OPTIMAL PRICING AND GRANT POLICIES FOR MUSEUMS

Considering two potential sources of income (public grants and ticket revenues),we have defined a theoretical model where the public agency is the principal and the manager of the museum is the agent. This model allows us to design the optimal contract between both sides and thus to establish the optimal values of grants, ticket prices, budget and effort applied by the manager. Furthermore, we have found a theoretical reason to explain the inelastic pricing strategy that has been found in some of the empirical research on cultural and sports economics. The main conclusion is that the optimal contract allows a Pareto optimum solution in prices that does not change if we introduce moral hazard into this relationship. This solution allows us to conclude that the public agency should regulate ticket prices in accordance with the social valuation. However, public grants and museum budgets would be affected by the existence of this problem, moving the equilibrium away from the Pareto optimum situation. In this case, even with a risk averse manager and a risk neutral public agency, grants and budgets will depend on results because higher budgets related to good results provide the main incentives to increase the manager’s level of effort. Although the focus of this paper is on museum administration, the model that we have developed can be easily generalized and applied to other institutions, such as schools, sport facilities or NGOs, which are able to raise funds directly from private (e. g. ticket revenues or membership fees) or public sources (e.g. public grants).cultural economics, grants, public prices, museums, principal- agent model

How do your rivals' releasing dates affect your box office?

In this paper, we study to what extent a movie's box office receipts are affected by the temporal distribution of rival films. We propose a theoretical model that analyses the effects of past, present and future releases on a film's results. Using this model we can analyse how rivals' release dates impact on others' box office revenues. This theoretical model also allows us to carry out some comparative statics by changing some relevant parameters such as time depreciation, film quality or the timeline of exhibition. We have tested the empirical implications of this model using information on the films released in five countries: the USA, the United Kingdom, Germany, France and Spain. In order to maintain a degree of homogeneity, we have constructed an unbalanced panel consisting of films that were released in at least three of these countries. The geographical dimension of our data set allows us to use panel data techniques to control for unobserved heterogeneity among the films released. This allows us to control for one of the most relevant features of the movie market, namely the presence of highly differentiated products.temporal competition, movie exhibition, film industry, panel data, unobserved heterogeneity, differentiated product

Developing a Mobile Learning Environment: An Axiomatic Approach

A new mobile environment for learning has been designed via an axiomatic approach. And by simultaneously designing both tools (software) and processes (pedagogy), the resulting environment matches the functional requirements of the instructional program. This paper describes the axioms established for mobile learning as well as development of the mobile computing environment. The paper discusses the developmental evolution and system architecture as well as the requirements of the portable training programs being offered via this new system. Apps are designed to connect learners, instructors and practitioners as well as to facilitate collaborative learning from a variety of mobile devices, anywhere in the World. Future content, apps and systems development will connect the physical and virtual environments, in order to truly enhance the mobile learning experience for people on the move

Transformer-based Atmospheric Density Forecasting

As the peak of the solar cycle approaches in 2025 and the ability of a single geomagnetic storm to significantly alter the orbit of Resident Space Objects (RSOs), techniques for atmospheric density forecasting are vital for space situational awareness. While linear data-driven methods, such as dynamic mode decomposition with control (DMDc), have been used previously for forecasting atmospheric density, deep learning-based forecasting has the ability to capture nonlinearities in data. By learning multiple layer weights from historical atmospheric density data, long-term dependencies in the dataset are captured in the mapping between the current atmospheric density state and control input to the atmospheric density state at the next timestep. This work improves upon previous linear propagation methods for atmospheric density forecasting, by developing a nonlinear transformer-based architecture for atmospheric density forecasting. Empirical NRLMSISE-00 and JB2008, as well as physics-based TIEGCM atmospheric density models are compared for forecasting with DMDc and with the transformer-based propagator.Comment: Conference: 24th Advanced Maui Optical and Space Surveillance Technologies At: Maui, Hawaii, United State

Antioxidant Capacity and Antimicrobial Activity of Commercial Samples of Guava Leaves (\u3cem\u3ePsidium guajava\u3c/em\u3e)

Psidium guajava is a small tree native to South and Central America. Guava leaves have traditionally been used for treating different illnesses. These benefits can be attributed to phenolics and flavonoids produced by guava. The chemical composition of guava leaf extracts was correlated with biological activity. Total phenolics, total flavonoids, ABTS/DPPH, TZM-bl, plaque reduction, XTT, spectrophotometric and Kirby-Bauer assays were used to test phenols, flavonoids, antioxidant properties, antiviral activity, cytotoxicity, and antibacterial activity, respectively. The median cytotoxicity concentration and half-maximal effective concentration values were obtained in order to determine antiviral selectivity against human immunodeficiency virus type 1 and herpes simplex virus type 1. Antibacterial activity against Escherichia coli and Bacillus subtilis were evaluated using a spectrophotometric assay and Kirby-Bauer test. The guava leaf extracts had a high phenol (0.8 to 2.1 GAE mg/mL) and flavonoid (62.7 to 182.1 Rutin Eq mg/g DW) content that correlated with high antioxidant capacity and selective antiviral activity (therapeutic index values above 10). Results of antibacterial tests indicated that the extracts have activity against gram-negative and gram-positive bacteria

DeepVATS : Deep Visual Analytics for time series

The field of Deep Visual Analytics (DVA) has recently arisen from the idea of developing Visual Interactive Systems supported by deep learning, in order to provide them with large-scale data processing capabilities and to unify their implementation across different data and domains. In this paper we present DeepVATS, an open-source tool that brings the field of DVA into time series data. DeepVATS trains, in a self-supervised way, a masked time series autoencoder that reconstructs patches of a time series, and projects the knowledge contained in the embeddings of that model in an interactive plot, from which time series patterns and anomalies emerge and can be easily spotted. The tool includes a back-end for data processing pipeline and model training, as well as a front-end with an interactive user interface. We report on results that validate the utility of DeepVATS, running experiments on both synthetic and real datasets. The code is publicly available on https://github.com/vrodriguezf/deepvats

BIRAFFE : bio-reactions and faces for emotion-based personalization

In this paper we introduce the BIRAFFE data set which is the result of the experiment in affective computing we conducted in early 2019. The experiment is part of the work aimed at the development of computer models for emotion classification and recognition. We strongly believe that such models should be personalized by design as emotional responses of different persons are subject to individual differences due to their personality. In the experiment we assumed data fusion from both visual and audio stimuli both taken from standard public data bases (IADS and IAPS respectively). Moreover, we combined two paradigms. In the first one, subjects were exposed to stimuli, and later their bodily reactions (ECG, GSR, and face expression) were recorded. In the second one the subjects played basic computer games, with the same reactions constantly recorded. We decided to make the data set publicly available to the research community using the Zenodo platform. As such, the data set contributes to the development and replication of experiments in AfC

A mechatronic leg replica to benchmark human-exoskeleton physical interactions

: Evaluating human-exoskeleton interaction typically requires experiments with human subjects, which raises safety issues and entails time-consuming testing procedures. This paper presents a mechatronic replica of a human leg, which was designed to quantify physical interaction dynamics between exoskeletons and human limbs without the need for human testing. In the first part of this work, we present the mechanical, electronic, sensory system and software solutions integrated in our leg replica prototype. In the second part, we used the leg replica to test its interaction with two types of commercially available wearable devices, i.e. an active full leg exoskeleton and a passive knee orthosis. We ran basic test examples to demonstrate the functioning and benchmarking potential of the leg replica to assess the effects of joint misalignments on force transmission. The integrated force sensors embedded in the leg replica detected higher interaction forces in the misaligned scenario in comparison to the aligned one, in both active and passive modalities. The small standard deviation of force measurements across cycles demonstrates the potential of the leg replica as a standard test method for reproducible studies of human-exoskeleton physical interaction

Il-15 enhances the persistence and function of bcma-targeting car-t cells compared to il-2 or il-15/il-7 by limiting car-t cell dysfunction and differentiation

Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the treatment of B-lymphoid malignancies. For multiple myeloma (MM), B-cell maturation antigen (BCMA)-targeted CAR-T cells have achieved outstanding complete response rates, but unfortunately, patients often relapse within a year of receiving the therapy. Increased persistence and reduced dysfunction are crucial features that enhance the durability of CAR-T cell responses. One of the factors that influence CAR-T cell in vivo longevity and loss of function, but which has not yet been extensively studied for BCMA-directed CAR-T cells, are the cytokines used during their production. We here compared the impact of IL-2, IL-15 and a combination of IL-15/IL-7 on the phenotype and function of ARI2h, an academic BCMA-directed CAR-T cell that is currently being administered to MM patients. For this study, flow cytometry, in vitro cytotoxicity assays and analysis of cytokine release were performed. In addition, ARI2h cells expanded with IL-2, IL-15, or IL-15/IL-7 were injected into MM tumor-bearing mice to assess their in vivo efficacy. We demonstrated that each of the cytokine conditions was suitable for the expansion of ARI2h cells, with clear in vitro activity. Strikingly, however, IL-15-produced ARI2h cells had improved in vivo efficacy and persistence. When explored further, it was found that IL-15 drove a less-differentiated ARI2h phenotype, ameliorated parameters related to CAR-T cell dysfunction, and lowered the release of cytokines potentially involved in cytokine release syndrome and MM progression. Moreover, we observed that IL-15 was less potent in inducing T cell senescence and DNA damage accumulation, both of which may contribute to an unfavorable CAR-T cell phenotype. These findings show the superiority of IL-15 to IL-2 and IL-15/IL-7 in the quality of anti-BCMA CAR-T cells, particularly their efficacy and persistence, and as such, could improve the duration of responses if applied to the clinical production of CAR-T cells for patients

Relationship Between Logistics Management and Public Sector Transparency in Peru

Purpose:  The objective of this research was to determine the relationship of significance between logistics management and public transparency in the public sector in Peru.   Theoretical framework: Current literature has reported good findings on both logistics management and transparency. However, there is still much to research and learn about GL and T because it is an ever-evolving development.   Design/methodology/approach: The methodology was quantitative, using deductive and analytical methods addressing non-experimental and correlational inferences. The instrument was a survey, through an applied questionnaire to 90 public sector workers.   Findings:  The results revealed that logistics management is deficient 43%, public transparency is deficient 57%, likewise, a p=0.000<0.01, Kendall's Tau-b (65%) and Spearman's Rho (67%) were reached.   Research, Practical & Social implications:  We suggest an agenda for future research and highlight the contributions made to logistics management and transparency.   Originality/value: the level of relationship between logistics management and public transparency is considerable positive and highly significant, which means that by complying with supply standards and stock control, the entity can provide quality information and thus the inspection office will be able to audit the transparency of the data