Soft phototactic swimmer based on self-sustained hydrogel oscillator.

Oscillations are widely found in living organisms to generate propulsion-based locomotion often driven by constant ambient conditions, such as phototactic movements. Such environment-powered and environment-directed locomotions may advance fully autonomous remotely steered robots. However, most man-made oscillations require nonconstant energy input and cannot perform environment-dictated movement. Here, we report a self-sustained soft oscillator that exhibits perpetual and untethered locomotion as a phototactic soft swimming robot, remotely fueled and steered by constant visible light. This particular out-of-equilibrium actuation arises from a self-shadowing-enabled negative feedback loop inherent in the dynamic light-material interactions, promoted by the fast and substantial volume change of the photoresponsive hydrogel. Our analytical model and governing equation unveil the oscillation mechanism and design principle with key parameters identified to tune the dynamics. On this autonomous oscillator platform, we establish a broadly applicable principle for converting a continuous input into a discontinuous output. The modular design can be customized to accommodate various forms of input energy and to generate diverse oscillatory behaviors. The hydrogel oscillator showcases agile life-like omnidirectional motion in the entire three-dimensional space with near-infinite degrees of freedom. The large force generated by the powerful and long-lasting oscillation can sufficiently overcome water damping and effectively self-propel away from a light source. Such a hydrogel oscillator-based all-soft swimming robot, named OsciBot, demonstrated high-speed and controllable phototactic locomotion. This autonomous robot is battery free, deployable, scalable, and integratable. Artificial phototaxis opens broad opportunities in maneuverable marine automated systems, miniaturized transportation, and solar sails

Multicast in SDN based on Hierarchical Domain BIER

【Objective】Aiming at the problem that BitString can not represent all Bit-Forwarding Routers (BFRs) in large-scale Software Defined Networking (SDN) multicast based on Bit Index Explicit Replication (BIER) due to the limited length, this study designs a Hierarchical Domain (HD)-BIER model and devises its construction algorithm.【Methods】The HD-BIER model is a multi-layer BIER network composed of multiple small-scale Sub Domains (SD), which enables BIER to support a number of devices exceeding the capacity of the BitString representation in large-scale networks. The proposed HD-BIER construction algorithm takes into account the BitString Length (BSL) limitation, link lengths between nodes, and network connectivity. It leverages the concept of community partition algorithms and introduces a modularity function based on node similarity as an evaluation metric for BIER SD partitioning. The construction follows a bottom-up approach to dynamically build the HD-BIER network.【Results】The simulation results show that the HD-BIER construction algorithm can effectively construct HD-BIER networks that exceed the BSL limit in either simple networks or the complex networks with a large number of nodes. Additionally, the resulting HD-BIER model not only ensures normal transmission of multicast service data flows through the gradual encapsulation and decapsulation of BitString layers but also maintains SDN multicast communication performance throughout this process.【Conclusion】The simulation results validate that the proposed HD-BIER model presents an effective multicast service support solution for even larger-scale networks

Multi-year mapping of cropping systems in regions with smallholder farms from Sentinel-2 images in Google Earth engine

ABSTRACTAccurate acquisition of spatial and temporal distribution information for cropping systems is important for agricultural production and food security. The challenges of extracting information about cropping systems in regions with smallholder farms are considerable, given the varied crops, complex cropping patterns, and the fragmentation of cropland with frequent reclamation and abandonment. This study presents a specialized workflow to solve this problem for regions with smallholder farms, which utilizes field samples and Sentinel-2 data to extract cropping system information over multiple years. The workflow involves four steps: 1) processing Sentinel-2 data to simulate crop growth curves with the Savitzky‒Golay filter and computing feature variables for classification, including phenology indices, spectral bands, and time series of vegetation indices; 2) mapping annual croplands with one-class support vector machine; 3) mapping various cropping patterns, including single cropping, intercropping, double cropping, multiple harvest, and fallow by decision tree and K-means clustering; and 4) mapping crops with random forest where Jeffries-Matusita distance was used to select appropriate vegetation indices. The workflow was applied in the Hetao irrigation district in Inner Mongolia Autonomous Region, China from 2018 to 2021. The overall accuracies were 0.98, 0.96, and 0.97 for cropland, cropping patterns, and crop type mapping, respectively. The mapping results indicated that the study area has low cropping continuity and is dominated by single cropping patterns. Furthermore, the area of wheat cultivation has decreased, and vegetable cultivation has expanded. Overall, the proposed workflow facilitated the accurate acquisition of cropping system information in regions with smallholder farms and demonstrated the effectiveness of available Sentinel-2 imagery in classifying complex cropping patterns. The workflow is available on Google Earth Engine

Rearch on Electromagnetic Scattering from ocean covered by foams

Back scattering of ocean surface is investigated by considering the foams coverage on its surface. Firstly, by adopting modified two-scale mode and the vector radiative transfer theory, zero and first order scattering coefficients are obtained by solving VRT equations. Then, MIE theory is used to get the scattering from foams, and fraction of foams coverage is analyzed by changing parameters of wind speed and temperature difference of ocean-air. Finally, the modified two-scale model and algorithms are verified by comparing its results with measured results, and simulations of calculating back scattering from ocean surface with and without foams are carried out. The conclusion is obtained that wind speed has different influence on back scattering under different incident angles

Multi-year mapping of flood autumn irrigation extent and timing in harvested croplands of arid irrigation district

Flood irrigation after crop harvest, e.g. autumn irrigation (AI), is a common irrigation practice in arid and semi-arid regions like Hetao Irrigation District (HID) in Northwest China to increase soil moisture and leach soil salt. Detailed information about the extent, timing, and amount of AI is imperative for modeling agro-hydrological processes and irrigation management. However, little attention is given to the identification of the above AI factors. There are basically three major difficulties in estimating the annual changes in AI, including a suitable index to identify AI, temporal instability of thresholds, and an effective validation method for irrigation timing. Therefore, this study proposes a simple and effective threshold-based method to extract the extent and timing of AI in the HID using MODIS water indices at a daily timescale. The Multi-Band Water Index (MBWI) time series is first reconstructed using an adaptive weighted Savitzky-Golay filter and then used to identify the AI extent and time. The proposed model has a stronger generalization capability both in time and space due to robust thresholds selected from the Z-score normalized feature variable. The model is validated both at pixels generated by the segmentation of Sentinel-derived MBWI using a threshold-based model and at sampling points from the field survey. Results show that the model performed well with an overall accuracy of more than 90.0% for the irrigation area. The overall accuracies of irrigation timing are 76.4% and 91.7% based on the middle-to-late and whole irrigation periods, respectively. We found a decreasing trend in the AI area and a gradual delay in the starting time of AI in the HID, mainly due to changes in cropping patterns, climate, and irrigation fees. Overall, the model is promising in identifying flood irrigation extent and timing in large irrigation districts and is helpful for irrigation scheduling

Multi-year mapping of cropping systems in regions with smallholder farms from Sentinel-2 images in Google Earth engine

Accurate acquisition of spatial and temporal distribution information for cropping systems is important for agricultural production and food security. The challenges of extracting information about cropping systems in regions with smallholder farms are considerable, given the varied crops, complex cropping patterns, and the fragmentation of cropland with frequent reclamation and abandonment. This study presents a specialized workflow to solve this problem for regions with smallholder farms, which utilizes field samples and Sentinel-2 data to extract cropping system information over multiple years. The workflow involves four steps: 1) processing Sentinel-2 data to simulate crop growth curves with the Savitzky‒Golay filter and computing feature variables for classification, including phenology indices, spectral bands, and time series of vegetation indices; 2) mapping annual croplands with one-class support vector machine; 3) mapping various cropping patterns, including single cropping, intercropping, double cropping, multiple harvest, and fallow by decision tree and K-means clustering; and 4) mapping crops with random forest where Jeffries-Matusita distance was used to select appropriate vegetation indices. The workflow was applied in the Hetao irrigation district in Inner Mongolia Autonomous Region, China from 2018 to 2021. The overall accuracies were 0.98, 0.96, and 0.97 for cropland, cropping patterns, and crop type mapping, respectively. The mapping results indicated that the study area has low cropping continuity and is dominated by single cropping patterns. Furthermore, the area of wheat cultivation has decreased, and vegetable cultivation has expanded. Overall, the proposed workflow facilitated the accurate acquisition of cropping system information in regions with smallholder farms and demonstrated the effectiveness of available Sentinel-2 imagery in classifying complex cropping patterns. The workflow is available on Google Earth Engine. We proposed an integrated method to map cropping systems into smallholder regions. Annual cropland mapping is necessary in regions with complex cropping pattern. The method requires only crop samples as input and is completed on the GEE. Sentinel-2 data can effectively classify cropland, cropping patterns, and crops. The 10-day interval performs better on phenology curves based on Sentinel-2.</p

GMSC-Derived Exosomes Combined with a Chitosan/Silk Hydrogel Sponge Accelerates Wound Healing in a Diabetic Rat Skin Defect Model

Background: Delayed wound healing in diabetic patients is one of the most challenging complications in clinical medicine, as it poses a greater risk of gangrene, amputation and even death. Therefore, a novel method to promote diabetic wound healing is of considerable interest at present. Previous studies showed that injection of MSC-derived exosomes has beneficial effects on wound healing. In current studies, we aimed to isolate exosomes derived from gingival mesenchymal stem cells (GMSCs) and then loading them to the chitosan/silk hydrogel sponge to evaluate the effects of this novel non-invasive method on skin defects in diabetic rats.Methods: GMSCs were isolated from human gingival connective tissue and characterized by surface antigen analysis and in vitro multipotent differentiation. The cell supernatant was collected to isolate the exosomes. The exosomes were characterized by transmission electron microscopy, Western blot and size distribution analysis. The chitosan/silk-based hydrogel sponge was prepared using the freeze-drying method and then structural and physical properties were characterized. Then, the exosomes were added to the hydrogel and tested in a diabetic rat skin defect model. The effects were evaluated by wound area measurement, histological, immunohistochemical and immunofluorescence analysis.Results: We have successfully isolated GMSCs and exosomes with a mean diameter of 127 nm. The chitosan/silk hydrogel had the appropriate properties of swelling and moisture retention capacity. The in vivo studies showed that the incorporating of GMSC-derived exosomes to hydrogel could effectively promote healing of diabetic skin defects. The histological analysis revealed more neo-epithelium and collagen in the hydrogel-exosome group. In addition, the hydrogel-exosome group had the highest microvessel density and nerve density.Conclusions: The combination of GMSC-derived exosomes and hydrogel could effectively promote skin wound healing in diabetic rats by promoting the re-epithelialization, deposition and remodeling of collagen and by enhancing angiogenesis and neuronal ingrowth. These findings not only provide new information on the role of the GMSC-derived exosomes in wound healing but also provide a novel non-invasive application method of exosomes with practical value for skin repair