Influence of viscosity and the adiabatic index on planetary migration

The strength and direction of migration of low mass embedded planets depends on the disk's thermodynamic state, where the internal dissipation is balanced by radiative transport, and the migration can be directed outwards, a process which extends the lifetime of growing embryos. Very important parameters determining the structure of disks, and hence the direction of migration, are the viscosity and the adiabatic index. In this paper we investigate the influence of different viscosity prescriptions (alpha-type and constant) and adiabatic indices on disk structures and how this affects the migration rate of planets embedded in such disks. We perform 3D numerical simulations of accretion disks with embedded planets. We use the explicit/implicit hydrodynamical code NIRVANA that includes full tensor viscosity and radiation transport in the flux-limited diffusion approximation, as well as a proper equation of state for molecular hydrogen. The migration of embedded 20Earthmass planets is studied. Low-viscosity disks have cooler temperatures and the migration rates of embedded planets tend toward the isothermal limit. In these disks, planets migrate inwards even in the fully radiative case. The effect of outward migration can only be sustained if the viscosity in the disk is large. Overall, the differences between the treatments for the equation of state seem to play a more important role in disks with higher viscosity. A change in the adiabatic index and in the viscosity changes the zero-torque radius that separates inward from outward migration. For larger viscosities, temperatures in the disk become higher and the zero-torque radius moves to larger radii, allowing outward migration of a 20 Earth-mass planet to persist over an extended radial range. In combination with large disk masses, this may allow for an extended period of the outward migration of growing protoplanetary cores

Where Do People Vape? Insights from Twitter Data.

Background: Emerging evidence suggests that exposure to secondhand and thirdhand aerosol from electronic cigarettes may have serious health risks including respiratory and cardiovascular diseases. Social media data can help identify common locations referenced in vaping-related discussions and offer clues about where individuals vape. These insights can strengthen current tobacco regulations and prioritize new policies to improve public health. This study identified commonly referenced locations in vaping-related discussions on Twitter in 2018. Methods: Vaping-related posts to Twitter were obtained from 1 January 2018 to 31 December 2018. Rule-based classifiers categorized each Twitter post into 11 location-related categories (social venues, living spaces, stores, modes of transportation, schools, workplaces, healthcare offices, eateries, correctional facilities, religious institutions, and miscellaneous) using a data dictionary of location-related keywords (n = 290,816). Results: The most prevalent category was social venues (17.9%), followed by living spaces (16.7%), stores (15.9%), modes of transportation (15.5%), schools (14.9%), and workplaces (11.9%). Other categories pertained to: healthcare offices (2.0%), eateries (1.2%), correctional facilities (0.7%), and religious institutions (0.4%). Conclusion: This study suggests that locations related to socialization venues may be priority areas for future surveillance and enforcement of smoke-free air policies. Similarly, development and enforcement of similar policies at workplaces, schools and multi-unit housing may curb exposure to secondhand and thirdhand aerosol among the public

AIRBNB: ASSESSING ITS ENGAGEMENT AND SUSTAINABILITY IN ATHENS, GA

AIRBNB: ASSESSING ITS SUSTAINABILITY USING A TBL FRAMEWORK IN ATHENS, GA Introduction The growth of the sharing economy has been widely noted from Fortune magazine to President Obama (Eckhardt & Bardhi 2015). It is also touted as one of the 10 ideas that will change the world in the 21st Century (Teubner 2014). Moreover, its potential to reduce waste within economic, social, and environmental processes has been dubbed as important as the Industrial Revolution in terms of how we value ownership of goods and services (Belk 2014). The sharing economy was valued at 26 billion in 2013 (Geron 2013b; Cannon & Summers 2014). Airbnb, a major shared-lodging player in this economy, was valued at 10 billion in April 2014 (Ember 2014) with more than 11 million guests choosing between more than 600,000 private accommodations in more than 34,000 cities and 192 countries (Smolka & Hienerth 2014). With this type of growth, Airbnb has earned attention from the global hospitality and tourism industry because of its ability to secure what some might see as an unfair economic competitive advantage by circumventing sales and occupancy taxes, the two major sources of income for CVBs and DMOs, and its ability to supply inexpensive accommodations in the heart of tourist centers (Zervas, Prosperio, & Byers 2014). While the economic competitive advantage presents a challenge to traditional accommodation options, the true impacts of Airbnb have not been studied from a triple bottom line (TBL) framework assessing economic, social, and environmental impacts (Dubois 2015; Sigala 2014). This study aims to study whether Airbnb participants are creating net economic, social, and environmental value to the Athens, GA community. Literature Review While shared-economy literature has primarily addressed economic impacts, analyzing economic, socio-cultural and environmental impacts underneath a triple bottom line framework helps in assessing the sharing economy’s potential to contribute to sustainable development, particularly in tourism (Elkington 1994; Dwyer 2005). Below is a brief review of the research within each of the three categories of the TBL. Economic Impacts Hosts’ and guests’ economic motivations for engaging in the sharing economy have been examined from a variety of methods such as consumer segmentation (Müller 2014), online surveys (Tussyadiah 2015), semi-structured interviews with hosts (Bardhi, Eckhardt & Arnould 2012), and web crawlers investigating price reaction within online rating platforms (Gutt & Hermann 2015). Researchers have also attempted to understand participation from the theoretical lenses of the theory of planned behavior and social exchange theory (Matzner et al. 2015; Ikkala 2015; Kim, Yoon, & Zo 2015). Research has identified economic incentives such as earning more in collaborative production than in the traditional market place, cost consciousness (Bardhi et al. 2012; Hamari et al. 2013; Dubois 2015); time, space and effort saving as reasons for participating in the sharing economy. The degree of negative economic impacts of Airbnb demand on the supply of traditional lodging options varies by lodging type (Zervas, Prosperio, & Byers 2015). For example, in a study by Zervas et al. (2014), it was found that in Houston, Texas, lower-end hotels and motels that do not cater to business travelers were the most affected with a 0.05% decrease in quarterly hotel revenues per 1% increase in Airbnb listings in the area. In contrast, businesses comprising the tourism supply of an area have in some cases, experienced positive economic externalities from the existence of nearby Airbnb’s (HR&A 2012). Some have even speculated that reducing housing supply might increase demand and subsequent housing market values (National Realtors Association 2011). While motivations for participation might seem mostly formative , there are certainly substantive reasons for participation in the sharing economy to be considered as well as the potential social impacts of this participation (McGehee, 2007). Social Impacts Trust, reputation, (Tussyadiah 2015; Botsman & Rogers 2010; Lamberton & Rose 2012; Schor & Fitzmaurice 2014) and the desire to belong to a community (Belk 2010; Giesler and Pohlmann 2003) are among some of the substantive reasons for participation in the sharing economy. However participation as a guest or host in Airbnb might be accompanied with some risks such as the ability for Airbnb listings in some places to circumvent safety regulations enforced by a third party (Chasin & Scholta 2015). Some researchers worry about challenges faced by collaborative consumptive employees such as exploitation by hiring contracted workers rather than employees (Cheng 2014). On the other hand, authenticity remains a potential benefit of Airbnb for the tourism economy. While there is potential for an unwanted intrusion into community fabric, embedding the tourist experience might create a socially sustainable and authentic experience (Guttentag 2013) desired by tourists (Mac Cannell 1973) through opportunities for education and increased appreciation for the community. The demand for authentic experiences is reinforced through Airbnb’s through promotional videos (Airbnb 2014). Understanding the socially nuanced motivations for participation might help gauge the stability of support for the sharing economy. If there are expressed concerns for feeling disconnected from the community or favorable reviews for the ability to provide tourists with authentic experiences, these are insights helpful to gauging the stability and future support for the sharing economy in tourism. Environmental Impacts Very little literature addresses environmental impacts in the sharing. Growing environmental awareness (Gansky 2010) and an increasingly critical view of over consumption (Belk 2014: Coyle 2011; Leismann, Schmitt, Rohn & Baedeker 2013) are thought as environmentally motivated reasons for participation in the sharing economy. The resource-saving benefits of collaborative consumption have been conceptualized (Liesmann et al. 2013; Sigala 2014), however, this idea has not been empirically tested leaving much room for investigation into the environmental impacts of the sharing economy. Methodology Study Area The study area will be confined to the city of Athens, GA as done by Zervas et al. (2014) who proposed that this geographic range is large enough to see accommodation substitution patterns between Airbnb listings and other lodging options. Assessing the Impacts of Airbnb through the TBL Economic Impacts Guests for this portion of the study will be sampled from economical, boutique, high-end, and Airbnb locations in town. The Athens, GA CVB STR report’s average occupancy rates and site specific average daily rates, will be used to calculate potential revenue per available room among (RevPAR) traditional lodging options. Numbers of Airbnb stays obtained from mining the Airbnb website across the same time period will be calculated to determine the RevPAR from these visitors. Surveys left in guests’ rooms or offered at the front desk (depending on the lodging facility) will be administered to obtain guests’ perceived expenditure patterns while in town. The occupancy and length of stay of all guests in the study will be plugged into an EIA program, such as IMPLAN to examine the multiplier effect of guests across different types of lodging. Social Impacts Semi-structured interviews will be conducted with hosts recruited through Airbnb’s online messaging system lasting a total of 30-90 minutes either over video chat or in person (Dubois 2015). Hosts will also be asked about their attachment to the community, to describe their sense of place of not only their accommodation but of Athens, and their perceived contribution to the community through their participation in Airbnb. Other qualitative methods such as pile-sort of economic benefits from occupancy and sales tax to understand motivations for participation in Airbnb and to understand knowledge of the local economy The second measure of social impacts will be the perceived positive and negative impacts of Airbnb on the Athens community from Airbnb non-users. Airbnb non-users will be chosen based on their proximity to interviewed Airbnb hosts. Lastly, a historical investigation will be made into a timeline for the development of different types of lodging in town and the community participation and published opinions of their development. For instance, articles within the local independent newspaper about Airbnb will be analyzed for the topic covered and the comments if any on the topic. Environmental Impacts Chosen hotels and residential properties of interviewed hosts will be assessed for their embodied energy (Haynes 2010; Rosselló-Batle., Moià, Cladera, & Martínez 2010). Understanding the life cycle of chosen lodging options creates a point to compare proposed and apparent economic benefits to for a ratio that highlights whether each location’s environmental footprint is offset by the economic benefits it provides. Alternative development plans, if any, identified through the above mentioned historical investigation will be used to assess tradeoffs associated with different development choices. Expected Outcomes The intense focus on the economic impacts of Airbnb hinders a progressive and holistic understanding of a stakeholder who is likely to revolutionize the tourism industry. The TBL framework supports the inextricability of social and environmental tradeoffs with economic ones. The findings from this study will present an opportunity for tourism industry stakeholders to transform a defensive reaction against the economic changes that the sharing economy brings to a proactive strategy that considers also the new social and environmental tradeoffs that might deserve mediation or could benefit tourism at all scales. References Arnould, Eric, and Melanie Wallendorf (1994), “Market Oriented Ethnography: Interpretation Building and Market Strategy Formulation,” Journal of Marketing Research, 31 (4), 484–504. Bardhi, Fleura, Giana M. Eckhardt, and Eric J. Arnould (2012),“Liquid Relationship to Possessions,” Journal of Consumer Research, 39 (3), electronically published January 12. Belk, R. (2010). Sharing. Journal of consumer research, 36(5), 715-734. Belk, R. (2014). You are what you can access: Sharing and collaborative consumption online. Journal of Business Research, 67(8), 1595-1600. Botsman, R. and Rogers, R. (2010). What’s Mine Is Yours: The Rise of Collaborative Consumption. Cannon, S. and Summers, L. H. (2014). How Uber and the Sharing Economy Can Win Over Regulators - HBR. Harvard business review Chasin, F., & Scholta, H. (2015). Taking Peer-to-Peer Sharing and Collaborative Consumption onto the Next Level-New Opportunities and Challenges for E-Government. Cheng, D. F. (2014). Reading between the lines: blueprints for a worker support infrastructure in the peer economy (Doctoral dissertation, Massachusetts Institute of Technology). Coyle, Diane (2011). The Economics of Enough: How to Run the Economy as if the Future Matters.Princeton, NJ: Princeton University Press. Dubois, E. (2015). The Field of Consumption: Contemporary Dynamics of Status, Capital, and Exchange (Doctoral dissertation, BOSTON COLLEGE). Dwyer, L. (2005). Relevance of triple bottom line reporting to achievement of sustainable tourism: A scoping study. Tourism Review International, 9(1), 79-938. Eckhardt, G. M. and Bardhi, F. (2015). The Sharing Economy Isn’t About Sharing at All - HBR.Harvard business review. Elkington, J. (1994). Towards the sustainable corporation: Win-win-win business strategies for sustainable development. California management review, 36(2), 90. Ember, S. (2014, April 21). Airbnb’s Huge Valuation. Retrieved May 6, 2014, from http://dealbook.nytimes.com/2014/04/21/morning-agenda-airbnbs-10-billion-valuation/?_php=true&_type=blogs&_php=true&_type=blogs&_r=1& Gansky, Lisa (2010). The Mesh: Why the Future of Business Is Sharing. New York City, NY: Penguin Group US. Geron, T. (2013b). Airbnb and the Unstoppable Rise of the Share Economy - Forbes. Forbes. Giesler, Markus and Mali Pohlmann (2003). “The Anthropology of File Sharing: Consuming Napster As Gutt, D., & Herrmann, P. (2015). Sharing Means Caring? Hosts\u27 Price Reaction to Rating Visibility. Guttentag, D. 2013. Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector. CurrentIssues in Tourism, (ahead-of-print), 1-26. Hamari, Juho et al. (2013). “The Sharing Economy: Why People Participate in Collaborative Consumption.”SSRN Electronic Journal, 1–19. HR&A. 2012. Airbnb: Economic Impacts in San Francisco and Its Neighborhoods. Data analysis. San Francisco: Airbnb. Ikkala, T., & Lampinen, A. (2014, February). Defining the price of hospitality: networked hospitality exchange via Airbnb. In Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 173-176). ACM. Kim, J., Yoon, Y., & Zo, H. (2015). Why People Participate in the Sharing Economy: A Social Exchange Perspective. Lamberton, C. P. and Rose, R. L. (2012). When Is Ours Better Than Mine? A Framework for Understanding and Altering Participation in Commercial Sharing Systems. Journal of Marketing, 76(July), 109–125. Leismann, Kristen, Schmitt, M., Rohn, H., Baedeker, C. (2013). “Collaborative Consumption: Towards a Resource-Saving ConsumptionCulture.” Resources 2 (3), 184–203. Matzner, M., & Chasin, F. (2015). To share or not to share: towards understanding the antecedents of participation in it-enabled sharing series. McGehee, N. G. (2007). An agritourism systems model: A Weberian perspective. Journal of Sustainable Tourism, 15(2), 111-124. Müller, M. P. (2014). An economic analysis of online sharing systems’ implications on social welfare. National Realtors Association (2011). Short-Term Rental Housing Restrictions. Retrieved January 21, 2016, from http://www.realtor.org/sites/default/files/reports/2011/short-term-rental-housing-restrictions-white-paper-2011-09.pdf Schor, J. B. and Fitzmaurice, C. J. (2014). Collaborating and Connecting: The emergence of the sharing economy. Cheltenham, Handbook on research on teaching Sigala, M. (2014). Collaborative commerce in tourism: implications for research and industry. Current Issues in Tourism, (ahead-of-print), 1-10. Smolka, C., & Hienerth, C. (2014). The best of both worlds: Conceptualizing Trade-offs between Openness and Closedness for Sharing Economy Models. Teubner, T. (2014). Thoughts on the sharing economy. In Proceedings of the International Conference on e-Commerce Tussyadiah, I. P. (2015). An exploratory study on drivers and deterrents of collaborative consumption in travel. In Information and Communication Technologies in Tourism 2015 (pp. 817-830). Springer International Publishing. Zervas, G., Proserpio, D., & Byers, J. (2014). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Boston U. School of Management Research Paper, (2013-16). Zervas, G., Proserpio, D., & Byers, J. (2015). A First Look at Online Reputation on Airbnb, Where Every Stay is Above Average. Where Every Stay is Above Average (January 23, 2015)

E-liquid-related posts to Twitter in 2018: Thematic analysis.

IntroductionE-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and communicative cues associated with e-liquids. We analyzed Twitter data to characterize key topics of conversation about e-liquids to inform surveillance, and regulatory efforts.MethodsTwitter posts containing e-liquid-related terms ("e-liquid(s)," "e-juice(s)") were obtained from 1 January 2018 to 31 December 2018. Text classifiers were used to identify topics of the posts (n = 15,927).ResultsThe most prevalent topic was Promotional at 29.35% followed by Flavors at 24.22%, and Person Tagging at 21.47%. Juice Composition was next most prevalent at 17.61% followed by Cannabis at 16.83%, and Nicotine Health Risks at 6.39%. Quit Smoking was rare at 0.57%.ConclusionThese results suggest that flavors, cannabis, health risks of nicotine, and composition warrant consideration as targets in future surveillance, public policy, and interventions addressing the use of e-liquids. Twitter provides ample opportunity to influence the normalization, and uptake, of e-cigarette-related products among non-smokers and youth, unless regulatory restrictions, and counter messaging campaigns are developed to reduce this risk

Managers' Practices of Tobacco and Marijuana Smoking Policies in Hispanic-Occupied Multiunit Housing.

Purpose: This study assessed the knowledge, attitudes, and practices of managers of Hispanic-occupied multiunit housing (MUH) related to the prevalence and prevention of secondhand smoke (SHS), thirdhand tobacco smoke, and secondhand marijuana smoke (SHMS). Methods: A narrative analysis was conducted of 20 interviews with live-in apartment managers. Their opinions on policies and an educational fotonovela were also gathered. Results: The properties were located in 10 cities within the Los Angeles County, representing a wide array of local policies and practices. Only two managers were correctly informed of the existing MUH smoking policies in their cities. Participants reported ambiguity in city laws and company rules regarding smoking. Managers do not distinguish between smoking recreational marijuana and medicinal marijuana. Several respondents believed the landlords have more power to create rules. Most favored a total ban on smoking of all substances on the premises. Conclusions: Most managers report low agency in being able to pass no-smoking rules. Participants support smoking policies that include all smokable products. Managers would like new government policies, manager trainings, tenant education, and ways to enforce rules to protect apartment tenants from SHS and SHMS. Educational interventions should coincide with the timing of key manager/tenant activities. Results can be used in policy development and educational interventions

Interactions Between Moderate- and Long-Period Giant Planets: Scattering Experiments for Systems in Isolation and with Stellar Flybys

The chance that a planetary system will interact with another member of its host star's nascent cluster would be greatly increased if gas giant planets form in situ on wide orbits. In this paper, we explore the outcomes of planet-planet scattering for a distribution of multiplanet systems that all have one of the planets on an initial orbit of 100 AU. The scattering experiments are run with and without stellar flybys. We convolve the outcomes with distributions for protoplanetary disk and stellar cluster sizes to generalize the results where possible. We find that the frequencies of large mutual inclinations and high eccentricities are sensitive to the number of planets in a system, but not strongly to stellar flybys. However, flybys do play a role in changing the low and moderate portions of the mutual inclination distributions, and erase dynamically cold initial conditions on average. Wide-orbit planets can be mixed throughout the planetary system, and in some cases, can potentially become hot Jupiters, which we demonstrate using scattering experiments that include a tidal damping model. If planets form on wide orbits in situ, then there will be discernible differences in the proper motion distributions of a sample of wide-orbit planets compared with a pure scattering formation mechanism. Stellar flybys can enhance the frequency of ejections in planetary systems, but auto-ionization is likely to remain the dominant source of free-floating planets.Comment: Accepted for publication by Ap