Is premium pricing strategy a viable option to pursue higher revenue performance? A case study of relative pricing strategy in the Singapore lodging market

This is an exploratory research paper on how relative pricing affects an individual hotel’s revenue performance in the Singapore lodging market. First, it measures the REVPAR effects for both a discounting and premium pricing strategy at a local hotel against its competitive set. The findings conclude that a premium pricing strategy is a better way to improve REVPAR performance due to the inelastic nature of the demand curve for hotel rooms in the Singapore market. The findings also show that there is a price limit to a premium pricing strategy, beyond which the growth of REVPAR stagnates because customers were willing to seek for alternatives in the market. Second, the study concludes that pricing strategies have little impact on guest satisfaction levels or customer loyalty as long as service standards were maintained. In fact, customers were willing to tolerate increased pricing up to a limit for high standards of service. This paper therefore recommends that premium pricing be adopted as a strategy by mid-tier hotels to increase REVPAR performance in both good and bad economic times

The Evolving Identity and Competence of New Nursing Graduates in Practice: A Community of Practice Perspective

Novices’ transition is identified as a period of time at the beginning of their professional career, when they go through role changes from students to independent practitioners. The transitional literature indicates novices’ incompetence and difficulties in transition in nursing and other professions. I argue that these findings were based on a fixed model of competent identity, while novices’ transitional mechanism is not well understood. Aiming to examine how transition happens, a focused ethnographic study underpinned by Wenger’s Community of Practice theory was conducted to explore novice nurses’ practice in a tertiary hospital in Singapore. Data was collected using observation over four months and focus group discussions. I identified sociocultural elements indicating the local rules the nurses make reference to in their participation. These elements include the need to assess the situation, to recognise the different characteristics of people and to be able to work with them, to identify and prioritise tasks, and to express and understand one another’s participation. The novices were found to be negotiating meaning and relational positions with different nurses in different situations at different levels, indicating the effect of sociocultural elements on their practice and the formation of community membership identities. The study findings reveal how complex the novices’ workplace and work really are and help us to better understand how competence and membership identity are negotiated among members. I argue that novices’ transitional mechanism is their evolving learning of the workplace and work, and negotiation of membership identity, a necessary part of their professional development. This study extends nursing and wider interdisciplinary literature on novices’ transition to a broader notion of meaning making and identity negotiation among members in practice. The new concepts developed add clarity to Community of Practice theory in understanding members’ negotiation of participation and membership. Implications for policy, education, practice and future research studies are discussed

Targeting Intrinsically Disordered Proteins through Dynamic Interactions

Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be targeted using small molecules for therapeutic purposes. While most existing studies have focused on extending the traditional structure-centric drug design strategies and emphasized exploring pre-existing structure features of IDPs for specific binding, several examples have also emerged to suggest that small molecules could achieve specificity in binding IDPs and affect their function through dynamic and transient interactions. These dynamic interactions can modulate the disordered conformational ensemble and often lead to modest compaction to shield functionally important interaction sites. Much work remains to be done on further elucidation of the molecular basis of the dynamic small molecule–IDP interaction and determining how it can be exploited for targeting IDPs in practice. These efforts will rely critically on an integrated experimental and computational framework for disordered protein ensemble characterization. In particular, exciting advances have been made in recent years in enhanced sampling techniques, Graphic Processing Unit (GPU)-computing, and protein force field optimization, which have now allowed rigorous physics-based atomistic simulations to generate reliable structure ensembles for nontrivial IDPs of modest sizes. Such de novo atomistic simulations will play crucial roles in exploring the exciting opportunity of targeting IDPs through dynamic interactions

Atomistic Peptide Folding Simulations Reveal Interplay of Entropy and Long-Range Interactions in Folding Cooperativity

Understanding how proteins fold has remained a problem of great interest in biophysical research. Atomistic computer simulations using physics-based force fields can provide important insights on the interplay of different interactions and energetics and their roles in governing the folding thermodynamics and mechanism. In particular, generalized Born (GB)-based implicit solvent force fields can be optimized to provide an appropriate balance between solvation and intramolecular interactions and successfully recapitulate experimental conformational equilibria for a set of helical and β-hairpin peptides. Here, we further demonstrate that key thermodynamic properties and their temperature dependence obtained from replica exchange molecular dynamics simulations of these peptides are in quantitative agreement with experimental results. Useful lessons can be learned on how the interplay of entropy and sequentially long-range interactions governs the mechanism and cooperativity of folding. These results highlight the great potential of high-quality implicit solvent force fields for studying protein folding and large-scale conformational transitions

Users’ Perception and Utility of Health Information Based on WeChat

Objective: To explore the ability of users to identify the health information spread on WeChat platform, and then to discuss the utility of such information on them. Methods: Questionnaire survey and descriptive statistical methods were used to collect and analyze the data. The process of “get health related information, judge true or false, production related behavior” was used to design the survey problem, finally, the paper and network surveys were investigated in users. Results: The proportion of accurate recognition, ambiguous recognition, none recognition and none classification were 21.55%, 63.26%, 4.41%, 10.78% respectively. The average frequency of identification, transmission, guidance and none behavior of originally true health information were 52.00, 78.40, 45.20, 31.80 respectively, and originally false health information were 21.30, 27.70, 14.10, 5.50 respectively.Conclusions: Most WeChat users surveyed lack the ability to accurately identify the authenticity of health information, and improvement of citizens’ health literacy has long way to go. WeChat is an effective platform for the dissemination of health information, but also provides a fertile soil for the spread of false health information. Additionally, users are not aware of the problem of their ability to identify information, even if produced a false judgment of false health information, most of the active users will also lead this kind of information still widely spread

CiGNN: A Causality-informed and Graph Neural Network Based Framework for Cuffless Continuous Blood Pressure Estimation:A Causality-informed and Graph Neural Network Based Framework for Cuffless Continuous Blood Pressure Estimation

Causality holds profound potentials to dissipate confusion and improve accuracy in cuffless continuous blood pressure (BP) estimation, an area often neglected in current research. In this study, we propose a two-stage framework, CiGNN, that seamlessly integrates causality and graph neural network (GNN) for cuffless continuous BP estimation. The first stage concentrates on the generation of a causal graph between BP and wearable features from the the perspective of causal inference, so as to identify features that are causally related to BP variations. This stage is pivotal for the identification of novel causal features from the causal graph beyond pulse transit time (PTT). We found these causal features empower better tracking in BP changes compared to PTT. For the second stage, a spatio-temporal GNN (STGNN) is utilized to learn from the causal graph obtained from the first stage. The STGNN can exploit both the spatial information within the causal graph and temporal information from beat-by-beat cardiac signals for refined cuffless continuous BP estimation. We evaluated the proposed method with three datasets that include 305 subjects (102 hypertensive patients) with age ranging from 20-90 and BP at different levels, with the continuous Finapres BP as references. The mean absolute difference (MAD) for estimated systolic blood pressure (SBP) and diastolic blood pressure (DBP) were 3.77 mmHg and 2.52 mmHg, respectively, which outperformed comparison methods. In all cases including subjects with different age groups, while doing various maneuvers that induces BP changes at different levels and with or without hypertension, the proposed CiGNN method demonstrates superior performance for cuffless continuous BP estimation. These findings suggest that the proposed CiGNN is a promising approach in elucidating the causal mechanisms of cuffless BP estimation and can substantially enhance the precision of BP measurement