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Purpose Microbial resources are abundant in fermented grains of the Chinese Fen-flavor Baijiu, which is closely related to the quality of Baijiu. The purpose of this study was to investigate the microbial community structure and function in Daqu and fermented grains. Methods We systematically compared two technical approaches, amplicon sequencing, and metagenomic sequencing, to analyze the microbial communities during Baijiu fermentation. Result The results showed that lactic acid bacteria (LAB) and yeasts were the main microorganisms in the fermentation process. Firmicutes (Lactobacillus, Pediococcus, and Weissella) were the dominant bacteria, and Ascomycota (Issatchenkia or Pichia) was the dominant fungus in fermented grains. Moreover, Pichia kudriavzevii, Lichtheimia ramosa, and Companilactobacillus paralimentarius were the dominant species at the initial stage of fermentation by metagenomic sequencing. Latilactobacillus curvatus, Loigolactobacillus coryniformis subsp. coryniformis, and Lentilactobacillus parabuchneri became dominant during the middle stage of fermentation. Lentilactobacillus parabuchneri and Lactobacillus acetotolerans were the dominant species in the final stage of fermentation. Spearman correlation analysis showed that LAB inhibited the growth of yeasts. Conclusion Combining the two sequencing methods provided valuable insights into the dynamic succession of microorganisms during the fermentation of Baijiu. It had had a particular significance for mining microbial species resources in fermented grains.

Privacy protection has received a lot of attention in recent years since in the era of big data, abundant information about individuals can be easily acquired. Meanwhile, as a prerequisite for effective privacy protection, the measurement of privacy disclosure is essential. Although some work has been done on the evaluation of privacy disclosure via quantification for the protection of privacy, not much attention has been placed on exploring the relationships between privacy information, resulting in underestimation, if not ill-formed reasoning, of privacy disclosure. In this paper, we propose an ontology-based approach to measure privacy disclosure by exploring the relationships between privacy information based on the WordNet. We first propose an algorithm for deriving or measuring privacy disclosure based on a set of words or concepts from text data related to individuals to ensure that the disclosure of certain user privacy can still be deduced and measured even if the set of words or concepts don’t seem to be much related to it. We then perform a set of experiment by applying the proposed algorithm to some public information of ten public figures from different walks of life to evaluate the effectiveness of the algorithm and to shed some light on the characteristics of privacy disclosure in the real world in the era of big data. The work can thus serve as the foundation for the development of mechanisms for limiting or reducing privacy disclosure to achieve better protection of individual privacy.

OBJECTIVE To investigate the molecular mechanisms underlying the effects of arsenic trioxide (As2O3) in combination with leflunomide on the hamster-to-rat heart xenotransplant. METHODS Transplantation of LVG hamster hearts to Lewis rats was performed by anastomosis of vessels in the neck using end-to-end anastomosis with a non-suture cuff technique. Four groups of recipient rats (n=6 in each) were treated with normal saline (control), As2O3 [5 mg/(kg·day) intraperitoneally], leflunomide [5 mg/(kg·d) orally], or leflunomide [5 mg/(kg·d)+As2O3 [5 mg/(kg·d)] in combination. Donor hearts and/or rat spleens were harvested and analyzed 4 days after transplantation. Quantitative reverse-transcription polymerase chain reaction and Western blot analysis were performed to detect the expression of the nuclear factor erythroid-derived factor 2-related factor (Nrf2) and its target gene heme oxygenase-1 (HO-1), Treg cell marker fork-head Box P3 (FOXP3), apoptosis-associated proteins Bcl-2, Bax, and cleaved caspase-3. Immunohistochemical staining was used to detect the levels of inflammatory natural killer cell and macrophage infiltration, intercellular cell adhesion molecule-1 (ICAM-1) and complement C3. RESULTS Expression of Nrf2-ARE-HO-1 signaling pathway was upregulated in heart xenografts in rats treated with As2O3 plus leflunomide compared with control rats or rats treated with either drug alone (P

Renal cell carcinoma (RCC) is a kidney cancer that is originated from the lined proximal convoluted tubule, and its major histological subtype is clear cell RCC (ccRCC). This study aimed to retrospectively analyze single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, to explore the correlation among the evolution of tumor microenvironment (TME), clinical outcomes, and potential immunotherapeutic responses in combination with bulk RNA-seq data from The Cancer Genome Atlas (TCGA) database, and to construct a differentiation-related genes (DRG)-based prognostic risk signature (PRS) and a nomogram to predict the prognosis of ccRCC patients. First, scRNA-seq data of ccRCC samples were systematically analyzed, and three subsets with distinct differentiation trajectories were identified. Then, ccRCC samples from TCGA database were divided into four DRG-based molecular subtypes, and it was revealed that the molecular subtypes were significantly correlated with prognosis, clinicopathological features, TME, and the expression levels of immune checkpoint genes (ICGs). A DRG-based PRS was constructed, and it was an independent prognostic factor, which could well predict the prognosis of ccRCC patients. Finally, we constructed a prognostic nomogram based on the PRS and clinicopathological characteristics, which exhibited a high accuracy and a robust predictive performance. This study highlighted the significance of trajectory differentiation of ccRCC cells and TME evolution in predicting clinical outcomes and potential immunotherapeutic responses of ccRCC patients, and the nomogram provided an intuitive and accurate method for predicting the prognosis of such patients.

To achieve the deep recovery of exhaust waste heat, a combined cooling heating and power (CCHP) dynamic exhaust low temperature waste heat coupled air source heat pump system is proposed in this paper. Aspen Plus software was used to simulate the system and analyze the effects of the recyclable waste heat of the system, the coefficient of performance (COP) of the heat pump and the impact of the primary energy utilization rate. The results showed that under the design condition, the exhaust waste heat of CCHP system was 1.22 kW, the recyclable waste heat of heat pump system was up to 1.07 kW, the exhaust waste heat recovery rate was 87.7%. The COP was up to 4.66, increased 39.5%. The primary energy utilization efficiency was increased by 3.9%. It solves the problem of heat pump evaporator frosting and poor performance of low temperature in cold regions. This study provides an important reference for the combined and efficient application of CCHP systems and heat pump units.

Privacy protection is a fundamental issue in the era of big data. For personalized privacy protection, it is necessary to measure the amount or the degree of privacy leakage. To facilitate such measurement, semantic similarities and relationships of words should be determined since the words may come from multiple sources and present themselves in as many different ways as one can imagine, an intrinsic nature of big data. WordNet has been widely used for measuring the semantic similarity of words. This paper aims at analyzing the suitability of applying WordNet to measuring the semantic similarity or relatedness of words in the field of privacy. The analysis includes an experiment designed to obtain human rating scores as the benchmark dataset and a comprehensive comparison between results from four WordNet based measures and the human rating scores. The conclusion of the analysis is that current WordNet based measures are not very suitable for privacy measurement. Therefore, this paper also provides some suggestions on possible ways of enhancing WordNet to improve the effectiveness of semantic similarity or relatedness measurement in the field of privacy to support more effective and personalized privacy protection.

The toxicity and bioavailability of single arsenic species have been widely investigated, however, the biological effects of mixed arsenic species co-existing in natural waters still remain unknown. The objective of this work was to discern the adverse effects of combined arsenite (As(III)) and dimethylarsenic acid (DMA) on diatom Nitzschia palea. The combined ecotoxicity of As(III) and DMA on N. palea was observed to be time-dependent and showed dose-effect relation. The toxicity of DMA and As(III) mixture was higher than individual DMA or As(III) when the As(III) concentration was in the range of 0.085–0.316 mg L−1. As the As(III) concentration increased from 0.487 to 0.858 mg L−1, the antagonistic effect was found, which could be due to the higher thiols contents in the thiol-containing proteins (e.g., frustulins, silaffins and other glycoproteins). The content of malondialdehyde (MDA) in the treatment of mixed arsenic species was found to be at the same level compared to the As-free control after 72 h of exposure, indicating that the co-toxicity of As(III) and DMA on diatom frustules was not significant. Furthermore, the increase of frustule formation rate in the mixture of EC50 As(III)-EC10 DMA at 72 h exposure time indicated that the damaged diatom cell walls was likely repaired gradually. The results from this study suggested that the effects of co-existed arsenic species were concentration-specific and should be considered in the risk assessment of arsenic and development of water quality criteria for the protection of aquatic ecosystems.

The registration of point cloud is important for large object measurement. A measurement method for coordinate system transformation based on robot is proposed in this paper. Firstly, for obtaining extrinsic parameters, the robot moves to three different positions to capture the images of three targets. Then the transformation matrix X between camera and tool center point (TCP) coordinate systems can be calculated by using the known parameters of robot and the extrinsic parameters, and finally the multi-view coordinate system can be transformed into robot coordinate system by the transformation matrix X. With the help of robot, the multi-view point cloud can be easily transformed into a unified coordinate system. By using robot, the measurement doesn’t need any mark. Experimental results show that the method is effective.

For fabric defect identification in the textile industry, a three-dimensional (3D) color phase shift profilometry (CPSP) method is proposed. The detecting system is mainly composed of one CCD camera and one digital-light-processing (DLP) projector. Before detection, the system should be calibrated to make sure the camera parameters. The CPSP color grating is projected to the measured fabric by DLP projector, and then it is collected by CCD camera to obtain the grating phase. The 3D measurement can be completed by the grating phase difference. In image acquisition, only invariable grating is projected to the object. In order to eliminate the interference from background light during the image acquisition, the brightness correction method is researched for improving the detection accuracy. The experimental results show that the false rate of detecting the fabric defects is 5.78%, the correct rates of detecting the fabric defects of hole and qualified fabric are both 100%, and the correct rates of detecting the fabric defect of scratch and fold are 98% and 96%, respectively. The experiment proves that the proposed method can accurately identify fabric defects.