Modal Analysis and an Experimental Study Into a Marine Gearbox Featuring Confluence Transmission

An approach to calculating vibration modal characteristics of a marine gear system featuring confluence transmission based on the theoretical and the experimental modal analysis is given in view of the fact that it is difficult to accurately determine the modal data of the system because of its complex vibration mechanism. Firstly, a dynamic finite element model of a coupled gear-rotor-bearing-housing system is developed by combining the gearbox transmission model with the gearbox housing model using the modal parameter identification data. Then, the modal frequency and the mode of vibration can be obtained. In fact, the proposed model can provide a faster approach to analysing the mode of the gear system vibration. Finally, experimental testing of the mode of vibration is performed on the experimental prototype to verify the rationality of the theoretical analysis. A comparison of the two sets of results shows that the experimental results are in good agreement with the computational results, with a maximum error of 6.3%

Characterization of ultra-deeply buried middle Triassic Leikoupo marine carbonate petroleum system (!) in the Western Sichuan depression, China

Ultra-deeply buried (>5000 m) marine carbonate reservoirs have gradually become important exploration targets. This research focuses on providing an understanding of the basic elements of the ultra-deeply buried Middle Triassic Leikoupo marine carbonate petroleum system within the Western Sichuan Depression, China. Comprehensive analyses of organic geochemistry, natural gas, and C–H–He–Ne–Ar isotope compositions suggest that the reservoir is charged with compound gases from four source rock units including the Permian Longtan, Middle Triassic Leikoupo, Late Triassic Maantang and Xiaotangzi formations. Approximately a 50-m thick outcrop and 100-m length of drilling cores were examined in detail, and 108 samples were collected from six different exploration wells in order to conduct petrographic and petrophysical analyses. Thin-section and scanning electron microscope (SEM) observations, helium porosity and permeability measurements, mercury injection capillary pressure (MICP) analysis, and wire-line logging (5,500–6,900 m) indicate that the reservoir lithologies include argillaceous algal limestones, dolograinstones, crystalline dolostones, and microbially-derived stromatolitic and thrombolitic dolostones. Reservoir properties exhibit extreme heterogeneity due to different paleogeographic environmental controls and mutual interactions between constructive (e.g., epigenetic paleo-karstification, burial dissolution, structural movement, pressure-solution and dolomitization) and destructive (e.g., physical/chemical compaction, cementation, infilling, recrystallization, and replacement) diagenetic processes. An unconformity-related epigenetic karstification zone was identified in the uppermost fourth member of the Leikoupo Formation, which has developed secondary solution-enhanced pores, vugs, and holes that resulted in higher porosity (1.8–14.2%) and permeability (0.2–7.7 mD). The homogeneity and tightness of the reservoir increases with depth below the unconformity, and it is characterized by primary intergranular and intracrystalline pores, solution pores, fractures, stylolites, and micropores with a lower helium porosity (0.6–4.1%) and permeability (0.003–125.2 mD). Regional seals consist of the Late Triassic Xujiahe Formation, comprised of ~300 m of mudstones that are overlain by ~5,000-m thick of Jurassic to Quaternary continental argillaceous overburden rocks. Effective traps are dominated by a combination of structural-stratigraphic types. Paleo- reservoir crude oil cracking, wet-gases, and dry-gases from three successive hydrocarbon generation processes supplied the sufficient hydrocarbon resources. The homogenization temperatures of the hydrocarbon-associated aqueous fluid inclusions range from 98–130 °C and 130–171 °C, which suggests hydrocarbon charging occurred between 220–170 Ma and 130–90 Ma, respectively. One-dimensional basin evolution models combined with structural geologic and seismic profiles across wells PZ1-XQS1-CK1-XCS1-TS1 show that hydrocarbon migration and entrapment mainly occurred via the unconformity and interconnected fault-fracture networks with migration and charging driven by formation overpressure, abnormal fluid flow pressure, and buoyancy forces during the Indosinian and Yanshanian orogenies, with experiencing additional transformation occurring during the Himalayan orogeny. The predicted estimated reserves reached ~300 × 109 m3. The results provide excellent scientific implications for similar sedimentary basin studies, it is believed that abundant analogous deeply buried marine carbonate hydrocarbon resources yet to be discovered in China and elsewhere worldwide in the near future

QSAR and Classification Study on Prediction of Acute Oral Toxicity of N-Nitroso Compounds

To better understand the mechanism of in vivo toxicity of N-nitroso compounds (NNCs), the toxicity data of 80 NNCs related to their rat acute oral toxicity data (50% lethal dose concentration, LD50) were used to establish quantitative structure-activity relationship (QSAR) and classification models. Quantum chemistry methods calculated descriptors and Dragon descriptors were combined to describe the molecular information of all compounds. Genetic algorithm (GA) and multiple linear regression (MLR) analyses were combined to develop QSAR models. Fingerprints and machine learning methods were used to establish classification models. The quality and predictive performance of all established models were evaluated by internal and external validation techniques. The best GA-MLR-based QSAR model containing eight molecular descriptors was obtained with Q2loo = 0.7533, R2 = 0.8071, Q2ext = 0.7041 and R2ext = 0.7195. The results derived from QSAR studies showed that the acute oral toxicity of NNCs mainly depends on three factors, namely, the polarizability, the ionization potential (IP) and the presence/absence and frequency of C–O bond. For classification studies, the best model was obtained using the MACCS keys fingerprint combined with artificial neural network (ANN) algorithm. The classification models suggested that several representative substructures, including nitrile, hetero N nonbasic, alkylchloride and amine-containing fragments are main contributors for the high toxicity of NNCs. Overall, the developed QSAR and classification models of the rat acute oral toxicity of NNCs showed satisfying predictive abilities. The results provide an insight into the understanding of the toxicity mechanism of NNCs in vivo, which might be used for a preliminary assessment of NNCs toxicity to mammals

Effective multi-label active learning for text classification

Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical when a very large amount of data is needed for training multi-label text classifiers. To minimize the human-labeling efforts, we propose a novel multi-label active learning ap-proach which can reduce the required labeled data with-out sacrificing the classification accuracy. Traditional active learning algorithms can only handle single-label problems, that is, each data is restricted to have one label. Our ap-proach takes into account the multi-label information, and aims to label data which can optimize the expected loss re-duction. Specifically, the model loss is approximated by the size of version space, and we optimize the reduction rate of the size of version space with Support Vector Machines (SVM). Furthermore, we design an effective method to pre-dict possible labels for each unlabeled data point, and ap-proximate the expected loss by summing up losses on all labels according to the most confident result of label pre-diction. Experiments on seven real-world data sets (all are publicly available) demonstrate that our approach can ob-tain promising classification result with much fewer labeled data than state-of-the-art methods

Tumor Energy Metabolism and Potential of 3-Bromopyruvate as an Inhibitor of Aerobic Glycolysis: Implications in Tumor Treatment

Tumor formation and growth depend on various biological metabolism processes that are distinctly different with normal tissues. Abnormal energy metabolism is one of the typical characteristics of tumors. It has been proven that most tumor cells highly rely on aerobic glycolysis to obtain energy rather than mitochondrial oxidative phosphorylation (OXPHOS) even in the presence of oxygen, a phenomenon called “Warburg effect”. Thus, inhibition of aerobic glycolysis becomes an attractive strategy to specifically kill tumor cells, while normal cells remain unaffected. In recent years, a small molecule alkylating agent, 3-bromopyruvate (3-BrPA), being an effective glycolytic inhibitor, has shown great potential as a promising antitumor drug. Not only it targets glycolysis process, but also inhibits mitochondrial OXPHOS in tumor cells. Excellent antitumor effects of 3-BrPA were observed in cultured cells and tumor-bearing animal models. In this review, we described the energy metabolic pathways of tumor cells, mechanism of action and cellular targets of 3-BrPA, antitumor effects, and the underlying mechanism of 3-BrPA alone or in combination with other antitumor drugs (e.g., cisplatin, doxorubicin, daunorubicin, 5-fluorouracil, etc.) in vitro and in vivo. In addition, few human case studies of 3-BrPA were also involved. Finally, the novel chemotherapeutic strategies of 3-BrPA, including wafer, liposomal nanoparticle, aerosol, and conjugate formulations, were also discussed for future clinical application

A Hybrid Heuristic Algorithm for Ship Block Construction Space Scheduling Problem

Ship block construction space is an important bottleneck resource in the process of shipbuilding, so the production scheduling optimization is a key technology to improve the efficiency of shipbuilding. With respect to ship block construction space scheduling problem, a hybrid heuristic algorithm is proposed in this paper. Firstly, Bottom-Left-Fill (BLF) process is introduced. Next, an initial solution is obtained by guiding the sorting process with corners. Then on the basis of the initial solution, the simulated annealing arithmetic (SA) is used to improve the solution by offering a possibility to accept worse neighbor solutions in order to escape from local optimum. Finally, the simulation experiments are conducted to verify the effectiveness of the algorithm

Metabolic Activation and Carcinogenesis of Tobacco-Specific Nitrosamine N’-Nitrosonornicotine (NNN): A Density Function Theory and Molecular Docking Study

N’-nitrosonornicotine (NNN) is one of the tobacco-specific nitrosamines (TSNAs) that exists widely in smoke and smokeless tobacco products. NNN can induce tumors in various laboratory animal models and has been identified by International Agency for Research on Cancer (IARC) as a human carcinogen. Metabolic activation of NNN is primarily initiated by cytochrome P450 enzymes (CYP450s) via 2′-hydroxylation or 5′-hydroxylation. Subsequently, the hydroxylating intermediates undergo spontaneous decomposition to generate diazohydroxides, which can be further converted to alkyldiazonium ions, followed by attacking DNA to form various DNA damages, such as pyridyloxobutyl (POB)-DNA adducts and pyridyl-N-pyrrolidinyl (py-py)-DNA adducts. If not repaired correctly, these lesions would lead to tumor formation. In the present study, we performed density functional theory (DFT) computations and molecular docking studies to understand the mechanism of metabolic activation and carcinogenesis of NNN. DFT calculations were performed to explore the 2′- or 5′- hydroxylation reaction of (R)-NNN and (S)-NNN. The results indicated that NNN catalyzed by the ferric porphyrin (Compound I, Cpd I) at the active center of CYP450 included two steps, hydrogen abstraction and rebound reactions. The free energy barriers of the 2′- and 5′-hydroxylation of NNN are 9.82/8.44 kcal/mol (R/S) and 7.99/9.19 kcal/mol (R/S), respectively, suggesting that the 2′-(S) and 5′-(R) pathways have a slight advantage. The free energy barriers of the decomposition occurred at the 2′-position and 5′-position of NNN are 18.04/18.02 kcal/mol (R/S) and 18.33/19.53 kcal/mol (R/S), respectively. Moreover, we calculated the alkylation reactions occurred at ten DNA base sites induced by the 2′-hydroxylation product of NNN, generating the free energy barriers ranging from 0.86 to 4.72 kcal/mol, which indicated that these reactions occurred easily. The docking study showed that (S)-NNN had better affinity with CYP450s than that of (R)-NNN, which was consistent with the experimental results. Overall, the combined results of the DFT calculations and the docking obtained in this study provide an insight into the understanding of the carcinogenesis of NNN and other TSNAs

Calcium-silicate mesoporous nanoparticles loaded with chlorhexidine for both anti- Enterococcus faecalis and mineralization properties

Abstract Background In infected periapical tissues, Enterococcus faecalis is one of the most common dominant bacteria. Chlorhexidine has been proved to show strong antibacterial ability against E. faecalis but is ineffective in promoting mineralization for tissues around root apex. Mesoporous calcium-silicate nanoparticles are newly synthesized biomaterials with excellent ability to promote mineralization and carry-release bioactive molecules in a controlled manner. In this study, mesoporous calcium-silicate nanoparticles were functionalized with chlorhexidine and their releasing profile, antibacterial ability, effect on cell proliferation and in vitro mineralization property were evaluated. Results The chlorhexidine was successfully incorporated into mesoporous calcium-silicate nanoparticles by a mixing-coupling method. The new material could release chlorhexidine as well as Ca2+ and SiO3 2− in a sustained manner with an alkaline pH value under different conditions. The antimicrobial ability against planktonic E. faecalis was dramatically improved after chlorhexidine incorporation. The nanoparticles with chlorhexidine showed no negative effect on cell proliferation with low concentrations. On dentin slices, the new synthesized material demonstrated a similar inhibitory effect on E. faecalis as the chlorhexidine. After being immersed in SBF for 9 days, numerous apatite crystals could be observed on surfaces of the material tablets. Conclusions Mesoporous calcium-silicate nanoparticles loaded with chlorhexidine exhibited release of ions and chlorhexidine, low cytotoxicity, excellent antibacterial ability and in vitro mineralization. This material could be developed into a new effective intra-canal medication in dentistry or a new bone defect filling material for infected bone defects