Social interaction and sleep as possible mechanisms of the association between loneliness and increased blood pressure

Previous research has found that loneliness is associated with increased blood pressure in old adults (Hawkley, Masi, Berry, & Cacioppo, 2006; Hawkley, Thisted, Masi, & Cacioppo, 2010). However, later studies suggested that this association between loneliness and blood pressure may not be replicable. The present study examined whether there was an association between loneliness and blood pressure in a sample of 391 mid-aged and older adults (SHINE: Study of Health and Interactions in the Natural Environment), with loneliness measured by UCLA Loneliness Scale-Revised and blood pressure assessed during a four-day ambulatory monitoring study. Moreover, building on the loneliness model proposed by Hawkley and Cacioppo (2010), the current study examined whether social interaction quality and sleep may explain such a link between loneliness and increased blood pressure in this sample, with social interaction quality measured by ecological momentary assessment and sleep measured objectively by actigraphy and subjectively by the Pittsburgh Sleep Quality Index. Findings showed that loneliness was not associated with blood pressure in mid-aged and older adults after controlling for age, sex, race, and education. Loneliness was also not related to Actigraphy-assessed sleep (total sleep time and sleep efficiency). However, loneliness was significantly related to lower self-reported sleep quality as well as to lower social interaction positivity and higher social interaction negativity among participants in daily life. The results of the current study have implications for current models of loneliness, social interactions, and health

Atmospheric-Pressure Plasma Sources for Polymer Surface Modification

Plasma processing is widely used in the microelectronics industry for deposition of thin films. It is also used in etching of semiconductors, metals and organic materials such as photoresists. In addition, plasmas are widely used to modify material surfaces. Plasma surface modification can improve the surface adhesion of polymeric materials, which can be used as insulating layers in multilayer semiconductor structures. In deposition and etching, relatively a large amount of material is added to or removed from the surface. In plasma surface modification, only the surface layer is changed in composition or structure, and no significant amount of material is added or removed. In this research, two atmospheric-pressure plasmas were generated and characterized, and were used to modify polyethyleneterephthalate (PET) surfaces. An atmospheric-pressure helium plasma source was generated without any need of vacuum. The plasma was first characterized with a Langmuir Probe for electron density estimation. The emission spectrum was measured and the spectroscopic identification allowed main components of the plasma to be identified. In addition, absorption spectroscopy was used to measure the ozone density from the plasma. A PET surface was modified with this plasma. Contact angles were measured on the modified PET surface. Hydrophilic and Hydrophobic PET surfaces were obtained with different minority gas or chemicals added to the feeding helium gas. The changes of the contact angles of the modified surfaces were monitored as a function of time. The surface modification was determined to be mainly a chemical and photochemical process through analysis and experiments on ions, ultraviolet photons, oxygen atoms and ozone molecules. An atmospheric-pressure air plasma source was developed without the need of vacuum and the need of expensive helium gas. The peak electron density was determined by measuring and analyzing current-voltage characteristics of the plasma. The emission spectrum was measured and the main peaks were identified. Absorption spectroscopy was used to estimate ozone density. This plasma was used to modify PET surfaces with very high throughput

From Data Flows to Privacy Issues: A User-Centric Semantic Model for Representing and Discovering Privacy Issues

In today\u27s highly connected cyber-physical world, people are constantly disclosing personal and sensitive data to different organizations and other people through the use of online and physical services. Such data disclosure activities can lead to unexpected privacy issues. However, there is a general lack of tools that help to improve users\u27 awareness of such privacy issues and to make more informed decisions on their data disclosure activities in wider contexts. To fill this gap, this paper presents a novel user-centric, data-flow graph based semantic model, which can show how a given user\u27s personal and sensitive data are disclosed to different entities and how different types of privacy issues can emerge from such data disclosure activities. The model enables both manual and automatic analysis of privacy issues, therefore laying the theoretical foundation of building data-driven and user-centric software tools for people to better manage their data disclosure activities in the cyber-physical world

Breaking a chaos-noise-based secure communication scheme

This paper studies the security of a secure communication scheme based on two discrete-time intermittently-chaotic systems synchronized via a common random driving signal. Some security defects of the scheme are revealed: 1) the key space can be remarkably reduced; 2) the decryption is insensitive to the mismatch of the secret key; 3) the key-generation process is insecure against known/chosen-plaintext attacks. The first two defects mean that the scheme is not secure enough against brute-force attacks, and the third one means that an attacker can easily break the cryptosystem by approximately estimating the secret key once he has a chance to access a fragment of the generated keystream. Yet it remains to be clarified if intermittent chaos could be used for designing secure chaotic cryptosystems.Comment: RevTeX4, 11 pages, 15 figure

Segmenting travelers based on responses to nudging for information disclosure

Digital technologies shape travel environments. Noticing online privacy issues, consumers can hold distinct attitudes towards disclosing personal information to service providers. We conducted a panel survey to gauge travelers’ willingness to share personal information with service providers, provided with different types of nudges. Based on the results of clustering analysis, two segments were identified: travelers who are reasonably willing to share (Privacy Rationalists) and those who are reluctant to share (Privacy Pessimists). This study provides empirical evidence of privacy segmentations in the travel context, which has not been reported before and thus deserves more attention from both researchers and practitioners

HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image Segmentation

Modern deep neural networks struggle to transfer knowledge and generalize across diverse domains when deployed to real-world applications. Currently, domain generalization (DG) is introduced to learn a universal representation from multiple domains to improve the network generalization ability on unseen domains. However, previous DG methods only focus on the data-level consistency scheme without considering the synergistic regularization among different consistency schemes. In this paper, we present a novel Hierarchical Consistency framework for Domain Generalization (HCDG) by integrating Extrinsic Consistency and Intrinsic Consistency synergistically. Particularly, for the Extrinsic Consistency, we leverage the knowledge across multiple source domains to enforce data-level consistency. To better enhance such consistency, we design a novel Amplitude Gaussian-mixing strategy into Fourier-based data augmentation called DomainUp. For the Intrinsic Consistency, we perform task-level consistency for the same instance under the dual-task scenario. We evaluate the proposed HCDG framework on two medical image segmentation tasks, i.e., optic cup/disc segmentation on fundus images and prostate MRI segmentation. Extensive experimental results manifest the effectiveness and versatility of our HCDG framework.Comment: this paper is currently not publishe