110 research outputs found
Genuine full characterization of partially coherence beam
For partially coherent light fields with random fluctuations, the intensity
distributions and statistics have been proven to be more propagation robust
compared with coherent light. However, its full potential in practical
applications has not been realized due to the lack of four-dimensional optical
field measurement. Here, a general modal decomposition method of partially
coherent light field is proposed and demonstrated. The decomposed random modes
can be used to, but not limited to, reconstruct average intensity, cross
spectral density and orthogonal decomposition properties of the partially
coherent light fields. Due to its versatility and flexibility, this method
provides a powerful tool to further reveal light field invariant or retrieve
embedded information after propagation through complex media. The
Gaussian-shell-model beam and partially coherent Gaussian array are used as
examples to demonstrate the reconstruction and even prediction of second-order
statistical characteristics. This method is expected to pave the way for
applications of partially coherent light in optical imaging, optical encryption
and anti-turblence optical communication
Real space iterative reconstruction for vector tomography (RESIRE-V)
Tomography has had an important impact on the physical, biological, and
medical sciences. To date, most tomographic applications have been focused on
3D scalar reconstructions. However, in some crucial applications, vector
tomography is required to reconstruct 3D vector fields such as the electric and
magnetic fields. Over the years, several vector tomography methods have been
developed. Here, we present the mathematical foundation and algorithmic
implementation of REal Space Iterative REconstruction for Vector tomography,
termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates
between the projections and a 3D reconstruction. Each iteration consists of a
forward step using the Radon transform and a backward step using its transpose,
then updates the object via gradient descent. Incorporating with a 3D support
constraint, the algorithm iteratively minimizes an error metric, defined as the
difference between the measured and calculated projections. The algorithm can
also be used to refine the tilt angles and further improve the 3D
reconstruction. To validate RESIRE-V, we first apply it to a simulated data set
of the 3D magnetization vector field, consisting of two orthogonal tilt series,
each with a missing wedge. Our quantitative analysis shows that the three
components of the reconstructed magnetization vector field agree well with the
ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D
magnetization vector field of a ferromagnetic meta-lattice consisting of three
tilt series. Our 3D vector reconstruction reveals the existence of topological
magnetic defects with positive and negative charges. We expect that RESIRE-V
can be incorporated into different imaging modalities as a general vector
tomography method
Catalytic Removal of Ozone by Pd/ACFs and Optimal Design of Ozone Converter for Air Purification in Aircraft Cabin
Ozone in aircraft cabin can bring obvious adverse impact on indoor air quality and occupant health. The objective of this study is to experimentally explore the ozone removal performance of flat-type catalyst film by loading nanometer palladium on the activated carbon fibers (Pd/ACFs), and optimize the configuration of ozone converter to make it meet the design requirements. A one-through ozone removal unit with three different Pd/ACFs space was used to test the ozone removal performance and the flow resistance characteristic under various temperature and flow velocity. The results show that the ozone removal rate of the ozone removal unit with the Pd/ACFs space of 1.5 mm can reach 99% and the maximum pressure drop is only 1.9 kPa at the reaction temperature of 200℃. The relationship between pressure drop and flow velocity in the ozone removal unit has a good fit to the Darcy-Forchheimer model. An ozone converter with flat-type reactor was designed and processed based on the one-through ozone removal experiment, its ozone removal rate and maximum pressure drop were 97% and 7.51 kPa, separately, with the condition of 150℃ and 10.63 m/s. It can meet the design requirements of ozone converter for air purification and develop a healthier aircraft cabin environment
Nonparaxial propagation properties of an anomalous hollow beam with orbital angular momentum
The analytical nonparaxial propagation formula of an anomalous hollow beam (AHB) with orbital angular momentum (OAM) in free space is derived based on the generalized Raleigh-Sommerfeld diffraction integral. The nonparaxial properties of AHB with OAM such as intensity, phase and OAM density distributions are studied in detail, using the pertinent nonparaxial propagation formula. The comparison between the paraxial and nonparaxial results is also carried out. The results show that the nonparaxial properties of an AHB with OAM are determined by the initial beam parameters, such as beam waist size and topological charge and propagation distance
Association of urban forest landscape characteristics with biomass and soil carbon stocks in Harbin City, Northeastern China
Background Urban forests help in mitigating carbon emissions; however, their associations with landscape patterns are unclear. Understanding the associations would help us to evaluate urban forest ecological services and favor urban forest management via landscape regulations. We used Harbin, capital city of the northernmost province in China, as an example and hypothesized that the urban forests had different landscape metrics among different forest types, administrative districts, and urban–rural gradients, and these differences were closely associated with forest carbon sequestration in the biomass and soils. Methods We extracted the urban forest tree coverage area on the basis of 2 GF-1 remote sensing images and object-oriented based classification method. The analysis of forest landscape patterns and estimation of carbon storage were based on tree coverage data and 199 plots. We also examined the relationships between forest landscape metrics and carbon storage on the basis of forest types, administrative districts, ring roads, and history of urban settlements by using statistical methods. Results The small patches covering an area of less than 0.5 ha accounted for 72.6% of all patches (average patch size, 0.31 ha). The mean patch size (AREA_MN) and largest patch index (LPI) were the highest in the landscape and relaxation forest and Songbei District. The landscape shape index (LSI) and number of patches linearly decreased along rural-urban gradients (p < 0.05). The tree biomass carbon storage varied from less than 10 thousand tons in the urban center (first ring road region and 100-year regions) to more than 100 thousand tons in the rural regions (fourth ring road and newly urbanized regions). In the same urban–rural gradients, soil carbon storage varied from less than five thousand tons in the urban centers to 73–103 thousand tons in the rural regions. The association analysis indicated that the total forest area was the key factor that regulates total carbon storage in trees and soils. However, in the case of carbon density (ton ha−1), AREA_MN was strongly associated with tree biomass carbon, and soil carbon density was negatively related to LSI (p < 0.01) and AREA_MN (p < 0.05), but positively related to LPI (p < 0.05). Discussion The urban forests were more fragmented in Harbin than in other provincial cities in Northeastern China, as shown by the smaller patch size, more complex patch shape, and larger patch density. The decrease in LSI along the rural-urban gradients may contribute to the forest carbon sequestrations in downtown regions, particularly underground soil carbon accumulation, and the increasing patch size may benefit tree carbon sequestration. Our findings help us to understand how forest landscape metrics are associated with carbon storage function. These findings related to urban forest design may maximize forest carbon sequestration services and facilitate in precisely estimating the forest carbon sink
Cell transcriptomic atlas of the non-human primate Macaca fascicularis.
Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding
Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland
Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for
technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene
expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi
from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing
reagents. This work was supported by the Shenzhen Basic Research Project for Excellent
Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics
(ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In
addition, L.L. was supported by the National Natural Science Foundation of China (31900466),
Y. Hou was supported by the Natural Science Foundation of Guangdong Province
(2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award
(419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences
(XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science
joint research project (GJHZ2093), the National Natural Science Foundation of China
(92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation
(2021B1515120075). M.L. was supported by the National Key Research and Development
Program of China (2021YFC2600200).S
Integrated Assessment of Heavy Metal Contamination in Sediments from a Coastal Industrial Basin, NE China
The purpose of this study is to investigate the current status of metal pollution of the sediments from urban-stream, estuary and Jinzhou Bay of the coastal industrial city, NE China. Forty surface sediment samples from river, estuary and bay and one sediment core from Jinzhou bay were collected and analyzed for heavy metal concentrations of Cu, Zn, Pb, Cd, Ni and Mn. The data reveals that there was a remarkable change in the contents of heavy metals among the sampling sediments, and all the mean values of heavy metal concentration were higher than the national guideline values of marine sediment quality of China (GB 18668-2002). This is one of the most polluted of the world’s impacted coastal systems. Both the correlation analyses and geostatistical analyses showed that Cu, Zn, Pb and Cd have a very similar spatial pattern and come from the industrial activities, and the concentration of Mn mainly caused by natural factors. The estuary is the most polluted area with extremely high potential ecological risk; however the contamination decreased with distance seaward of the river estuary. This study clearly highlights the urgent need to make great efforts to control the industrial emission and the exceptionally severe heavy metal pollution in the coastal area, and the immediate measures should be carried out to minimize the rate of contamination, and extent of future pollution problems
Analysis of Land Use in Jining City
Jining City is a typical area with complex and diverse landforms, developed water systems and rich mineral resources. Research on its land use changes will be of great significance in terms of sustainable development and ecological protection. This paper is based on the four LANDSAT remote sensing image data in 2000, 2005, 2010 and 2015, using RS, GIS, mathematical statistics and other methods, mainly analyze the land use of Jining City from 2000 to 2015 from three aspects: land use structure, land use characteristics and problems, land use area and structure changes. The results show that: (1) Jining City has the largest area of dry land, which is widely distributed in various regions; followed by construction land, water, grass, woodland, paddy field, and unutilized land. (2) The land use characteristics of Jining City are: high arable land rate, high land utilization rate, large proportion of water area, abundant surface water resources, and obvious regional differences in land use; the problems are that the land use structure is unreasonable, per capita land resources are few, and the contradiction between people and land has become increasingly prominent. (3) On the whole, land use changes in Jining City are relatively complex. The town house area has been showing an increasing trend; the grass area has shown a continuous decreasing trend; the fluctuations of dry land, paddy field, woodland, house-site in the countryside, water, and unutilized land area fluctuations are obvious. During the 15 years from 2000 to 2015, the largest change in the land use structure of Jining City was town house, followed by paddy field, house-site in the countryside, dry land, grass, woodland, unutilized land, and water. The area of town house, dry land, forest land, and water has increased, while the area of paddy field, house-site in the countryside, grass, and unutilized land has decreased
Impact of Epidemics on Enterprise Innovation: An Analysis of COVID-19 and SARS
This study analyzes the impact of SARS and COVID-19, the two most severe epidemics to occur in China since the 21st century, on corporate innovation, in order to find a path for sustained innovation growth under the epidemic. For COVID-19, the analysis used data from China’s A-share-listed companies from 2019 to 2020; a longer period (1999–2006) and a wider sample of Chinese industrial enterprises were used for the SARS epidemic. The empirical model was constructed using the difference-in-differences method. Both COVID-19 and SARS were found to have significantly reduced enterprise innovation. However, the effect of SARS disappeared after two years. For COVID-19, information asymmetry, financing constraints, and economic policy uncertainty moderated the epidemic’s effect on innovation. The results show that financing constraints and economic policy uncertainty reduce the epidemic’s negative impact. However, while most previous studies have found that an epidemic reduces the information asymmetry between investors and enterprises in the short term, thus raising enterprise innovation, we found that information asymmetry aggravated the epidemic’s negative impact. These findings can be applied to alleviate the current epidemic’s negative impact as well as improve enterprise innovation thereafter
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