Experiential value of exhibition in the cultural and creative park: antecedents and effects on CCP experiential value and behavior intentions

The protection of industrial cultural heritage is related to sustainable urban development. Cultural and creative parks (CCPs) are a way for many cities to protect their industrial cultural heritage. In the context of CCPs, this study examines the relationships among the antecedents of exhibition experiential value, CCP experiential value, and behavioral intentions. Surveying 428 visitors in two well-known CCPs in Taipei, this study found that the four antecedents (attractiveness, existential authenticity, self-congruence, and exhibition–park image congruence) have a positive impact on exhibition experiential value. Exhibition experiential value has a positive impact on CCP experiential value, which in turn, affects behavioral intentions toward the CCP. In addition, this study finds that exhibition experiential value has a mediating effect between the four antecedents and CCP experiential value. Moreover, CCP experiential value has a mediating effect between exhibition experiential value and behavioral intentions. The findings of this study provide a direction for CCPs to achieve sustainable development through exhibitions that can attract more tourists

Generalized Deep Learning-based Proximal Gradient Descent for MR Reconstruction

The data consistency for the physical forward model is crucial in inverse problems, especially in MR imaging reconstruction. The standard way is to unroll an iterative algorithm into a neural network with a forward model embedded. The forward model always changes in clinical practice, so the learning component's entanglement with the forward model makes the reconstruction hard to generalize. The deep learning-based proximal gradient descent was proposed and use a network as regularization term that is independent of the forward model, which makes it more generalizable for different MR acquisition settings. This one-time pre-trained regularization is applied to different MR acquisition settings and was compared to conventional L1 regularization showing ~3 dB improvement in the peak signal-to-noise ratio. We also demonstrated the flexibility of the proposed method in choosing different undersampling patterns.Comment: Keywords: MRI reconstruction, Deep Learning, Proximal gradient descent, Learned regularization ter

A Simple Model for Cavity Enhanced Slow Lights in Vertical Cavity Surface Emission Lasers

We develop a simple model for the slow lights in Vertical Cavity Surface Emission Lasers (VCSELs), with the combination of cavity and population pulsation effects. The dependences of probe signal power, injection bias current and wavelength detuning for the group delays are demonstrated numerically and experimentally. Up to 65 ps group delays and up to 10 GHz modulation frequency can be achieved in the room temperature at the wavelength of 1.3 $\mu$m. The most significant feature of our VCSEL device is that the length of active region is only several $\mu$m long. Based on the experimental parameters of quantum dot VCSEL structures, we show that the resonance effect of laser cavity plays a significant role to enhance the group delays