This paper proposes a novel biologically inspired design for an insect-scale flapping robot. The proposed scheme employs two motors to drive four wings, mimicking the flapping motion of nat-ural four-winged insects. The vehicle incorporates two pairs of flapping wings to generate lift force, with a transmission mechanism featuring flexure hinges instead of pivot joints, resulting in reduced weight and volume. The flexure hinges also exhibit nonlinear stiffness to facilitate smooth wing motion. The vehicle is designed to be symmetrical in structure, with the wings of each section generating greater lift through the clap-and-fling mechanism. The final product weighs 6.2g, pos-sesses a wingspan of 17cm, a one-sided flapping wing angle of 103 degrees, and generates lift that exceeds its weight, attesting to its successful design.

Full waveform (FW) LiDAR holds great potential for retrieving vegetation structure parameters at a high level of detail, but this prospect is constrained by practical factors such as lack of available handy processing tools and technical intricacy of waveform processing. This study introduces a new product, named the Hyper Point Cloud (HPC) derived from FW LiDAR data, and explore its potential applications such as tree crown delineation using the HPC-based intensity and percentile height (PH) surfaces, which show a promising solution to the constraints of using FW LiDAR data. Results of the HPC present a new direction to handle FW LiDAR data and offer prospects for studying the mid-story and understory of vegetation with high point density (~ 182 points/m2). The intensity-derived digital surface model (DSM) generated from the HPC shows that the ground region has larger maximum intensity (MAXI) and mean intensity (MI) than the vegetation region while having smaller total intensity (TI) and number of intensities (NI) at the given grid cell. Our analysis of intensity distribution contours at individual tree level exhibit similar patterns, indicating that the MAXI and MI are decreasing from the tree crown center to tree boundary while a rising trend is observed for TI and NI. These intensity variable contours provide a theoretical justification for using HPC-based intensity surfaces to segment tree crowns and exploit their potential for extracting tree attributes. The HPC-based intensity surfaces and the HPC-based PH Canopy Height Models (CHM) demonstrate promising tree segmentation results comparable to the LiDAR derived CHM for estimating tree attributes such as tree locations, crown widths and tree heights. We envision that products such as the HPC and the HPC-based intensity and height surfaces introduced in this study can open new perspectives to use FW LiDAR data and alleviate the technical barrier of exploring FW LiDAR data for detailed vegetation structure characterization.

Hospital readmission within 30 days of discharge (30-day readmission) is a high-priority quality measure and cost target. The purpose of this study was to explore the feasibility and efficacy of the Diabetes Transition of Hospital Care (DiaTOHC) Program on readmission risk in high-risk adults with diabetes. This was a non-blinded pilot randomized controlled trial (RCT) that compared usual care (UC) to DiaTOHC at a safety-net hospital. The primary outcome was all-cause 30-day readmission. Between 10/16/2017 and 05/30/2019, 115 patients were randomized. In the intention-to-treat (ITT) population, 14 (31.1%) of 45 DiaTOHC subjects and 15 (32.6%) of 46 UC subjects had a 30-day readmission (p=0.88) while 35.6% DiaTOHC and 39.1% UC subjects had a 30-day readmission or ED visit (p=0.72). The Intervention:UC cost ratio was 0.33 (0.13-0.79)95%CI (p<0.01). Among the 69 subjects with baseline HbA1c >7.0% (53 mmol/mol), 30-day readmission rates were 23.5% (DiaTOHC) and 31.4% (UC, p=0.46) and composite 30-day readmission or ED visit rates were 26.5% (DiaTOHC) and 40.0% (UC, p=0.23). In this subgroup, the Intervention:UC cost ratio was 0.21 (0.08-0.58)95%CI (p=0.002). The DiaTOHC Program is feasible and may decrease combined 30-day readmission/ED visit risk as well as healthcare costs among patients with higher HbA1c levels.