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The accuracy of X-ray pulsar-based navigation is greatly affected by the Doppler effect caused by the spacecraft orbital motion and the systematic biases introduced by the pulsar directional error, spacecraft-borne clock error, etc. In this paper, an innovative navigation method simultaneously employing the pulse phase (PP), the difference of two neighbor PPs (DPP) and the Doppler frequency (DF) of X-ray pulsars as measurements is proposed to solve this problem. With the aid of the spacecraft orbital dynamics, a single pair of PP and DF relative to the spacecraft's state estimation error can be estimated by using the joint probability density function of the arrival photon timestamps as the likelihood function. The systematic biases involved to the PP is proved to be nearly invariant over two adjacent navigation periods and the major part of it is eliminated in the DPP; therefore, the DPP is also exploited as additional navigation measurement to weaken the impact of systematic biases on navigation accuracy. Results of photon-level simulations show that the navigation accuracy of the proposed method is remarkably better than that of the method only using PP, the method using both PP and DF and the method using both PP and DPP for Earth orbit. [ABSTRACT FROM AUTHOR]

The third Dutch national airborne laser scanning flight campaign (AHN3, Actueel Hoogtebestand Nederland) conducted between 2014 and 2019 during the leaf-off season (October-April) across the whole Netherlands provides a free and open-access, country-wide dataset with ∼700 billion points and a point density of ∼10(-20) points/m 2 . The AHN3 point cloud was obtained with Light Detection And Ranging (LiDAR) technology and contains for each point the x, y, z coordinates and additional characteristics (e.g. return number, intensity value, scan angle rank and GPS time). Moreover, the point cloud has been pre-processed by 'Rijkswaterstraat' (the executive agency of the Dutch Ministry of Infrastructure and Water Management), comes with a Digital Terrain Model (DTM) and a Digital Surface Model (DSM), and is delivered with a pre-classification of each point into one of six classes (0: Never Classified, 1: Unclassified, 2: Ground, 6: Building, 9: Water, 26: Reserved [bridges etc.]). However, no detailed information on vegetation structure is available from the AHN3 point cloud. We processed the AHN3 point cloud (∼16 TB uncompressed data volume) into 10 m resolution raster layers of ecosystem structure at a national extent, using a novel high-throughput workflow called 'Laserfarm' and a cluster of virtual machines with fast central processing units, high memory nodes and associated big data storage for managing the large amount of files. The raster layers (available as GeoTIFF files) capture 25 LiDAR metrics of vegetation structure, including ecosystem height (e.g. 95 th percentiles of normalized z), ecosystem cover (e.g. pulse penetration ratio, canopy cover, and density of vegetation points within defined height layers), and ecosystem structural complexity (e.g. skewness and variability of vertical vegetation point distribution). The raster layers make use of the Dutch projected coordinate system (EPSG:28992 Amersfoort / RD New), are each ∼1 GB in size, and can be readily used by ecologists in a geographic information system (GIS) or analytical open-source software such as R and Python. Even though the class '1: Unclassified' mainly includes vegetation points, other objects such as cars, fences, and boats can also be present in this class, introducing potential biases in the derived data products. We therefore validated the raster layers of ecosystem structure using >180,000 hand-labelled LiDAR points in 100 randomly selected sample plots (10 m × 10 m each) across the Netherlands. Besides vegetation, objects such as boats, fences, and cars were identified in the sampled plots. However, the misclassification rate of vegetation points (i.e. non-vegetation points that were assumed to be vegetation) was low (∼0.05) and the accuracy of the 25 LiDAR metrics derived from the AHN3 point cloud was high (∼90%). To minimize existing inaccuracies in this country-wide data product (e.g. ships on water bodies, chimneys on roofs, or cars on roads that might be incorrectly used as vegetation points), we provide an additional mask that captures water bodies, buildings and roads generated from the Dutch cadaster dataset. This newly generated country-wide ecosystem structure data product provides new opportunities for ecology and biodiversity science, e.g. for mapping the 3D vegetation structure of a variety of ecosystems or for modelling biodiversity, species distributions, abundance and ecological niches of animals and their habitats., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Objective: To investigate the safety, efficacy and long-term outcomes of Jinling procedure in the treatment of adult Hirschsprung disease., Methods: Clinical and follow-up data of 125 patients with adult Hirschsprung disease undergoing Jinling procedure at the Department of General Surgery between January 2000 and January 2013 were summarized. All the patients were diagnosed by CT, barium enema, anorectal pressure detection and pathology examination. Abdominal symptoms, gastrointestinal quality of life index(GIQLI, the lower score, the worse quality of life), Wexner constipation score (higher score indicated worse symptom), defecography (evaluation included rectocele, mucosal prolapse, intramucosal intussusception, perineal prolapse) and other operative complications were compared before and after operation., Results: Among 125 patients, 69 were male and 56 were female with median age of (41.2±15.5) (18 to 75) years. The follow-up rates were 94.4%(118/125), 92.0%(115/125), 89.6%(112/125) and 88.0%(110/125) at postoperative months 1, 3, 6, and 12. Incidences of abdominal distension and abdominal pain were 100% and 82.4%(103/125) before operation, and were 7.3%(8/110) and 20.9%(23/110) at 12 months after surgery. Wexner score was significantly lower at postoperative months 1(8.7±2.9), 3 (7.2±2.8), 6(6.7±2.2) and 12(6.3±1.7) than that before operation (21.4±7.2) (P<0.01). GIQLI score was 51.6±11.9 before operation, though it decreased at 1 month (47.3±5.5)(P<0.05) after surgery, but increased significantly at postoperative months 3, 6, 12(68.9±8.0, 96.5±8.2, 103.2±8.6)(P<0.01). Abnormal rate of defecography was 70.4%(81/115), 48.2%(54/112) and 27.3%(30/110) at postoperative months 3, 6, 12, which was significantly lower than 91.2%(114/125) before operation (P<0.01). Morbidity of postoperative complication was 29.6%(37/125), including 5 cases of surgical site infection (4.0%), 2 of anastomotic bleeding (1.6%), 8 of anastomotic leakage (6.4%, one died of severe abdominal infection), 4 of urinary retention (3.2%), 3 of recurrent constipation (2.4%, without megacolon relapse), 11 of bowel obstruction (8.8%), 2 of anastomotic stricture(1.6%) and 2 of refractory staphylococcus aureus enteritis (1.6%, diagnosed by stool smear and culture, and both died finally)., Conclusion: Jinling procedure is a safe and effective surgical procedure for adult Hirschsprung's disease.