923 research outputs found
How much you talk matters: cheap talk and collusion in a Bertrand oligopoly game
This study investigates the impact of cheap talk on price in a repeated Bertrand oligopoly experiment. Each participant plays 20 rounds. Participants are placed in three-person bidding groups where the lowest bid wins. During the first 10 rounds, participants are not allowed to communicate with each other. All three-person groups converged to the zero-profit equilibrium in the first 10 periods. We then play another 10 rounds where participants can text with one another using an instant message system. Some groups were allowed to text before every round, some to text before every other round, some to text every third round, some to text every fourth round, and some to text only every fifth round. When texting is allowed, All groups attempt to collude to raise the price after being allowed to text, but the only groups who can maintain the higher price and converge over time to the joint-profit maximum are the groups who can text before every period. Hence, cheap talk is only effective when subjects can continuously monitor or converse
Joint Person Re-identification and Camera Network Topology Inference in Multiple Cameras
Person re-identification is the task of recognizing or identifying a person
across multiple views in multi-camera networks. Although there has been much
progress in person re-identification, person re-identification in large-scale
multi-camera networks still remains a challenging task because of the large
spatio-temporal uncertainty and high complexity due to a large number of
cameras and people. To handle these difficulties, additional information such
as camera network topology should be provided, which is also difficult to
automatically estimate, unfortunately. In this study, we propose a unified
framework which jointly solves both person re-identification and camera network
topology inference problems with minimal prior knowledge about the
environments. The proposed framework takes general multi-camera network
environments into account and can be applied to online person re-identification
in large-scale multi-camera networks. In addition, to effectively show the
superiority of the proposed framework, we provide a new person
re-identification dataset with full annotations, named SLP, captured in the
multi-camera network consisting of nine non-overlapping cameras. Experimental
results using our person re-identification and public datasets show that the
proposed methods are promising for both person re-identification and camera
topology inference tasks.Comment: 14 pages, 14 figures, 6 table
Employment Opportunities and High School Completion during the COVID-19 Recession
COVID-19 created major disruptions for young people including health concerns, school closures, reduced social opportunities, and a wilting economy. We examine the effect of COVID-19 on high school completion in the United States. We find that high school completion rates increased considerably in 2020 compared to previous years. We investigate various mechanisms and find that worse employment conditions were the driving force. The lower opportunity costs of schooling because of the pandemic recession encouraged more young people to complete high school. The pandemic created extensive problems in education, but fortunately it did not reduce overall high school completion rates
COVID-19 Employment Status Impacts on Food Sector Workers
Food production and distribution is essential for human well-being, but the food sector has experienced a number of difficulties maintaining worker health and productivity during the COVID-19 pandemic. We examine employment status changes of persons recently employed in the U.S. food sector with a focus on food manufacturing and grocery stores. We find that the pandemic significantly reduced the probability of continued active employment for previous workers in both food manufacturing and grocery stores. Individual-level analysis confirms that the COVID-19 infection rate in an individual’s local labor market is a strong and significant factor. The employment changes are not just due to unemployment during facility closures. Previous workers increasingly exit the labor force as the severity of the COVID-19 infection rate in their local area worsens. The considerable risk of infection drives many previous food sector workers to stop working altogether. Maintaining worker health and safety is essential for a stable food supply
Employment Impacts of the COVID-19 Pandemic across Metropolitan Status and Size
We examine effects of the COVID-19 pandemic on employment losses across metropolitan area status and population size. Non-metropolitan and metropolitan areas of all sizes experienced significant employment losses, but the impacts are much larger in large metropolitan areas. Employment losses manifest as increased unemployment, labor force withdrawal, and temporary absence from work. We examine the role of individual and local area characteristics in explaining differing employment losses across metropolitan status and size. The local COVID-19 infection rate is a major driver of differences across MSA size. Industry mix and employment density also matter. The pandemic significantly altered urban economic activity
Development of Test-Bed AUV \u27ISiMI\u27 and Underwater Experiments on Free Running and Vision Guided Docking
MicroRNA-29a suppresses the growth, migration, and invasion of lung adenocarcinoma cells by targeting carcinoembryonic antigen-related cell adhesion molecule 6
AbstractCarcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) is an important regulator of cell adhesion, invasion, and metastasis. The aim of this study was to evaluate the functional roles of CEACAM6 in lung adenocarcinoma and to identify miRNAs that inhibit the growth, migration, and invasion of lung adenocarcinoma cells by targeting CEACAM6. CEACAM6 expression is associated with poor prognosis of patients with lung adenocarcinoma, and CEACAM6 has important functional roles in controlling the growth, migration, and invasion of lung adenocarcinoma cells in vitro and in vivo. Furthermore, miR-29a can suppress the growth, migration, and invasion of lung adenocarcinoma cells by targeting CEACAM6. Therefore, miR-29a/CEACAM6 axis represents a potential therapeutic target for treatment of lung adenocarcinoma
Using the CLEAN Method in Three-Dimensional Polarimetric ISAR Imaging Based on Volumetric Scattering Points
We developed a new technique for generating three-dimensional monostatic inverse synthetic aperture radar (ISAR) images using various types of polarimetric information on targets. To remove clutter around a target, we adopted the CLEAN method, in which only the main signals were reconstructed using an iterative algorithm. We conducted a simulation as follows: electric field data that were subjected to polarimetric scattering were obtained for the target using a full-wave electromagnetic analysis simulator. The linear polarization data of a 2 × 2 matrix were compressed into the linear to circular polarization data of a 2 × 1 matrix using the Jones vector based on circular polarization. On the grounds of the post-processed data, inverse Fourier transform was carried out to map scattering points to the spatial domain, after which the CLEAN method was used to retain only the primary scattering points
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