1,150 research outputs found
sj-docx-1-jtr-10.1177_00472875231151395 – Supplemental material for Travelers’ Psychological Ownership: A Systematic Review and Future Research Agenda
No full textSupplemental material, sj-docx-1-jtr-10.1177_00472875231151395 for Travelers’ Psychological Ownership: A Systematic Review and Future Research Agenda by Cenhua Lyu, Yangyang Jiang and M. S. Balaji in Journal of Travel Research</p
sj-docx-1-jtr-10.1177_00472875231206548 – Supplemental material for Assessing the Effectiveness of Environmental Sustainability Performance Communication in Tourism: Mediation and Moderation Effects
No full textSupplemental material, sj-docx-1-jtr-10.1177_00472875231206548 for Assessing the Effectiveness of Environmental Sustainability Performance Communication in Tourism: Mediation and Moderation Effects by Jishnu Bhattacharyya, M. S. Balaji and Yangyang Jiang in Journal of Travel Research</p
An introduction to socially responsible sustainable consumption: issues and challenges
Get PDFNo abstract available
Interleukin-1 mediated cell-type specific signaling in hippocampal neurons and astrocytes
No full textInterleukin-1β (IL-1β) is a pro-inflammatory cytokine that is implicated in immune and inflammatory responses. In the central nervous system (CNS), IL-1β is synthesized and released during injury, infection, and many neurodegenerative diseases, but also under physiological conditions. Several IL-1-mediated signaling pathways and effects have been identified in hippocampal neurons and astrocytes, but their mechanisms have not been fully defined. IL-1 signaling requires the type one IL-1 receptor (IL-1RI) as well as IL-1 receptor accessory protein (IL-1RAcP) as a receptor partner. A novel isoform of the IL-1 receptor accessory protein, AcPb, has also been found in the CNS, but its role remains unclear. This thesis examined AcPb function in regulating IL-1β signaling. The results showed that IL-1β activated p38 MAPK but not NFκB in neurons. In astrocytes, IL-1β induced both p38 and NFκB pathways in regulating inflammatory responses. AcPb was not involved in mediating either p38 or NFκB in either cell type. In contrast, a physiological level of IL-1β treatment (0.01ng/ml) activated p-Src in neurons via AcPb in vitro. In addition, overexpression of AcPb in astrocytes was sufficient to induce p-Src mediated by IL-1β. Taken together, these results suggest that the restricted expression of AcPb in CNS neurons may mediate neuronal specific IL-1 pathways and outcomes, and that physiological and pathophysiological levels of IL-1β mediate particular neuronal functions via separate pathways.Ph. D.Includes abstractIncludes bibliographical referencesby Yangyang Huan
sj-docx-1-taj-10.1177_20406223221109651 – Supplemental material for Sarcopenia and frailty combined increases the risk of mortality in patients with decompensated cirrhosis
No full textSupplemental material, sj-docx-1-taj-10.1177_20406223221109651 for Sarcopenia and frailty combined increases the risk of mortality in patients with decompensated cirrhosis by Gaoyue Guo, Chaoqun Li, Yangyang Hui, Lihong Mao, Mingyu Sun, Yifan Li, Wanting Yang, Xiaoyu Wang, Zihan Yu, Xiaofei Fan, Kui Jiang and Chao Sun in Therapeutic Advances in Chronic Disease</p
Earthworms differentially modify the microbiome of arable soils varying in residue management
No full textMolecular simulations of rheological, mechanical and transport properties of solid-fluid systems:
No full textIn this dissertation, two distinct but relevant systems are chosen as representatives of interesting solid-fluid systems. Molecular dynamics (MD) and Monte Carlo techniques are applied to investigate the rheological, mechanical and transport properties of these systems.
Firstly, polyethylene melt embedded with silica nanoparticles is examined to be of our interest. Since it is computationally impractical to model a complex system with a molecular description, a multiscale modeling approach, which combines both atomistic and mesoscale simulations, is employed to efficiently represent and study the polymer nanoparticle systems. Based on a coarse-grained force field for polyethylene, a novel method is developed for determining the solid-fluid interaction at the spherical interface. Our coarse grained model is designed to mimic 4 nm silica nanoparticles in polyethylene melt at 423K. A series of MD simulations are performed to investigate the factors that control the homogeneity of nanofillers inside polymer matrix, also in the presence of nonionic surfactants (short chain alcohols). The effects of nanoparticle filling fraction, polymer chain length, and relative sizes between nanoparticles and polymer chains on the particle dispersion are explored. In addition, a fundamental relationship is pursued between the microstructure and macroscopic properties (transport and rheological) of polymer nanoparticle composites.
In this work another method for determining the solid-fluid interaction parameter is presented: the experimental adsorption isotherms are used to validate the potential parameters. The rapid expansion of silica nanoparticle agglomerates in supercritical carbon dioxide (RESS process) is chosen to be the system of interest. The simulations show that the effective attraction between two identical nanoparticles is most prominent for densely hydroxylated particle surfaces that interact strongly with CO2 via hydrogen bonds, while it is significantly weaker for dehydroxylated particles. We also explore the shearing forces necessary to break an agglomerate in supercritical fluid. The agglomerate experiences deformation followed by elongation, and finally break-up. The calculated diffusion coefficient of CO2 is expected to be smaller than the experimental value, because the nanoparticle agglomerate hinders fluid movement. In the direction of shearing forces, the diffusion of CO2 shows a steep increase after the breakup, confirming the rupture of the agglomerate.Ph.D.Includes bibliographical references (p. 136-142)by Yangyang She
A Novel Geometric Algorithm for Blind Image Restoration Based on High-Dimensional Space
No full textA novel geometric algorithm for blind image restoration is proposed in this paper, based on High-Dimensional Space Geometrical Informatics (HDSGI) theory. In this algorithm every image is considered as a point, and the location relationship of the points in high-dimensional space, i.e. the intrinsic relationship of images is analyzed. Then geometric technique of "blurring-blurring-deblurring" is adopted to get the deblurring images. Comparing with other existing algorithms like Wiener filter, super resolution image restoration etc., the experimental results show that the proposed algorithm could not only obtain better details of images but also reduces the computational complexity with less computing time. The novel algorithm probably shows a new direction for blind image restoration with promising perspective of applications
Hydrophobic ionic liquids-assisted polymer recovery during penicillin extraction in aqueous two-phase system
No full textIn this study, terminal modified poly(ethylene glycerol) (PEG) was employed as the phase-forming polymer to construct aqueous two-phase (ATP). After the phase equilibrium, 95.8% penicillin could be extracted into imidazole-terminal PEG-rich phase efficiently. Imidazole-terminal PEG (I-PEG) was separated from the aqueous phase containing penicillin to hydrophobic ionic liquid phase at basic pH, and a weak acidic aqueous phase was then employed to recover the I-PEG from the hydrophobic ionic liquid phase into water at pH 5.5-6. The recycle of the polymer was achieved with the aid of hydrophobic ionic liquids. (C) 2008 Elsevier B.V. All rights reserved
Towards robust malware detection
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 45-48).A central challenge of malware detection using machine learning methods is the presence of adversarial variants, small changes to detectable malware that allow it to evade a model (i.e. be classified as benign). We take inspiration from adversarial variant generation methods in the continuous-valued image domain to introduce methods for malware in the binary domain. We incorporate these methods in the training of hardened models towards the goal of robustness against adversarial variants. Additionally, we provide visualization tools for analysis of hardened models. Our tools illustrate the difference in loss behavior between models trained with different methods, the effect of adversarial learning on the loss landscape of a model, and the effect of adversarial learning on the decision map of a model. The adversarial learning framework and the visualization tools in combination allow for the creation and understanding of robust models.by Alex Yangyang Huang.M. Eng
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