Isolation and identification of Lactobacillus and yeast species and their effect on the quality of fermented rice cakes

In this study, microbes were isolated from the rice slurry of a fermented rice cake to obtain lactic acid bacteria and yeast species. These species were identified using microbial physiology and gene sequence analyses. As the growth of the lactic acid bacterial strain R-2b and the yeast J-3a strains were found to be the best, a composite starter comprising these microbes was used for the preparation of fermented rice cakes. Based on single factor and orthogonal experiments, when the proportion of Lactobacillus plantarum, Saccharomyces cerevisiae, and Candida humilis was 1:3:6, the optimal fermentation conditions were addition of sugar and starter amounts of 20% and 6%, respectively, a fermentation temperature of 32 °C, and fermentation time of 8 h. The fermented rice cake with this optimum ratio had the most abundant volatile components and qualified physicochemical and microbial indexes. Additionally, the overall quality was better than that of commercially available products.     

Mechanical and thermal properties and microstructural evolution of Ta-doped Nb4AlC3

(Nb_1-xTa_x)₄AlC₃ (x = 0–0.5) ceramics were prepared by the hot press sintering method. The XRD results show that the second phase (Nb_1-xTa_x)C is formed when the Ta content increases to 25 mol%. The SEM micrographs show that (Nb_1-xTa_x)C has a core/rim structure, whose formation mechanism was also investigated. Substituting some Ta for Nb can significantly improve the mechanical properties of Nb₄AlC₃. (Nb_0.75Ta_0.25)₄AlC₃ exhibits an excellent fracture toughness of 8.3 ± 0.3 MPa m^1/2 at room temperature (RT). The highest Young's modulus (349 ± 16 GPa) and Vickers hardness (4.5 ± 0.3 GPa) at RT are exhibited by the (Nb_0.5Ta_0.5)₄AlC₃ sample, which correlate to increases of 18% and 80%, respectively, compared with those of Nb₄AlC₃. The flexural strengths of (Nb_0.5Ta_0.5)₄AlC₃ are 439 ± 18 MPa at RT and 344 ± 22 MPa at 1100 °C, which correlate to increases of 27% and 45%, respectively, compared with those of Nb₄AlC₃. The solid solution of Ta and the formation of (Nb_1-xTa_x)C are beneficial to the strengthening of Nb₄AlC₃. The coefficient of thermal expansion (CTE) increases slightly from 7.08 × 10⁻⁶ K⁻¹ for Nb₄AlC₃ to 7.24 × 10⁻⁶ K⁻¹ for (Nb_0.75Ta_0.25)₄AlC₃ at 25–1400 °C. The thermal conductivity of (Nb_0.75Ta_0.25)₄AlC₃ (28.4–29.8 W/m·K) is higher than that of Nb₄AlC₃ (18.1–21.2 W/m·K) over the whole test range (25–1000 °C). Owing to their excellent mechanical and thermal properties, Ta-doped Nb₄AlC₃ ceramics have good potential as structural materials.     

Evaluation of China's new energy vehicle policy texts with quantitative and qualitative analysis

As one of the strategic emerging industries, the new energy vehicle (NEV) industry receives strong support from the Chinese government. The Chinese government has formulated a large number of policies to promote the development of NEV industry. Evaluating and analyzing the NEV policies are of great significance for improving policy formulation. In this study, we comprehensively analyze 253 NEV policy texts by employing quantitative and qualitative methods. We present the policy instrument types and semantic structure characteristics of policy texts based on the content analysis. The advantages and disadvantages of policy texts are identified by using a quantitative evaluation model. Our results show that the most frequently used policy instrument is regulatory, and the main policy objective is the demand-pull. The policies with higher scores are more comprehensive. Three suggestions are put forward to improve NEV policies.     

Generating video animation from single still image in social media based on intelligent computing

Bringing a single still image into reality is a challenging topic in computer animation because the driven and structural information in single still image is inadequate. In this paper, we present an image animating method for enhancing single still image in social media with virtual realistic and animated motions without prior information. We imitate the interaction between the active objects in an image and their neighboring passive objects. The existing actions in the image and the virtual specified force are employed to animate the active objects. Observing that the change between two subsequent motions of the active objects derives a motion tendency, we can calculate a virtual driving force based on the motion tendency. By virtue of the virtual driving force, the stochastic motion texture is used to animate the passive objects. Finally, the convolutional neural network is employed to optimize the virtual motion animations. In this way, the proposed method produces visually natural results while guaranteeing motion harmony between active objects and passive objects. To demonstrate the applicability and rationality of virtual animation driving force, our method generates several animations from still images in Social Media.     

Simulation of police shooting stability training based on FPGA and sensors

Stability training refers to the practice, while the surface is unstable and activation stabilizer muscles of the trunk and goals, which may ignore other forms of exercise. For stability, the train network control system is caused by network latency and packet drop out of school. The current study aimed to analyze the accuracy of necessary shooting skills and check the balanced posture, stability, and rifle shooting performance bracelets. There is no burden on the body in different performance groups. No. Equivalent continuous-time model, proposed account. The train network control system model uses Romanov theory, some new analytical techniques to get in, and less conservative results. It will be completed. The effectiveness of the proposed method of numerical display. The proposed training in the correct use of architecture to shape muscle memory training interns position signal trainee lead to incorrect behavior. Students warned that the recent shooting would be suspended after the retry using the selected function when needed for phase detection of unnecessary or excessive exercise pistol. Combined with real-time biofeedback applications, it can lead to accelerated learning, training the number of shots that poverty can be reduced, thereby saving time and costs.     

某热镀锌车间腐蚀后鉴定分析与加固措施

通过对于某腐蚀环境下钢筋混凝土工业厂房的现场测试和构件受力性能的分析研究对构件的安全性能作出了合理的评价,提出了保证正常施工情况下结构的维修加固方案。     

Detecting outlier pairs in complex network based on link structure and semantic relationship

In this paper, we propose an outlier pair detection method, called LSOutPair, which discovers the vast differences between link structure and semantic relationship. LSOutPair addresses three important challenges: (1) how can we measure the target object's link similarity among multi-typed objects and multi-typed relations? (2) how can we measure the semantic similarity using the short texts? (3) how can we find the objects’ maximum differences between link structure and semantic relationship? To tackle these challenges, LSOutPair applies three main techniques: (1) two matrices are used to store link similarity and semantic similarity, (2) a k-step index algorithm, which calculates the term weighting for each object, (3) applying the linear transformation of Frobenius norm to matrices can obtain the top-K outlier pairs. LSOutPair considers link and semantics in complex network simultaneously, which is a new attempt in data mining. Substantial experiments show that LSOutPair is very effective for outlier pair detection.     

Fault Detection and Diagnosis in dynamic systems using Weightless Neural Networks

This work examines Fault Detection and Diagnosis (FDD) based on Weightless Neural Networks (WNN) with applications in univariate and multivariate dynamic systems. WNN use neurons based on RAM (Random Access Memory) devices. These networks use fast and flexible learning algorithms, which provide accurate and consistent results, without the need for residual generation or network retraining, and therefore they have great potential use for pattern recognition and classification (Ludermir, Carvalho, Braga, de Souto, 1999). The proposed system firstly executes the selection of attributes (in the multivariable case) and does the time series mapping of the data. In the intermediate stage, the WNN performs the detection and diagnosis per class. The network outputs are then passed through a clustering filter in the final stage of the system, if a diagnosis per fault groups is necessary. The system was tested with two case studies: one was an actual application for the temperature monitoring of a sales gas compressor in a natural gas processing unit; and the other one uses simulated data for an industrial plant, known in the literature as “Tennessee Eastman Process”. The results show the efficiency of the proposed systems for FDD with classification accuracies of up to 98.78% and 99.47% for the respective applications.     

Combining heterogeneous sources in an interactive multimedia content retrieval model

Interactive multimodal information retrieval systems (IMIR) increase the capabilities of traditional search systems, by adding the ability to retrieve information of different types (modes) and from different sources. This article describes a formal model for interactive multimodal information retrieval. This model includes formal and widespread definitions of each component of an IMIR system. A use case that focuses on information retrieval regarding sports validates the model, by developing a prototype that implements a subset of the features of the model. Adaptive techniques applied to the retrieval functionality of IMIR systems have been defined by analysing past interactions using decision trees, neural networks, and clustering techniques. This model includes a strategy for selecting sources and combining the results obtained from every source. After modifying the strategy of the prototype for selecting sources, the system is re-evaluated using classification techniques. This evaluation compares the normalised discounted cumulative gain (NDCG) measure obtained using two different approaches: the multimodal system using a baseline strategy based on predefined rules as a source selection strategy, and the same multimodal system with the functionality adapted by past user interactions. In the adapted system, a final value of 81,54% was obtained for the NDCG.