Liquid crystal elastomer (LCE) fiber actuators are promising candidates for smart textiles owing to their reversible large-stroke actuation and high aspect ratios. However, current LCEs require ultraviolet (UV) curing and are not recyclable. In addition, research is mainly focused on flat knitted thermo-responsive textiles. Here, a scalable recycling route for smart LCE textiles is developed by melt-extruding a thermoplastic LCE containing a near-infrared photothermal dye. The LCE fibers exhibit ∼30% reversible actuation strain and display light-driven rolling motions with left- or right-turning trajectories according to their programmed twist handedness. Using commercial knitting machines, multi-material plain- and rib-knit textiles are fabricated that exhibit in-plane contraction and out-of-plane deformations including bending and twisting under thermal and photo stimuli. Circularly knitted tubular structures exhibit reversible contraction in both radial and axial directions, reaching approximately 16% in outer diameter, 19% in inner diameter, and 14% in length, enabling applications in autonomous climbing, controlled liquid release, and micro pumping. Finally, thermo-mechanical recycling yields recycled fibers and both flat and circularly knitted textile structures with nearly unchanged actuation performance and comparable mechanical properties, demonstrating robust recyclability. Our results demonstrate the creation of smart textiles that are simultaneously intelligent in function and sustainable in design.

In this paper, a non-intrusive pressure measurement scheme based on particle image velocimetry (PIV) is presented for the complex supersonic flows with intense shock systems, by elaborately combining the MacCormack method, the streamline-based method, and the spatial integration in conservative form. According to the detailed analyses of flow structures, the pressure fields are well reconstructed by the proposed scheme for the two typical shock-wave/boundary-layer interactions containing regular and Mach reflections, which are induced by the relatively strong oblique shock waves generated by the wedges of 21° and 17° in the freestreams of Mach 2.5 and 2.0, respectively. Based on the theoretical solutions by oblique shock relationship, free interaction theory, and shock polar analysis, this pressure reconstruction scheme is completely validated to effectively suppress the propagation of PIV velocity error to the pressure field and the accumulation of reconstructed pressure error behind the strong shock wave. Compared with the literature presently, this work would be the most challenging application of PIV-based pressure measurement to such complex supersonic flows with intense shock reflections, large oscillations, wide speed ranges, and various compressible flow structures. These good results could confirm the feasibility and high accuracy of the proposed reconstruction scheme and may greatly promote its applications in academic research and engineering test for supersonic flows in the future.

Spatiotemporal residual noise in terrestrial earth observation products, often caused by unfavorable atmospheric conditions, impedes their broad applications. Most users prefer to use gap-filled remote sensing products with time series reconstruction (TSR) algorithms. Applying currently available implementations of TSR to large-volume datasets is time-consuming and challenging for non-professional users with limited computation or storage resources. This study introduces a new open-source software package entitled ‘HANTS-GEE’ that implements a well-known and robust TSR algorithm, i.e. Harmonic ANalysis of Time Series (HANTS), on the Google Earth Engine (GEE) platform for scalable reconstruction of terrestrial earth observation data. Reconstruction tasks can be conducted on user-defined spatiotemporal extents when raw datasets are available on GEE. According to site-based and regional-based case evaluation, the new tool can effectively eliminate cloud contamination in the time series of earth observation data. Compared with traditional PC-based HANTS implementation, the HANTS-GEE provides quite consistent reconstruction results for most terrestrial vegetated sites. The HANTS-GEE can provide scalable reconstruction services with accelerated processing speed and reduced internet data transmission volume, promoting algorithm usage by much broader user communities. To our knowledge, the software package is the first tool to support full-stack TSR processing for popular open-access satellite sensors on cloud platforms.

This study analyses domestic market integration’s (DMI’s) dynamic influence on regional economic growth in China. The authors construct a matrix of annual DMI indices for 29 provinces for 1997–2015. They calculate the reciprocal matrix and combine it with the β-convergence model and spatial econometrics to analyse the relationships between DMI and regional economic growth. Their findings indicate that the relation between these two variables is not straightforward, and 2004 was a tipping-point year. Before 2004, the statistical relationship between DMI and regional economic growth was downward sloping, which suggests a trend of divergence and negative spillover effects across the 29 provinces. After 2004, the relationship between DMI and regional economic growth becomes positive: increased DMI now is strengthening (regional) economic growth. The authors provide the possible explanations for the unstable relationship combined with China’s reality as well.