Machinery Early Fault Detection Based on Dirichlet Process Mixture Model

© 2013 IEEE. The most commonly used single feature-based anomaly detection method for the complex machinery, such as large wind power equipment, steam turbine generator sets, and reciprocating compressors, exhibits a defect of low-alarm accuracy due to the non-stationary characteristic of the vibration signals. In order to improve the accuracy of fault detection, a novel method based on the Dirichlet process mixture model (DPMM) is proposed. First, the features of the mechanical vibration signals are used to construct the feature space of the equipment. The DPMM modeling method is then applied to self-learn the probabilistic mixture model of the feature space. The normal working condition model is used as the benchmark model. The early fault detection is realized by using a precise difference measurement method based on Kullback-Leibler divergence to calculate the difference between the real-time model and the benchmark model accurately, and by comparing the calculation result with a self-learned alarm threshold. The effectiveness and the adaptability of this novel early fault detection method are verified by comparing it to the single feature-based anomaly detection method and the Gaussian mixture model (GMM)-based early fault detection method

Climate and soil moisture content during development ofthe frst palaeosol in the southern Loess Plateau

The scientific problems concerning Quaternary soil water content and the water cycle have not been researched. This study examined the soil water content and depth of distribution of gravitational water in the south Loess Plateau during development of the first palaeosol layer (S1) by methods such as field investigation, electron microscopy, energy spectrum analysis, chemical analysis, and so on. The purpose was to reveal the climate, water balance and vegetation type at the time when S1 developed. The depth of migration of CaCO3 and Sr were 4.2 m below the upper boundary of the S1 palaeosol, and the depth of weathered loess beneath the argillic horizon was 4.0 m. Ferri‐argillans developed well in the argillic horizon and their depth of migration was 1 m below the argillic horizon. These findings suggest that the climate during the last interglacial was subtropical and humid, and the soil‐water balance was positive. Gravitational water was present to a depth of least 4.2 m from the top of S1, and the water content was adequate for tree growth. The chemical weathering index showed that this palaeosol has been moderately weathered

Effects of pulsed anodic oxide on the intermixing in InGaAs/GaAs and LnGaAs/AlGaAs quantum wells

Intermixing in InGaAs/AlGaAs quantum well structures was studied with and without an anodic oxide cap by rapid thermal annealing. Blueshifts in the photoluminescence (PL) energy were observed. Anodic oxide was demonstrated to suppress the blueshift noticeably. The suppression of the blueshift was attributed to a strain reduction.published_or_final_versio

Simulation of multilevel cell spin transfer switching in a full-Heusler alloy spin-valve nanopillar

Author name used in this publication: Shi, S. Q.2012-2013 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Research Progress of Baihe Gujin Decoction in the Treatment of Lung Cancer

Shi-hao Zhao,1 Wen-hui Wang,1 Yu-cong Liang,1 Kai-xin Zhang,1 Kuan Chen,1 Hong-ling Wang,2 Xiang-qi Wang2 1Acupuncture and Moxibustion Massage College, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China; 2Department of Oncology, Third Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, 450008, People’s Republic of ChinaCorrespondence: Xiang-qi Wang, Email [email protected]: Baihe Gujin decoction is one of the most commonly used decoction in traditional Chinese medicine for the treatment of lung cancer. It can nourish yin and moisten the lung as well as prevent phlegm from forming and stop coughing. On the one hand, Baihe Gujin decoction is characterized with extensive application, proven efficacy, a long history, and high safety. On the other hand, Baihe Gujin decoction can induce apoptosis of tumor cells, improve immune function and inhibit inflammation. The main anti-tumor components of this include kaempferol, quercetin, isorhamnetin, glycyrrhizin and β-sitosterol. Clinically, Baihe Gujin decoction can improve the adverse reactions caused by radiotherapy, chemotherapy and immunotherapy for lung cancer, enhance the quality of life of patients, and prolong their survival time. At present, there are a large number of clinical and basic researches on the treatment of lung cancer with Baihe Gujin decoction. In this paper, we mainly discussed the treatment of lung cancer with Baihe Gujin decoction through analyzing basic and clinical researches at home and abroad in the past 20 years. Through the discussion, we aimed to probe deeper into Baihe Gujin decoction for the treatment of lung cancer, thereby providing a broader idea for clinical diagnosis and treatment of lung cancer.Keywords: Baihe Gujin decoction, lung cancer, traditional Chinese medicine, basic research, clinical stud

Local structure adaptability through multi cations for oxygen redox accommodation in Li-Rich layered oxides

Stable lattice oxygen redox (l-OR) is the key enabler for achieving attainable high energy density in Li-rich layered oxide cathode materials for Li-ion batteries. However, the unique local structure response to oxygen redox in these materials, resulting in energy inefficiency and hysteresis, still remains elusive, preventing their potential applications. By combining the state-of-the-art neutron pair distribution function with crystal orbital overlap analysis, we directly observe the distinct local structure adaption originated from the potential O–O chemical bonds. The structure adaptability is optimized based on the nature of multi transition metals in our model compound Li1.2Ni0.13Mn0.54Co0.13O2, which accommodates the oxygen redox and at the same time preserves the global layered structure. These findings not only advance the understanding of l-OR, but also provide new perspectives in the rational design of high-energy-density cathode materials with reversible and stable l-OR

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Selection of Saccharomyces cerevisiae strains for efficient very high gravity bio-ethanol fermentation processes

An optimized very high gravity (VHG) glucose medium supplemented with low cost nutrient sources was used to evaluate bio-ethanol production by 11 Saccharomyces cerevisiae strains. The industrial strains PE-2 and CA1185 exhibited the best overall fermentation performance, producing an ethanol titre of 19.2% (v/v) corresponding to a batch productivity of 2.5 g l-1 h-1, while the best laboratory strain (CEN.PK 113-7D) produced 17.5% (v/v) ethanol with a productivity of 1.7 g l-1 h-1. The results presented here emphasize the biodiversity found within S. cerevisiae species and that naturally adapted strains, such as PE-2 and CA1185, are likely to play a key role in facilitating the transition from laboratory technological breakthroughs to industrialscale bio-ethanol fermentations.Fundação para a Ciência e a Tecnologia (FCT) - PTDC/BIO/66151/2006, SFRH/ BD/64776/2009, SFRH/BPD/44328/ 200

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads