A Method of Protein Model Classification and Retrieval Using Bag-of-Visual-Features

In this paper we propose a novel visual method for protein model classification and retrieval. Different from the conventional methods, the key idea of the proposed method is to extract image features of proteins and measure the visual similarity between proteins. Firstly, the multiview images are captured by vertices and planes of a given octahedron surrounding the protein. Secondly, the local features are extracted from each image of the different views by the SURF algorithm and are vector quantized into visual words using a visual codebook. Finally, KLD is employed to calculate the similarity distance between two feature vectors. Experimental results show that the proposed method has encouraging performances for protein retrieval and categorization as shown in the comparison with other methods

The Indoor Thermal Environment Simulation and Testing Validation of a Power Plant Turbine Room in Extreme Cold Area

AbstractThis paper conducts an analysis study on indoor thermal environment of a steam turbine room in power plant by CFD. Refer to a typical steam turbine room in an actual thermal power plant which has been conducted field test, the typical numerical simulation model is built including a reasonable indoor heat conditions, structural parameters and envelope architectural opening, flow boundary conditions. Indoor air temperature distribution and air velocity distribution of steam turbine room is obtained. Comparing the simulation results with the corresponding field measurement data on typical location show that two sets of results are very close. So accuracy and applicability of CFD simulations is proved. It is also proved that complete method for CFD simulations of the paper is appropriate for interior thermal environment study of typical steam turbine room and thus laid the foundation for the further studies of a large number of universal cases

Nonlinear Radon Transform Using Zernike Moment for Shape Analysis

We extend the linear Radon transform to a nonlinear space and propose a method by applying the nonlinear Radon transform to Zernike moments to extract shape descriptors. These descriptors are obtained by computing Zernike moment on the radial and angular coordinates of the pattern image's nonlinear Radon matrix. Theoretical and experimental results validate the effectiveness and the robustness of the method. The experimental results show the performance of the proposed method in the case of nonlinear space equals or outperforms that in the case of linear Radon

A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning

The identification of underground formation lithology can serve as a basis for petroleum exploration and development. This study integrates Extreme Gradient Boosting (XGBoost) with Bayesian Optimization (BO) for formation lithology identification and comprehensively evaluated the performance of the proposed classifier based on the metrics of the confusion matrix, precision, recall, F1-score and the area under the receiver operating characteristic curve (AUC). The data of this study are derived from Daniudui gas field and the Hangjinqi gas field, which includes 2153 samples with known lithology facies class with each sample having seven measured properties (well log curves), and corresponding depth. The results show that BO significantly improves parameter optimization efficiency. The AUC values of the test sets of the two gas fields are 0.968 and 0.987, respectively, indicating that the proposed method has very high generalization performance. Additionally, we compare the proposed algorithm with Gradient Tree Boosting-Differential Evolution (GTB-DE) using the same dataset. The results demonstrated that the average of precision, recall and F1 score of the proposed method are respectively 4.85%, 5.7%, 3.25% greater than GTB-ED. The proposed XGBoost-BO ensemble model can automate the procedure of lithology identification, and it may also be used in the prediction of other reservoir properties

Biotechnologies for bulk production of microalgal biomass: from mass cultivation to dried biomass acquisition

Microalgal biomass represents a sustainable bioresource for various applications, such as food, nutraceuticals, pharmaceuticals, feed, and other bio-based products. For decades, its mass production has attracted widespread attention and interest. The process of microalgal biomass production involves several techniques, mainly cultivation, harvesting, drying, and pollution control. These techniques are often designed and optimized to meet optimal growth conditions for microalgae and to produce high-quality biomass at acceptable cost. Importantly, mass production techniques are important for producing a commercial product in sufficient amounts. However, it should not be overlooked that microalgal biotechnology still faces challenges, in particular the high cost of production, the lack of knowledge about biological contaminants and the challenge of loss of active ingredients during biomass production. These issues involve the research and development of low-cost, standardized, industrial-scale production equipment and the optimization of production processes, as well as the urgent need to increase the research on biological contaminants and microalgal active ingredients. This review systematically examines the global development of microalgal biotechnology for biomass production, with emphasis on the techniques of cultivation, harvesting, drying and control of biological contaminants, and discusses the challenges and strategies to further improve quality and reduce costs. Moreover, the current status of biomass production of some biotechnologically important species has been summarized, and the importance of improving microalgae-related standards for their commercial applications is noted.ISSN:2731-365

Stable Human Hepatoma Cell Lines for Efficient Regulated Expression of Nucleoside/Nucleotide Analog Resistant and Vaccine Escape Hepatitis B Virus Variants and Woolly Monkey Hepatitis B Virus.

Hepatitis B virus (HBV) causes acute and chronic hepatitis B (CHB). Due to its error-prone replication via reverse transcription, HBV can rapidly evolve variants that escape vaccination and/or become resistant to CHB treatment with nucleoside/nucleotide analogs (NAs). This is particularly problematic for the first generation NAs lamivudine and adefovir. Though now superseded by more potent NAs, both are still widely used. Furthermore, resistance against the older NAs can contribute to cross-resistance against more advanced NAs. For lack of feasible HBV infection systems, the biology of such variants is not well understood. From the recent discovery of Na+-taurocholate cotransporting polypeptide (NTCP) as an HBV receptor new in vitro infection systems are emerging, yet access to the required large amounts of virions, in particular variants, remains a limiting factor. Stably HBV producing cell lines address both issues by allowing to study intracellular viral replication and as a permanent source of defined virions. Accordingly, we generated a panel of new tetracycline regulated TetOFF HepG2 hepatoma cell lines which produce six lamivudine and adefovir resistance-associated and two vaccine escape variants of HBV as well as the model virus woolly monkey HBV (WMHBV). The cell line-borne viruses reproduced the expected NA resistance profiles and all were equally sensitive against a non-NA drug. The new cell lines should be valuable to investigate under standardized conditions HBV resistance and cross-resistance. With titers of secreted virions reaching >3 x 10(7) viral genome equivalents per ml they should also facilitate exploitation of the new in vitro infection systems

Truncated active human matrix metalloproteinase-8 delivered by a chimeric adenovirus-hepatitis B virus vector ameliorates rat liver cirrhosis.

Liver cirrhosis is a potentially life-threatening disease caused by progressive displacement of functional hepatocytes by fibrous tissue. The underlying fibrosis is often driven by chronic infection with hepatitis B virus (HBV). Matrix metalloproteinases including MMP-8 are crucial for excess collagen degradation. In a rat model of liver cirrhosis, MMP-8 delivery by an adenovirus (Ad) vector achieved significant amelioration of fibrosis but application of Ad vectors in humans is subject to various issues, including a lack of intrinsic liver specificity.HBV is highly liver-specific and its principal suitability as liver-specific gene transfer vector is established. HBV vectors have a limited insertion capacity and are replication-defective. Conversely, in an HBV infected cell vector replication may be rescued in trans by the resident virus, allowing conditional vector amplification and spreading. Capitalizing on a resident pathogen to help in its elimination and/or in treating its pathogenic consequences would provide a novel strategy. However, resident HBV may also reduce susceptibility to HBV vector superinfection. Thus a size-compatible truncated MMP-8 (tMMP8) gene was cloned into an HBV vector which was then used to generate a chimeric Ad-HBV shuttle vector that is not subject to superinfection exclusion. Rats with thioacetamide-induced liver cirrhosis were injected with the chimera to evaluate therapeutic efficacy.Our data demonstrate that infectious HBV vector particles can be obtained via trans-complementation by wild-type virus, and that the tMMP8 HBV vector can efficiently be shuttled by an Ad vector into cirrhotic rat livers. There it exerted a comparable beneficial effect on fibrosis and hepatocyte proliferation markers as a conventional full-length MMP-8Ad vector.Though the rat cirrhosis model does not allow assessing in vivo HBV vector amplification these results advocate the further development of Ad-HBV vectors for liver-specific gene therapy, including and perhaps particularly for HBV-related disease