Application and renovation evaluation of Dalian's industrial architectural heritage based on AHP and AIGC.

This paper takes the example of industrial architectural heritage in Dalian to explore design scheme generation methods based on generative artificial intelligence (AIGC). The study compares the design effects of three different tools using the Analytic Hierarchy Process (AHP). It first establishes the key indicator weights for the renovation of industrial architectural heritage, with the criterion layer weights as follows: building renovation 0.

Deep learning solutions for smart city challenges in urban development.

In the realm of urban planning, the integration of deep learning technologies has emerged as a transformative force, promising to revolutionize the way cities are designed, managed, and optimized. This research embarks on a multifaceted exploration that combines the power of deep learning with Bayesian regularization techniques to enhance the performance and reliability of neural networks tailored for urban planning applications. Deep learning, characterized by its ability to extract complex patterns from vast urban datasets, has the potential to offer unprecedented insights into urban dynamics, transportation networks, and environmental sustainability.

ZnO@Carbon Dot Nanoparticles Stimulating the Antibacterial Activity of Polyvinylidene Fluoride-Hexafluoropropylene with a Higher Electroactive Phase for Multifunctional Devices.

To further advance the application of flexible piezoelectric materials in wearable/implantable devices and robot electronic skin, it is necessary to endow them with a new function of antibacterial properties and with higher piezoelectric performance. Introducing a specially designated nanomaterial based on the nanocomposite effect is a feasible strategy to improve material properties and achieve multifunctionalization of composites. In this paper, carbon dots (CDs) were sensitized onto the surface of ZnO to form ZnO@CDs nanoparticles, which were then incorporated into polyvinylidene fluoride-hexafluoropropylene (PVDF-HFP) to obtain a multifunctional composite.

Broadband mode-selective couplers based on tapered side-polished fibers.

We propose the broadband mode-selective coupler (MSC) formed with a side-polished six mode fiber (6MF) and a tapered side-polished small core single-mode fiber (SC-SMF) or an SMF. The MSCs are designed to allow the LP mode in the SC-SMF and SMF to completely couple to the LP, LP, LP, LP, LP, LP modes in the 6MF over a broadband wavelength range. The phase-matching conditions of the MSCs are satisfied by tapering the SC-SMF and SMF to specific diameters.

High performance all-fiber temperature sensor based on coreless side-polished fiber wrapped with polydimethylsiloxane.

A novel fiber structure, coreless side-polished fiber (CSPF) that is wrapped by polydimethylsiloxane (PDMS), is demonstrated to be highly sensitive to temperature because of the high refractive index sensitivity of the CSPF and the large thermal optic coefficient of the PDMS. Our numerical and experimental results show that the several dips in the transmitted spectra of PDMSW-CSPF is originated from the multimode interference (MMI) in the CSPF and will blueshift with the increase of temperature. Furthermore, for such a PDMSW-CSPF, we investigate its temperature sensing characteristics and the influences of residual thickness (RT) and dip wavelength on the sensitivity both numerically and experimentally.