapeutic Advances in Gastroenterology</p
sj-docx-3-tag-10.1177_17562848221101722 – Supplemental material for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study
No full textSupplemental material, sj-docx-3-tag-10.1177_17562848221101722 for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study by Yubin Cao, Jiaming Feng, Shihao Duan, Yi Yang and Yan Zhang in Therapeutic Advances in Gastroenterology</p
sj-pdf-1-mdm-10.1177_0272989X221107902 – Supplemental material for PaCAR: COVID-19 Pandemic Control Decision Making via Large-Scale Agent-Based Modeling and Deep Reinforcement Learning
No full textSupplemental material, sj-pdf-1-mdm-10.1177_0272989X221107902 for PaCAR: COVID-19 Pandemic Control Decision Making via Large-Scale Agent-Based Modeling and Deep Reinforcement Learning by Xudong Guo, Peiyu Chen, Shihao Liang, Zengtao Jiao, Linfeng Li, Jun Yan, Yadong Huang, Yi Liu and Wenhui Fan in Medical Decision Making</p
RETRACTED ARTICLE: Flot2 targeted by miR-449 acts as a prognostic biomarker in glioma
No full textWe, the Editors and Publisher of the journal Artificial Cells, Nanomedicine, and Biotechnology, have retracted the following article:Shaosong Huang, Shihao Zheng, Shengyue Huang, Hui Cheng, Ying Lin, Yuxing Wen & Wei Lin (2019) Flot2 targeted by miR-449 acts as a prognostic biomarker in glioma. Artificial Cells, Nanomedicine, and Biotechnology, 47(1), 250–255, DOI: 10.1080/21691401.2018.1549062Since publication, concerns have been raised about the integrity of the data in the article. When approached for an explanation, the authors have been unresponsive, and we have been unable to verify their original data. We are therefore retracting this article and the corresponding author listed in this publication has been informed.We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”
Physical Layer Security: Wireless Location Verification and Secure Communications
No full textThis thesis focuses on the utilization of reliable location information in wireless physical layer security. Specifically, new optimal Location Verification Systems (LVSs) are first developed to authenticate claimed locations, and then robust transmission strategies that utilize the verified locations are exploited in order to enhance physical layer security.
In the first half of this thesis, new optimal LVSs are developed and analyzed, leading to the following three main contributions. First, an information-theoretic framework for optimizing an LVS is developed and analyzed, in which the mutual information between the input and output data of the LVS is utilized as the optimization metric. Our analysis reveals that relative to more general frameworks the information-theoretic framework has a weaker dependence on critical unknown
parameters of the system.
Second, new optimal LVSs for a range of optimization metrics are proposed and examined under spatially correlated shadowing, with the conclusion that correlation in shadowing can lead to dramatic LVSs performance improvements. Third, analysis on an LVS under Rician fading channels discloses that the performance of the LVS increases significantly as the proportion of the line-of-sight component in the legitimate channel increases, or the tracking information on claimed locations accumulates. Surprisingly, our analysis also demonstrates that the performance limit of the LVS does not depend on the inherent properties of the channel between an adversary and the LVS.
In the second half of this thesis, robust transmission strategies utilizing verified location information are developed, leading to the following additional contributions. Fourth, an optimal location-based beamforming scheme that solely requires the locations of the intended receiver and the potential eavesdropper is proposed and analyzed under a Rician wiretap channel. Specifically, we provide the optimal location-based beamformer that minimizes the secrecy outage probability. Fifth, new antenna selection schemes which rely on verified locations are proposed. Our analysis reveals that the new antenna selection schemes enhance wireless physical layer security at the cost of only a minor increase in the feedback overhead. Sixth and finally, the optimization of wiretap code rates is investigated for a range of passive eavesdropping scenarios. Specifically, the optimal wiretap code rates for given locations of the eavesdropper are determined
Study of n-type Amorphous Silicon Alloy as the Anode in Li-ion Batteries
No full textIn recent years, the world has witnessed a dramatic advancement in sustainable energy development. Due to the inconsistent supply of such energy, a more efficient energy storage method is in need. Among many options, lithium-ion battery stands out due to its lightweight, high energy density, and high discharge potential. Currently, the most commonly adapted anode materials in lithium-ion batteries are carbon-based, most often graphite. It shows a layered structure that can be used to store Li+ ions based on the intercalation and de-intercalation mechanism. Although this material is stable and successfully commercialized, due to its low specific capacity efforts have been put into searching other potential anode materials. Potential materials are aluminum, tin, and silicon. Among them, silicon shows an ultra-high (theoretical) specific capacity that is 12 times higher than that of carbon. However, the volume taken up by the material increases by about 300% upon lithiation and de-lithiation. Hence, silicon anodes show a poor capacity retention ability comparing to its graphite counterpart. In this work, by using a silicon alloy, we aim to alleviate the effects of volume expansion of Si by introducing alloying species and by providing a porous structure. In this work it is demonstrated that this material structure is able to absorb the expansion, while still rendering a high specific capacity. Silicon alloy samples over a wide range of alloy concentration and porosity were synthesized using PECVD. Samples were assembled into pouch-cells and coin-cells and tests were performed to compare the battery performance of each sample. A FEM model was built, enabling more investigation opportunities. Together with the experiments, they revealed how alloy concentration and porosity influence the specific capacity and cycling ability of the anode.Materials Science and Engineerin
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