Taylors University

About: Taylors University is a based out in . It is known for research contribution in the topics: Tourism & Population. The organization has 1513 authors who have published 2954 publications receiving 33603 citations.

Endoplasmic Reticulum Stress Activates Unfolded Protein Response Signaling and Mediates Inflammation, Obesity, and Cardiac Dysfunction: Therapeutic and Molecular Approach

Abstract: Obesity has been implicated as a risk factor for insulin resistance and cardiovascular diseases (CVDs). Although the association between obesity and CVD is a well-established phenomenon, the precise mechanisms remain incompletely understood. This has led to a relative paucity of therapeutic measures for the prevention and treatment of CVD and associated metabolic disorders. Recent studies have shed light on the pivotal role of prolonged endoplasmic reticulum stress (ERS)-initiated activation of the unfolded protein response (UPR), and the ensuing chronic low-grade inflammation, and altered insulin signaling in promoting obesity-compromised cardiovascular system (CVS). In this aspect, potential ways of attenuating ERS-initiated UPR signaling seems a promising avenue for therapeutic interventions. We review intersecting role of obesity-induced ERS, chronic inflammation, insulin resistance, and oxidative stress in the discovery of targeted therapy. Moreover, this review highlights the current progress and strategies on therapeutics being explored in preclinical and clinical research to modulate ERS and UPR signaling.

Wearable payment: A deep learning-based dual-stage SEM-ANN analysis

Abstract: The research paper purports to assess the antecedents that affect users’ behavioral intention to use wearable payment. Specifically, this empirical research examines the roles of perceived aesthetics, technology readiness, mobile usefulness, and mobile ease of use on behavioral intention. Differing from past mobile payment studies, a newly proposed methodology that involves a dual-stage analysis and an emerging Artificial Intelligence analysis named deep learning was performed on 307 usable responses. Findings revealed that all relationships were supported except for the linkage between mobile ease of use and behavioral intention. The results of this study provide valuable insights to payment companies and smart wearable device manufacturers to come up with plans and marketing strategies to convince the potential adopters to adopt wearable payment, guiding marketers to design a more successful wearable payment solution. Theoretically, the newly integrated theoretical model that incorporates Mobile Technology Acceptance Model, Fashion Theory, and Technology Readiness Theory could help ascertain the relative significance of certain determinants, providing a clearer insight on the acceptance of wearable payment among consumers.

Comparative study of three digestion methods for elemental analysis in traditional medicine products using atomic absorption spectrometry

Abstract: Traditional medicine mainly of herbal origin is widely used all around the world. Heavy metal contamination in such products is frequently reported. Accumulation of heavy metals in the human body leads to various health hazards. Thus, precise determination for such contaminants is required for safety assurance. Sample preparation is a significant step in spectroscopic analysis to achieve reliable and accurate results. Wet digestion methods are basically used for the dissolution of herbal product samples prior to elemental analysis. This study has been designed to evaluate the efficiency of three acid digestion methods using different solvents. Five samples were digested with three different acid digestion methods namely method A (a combination of nitric-perchloric acids HNO3–HClO4 in a ratio 2:1), method B (only nitric acid HNO3), and method C (a mixture of nitric-hydrochloric acids HNO3–HCl in a ratio 1:3), to recommend the most efficient digestion method that gains the highest analyte recovery. The analysis of arsenic (As), cadmium (Cd), lead (Pb), nickel (Ni), zinc (Zn), and iron (Fe) was conducted using various techniques of atomic absorption spectrometry (AAS). The statistical analysis revealed that method C which represented the combination of nitric-hydrochloric acids HNO3–HCl in a ratio 1:3 was the most efficient digestion method for herbal product samples as it had given a significant high recovery (p < 0.05) for all metals compared to method A and method B. Accuracy of the proposed method was evaluated by the analysis of standard reference material (SRM) 1515 Apple Leaves from the National Institute of Standards and Technology (NIST) which presented good recoveries for all metals ranging from 94.5 to 108 %. Method C provides highest recovery for all the analytes under investigation using AAS in herbal medicine samples.

Secure Healthcare Data Aggregation and Transmission in IoT—A Survey

Abstract: Internet of medical things (IoMT) is getting researchers’ attention due to its wide applicability in healthcare Smart healthcare sensors and IoT enabled medical devices exchange data and collaborate with other smart devices without human interaction to securely transmit collected sensitive healthcare data towards the server nodes Alongside data communications, security and privacy is also quite challenging to securely aggregate and transmit healthcare data towards Fog and cloud servers We explored the existing surveys to identify a gap in literature that a survey of fog-assisted secure healthcare data collection schemes is yet contributed in literature This paper presents a survey of different data collection and secure transmission schemes where Fog computing based architectures are considered A taxonomy is presented to categorize the schemes Fog assisted smart city, smart vehicle and smart grids are also considered that achieve secure, efficient and reliable data collection with low computational cost and compression ratio We present a summary of these scheme along with analytical discussion Finally, a number of open research challenges are identified Moreover, the schemes are explored to identify the challenges that are addressed in each scheme