Numerical simulation of deposition of drifts and salt from multiple super-large seawater cooling towers

Abstract A three-dimensional CFD simulation model was established to study the characteristics of flow, drifts and salt deposition from 6 super-large seawater cooling towers in a power station. In the model, site meteorological data, design parameters of cooling tower, general layout, environmental characteristics, are considered. The results show that: (1) when the wind direction is parallel to the towers, the streams overlap, reducing deposition of drifts and salt onto the ground. (2) The drifts with particle size greater than 550 μm cannot float out of cooling towers. (3) In normal operation of 6 such cooling towers, the resulting salt deposition will not cause serious damage to plants

Conservation genomics provides insights into genetic resilience and adaptation of the endangered Chinese hazelnut, Corylus chinensis

Global climate change has increased concerns regarding biodiversity loss. However, many key conservation issues still required further research, including demographic history, deleterious mutation load, adaptive evolution, and putative introgression. Here we generated the first chromosome-level genome of the endangered Chinese hazelnut, Corylus chinensis, and compared the genomic signatures with its sympatric widespread C. kwechowensis–C. yunnanensis complex. We found large genome rearrangements across all Corylus species and identified species-specific expanded gene families that may be involved in adaptation. Population genomics revealed that both C. chinensis and the C. kwechowensis–C. yunnanensis complex had diverged into two genetic lineages, forming a consistent pattern of southwestern-northern differentiation. Population size of the narrow southwestern lineages of both species have decreased continuously since the late Miocene, whereas the widespread northern lineages have remained stable (C. chinensis) or have even recovered from population bottlenecks (C. kwechowensis–C. yunnanensis complex) during the Quaternary. Compared with C. kwechowensis–C. yunnanensis complex, C. chinensis showed significantly lower genomic diversity and higher inbreeding level. However, C. chinensis carried significantly fewer deleterious mutations than C. kwechowensis–C. yunnanensis complex, as more effective purging selection reduced the accumulation of homozygous variants. We also detected signals of positive selection and adaptive introgression in different lineages, which facilitated the accumulation of favorable variants and formation of local adaptation. Hence, both types of selection and exogenous introgression could have mitigated inbreeding and facilitated survival and persistence of C. chinensis. Overall, our study provides critical insights into lineage differentiation, local adaptation, and the potential for future recovery of endangered trees

Estimating PM_2.5 Concentrations Using the Machine Learning RF-XGBoost Model in Guanzhong Urban Agglomeration, China

Fine particulate matter (PM2.5) is a major pollutant in Guanzhong Urban Agglomeration (GUA) during the winter, and GUA is one of China’s regions with the highest concentrations of PM2.5. Daily surface PM2.5 maps with a spatial resolution of 1 km × 1 km can aid in the control of PM2.5 pollution. Thus, the Random Forest and eXtreme Gradient Boosting (RF-XGBoost) model was proposed to fill the missing aerosol optical depth (AOD) at the station scale before accurately estimating ground-level PM2.5 using the recently released MODIS AOD product derived from Multi-Angle Implementation of Atmospheric Correction (MAIAC), high density meteorological and topographic conditions, land-use, population density, and air pollutions. The RF-XGBoost model was evaluated using an out-of-sample test, revealing excellent performance with a coefficient of determination (R2) of 0.93, root-mean-square error (RMSE) of 12.49 μg/m3, and mean absolution error (MAE) of 8.42 μg/m3. The result derived from the RF-XGBoost model indicates that the GUA had the most severe pollution in the winter of 2018 and 2019, owing to the burning of coal for heating and unfavorable meteorological circumstances. Over 90% of the GUA had an annual average PM2.5 concentrations decrease of 3 to 7 μg/m3 in 2019 compared to the previous year. Nevertheless, the air pollution situation remained grim in the winter of 2019, with more than 65% of the study area meeting the mean PM2.5 values higher than 35 μg/m3 and the maximum reaching 95.57 μg/m3. This research would be valuable for policymakers, environmentalists, and epidemiologists, especially in urban areas

Systematic selection of suitable reference genes for quantitative real-time PCR normalization studies of gene expression in Lutjanus erythropterus

Abstract Quantitative real-time PCR (qRT-PCR) has been widely employed for the study of gene expression in fish, and accurate normalization is crucial. In this study, we aimed to identify the most stably expressed genes in various tissues, different developmental stages, and within astaxanthin treatment groups in Lutjanus erythropterus. Twelve candidate genes (EEF1A, CYB5R3, DLD, IDH3A, MRPL17, MRPL43, NDUFS7, PABPC1, PAGR1, PFDN2, PSMC3, and RAB10) were examined via qRT-PCR. We employed geNorm and NormFinder to assess their stability. The results revealed that RAB10 and PFDN2 exhibited relatively stable expression patterns across different tissue and astaxanthin treatment groups, while NDUFS7 and MRPL17 proved to be the most reliable reference gene combinations across various developmental stages. The stability of these selected genes was further validated by assessing the expression of two target genes, CRADD and CAPNS1, across developmental stages, reinforcing the reliability of NDUFS7 as it closely aligned with transcriptome-wide expression patterns at these stages. The present results will help researchers to obtain more accurate results in future qRT-PCR analysis in L. erythropterus

Transition to chaos of thermocapillary convection

Thermocapillary convection is a common flow in space. Experiments regarding thermocapillary convection were previously carried out in a large-scale liquid bridge with a diameter of 20 mm on the Tiangong-2 space station, and the transition process to chaos was systematically studied. Under microgravity conditions, gravity is greatly weakened, and the transition process of the flow is very slow. This allows for the opportunity to study the bifurcation process in detail. It has been found that there are abundant nonlinear physical phenomena associated with the changing geometric parameters in thermocapillary convection systems. The transition mechanisms interact with each other, leading to various transition routes. The phase space trajectories, the Lyapunov exponents, and correlation dimensions are calculated to distinguish the chaotic state under a variety of conditions. Through the chaotic dynamics analysis, the chaotic characteristics of the entire transition process are quantitatively discussed

The Payload Development and the Experiments for Studying Thermocapillary Convection in TG-2 Liquid Bridge

The development of space experiment payload for studying thermocapillary convection in the liquid bridge with large Pr number on TG-2 space laboratory as well as the experiments are presented in detail in this paper, and the objectives of the space experiments are confirmed. The functions of the payload are analyzed, and the technical and engineering specifications are determined. Detailed designs and experimental verifications are performed on the structure of liquid bridge columns, the method of bubble removing in the liquid, the bridge cleaning system, the accurate control of aspect ratio and volume ratio, and the high-sensitivity measurement of fluid temperature. Matching experiments on the ground according to space experiment properties are carried out, 5cSt silicone oil is selected as the fluid medium in space experiments. And the states of liquid bridge and temperature oscillation signals obtained from space experiments are presented at the end of this paper. Specific summarizations and discussions to the experiment project on fluid science in space are conducted in this paper, which will provide a useful reference for scientists participating space experimental research in the future

Real-Time qPCR Identifies Suitable Reference Genes for Borna Disease Virus-Infected Rat Cortical Neurons

Quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) is the most commonly-used technique to identify gene expression profiles. The selection of stably expressed reference genes is a prerequisite to properly evaluating gene expression. Here, the suitability of commonly-used reference genes in normalizing RT-qPCR assays of mRNA expression in cultured rat cortical neurons infected with Borna disease virus (BDV) was assessed. The expressions of eight commonly-used reference genes were comparatively analyzed in BDV-infected rat cortical neurons and non-infected control neurons mainly across 9 and 12 days post-infection. These reference genes were validated by RT-qPCR and separately ranked by four statistical algorithms: geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. Then, the RankAggreg package was used to construct consensus rankings. ARBP was found to be the most stable internal control gene at Day 9, and ACTB at Day 12. As the assessment of the validity of the selected reference genes confirms the suitability of applying a combination of the two most stable references genes, combining the two most stable genes for normalization of RT-qPCR studies in BDV-infected rat cortical neurons is recommended at each time point. This study can contribute to improving BDV research by providing the means by which to obtain more reliable and accurate gene expression measurements