Study on the methods for predicting the performance of a hybrid solar-assisted ground-source heat pump system

It is critical to find suitable setting parameters for designing a hybrid solar-assisted ground-source heat pump system in the practical engineering application, but the heat pump performance is unpredictable after many years of operation. This paper used 2000 sets of performance data collected from solar-assisted GSHP systems that keep operating over 20 years to simulate long term used heat pump with a professional software called GeoStar. Adopted the classification and regression tree (CART) method, the design of solar energy collector areas can be predicted. The multi-linear regression is also utilized to predict average monthly per meter borehole heat exchange. Seasonal factor decomposition and exponential smoothing are used to analyze the average monthly temperature of the circulating fluid, circulating fluid inlet and outlet temperatures of the heat pump after 20 years when we perform the time series prediction. Experimental results demonstrate that CART, multi-linear regression, seasonal factor decomposition and exponential smoothing are promising for practical applications

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

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.This work is part of the ‘‘SpatioTemporal Omics Consortium’’ (STOC) paper package. A list of STOC members is available at: http://sto-consortium.org. We would like to thank the MOTIC China Group, Rongqin Ke (Huaqiao University, Xiamen, China), Jiazuan Ni (Shenzhen University, Shenzhen, China), Wei Huang (Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China), and Jonathan S. Weissman (Whitehead Institute, Boston, USA) for their help. This work was supported by the grant of Top Ten Foundamental Research Institutes of Shenzhen, the Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), and the Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011); Longqi Liu was supported by the National Natural Science Foundation of China (31900466) and Miguel A. Esteban’s laboratory at the Guangzhou Institutes of Biomedicine and Health by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), National Natural Science Foundation of China (92068106), and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075).S

Single cell atlas for 11 non-model mammals, reptiles and birds.

The availability of viral entry factors is a prerequisite for the cross-species transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale single-cell screening of animal cells could reveal the expression patterns of viral entry genes in different hosts. However, such exploration for SARS-CoV-2 remains limited. Here, we perform single-nucleus RNA sequencing for 11 non-model species, including pets (cat, dog, hamster, and lizard), livestock (goat and rabbit), poultry (duck and pigeon), and wildlife (pangolin, tiger, and deer), and investigated the co-expression of ACE2 and TMPRSS2. Furthermore, cross-species analysis of the lung cell atlas of the studied mammals, reptiles, and birds reveals core developmental programs, critical connectomes, and conserved regulatory circuits among these evolutionarily distant species. Overall, our work provides a compendium of gene expression profiles for non-model animals, which could be employed to identify potential SARS-CoV-2 target cells and putative zoonotic reservoirs

Study on the methods for predicting the performance of a hybrid solar-assisted ground-source heat pump system

It is critical to find suitable setting parameters for designing a hybrid solar-assisted ground-source heat pump system in the practical engineering application, but the heat pump performance is unpredictable after many years of operation. This paper used 2000 sets of performance data collected from solar-assisted GSHP systems that keep operating over 20 years to simulate long term used heat pump with a professional software called GeoStar. Adopted the classification and regression tree (CART) method, the design of solar energy collector areas can be predicted. The multi-linear regression is also utilized to predict average monthly per meter borehole heat exchange. Seasonal factor decomposition and exponential smoothing are used to analyze the average monthly temperature of the circulating fluid, circulating fluid inlet and outlet temperatures of the heat pump after 20 years when we perform the time series prediction. Experimental results demonstrate that CART, multi-linear regression, seasonal factor decomposition and exponential smoothing are promising for practical applications

Effects of 5-hydroxytryptamine 2C receptor agonist MK212 and 2A receptor antagonist MDL100907 on maternal behavior in postpartum female rats

Maternal behavior in rats is a highly motivated and well-organized social behavior. Given the known roles of serotonin (5-HT) in emotion, motivation, social behavior, and major depression – and its known interaction with dopamine – it is likely that serotonin also plays a crucial role in this behavior. So far, there are surprisingly few studies focusing on 5-HT in maternal behavior, except for maternal aggression. In the present study,we examined the effects of 5-HT2C receptor agonism and 5-HT2A receptor antagonism on maternal behavior in postpartum female rats.We hypothesized that activation of 5-HT2C receptors and blockade of 5-HT2A receptors would produce a functionally equivalent disruption of maternal behavior because these two receptor subtypes often exert opposite effects on various brain functions and psychological processes relevant to rat maternal behavior. On postpartum Days 5, 7, and 9, Sprague–Dawley mother rats were given a single injection of 0.9% NaCl solution, the 5-HT2C agonist MK212 (0.5, 1.0 or 2.0 mg/kg, ip), or the 5-HT2A antagonist MDL100907 (0.05, 0.5 or 2.0 mg/kg, ip). Maternal behavior was tested 30 min before and 30 min, 120 min, 240 min after injection. Acute injection of MK212 significantly disrupted pup retrieval, pup licking, pup nursing, and nest building in a dose-dependent fashion. At the tested doses, MDL100907 had little effect on various components of rat maternal behavior. Across the 3 days of testing, no apparent sensitization or tolerance associated with repeated administration of MK212 and MDL100907 was found.We concluded that rat maternal performance is critically dependent on 5-HT2C receptors, while the role of 5-HT2A receptors is still inconclusive. Possible behavioral mechanisms of actions of 5-HT2C receptor in maternal behavior are discussed

Classification of Aviation Alloys Using Laser-Induced Breakdown Spectroscopy Based on a WT-PSO-LSSVM Model

It is well-known that aviation alloys of different grades show large differences in mechanical properties. At present, alloys must be strictly distinguished in the manufacturing plant because their close appearance and density are easily confused In this work, the wavelet transform (WT) method combined with the least squares support vector machine (LSSVM) is applied to the classification and identification of aviation alloys by laser-induced breakdown spectroscopy (LIBS). This experiment employed six different grades of aviation alloy as the classification samples and obtained 100 sets of spectral data for each sample. This research included the steps of preprocessing the obtained spectral data, model training, and parameter optimization. Finally, the accuracy of the training set was 99.98%, and the accuracy of the test set was 99.56%. Therefore, it is concluded that the model has superior generalization capacity and portability. The result of this work illustrates that LIBS technology can be adopted for the rapid identification of aviation alloys, which is of great significance for on-site quality control and efficiency improvement of aerospace parts manufacturing