Profiling visitors to Dalarna Museum : What are the motivational factors that influence visitors' frequency of visits

Prior studies on museum visitors are extensively centred on national museums, the studies on regional museums are scarce. To fill in the academic gap, a research is proposed concerning the visitors of Dalarna Museum, a regional museum in Sweden. With an aim to profile visitors’ demographic characteristics and investigate the motivational factors that influence visitors’ frequency of visits, a face-to-face questionnaire survey was implemented at Dalarna Museum. To get visitors’ demographic characteristics, a few closed and open questions are devised to profile visitors’ gender, age, occupation, income, education, number of children and residence place. To investigate the motivational factors that influence visitors’ frequency of visits, a seven-point Likert questionnaire is employed with 17 motivational factors included. During a 12-day data collection, 372 visitors were invited to participate in the questionnaire survey, whereof 357 had filled in the questionnaire, generating a response rate that is as high as 96 percent. After data cleansing, there are 355 completed and valid responses in total. According to the results, some of visitors’ demographic characteristics are similar including gender, age, occupation, income, and number of children. However, the characteristics regarding visitors’ residence places and educational attainments are different comparing the frequent visitors to occasional visitors. Through running a multiple regression analysis, 13 out of the 17 motivational factors are detected having significant influences on visitors’ frequency of visits to Dalarna Museum, of which the most influential one is visitors’ day-outs with their friends and relatives.

Quantum control of electromagnetically induced transparency dispersion via atomic tunneling in a double-well Bose-Einstein condensate

Electromagnetically induced transparency (EIT) is an important tool for controlling light propagation and nonlinear wave mixing in atomic gases with potential applications ranging from quantum computing to table top tests of general relativity. Here we consider EIT in an atomic Bose-Einstein condensate (BEC) trapped in a double-well potential. A weak probe laser propagates through one of the wells and interacts with atoms in a three-level Lambda configuration. The well through which the probe propagates is dressed by a strong control laser with Rabi frequency Omega(mu), as in standard EIT systems. Tunneling between the wells at the frequency g provides a coherent coupling between identical electronic states in the two wells, which leads to the formation of interwell dressed states. The macroscopic interwell coherence of the BEC wave function results in the formation of two ultranarrow absorption resonances for the probe field that are inside of the ordinary EIT transparency window. We show that these new resonances can be interpreted in terms of the interwell dressed states and the formation of a type of dark state involving the control laser and the interwell tunneling. To either side of these ultranarrow resonances there is normal dispersion with very large slope controlled by g. We discuss prospects for observing these ultranarrow resonances and the corresponding regions of high dispersion experimentally.

Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach

This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.