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Li, Juan

Publications and source records attributed to Li, Juan.

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Epidemiological investigation of coccidiosis and associated risk factors in broiler chickens immunized with live anticoccidial vaccines in China

Coccidiosis is a costly intestinal disease of chickens caused by Eimeria species. This infection is associated with high mortality, reduced feed efficiency, and slowed body weight gain. The diagnosis and control of coccidiosis becomes challenging due to the fact that chickens can be infected by seven different Eimeria species and often occur mixed-species co-infections. Grasping the epidemiology of Eimeria species is crucial to estimate the efficiency of poultry management. This study aimed to explore the distribution of Eimeria species in broiler chickens in China after administering live anticoccidial vaccines. A total of 634 samples were obtained, and the survey results showed that the prevalence of Eimeria was 86.12% (546/634), and the most common species were E. acervulina (65.62%), E. necatrix (50.95%), E. mitis (50.79%), E. tenella (48.42%), and E. praecox (41.80%). Most samples indicated mixed-species infections (an average of 3.29 species per positive sample). Notably, 63.98% of samples contain 3 to 5 Eimeria species within a single fecal sample. The most prevalent combinations were E. acervulina – E. tenella (38.96%) and E. acervulina – E. necatrix (37.22%). Statistical analysis showed that flocks vaccinated with trivalent vaccines were significantly positive for E. necatrix in grower chickens (OR = 3.30, p < 0.05) compared with starter chickens, and tetravalent vaccinated flocks showed that starter chickens demonstrated a higher susceptibility to E. tenella – E. brunetti (OR = 2.03, p < 0.05) and E. acervulina – E. maxima (OR = 2.05, p < 0.05) compared with adult chickens. Geographically, in the case of tetravalent vaccine-immunized flocks, a substantial positive association was observed between E. necatrix infection rates and flocks from eastern (OR = 3.88, p < 0.001), central (OR = 2.65, p = 0.001), and southern China (OR = 3.17, p < 0.001) compared with southwestern China. This study also found a positive association between E. necatrix (OR = 1.64, p < 0.05), E. acervulina (OR = 1.59, p < 0.05), and E. praecox (OR = 1.81, p < 0.05) infection and coccidiosis occurrence compared with non-infected flocks in tetravalent vaccinated flocks. This molecular epidemiological investigation showed a high prevalence of Eimeria species in the field. The emergent species, E. brunetti and E. praecox , might be incorporated into the widely-used live vaccines in the future. These insights could be useful in refining coccidiosis control strategies in the poultry industry.

Liao, Shenquan↗
DOE OSTI2023

High-Resolution PM2.5 Concentrations Estimation Based on Stacked Ensemble Learning Model Using Multi-Source Satellite TOA Data

Nepal has experienced severe fine particulate matter (PM2.5) pollution in recent years. However, few studies have focused on the distribution of PM2.5 and its variations in Nepal. Although many researchers have developed PM2.5 estimation models, these models have mainly focused on the kilometer scale, which cannot provide accurate spatial distribution of PM2.5 pollution. Based on Gaofen-1/6 and Landsat-8/9 satellite data, we developed a stacked ensemble learning model (named XGBLL) combined with meteorological data, ground PM2.5 concentrations, ground elevation, and population data. The model includes two layers: a XGBoost and Light GBM model in the first layer, and a linear regression model in the second layer. The accuracy of XGBLL model is better than that of a single model, and the fusion of multi-source satellite remote sensing data effectively improves the spatial coverage of PM2.5 concentrations. Besides, the spatial distribution of the daily mean PM2.5 concentrations in the Kathmandu region under different air conditions was analyzed. The validation results showed that the monthly averaged dataset was accurate (R2 = 0.80 and root mean square error = 7.07). In addition, compared to previous satellite PM2.5 datasets in Nepal, the dataset produced in this study achieved superior accuracy and spatial resolution.

Environmental Sciences & Ecology↗
DOE OSTI2023

Forest Soil Carbon Efflux Evaluation Across China: A New Estimate With Machine Learning

Forest soil respiration (Rs) plays an important role in the carbon balance of terrestrial ecosystems. China's forest occupies a large part of the world's forest. However, due to the lack of integrated observation data and appropriate upscaling methodologies, substantial uncertainties exist in the Rs evaluation, which limits our understanding of the carbon balance. Here, we re-evaluated the total soil carbon effluxes across China by combining field observations from 634 published annual Rs with a machine learning technique (i.e., Random Forest (RF)). Our results revealed that the combination of systematic measurements with the RF model allowed a definite estimate. The average annual Rs was 773.6 g C m -2 yr -1 , ranging from 404.6 to 1,772.3 g C m -2 yr -1 . Total forest soil carbon effluxes amounted to 1.17 Pg C yr -1 in China. Geographically, annual Rs showed a clear spatially increasing trend from northeast to southwest. Forest type is an important factor in determining the soil respiration rate. Bamboo and Evergreen broadleaf forests were higher than other types of forests. In conclusion, these results provide a unique insight into the magnitudes and mechanisms of soil CO 2 emissions in China's forest ecosystems.

58 GEOSCIENCES↗
NASA NTRS2011

Measurement of Phased Array Point Spread Functions for Use with Beamforming

Microphone arrays can be used to localize and estimate the strengths of acoustic sources present in a region of interest. However, the array measurement of a region, or beam map, is not an accurate representation of the acoustic field in that region. The true acoustic field is convolved with the array s sampling response, or point spread function (PSF). Many techniques exist to remove the PSF's effect on the beam map via deconvolution. Currently these methods use a theoretical estimate of the array point spread function and perhaps account for installation offsets via determination of the microphone locations. This methodology fails to account for any reflections or scattering in the measurement setup and still requires both microphone magnitude and phase calibration, as well as a separate shear layer correction in an open-jet facility. The research presented seeks to investigate direct measurement of the array's PSF using a non-intrusive acoustic point source generated by a pulsed laser system. Experimental PSFs of the array are computed for different conditions to evaluate features such as shift-invariance, shear layers and model presence. Results show that experimental measurements trend with theory with regard to source offset. The source shows expected behavior due to shear layer refraction when observed in a flow, and application of a measured PSF to NACA 0012 aeroacoustic trailing-edge noise data shows a promising alternative to a classic shear layer correction method.

Bahr, Chris↗