Kiwifruit is a perennial horticultural crop species with high nutritional and economic value. However, various pathogens stress brings a serious threat to kiwifruit. Pentatricopeptide repeat proteins (PPRs) are characterized by tandem repetitions of 35 amino acid motifs, and have been found to function in plant RNA editing. However, the roles of PPRs in plant development and disease resistance remain unclear. In this study, we performed a genome-wide identification and characterization of PPR gene family in two kiwifruit species (Actinidia chinensis (Ach), and Actinidia eriantha (Ace)) with markedly different disease resistance. A total of 497 and 499 PPRs were identified in Ach and Ace, respectively. All the kiwifruit PPRs could be phylogenetically divided into four subfamilies. There were about 40.68% PPRs predicted to be localized to mitochondria or chloroplasts. Synteny analysis showed that the expansion of kiwifruit PPRs mainly came from segmental duplication. Based on RNA-seq data from the fruit during 12 periods of development and maturity, weighted correlation network analysis suggested that two PPRs Actinidia20495.t1 and Actinidia15159.t1 were involved in the fruit development and maturation. In addition, we observed different gene expression of PPRs and chloroplast RNA editing profiles between resistant and susceptible kiwifruits after pathogen infection, indicating the roles of PPRs in stress response by modulating the editing extend of mRNA. The differentially expressed upstream transcription factors of PPRs were further identified, they may regulate resistance adaption by modulating the PPRs expression. These results provide a solid foundation for further analyses of the functions and molecular evolution of PPRs, in particular, for clarifying the resistance mechanisms in kiwifruits and breeding new cultivars with high resistance.

The heritage of ancient buildings is an important part of the world's history and culture, which has an extremely rich historical-cultural value and artistic research value. Beijing has a large number of palace ancient buildings, and because of the age of their construction, many of them have problems of varying degrees of peeling and mold on the inner surfaces of the envelope. To solve the problems of the damp and moldy interior of palace buildings, a mathematical model of indoor heat and moisture transfer was established based on a wooden palace ancient building in Beijing. Through the indoor mold distribution validation model, the effects of outdoor humidity, soil moisture, wall humidity, and other factors on the indoor heat and moisture transfer of ancient buildings were simulated and analyzed by using the control variables method. The results showed that the molds were distributed at the indoor corners and floors, and the simulation of indoor humidity match the measured humidity. Thus, the simulation results were consistent with the actual situation. The variable trend of the relative humidity of the indoor environment with the outdoor humidity is inconsistent from plane to plane, i.e. it increases or remains constant with the increase of the outdoor humidity. The indoor ambient relative humidity increased with increasing the wall humidity. And the indoor average temperature is 23.3 ℃ and indoor relative humidity ranged between 90.9 % to 92.44 %. Soil moisture and wall humidity were the main factors affecting the indoor environmental relative humidity.

At present, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed and treatment results. EMR has been recognized as a valuable resource for large scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation and data reduction. For semi-structured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (Named Entity Recognition) and RE (Relation Extraction). In this paper, we introduce the process of EMR processing, including data collection, data preprocessing, data mining, evaluation and knowledge application, analyze the current status of the key technologies, such as data preprocessing and data mining, and provide an overview of the application domains and prospects of EMR mining technologies. Finally, we summarize the existing problems in the research of EMR mining, and review the development trends.

The Arbas cashmere goat is a unique biological resource that plays a vital role in livestock husbandry in China. LCDM is a medium with special small molecules (consisting of human LIF, CHIR99021, (S)-(+)-dimethindene maleate, and minocycline hydrochloride) for generation pluripotent stem cells (PSCs) with bidirectional developmental potential in mice, humans, pigs, and bovines. However, there is no report on whether LCDM can support for generation of PSCs with the same ability in Arbas cashmere goats. In this study, we applied LCDM to generation goat induced PSCs (giPSCs) from goat fetal fibroblasts (GFFs) by reprogramming. The derived giPSCs exhibited stem cell morphology, expressing pluripotent markers, and could differentiate into three germ layers. Moreover, the giPSCs differentiated into the trophectoderm lineage by spontaneous and directed differentiation in vitro. The giPSCs contributed to embryonic and extraembryonic tissue in preimplantation blastocysts and postimplantation chimeric embryos. RNA-sequencing analysis showed that the giPSCs were very close to goat embryos at the blastocyst stage and giPSCs have similar properties to typical extended PSCs (EPSCs). The establishment of giPSCs with LCDM provides a new way to generate high quality of PSCs from domestic animals and lays the foundation for basic and applied research in biology and agriculture.

SLEUTH Model (slope, landuse, exclusion, urban extent, transportation and hillshade) is an important tool for landuse planning and land policy. To evaluate the performance of SLEUTH model, implementation of Sensitivity Analysis (SA) is essential. The main limitation of SA in SLEUTH application is a lack of insight into model input self-modification parameters (SMPs) variation, namely, uncertainty involved in the model transfer metrics and model presumptions, which often misled the decision makers and model users. To address this issue, this study divided the forward process into two stages. Firstly, during the transfer process ①, the contribution scores of five SMPs were drawn, and parameters highly sensitive to model output were given. Apart from that, the recommended initial value for SMPs of 0.11, 0.2, 0.87, 1.13, 15, 1.01, 0.49 were found to be subordinated to such a heterogeneous urban area simulation. Secondly, during the transfer process ②, SMP caused imagery metrics indicated the disparity between parameters with Fixed Reference and with Successive Reference. Reversely, it derives reasonable threshold for the best fit values of five prediction coefficients’ initialization by comparing the real image with the predicted one. The framework of SLEUTH model transfer mechanism not only could distinguish highly sensitive SMPs with higher contribution scores, but also could give parametric analysis for simulation imagery based on metrics. The study was found to be a practical tool for quantization response of model input variables for modelling complex urban systems. So, this insight can help geographic information scientists decide how to find out the inner forward transfer mechanism of SLEUTH model for further make good use of it and improve the model.

Three-dimensional (3D) printing has allowed for production of geometrically complex 3D objects with extreme flexibility, which is currently undergoing rapid expansions in terms of materials, functionalities, as well as areas of application. When attempting to print 3D microstructures in glass, femtosecond laser induced chemical etching (FLICE) – which is a subtractive 3D printing technique – has proved itself a powerful approach. Here, we demonstrate fabrication of macro-scale 3D glass objects of large heights up to ~3.8 cm with an identical lateral and longitudinal spatial resolution of ~20 μm. The remarkable accomplishment is achieved by revealing an unexplored regime in the interaction of ultrafast laser pulses with fused silica which results in aberration-free focusing of the laser pulses deeply inside fused silica.

The general circuit topology and principles of low-noise high-voltage power supply are investigated to meet the requirements of the high-voltage bias application in air kerma meters. Two topologies, flyback converter and Royer converter are simulated using SPICE simulation program. The simulation results indicate that the circuit structure of the Royer converter is more complex, but it obtains lower output high voltage noise. While we develop an adjustable high-voltage power supply according to the circuit structure of the Royer converter, and tested it to ensure the design requirements for continuously adjustable output high-voltage linearity. The test results show that the linear adjustment rate is not more than ±0.0025%, the load regulation rate is less than ±0.1%, and the output ripple noise voltage percentage is less than 0.01%. These tested performance make it more suitable for accurate nuclear measurements.

The first case of Corona Virus Disease 2019 (COVID-19) was reported in Wuhan, China in December 2019. Since then, COVID-19 has quickly spread out to all provinces in China and over 150 countries or territories in the world. With the first level response to public health emergencies (FLRPHE) launched over the country, the outbreak of COVID-19 in China is achieving under control in China. We develop a mathematical model based on epidemiology of COVID-19, incorporating the isolation of healthy people, confirmed cases and close contacts. We calculate the basic reproduction numbers 2.5 in China (excluding Hubei province) and 2.9 in Hubei province with the initial time on January 30 which show the severe infectivity of COVID-19, and verify that the current isolation method effectively contains the transmission of COVID-19. Under the isolation of healthy people, confirmed cases and close contacts, we find a noteworthy phenomenon that is the potential second epidemic of COVID-19, and estimate the peak time and value and the cumulative number of cases. Simulations show that the isolation of close contacts tracked measure can efficiently contain the transmission of the potential second epidemic of COVID-19. With isolation of all susceptible people or all infected people or both, there is no potential second epidemic of COVID-19. Furthermore, resumption of work and study can increase the transmission risk of the potential second epidemic of COVID-19.

Low temperature is a common biological abiotic stress in major cotton growing areas. Cold stress significantly affects the growth, yield and yield quality of cotton. Therefore, it is important to develop a more robust and cold stress tolerant cotton germplasms. Climate change and erratic climatic condition, plants have evolved various survival mechanisms, one of which induction of various stress responsive transcriptome factors, such as the C-repeat binding factor GthCBF4, which have been found to enhance cold tolerance in various plants. In this study detailed evaluation of the cotton C-repeat binding factor has been carried out. A total of29, 28, 25, 21, 30, 26 and 15 proteins encoded by the C-repeat binding factor were identified in G. herbaceum, G. arboreum, G. thurberi, G. raimondii, G. turneri, G. longicalyx and G. australe, respectively. Phylogeny evaluation revealed that the proteins were grouped into seven clades, with clade 1 and 6 being the largest. Moreover, majority of the proteins encoded by the genes were predicted to be located within. the nucleus, while some are distributed in other parts of the cell. Based on the transcriptome and RT-qPCR analysis, Gthu17439 (GthCBF4) was highly upregulated and was further validated through forward genetics. The Gthu17439 (GthCBF4) overexpressed plants showed a significantly tolerance to cold stress, with higher growth vigour compared to the wild types. The results showed that the Gthu17439 (GthCBF4) could be playing a significant role in enhancing cold stress tolerance in cotton and can be further exploited in developing a more cold stress tolerance cotton germplasm