Cicatricial Alopecia

Cicatricial alopecia represents a group of disorders sharing a final pathway of destruction followed by replacement with fibrous tissue of the hair follicle unit. Cicatricial alopecia is classified into two categories, namely primary cicatricial alopecia, in which the hair follicle is the sole target of a progressive inflammatory process in a group of diverse skin or systemic diseases, and secondary cicatricial alopecia, referring to the hair follicle destruction as a result of a nonspecific disruption of the dermis. Permanent hair loss may also occur in the late phases of some nonscarring alopecias that are called “biphasic alopecias.” Based on the pathological characteristics, the lesions of primary cicatricial alopecia are divided into lymphocyte-predominant subgroup, neutrophil-predominant subgroup, or mixed subgroup. In principle, the primary goal of the treatment aims to attenuate the progression of the inflammatory and the scarring processes at the earliest phase of the disease. In clinical practice, the lymphocyte-predominant lesions are treated with immunosuppressive agents, whereas the neutrophil-predominant lesions are treated with antimicrobials or dapsone. As the efficacy of medication treatment against the cicatricial alopecia varies significantly, autologous hair transplantation is recommended to patients who have a relatively stable primary or a secondary cicatricial alopecia

Moving Target Information Extraction Based on Single Satellite Image

The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method

On-Orbit Vicarious Radiometric Calibration and Validation of ZY1-02E Thermal Infrared Sensor

The ZY1-02E satellite carrying a thermal infrared sensor was successfully launched from the Taiyuan Satellite Launch Center on 26 December 2021. The quantitative characteristics of this thermal infrared camera, for use in supporting applications, were acquired as part of an absolute radiometric calibration campaign performed at the Ulansuhai Nur and Baotou calibration site (Inner Mongolia, July 2022). In this paper, we propose a novel on-orbit absolute radiometric calibration technique, based on multiple ground observations, that considers the radiometric characteristics of the ZY1-02E thermal infrared sensor. A variety of natural surface objects were selected as references, including bodies of water, bare soil, a desert in Kubuqi, and sand and vegetation at the Baotou calibration site. During satellite overpass, the 102F Fourier transform thermal infrared spectrometer and the SI-111 infrared temperature sensor were used to measure temperature and ground-leaving radiance for these surface profiles. Atmospheric water vapor, aerosol optical depth, and ozone concentration were simultaneously obtained from the CIMEL CE318 Sun photometer and the MICROTOP II ozonometer. Atmospheric profile information was acquired from radiosonde instruments carried by sounding balloons. Synchronous measurements of atmospheric parameters and ECMWF ERA5 reanalysis data were then combined and input to an atmospheric radiative transfer model (MODTRAN6.0) used to calculate apparent radiance. Calibration coefficients were determined from the measured apparent radiance and satellite-observed digital number (DN), for use in calculating the on-orbit observed radiance of typical surface objects. These values were then compared with the apparent radiance of each object, using radiative transfer calculations to evaluate the accuracy of on-orbit absolute radiometric calibration. The results show that the accuracy of this absolute radiometric calibration is better than 0.6 K. This approach allows the thermal infrared channel to be unrestricted by the limitations of spectrum matching between a satellite and field measurements, with strong applicability to various types of calibration sites

ZY3-02 Laser Altimeter On-orbit Geometrical Calibration and Test

ZY3-02 is the first satellite equipped with a laser altimeter for earth observation in China .This laser altimeter is an experimental payload for land elevation measurement experiment. The ranging and pointing bias of the laser altimeter would change due to the launch vibration, the space environment difference or other factors, and that could bring plane and elevation errors of laser altimeter. In this paper, we propose an on-orbit geometric calibration method using a ground-based electro-optical detection system based on the analysis of ZY3-02 laser altimeter characteristic, and this method constructs the rigorous geometric calibration model, which consider the pointing and ranging bias as unknown systematic errors, and the unknown parameters are calibrated with laser spot's location captured by laser detectors and the minimum ranging error principle. With the ALOS-DSM data as reference, the elevation accuracy of the laser altimeter can be improved from 100~150 meters before calibration to 2~3 meters after calibration when the terrain slope is less than 2 degree. With several ground control points obtained with RTK in laser footprint for validation, the absolute elevation precision of laser altimeter in the flat area can reach about 1 meter after the calibration. The test results demonstrated the effectiveness and feasibility of the proposed method

On-Orbit Geometric Calibration and Accuracy Validation for Laser Footprint Cameras of GF-7 Satellite

The Gaofen-7 (GF-7) satellite uses a two-beam laser altimetry system in which each beam is equipped with a laser footprint camera (LFC) to provide geometric processing of the laser footprint images that assist in optical image stereo mapping. Because of the violent vibrations during launch and the difference in the environment before and after entering orbit, the key parameters for geometric processing of the laser footprint images may change, which will cause large geolocation errors. Therefore, it is essential to carry out on-orbit calibration and validation for the laser footprint cameras. This study first constructs a rigorous geometric positioning model for the LFC of the GF-7 satellite and analyses various error sources that affect the geometric positioning accuracy of laser footprint images. Then, a comprehensive calibration method, which effectively eliminates the distortion of the LFC optical system, and the positioning error caused by the long-period jitter of the satellite platform, is proposed based on the multi-scene images combined with image simulation. The proposed method can effectively eliminate various errors that affect the geometric positioning accuracy of the GF-7 laser footprint image. The internal geometric positioning accuracy of the calibrated LFC is better than 0.7 pixels, and the absolute geometric positioning accuracy is within 6.0 m after using precise post-processing orbital and attitude data. Our study will contribute to the processing and application of laser altimetry data from the GF-7 satellite

Footprint Location Prediction Method of ZY3-02 Altimeter

On-orbit geometric calibration is an essential way to improve plane and elevation accuracy of laser altimeter data, and the laser footprint location prediction is a prerequisite for calibration based on land infrared detector. This paper builds a laser footprint location prediction model for China's first space-borne laser altimeter carried by ZY3-02, which refers to the satellite optical camera rigorous geometry imaging model. The model takes full account of the law of platform movement, and correlates laser emission center with ground footprint point. We get the precise predicted laser pointing by Pyramid terrain matching, ephemerisby acceleration prediction, and attitude by frequency analysis. The laser footprint location can be predicted. This laser footprint location prediction model were successfully applied in the calibration test of the laser altimeter on ZY3-02 satellite, and the maximum error between the predicted location and real footprint location obtained by triggered detectors is less than 150 m, which proves the validity of the proposed model. The proposed method provides the precise point-to-point prediction from satellite to ground for Chinese remote sensing satellite, and offers a technological support for the space-borne laser altimeter calibration in future

ZY3-02 Laser Altimeter Footprint Geolocation Prediction

Successfully launched on 30 May 2016, ZY3-02 is the first Chinese surveying and mapping satellite equipped with a lightweight laser altimeter. Calibration is necessary before the laser altimeter becomes operational. Laser footprint location prediction is the first step in calibration that is based on ground infrared detectors, and it is difficult because the sample frequency of the ZY3-02 laser altimeter is 2 Hz, and the distance between two adjacent laser footprints is about 3.5 km. In this paper, we build an on-orbit rigorous geometric prediction model referenced to the rigorous geometric model of optical remote sensing satellites. The model includes three kinds of data that must be predicted: pointing angle, orbit parameters, and attitude angles. The proposed method is verified by a ZY3-02 laser altimeter on-orbit geometric calibration test. Five laser footprint prediction experiments are conducted based on the model, and the laser footprint prediction accuracy is better than 150 m on the ground. The effectiveness and accuracy of the on-orbit rigorous geometric prediction model are confirmed by the test results. The geolocation is predicted precisely by the proposed method, and this will give a reference to the geolocation prediction of future land laser detectors in other laser altimeter calibration test

Estimating Nighttime PM_2.5 Concentration in Beijing Based on NPP/VIIRS Day/Night Band

Nighttime PM2.5 detection by remote sensing can expand understanding of PM2.5 spatiotemporal patterns due to wider coverage compared to ground monitors and by supplementing traditional daytime detection. However, using remote sensing data to invert PM2.5 at night is still challenging. Compared with daytime detection, which operates on sunlight, nighttime detection operates on much weaker moonlight and artificial light sources, complicating signal extraction. Moreover, as the attempts to sense PM2.5 remotely using satellite data are relatively recent, the existing nighttime models are still not mature, overlooking many important factors such as stray light, seasonality in meteorological effects, and observation angle. This paper attempts to improve the accuracy of nighttime PM2.5 detection by proposing an inversion model that takes these factors into consideration. The Visible Infrared Imaging Radiometer Suite/Day/Night Band (VIIRS/DNB) on board the polar-orbiting Suomi National Polar-orbiting Partnership (Suomi NPP) and National Oceanic Atmospheric Administration-20 (NOAA-20) was used to establish a nighttime PM2.5 inversion model in the Beijing area from 1 March 2018 to 28 February 2019. The model was designed by first studying the effects of these factors through a stepwise regression, then building a multivariate regression model to compensate for these effects. The results showed that the impact of satellite viewing zenith angle (VZA) was strongest, followed by seasonality and moonlight. Total accuracy was measured using correlation coefficient (R) compared to ground measurements, achieving 0.87 over the urban area and 0.74 over the suburbs. Specifically, the proposed method works efficiently at subsatellite points, which in this case correspond to VZA from 0 and 5°. In spring, summer, autumn, and winter, the R reached 0.95, 0.93, 0.94, and 0.97 at subsatellite points in the urban area, while it was 0.88, 0.82, 0.85, and 0.77 in the suburbs

A scallop IGF binding protein gene: molecular characterization and association of variants with growth traits.

BACKGROUND: Scallops represent economically important aquaculture shellfish. The identification of genes and genetic variants related to scallop growth could benefit high-yielding scallop breeding. The insulin-like growth factor (IGF) system is essential for growth and development, with IGF binding proteins (IGFBPs) serving as the major regulators of IGF actions. Although an effect of IGF on growth was detected in bivalve, IGFBP has not been reported, and members of the IGF system have not been characterized in scallop. RESULTS: We cloned and characterized an IGFBP (PyIGFBP) gene from the aquaculture bivalve species, Yesso scallop (Patinopecten yessoensis, Jay, 1857). Its full-length cDNA sequence was 1,445 bp, with an open reading frame of 378 bp, encoding 125 amino acids, and its genomic sequence was 10,193 bp, consisting of three exons and two introns. The amino acid sequence exhibited the characteristics of IGFBPs, including multiple cysteine residues and relatively conserved motifs in the N-terminal and C-terminal domains. Expression analysis indicated that PyIGFBP was expressed in all the tissues and developmental stages examined, with a significantly higher level in the mantle than in other tissues and a significantly higher level in gastrulae and trochophore larvae than in other stages. Furthermore, three single nucleotide polymorphisms (SNPs) were identified in this gene. SNP c.1054A>G was significantly associated with both shell and soft body traits in two populations, with the highest trait values in GG type scallops and lowest in AG type ones. CONCLUSION: We cloned and characterized an IGFBP gene in a bivalve, and this report also represents the first characterizing an IGF system gene in scallops. A SNP associated with scallop growth for both the shell and soft body was identified in this gene. In addition to providing a candidate marker for scallop breeding, our results also suggest the role of PyIGFBP in scallop growth

GF-7 dual-beam laser altimeter on-orbit geometric calibration and test verification

The GF-7 satellite is carrying the Chinese first dual-beam laser altimeter system for earth observation, aimed at assisting stereo optical cameras to realize 1∶10 000 mapping. Due to the influence of the vibration of the satellite during launch and the difference of environment between space and ground, the calibration values of the altimetry parameters on ground are deviated from the actual values in space. In order to improve the altimetry, a two-step on-orbit geometric calibration scheme from coarse to fine is proposed for the GF-7 dual-beam laser altimeter. Firstly, a single beam laser on-orbit geometric calibration model is constructed to estimate the location of the laser footprints based on the typical waveform analysis, so as to realize the single beam laser rough calibration. Secondly, based on the geometric calibration model of single beam laser, the geometric calibration model of dual-beam laser is constructed. Considering the factors such as atmospheric delay and tidal correction, the spot is captured by ground detector array as the ground control point, and realize the joint precision calibration of dual-beam laser. Finally, the relative and absolute elevation measurement accuracy after calibration was verified by using the laser altimeters data on the calm lake surface and the ground control data. The experimental results show that the relative accuracy of laser elevation measurement of GF-7 satellite is better than 0.06 m (1σ), and the absolute accuracy of laser elevation measurement in flat areas is up to 0.10 m (1σ)