Radiometric analysis of digitized Z-scope records in archival radar sounding film

The earliest airborne geophysical campaigns over Antarctica and Greenland in the 1960s and 1970s collected ice penetrating radar data on 35 mm optical film. Early subglacial topographic and englacial stratigraphic analyses of these data were foundational to the field of radioglaciology. Recent efforts to digitize and release these data have resulted in geometric and ice-thickness analysis that constrain subsurface change over multiple decades but stop short of radiometric interpretation. The primary challenge for radiometric analysis is the poorly-characterized compression applied to Z-scope records and the sparse sampling of A-scope records. Here, we demonstrate the information richness and radiometric interpretability of Z-scope records. Z-scope pixels have uncalibrated fast-time, slow-time, and intensity scales. We develop approaches for mapping each of these scales to physical units (microseconds, seconds, and signal to noise ratio). We then demonstrate the application of this calibration and analysis approach to a flight in the interior of East Antarctica with subglacial lakes and to a reflight of an East Antarctic ice shelf that was observed by both archival and modern radar. These results demonstrate the potential use of Z-scope signals to extend the baseline of radiometric observations of the subsurface by decades.

The effects of information and interpersonal continuity on physician service online: from the continuity of care perspective (Preprint)

BACKGROUND Online medical services have become an effective supplement to traditional services in hospitals and an essential organization in medical service. Prior studies have revealed that it’s useful to shorten the delayed admission time and enhance the treatment effect from the service continuity perspective. However, what specific measures the patients and physicians should take to improve service continuity remains unknown. OBJECTIVE Based on the information richness theory and continuity of care, this study investigates the dynamic impacts of information continuity and interpersonal continuity on physician’ service online. METHODS Data of 7200 patients with 360 physicians covering complete interaction records is collected from a professional online platform in China. Content analysis is used to recognize matching patient and physician and least square regression analysis is used to get all empirical results. RESULTS Empirical results show that in the short term, information continuity (including offline experience, medical records, and detailed information) influences physicians’ online service. And, their influences show heterogeneity. Moreover, by recognizing if a patient’s online physician is the same physician who he has visited offline, we find that interpersonal continuity is also important for service. In the long term, information and interpersonal continuity positively improve service continuity by facilitating repeat purchases. CONCLUSIONS Overall, our findings not only shed new light on patient behavior online and cross-channel behavior, but also provide practical insights into improving continuity of care in OHCs.

Consciousness is supported by near-critical cortical electrodynamics

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition, and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, for the first time, we empirically identify the specific critical point near which conscious cortical dynamics operate as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, GABAergic anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of cortical dynamics away from this critical point; conversely, we show that psychedelics may increase the information-richness of cortical activity by tuning cortical electrodynamics closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC), and show that assessing the proximity of cortical electrodynamics to the edge-of-chaos critical point may be clinically useful as a new biomarker of consciousness.

Prominence of Information Richness in Accepting Online Based Self-Service Technologies

Most of the service organizations are now moving to provide their services at a remote basis with Self-Service Technologies (SSTs). This is a natural outcome of technological maturity and would be the norm of many service transactions in future. Currently in many of the services, customers have the choice to use either SSTs or physical service encounters with service employees according to their desire. However, the future is predicted to replace many service employees with self-service machines and humanoid robots. Therefore, it is the responsibility of the service organizations to make their customers ready for such a future. Use of self-service technologies typically take place without the presence of organization’s service staff. Thus, machines should provide necessary guidance and instructions to customers so that they can perform well without difficulties. If SSTs are not rich with information, customers would be in trouble without proceeding with their transactions successfully. Therefore, the quality of information would be a matter for successful online based self -service transactions. Thus, the aim of this study is to understand the information richness in online based self-service technologies from the customer perspective. Using the qualitative approach, semi structured interviews were conducted with 25 individuals who have experience in using online based SSTs. The study found seven key factors which determine the richness of information in online platforms namely ‘Relevance, Timeliness, Accuracy, Clarity, Consistency, Sufficiency and Simplicity’. The study enriches the theoretical landscapes by broadening the understanding on significance of information richness in accepting online based self-service technologies while on practical ground provides insights for service providers in designing their SSTs with rich and necessary information which is required to perform successful transactions.

Value cocreation behavior of users in an online social question-andanswer community

Online social question-and-answer (Q&A) communities provide a platform for people to acquire high-quality knowledge and have become an important mode through which users can cocreate value. We applied self-determination theory and the stimulus–organism–response framework to develop a model of how platform characteristics influence users' self-determination in virtual communities, thereby influencing their value cocreation behavior. Data obtained from a survey of 385 users in an online social Q&A community show that personalized recommendations, social interaction, and information richness each had a positive impact on user selfcompetence, self-autonomy, and self-relatedness, which subsequently affected their knowledge-sharing and knowledge-integration behaviors. Moreover, self-determination had a mediating effect in the relationship between platform characteristics and users' knowledge-sharing and knowledge-integration behaviors. Our findings provide evidence for how to promote value cocreation in a social Q&A community.

Analyzing Restaurant Customers’ Evolution of Dining Patterns and Satisfaction during COVID-19 for Sustainable Business Insights

Observing and interpreting restaurant customers’ evolution of dining patterns and satisfaction during COVID-19 is of critical importance in terms of developing sustainable business insights. This study describes and analyzes customers’ dining behavior before and after the pandemic outbreak by means of statistically aggregating and empirically correlating 651,703 restaurant-user-generated contents posted by diners during 2019–2020. Twenty review topics, mostly food, were identified by latent Dirichlet allocation, whereas analysis of variation and rating-review regression were performed to explore whether and why customers became less satisfied. Results suggest that customers have been paying fewer visits to restaurants since the outbreak, assigning lower ratings, and showing limited evidence of spending more. Interestingly, queuing, the most annoying factor for restaurant customers during normal periods, turns out to receive much less complaint during COVID-19. This study contributes by discovering business knowledge in the context of COVID-19 based on big data that features accessibility, relevance, volume, and information richness, which is transferable to future studies and can benefit additional population and business. Meanwhile, this study also provides practical suggestions to managers regarding the framework of self-evaluation, business mode, and operational optimization.