The authors developed a suit of the three-dimensional information collection system of digital discus, which has won the national invention patent. This system includes a digital discus, USB connecting line, position machine software and a personal computer. The digital discus is made up of the higher and lower shell, eyelets, circuit boards, accelerometer and angular rate sensor, etc. This system can be used to collect the real-time signals which are sent out during the whole throwing process and can carry out the dynamics analysis. By the synthetical use of both the system and the three-dimensional camera shooting, the research tests 3 excellent male athletes and obtains the result: the three-dimensional information collection system of digital discus is convenient, reliable and accurate. It provides a new way for the technical diagnosis and scientific research of the discus throw program.
Nanofiber membranes are widely employed to prepare composite filter media. The traditional composite method of hot pressing may damage the structure of nanofiber membrane, and thus increase the pressure drop through the composite filter. In this study, three-dimensional PET/TPU (polyethylene terephthalate/thermoplastic polyurethane) composite nanofiber filters (PET/TPU-CNF) with beads-on-string structure were fabricated by one-step co-electrospinning. Besides a stronger adhesion strength of 1.385 N/cm between the nanofiber membrane and substrate, the PET/TPU-CNF presented a low pressure drop of 28.96 Pa and a filtration efficiency of 83.64% for ambient particles at a face velocity of 5.3 cm/s. A high tensile strength of 4.33 MPa was measured for the PET/TPU nanofiber membrane. Thanks to the beads-on-string structure, both the mechanical properties and filtration performances of PET/TPU-CNF were enhanced compared with the pure PET nanofiber composite filter. The present study provides a new route to improve the membrane adhesion strength of nanofiber membrane coated filters.
Spatially continuous canopy height is a vital input for modeling forest structures and functioning. The global ecosystem dynamics investigation (GEDI) waveform can penetrate a canopy to precisely find the ground and measure canopy height, but it is spatially discontinuous over the earth’s surface. A common method to achieve wall-to-wall canopy height mapping is to integrate a set of field-measured canopy heights and spectral bands from optical and/or microwave remote sensing data as ancillary information. However, due partly to the saturation of spectral reflectance to canopy height, the product of this method may misrepresent canopy height. As a result, neither GEDI footprints nor interpolated maps using the common method can accurately produce spatially continuous canopy height maps alone. To address this issue, this study proposes a framework of point-surface fusion for canopy height mapping (FPSF-CH) that uses GEDI data to calibrate the initial wall-to-wall canopy height map derived from a sub-model of FPSF-CH. The effectiveness of the proposed FPSF-CH was validated by comparison to canopy heights derived from (1) a high-resolution canopy height model derived from airborne discrete point cloud lidar across three test sites, (2) a global canopy height product (GDAL RH95), and (3) the results of the FPSF-CH sub-model without fusing with the GEDI canopy height. The results showed that the RMSE and rRMSE of FPSF-CH were 3.82, 4.05, and 3.48 m, and 18.77, 16.24, and 13.81% across the three test sites, respectively. The FPSF-CH achieved improvement over GDAL RH95, with reductions in RMSE values of 1.28, 2.25, and 2.23 m, and reductions in rRMSE values of 6.29, 9.01, and 8.90% across the three test sites, respectively. Additionally, the better performance of the FPSF-CH compared with its sub-model further confirmed the effectiveness of integrating GEDI data for calibrating wall-to-wall canopy height mapping. The proposed FPSF-CH integrates GEDI LiDAR data to provide a new avenue for accurate wall-to-wall canopy height mapping critical to applications, such as estimations of biomass, biodiversity, and carbon stocks.
Smart air filters are beneficial to provide highly efficient particle removal, treat multiple contaminants simultaneously and conserve energy during air filtration processes. Herein, a type of self-supporting smart air filter (SSSAF) was fabricated by sandwiching the VOC-responsive PZT/PVDF electrospun membrane with two metal mesh electrodes. Besides the high filtration efficiency for sub-micron particles, the SSSAF showed good responses to pressure drop in the range of 0 to 500 Pa via the electroactivity of PZT/PVDF membrane. In addition, the SSSAF achieved VOC sensing function via the swelling properties of PZT/PVDF membrane in organic vapors, demonstrated by its signal to 50 to 200 ppm ethanol vapors. The SSSAF was employed to harvest wind energy, which was further applied to inhibit bacterial growth without the need of additional power input. Our SSSAF was designed to take advantage of the energy carried by the filtration air flow, which is necessary in any filtration system thus brings a stable and innate energy source. The results provide new insight into development of all-in-one smart air filters.
Motivation: Macromolecules have significant spectral overlap with metabolites, confounding accurate quantification of metabolites in ultrashort-TE MRSI. Goal(s): To develop a novel method for effective and reliable separation of metabolites and macromolecules from ultrashort-TE FID MRSI data. Approach: We translated auxiliary macromolecule-free SE metabolite signals to FID signals using a learning-based approach. The translated metabolite reference was incorporated in the spectral model of FID MRSI data through generalized series modelling. Macromolecules signals were modelled with probabilistic subspaces. Results: The proposed method has been validated using numerical simulation and experimental data from healthy subjects and a tumor patient, producing encouraging results. Impact: This work provides a novel approach to exploiting the characteristic spectral features in FID and SE MRSI experiments for effective separation of metabolites and macromolecules.
The presence of metal salts has become one of the major limitations for measuring metallic nanoparticles (NPs) in single particle inductively coupled plasma mass spectrometry (spICP-MS). Their presence generate a background signal in spICP-MS that can be overlapped with the signal intensity of small particles, leading to inaccurate NP size distributions. To overcome this analytical problem, sample pretreatment methods (e.g. dilution or fractionation) have been applied to liquid samples before spICP-MS measurements to minimize the ionic interference. However, the number of studies focused on reducing the presence of metal salts in aerosol characterization is limited. In this contribution, we investigated three different technologies coupled to an ICP-MS for online separating metallic NPs signals from ionic interference signals of metal salts in the aerosol. A rotating disk diluter (RDD) was used for the online dilution of the aerosol, while a differential mobility analyzer (DMA) and a centrifugal particle mass analyzer (CPMA) were used for the online fractionation of specific-sized NPs in the aerosol. The results from the analysis of 100 nm gold NPs (AuNPs) mixed with gold salts (Au3+ , mass ratio 1:25) showed the particle size limit of detection decreased from 78 nm to 61, 50, and 33 nm by using RDD, DMA, and CPMA respectively. In addition, it was found that the separation performance of AuNPs was in the order of DMA>RDD>CPMA. The methods used in this study based on spICP-MS have the potential to characterize directly NPs in complex aerosols containing metal salts.
Sodium MRI can acquire important biological information about cell integrity and tissue viability, but its clinical application has been limited by low SNR and poor spatial resolution. We propose a novel method to reconstruct high-quality sodium images from limited and noisy k-space data. The new method synergistically integrates model-based reconstruction with deep learning. Simulation and experimental results show that the proposed method can reconstruct high-SNR and high-resolution sodium images, which clearly delineate lesions such as brain tumors.
The Global Ecosystem Dynamics Investigation (GEDI), a new spaceborne LiDAR system of the National Aeronautics and Space Administration (NASA), has the potential to revolutionize global measurements of vertical vegetation structure. However, GEDI performance among different forest types and factors influencing GEDI performance needs to be evaluated against similar measurements from existing airborne LiDAR platforms. Ideally, comparisons across diverse forest types will inform future work quantifying biomass or mapping species habitats. Thus, we compared the second version of GEDI L2A product (GEDI V2) with Airborne Observation Platform (AOP) leaf-on LiDAR data across 33 National Ecological Observation Network (NEON) sites. Comparisons were made for ground elevation and relative height (RH) of GEDI with simulated airborne laser scanning (ALS) waveforms from discrete point cloud LiDAR. Results indicated that GEDI V2 obtained high accuracy on ground elevation and RH100 estimations (3σ) with RMSEs of 1.38 m and 2.62 m, respectively. GEDI produced forest height estimations (RH100) for all 12 forest types with a %RMSE below 25%. GEDI RHs were sensitive to ground finding accuracy, and GEDI performance of RH estimation varied from forest profiles of different forest types. For factors influencing GEDI performance, greater than 21% of GEDI RH95 and 33% of ground elevation variations can be explained by land surface attributes, observing sensor system characteristics, and the collection time differences between GEDI and NEON LiDAR. Furthermore, geolocation error remains an essential factor affecting GEDI performance, which varies among forest and land cover types, especially for canopy height estimation. The findings reported here can provide insights to guide and enhance future GEDI-based global forest structure mapping and applications.
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