The locals casino as a social network – can an interconnected community of players detect differences in hold?

Abstract It is difficult for individual players to detect differences in theoretical hold between slot machines without playing an unrealistically large number of games. This difficulty occurs because the fractional loss incurred by a player converges only slowly to the theoretical hold in the presence of volatility designed into slot pay tables. Nevertheless, many operators believe that players can detect changes in hold or differences compared to competition, especially in a locals casino market, and therefore resist increasing holds. Instead of investigating whether individual players can detect differences in hold, we ask whether a population of casino regulars who share information via a network of social connections can detect differences. We present a simulation study, varying factors such as the distribution of holds and volatilities, the density and topology of the social network (i.e. the typical number of social connections, and whether connections are random or form closed groups), and the degree to which an individual’s belief about hold is influenced by their peers. We differentiate between conditions where players are kept guessing about the looseness or tightness of the slots and conditions where the belief of the entire locals casino community crystalizes to a correct conclusion about hold. Implication statement Academic studies showing that players cannot detect differences in hold due to volatile pay tables are over-simplified because they do not take into account communication and collective experience in a locals casino community. Network-based simulations can resolve this controversy by determining how effectively a community can learn what individuals cannot

COVID-19 in casinos: Analysis of COVID-19 contamination and spread with economic impact assessment

Abstract: The COVID-19 pandemic caused tremendous disruption for casinos, with the virus causing various lengths of shutdowns, capacity restrictions, and social distancing strategies such as machine removals or section closures. Although most of the world has now eased off these measures, it is important to review lessons learned to understand, and better prepare for similar circumstances in the future. We present Monte Carlo slot floor simulation software customized to simulate players spreading COVID-19 on the slot floor. We simulate the amount of touch surface contamination; the number of potential surface contact exposure events per day, and a proximity exposures statistic in person-hours per day, under various social distancing and cleaning scenarios. Quantitative results are presented, as well as videos of simulated player movements around the slot floor, including flagged contaminations and interactions. The economic impacts of shutdowns, diminished player interest, and capacity restrictions are also explored, leading to insights that are valuable to operators in both the COVID and post-COVID eras. A by-product of this work is that it demonstrates the economic impact of reasonable slot floor reductions is typically negligible, and sometimes beneficial for slot floor performance. An analysis on the resulting slot count optimization will be presented. Implication Statement This simulation study allows us to analyze slot performance from an economic standpoint, and virus spread from a health and safety perspective. The work helps operators and government entities prepare for capacity restricted scenarios by keeping their players safe and minimizing the negative economic impact to the casino

Statistical methods to generate artificial slot floor data for the advancement of casino related research

Abstract: A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated slot floor, which is realistic and statistically similar to the real source data used to generate it. Methods based on a transition probability matrix estimation are introduced and tested on an anonymous source data set. The process can accurately replicate event data and resultant session data distributions well, producing a robust artificial data set that can be used for research purposes. Implication Statement: Lack of detailed gambling data impedes both research and the rapid development of new gambling technologies by students, researchers, and entrepreneurs. The methods presented offer a solution by creating complete, statistically robust artificial slot data that can be used for research and development

β models for random hypergraphs with a given degree sequence

We introduce the beta model for random hypergraphs in order to represent the occurrence of multi-way interactions among agents in a social network. This model builds upon and generalizes the well-studied beta model for random graphs, which instead only considers pairwise interactions. We provide two algorithms for fitting the model parameters, IPS (iterative proportional scaling) and fixed point algorithm, prove that both algorithms converge if maximum likelihood estimator (MLE) exists, and provide algorithmic and geometric ways of dealing the issue of MLE existence

Dissociation Between Users’ Explicit and Implicit Attitudes Toward Artificial Intelligence: An Experimental Study

The latest developments in the field of artificial intelligence (AI) have given rise to many ethical and socio-economic concerns. Nonetheless, the impact of AI technologies is evident and tangible in our everyday life. This dichotomy leads to mixed feelings toward AI: people recognize the positive impact of AI, but they also show concerns, especially about their privacy and security. In this article, we try to understand whether the implicit and explicit attitudes toward AI are coherent. We investigated explicit and implicit attitudes toward AI by combining a self-report measure and an implicit measure, i.e., the implicit association test. We analyzed the explicit and implicit responses of 829 participants. Results revealed that while most of the participants explicitly express a positive attitude toward AI, their implicit responses seem to point in the opposite direction. Results also show that, in both the explicit and implicit measures, females show a more negative attitude than males, and people who work in the field of AI are inclined to be positive toward AI

A Chemical Strategy for the Preparation of Multimodified Peptide Imaging Probes

Multimodality probes appear of great interest for innovative imaging applications in disease diagnosis. Herein, we present a chemical strategy enabling site-specific doublemodification and cyclization of a peptide probe exploiting native chemical ligation (NCL) and thiol-maleimide addition. The synthetic strategy is straightforward and of general applicability for the development of double-labeled peptide multimodality probes

The stability of lidocaine and epinephrine solutions exposed to electric current and comparative administration rates of the two drugs into pig bladder wall.

Intravesical electromotive administration of local anesthetics is clinically successful but electrochemistry, cost and effectiveness limit the choice of drugs to diluted lidocaine HCl 4% mixed with epinephrine. These studies address the stability of lidocaine and epinephrine both over time and when exposed to electric current, i.e. transport rates with passive diffusion and electromotive administration. The drug mixture used was 50 ml lidocaine 4%, 50 ml H2O and 1 ml epinephrine 1/1000. For stability, the solution was placed either in bowls for 7 days or in a two chamber cell with the donor compartment (drugs) separated from the receptor compartment (NaCl solution) by a viable pig bladder wall. This was subjected to 30 mA for 45 min. Stability was measured with mass spectrometry. The cell was also used to determine transport rates with passive diffusion and currents of 20 mA and 30 mA, over 20, 30 and 45 min. Drug measurements in both compartments and bladder were made with HPLC. Lidocaine remained stable throughout the 7 days, epinephrine on day 1 only and both drugs were stable with 30 mA for 45 min. Comparing 20 mA and 30 mA with passive diffusion, there were significant differences in 6/6 donor compartment lidocaine levels, 4/6 receptor compartment levels and 6/6 bladder tissue levels and also in 6/6 epinephrine donor levels and 6/6 tissue levels. The combination lidocaine and epinephrine remains stable for 1 day and when exposed to 30 mA for 45 min. Electric current accelerates the transport of lidocaine and epinephrine

Technological and Economic Optimization of Functional Ready to Eat Meal

A ready meal based on precooked gluten-free pasta with a yogurt-based sauce enriched with probiotic bacteria was developed and optimized from both the nutritional and sensory point of view. Conceptually, the work aims at understanding the innovation stress in consumers and check whether the “perfect beauty” of a complex food product innovation, which is extremely admirable from a food technology point of view, could be effectively appreciated by consumers. In other words, we are interested in knowing whether there exists a gap between science-based or ”innovation-leading” technologists’ food preferences and consumers’ preferences, which are taste, information, price and promotion driven

DNA repair in post-mitotic neurons: a gene-trapping strategy

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Alterations of autophagy in the peripheral neuropathy Charcot-Marie-Tooth type 2B

Charcot-Marie-Tooth type 2B (CMT2B) disease is a dominant axonal peripheral neuropathy caused by 5 mutations in the RAB7A gene, a ubiquitously expressed GTPase controlling late endocytic trafficking. In neurons, RAB7A also controls neuronal-specific processes such as NTF (neurotrophin) trafficking and signaling, neurite outgrowth and neuronal migration. Given the involvement of macroautophagy/autophagy in several neurodegenerative diseases and considering that RAB7A is fundamental for autophagosome maturation, we investigated whether CMT2B-causing mutants affect the ability of this gene to regulate autophagy. In HeLa cells, we observed a reduced localization of all CMT2B-causing RAB7A mutants on autophagic compartments. Furthermore, compared to expression of RAB7AWT, expression of these mutants caused a reduced autophagic flux, similar to what happens in cells expressing the dominant negative RAB7AT22N mutant. Consistently, both basal and starvation-induced autophagy were strongly inhibited in skin fibroblasts from a CMT2B patient carrying the RAB7AV162M mutation, suggesting that alteration of the autophagic flux could be responsible for neurodegeneration.Peer reviewe