The Coal Mine Accident Causation Model Based on the Hazard Theory

AbstractOn the basis of the summary of the existing research, first of all, the essential factors of coal mine accidents was differentiated and analyzed, and the technology equipment defects was believed to be the essential reasons that affect the coal mine safety. And then using the hazard theory the accident causation in coal mine production system has been divided, and it was believed that coal mine hazard sources consisted of inherent hazards, technology equipment defects and safety management misconducts. On this basis, the coal mine accident causation model on a combination of hazard theory and energy accidental releasing theory was established. Finally, this model was used to analyze the roof-fall accident of Baishui Coal Mine

N 2,N 2′-Bis(3-nitro­benzyl­idene)pyridine-2,6-dicarbohydrazide dimethyl­formamide disolvate trihydrate

In the title compound, C21H15N7O6·2C3H7NO·3H2O, the N 2,N 2′-bis­(3-nitro­benzyl­idene)pyridine-2,6-dicarbohydrazide and one water mol­ecule are located on a twofold rotation axis. The mol­ecules are connected by hydrogen bonds. One dimethylformamide molecule is disordered over two positions; the site occupancy factors are ca 0.8 and 0.2

Activation of the hedgehog pathway in chronic myelogeneous leukemia patients

<p>Abstract</p> <p>Background</p> <p>Hedgehog (Hh) signaling pathway is involved in regulation of many tissues development and oncogenesis. Recently, Hh signaling has been identified as a required functional pathway for leukemia stem cells(LSCs), and loss of this pathway impairs leukemia progression.</p> <p>Objectives</p> <p>The aim of this study was to determine the expression of Hedgehog signaling molecules in Chronic Myelogeneous Leukemia (CML) patients and normal people by semiquantitative polymerase chain reaction (PCR) and to correlate mRNA expression to patients' clinical data.</p> <p>Results</p> <p>Here, we showed that Sonic hedgehog (Shh), Smoothened (Smo), and Gli1 genes of Hh signaling were significantly upregulated in CML patients when compared with normal people (P < 0.001). The levels of Shh, Smo mRNA in chronic phase of CML patients were obviously lower than that in blast crisis (p < 0.05). There were no significant differences of Shh, Ptch1, Smo, Gli1 mRNA expression found when comparing CML patients of chronic phase(CP) with imatinib(IM) treated or not(p > 0.05).</p> <p>Conclusions</p> <p>These findings suggested that activation of the Hh pathway maybe associated with CML progression. Treatment of CML with imatinib, a selective inhibitor of the BCR-ABL tyrosine kinase inhibitor, has no significant influence on the inhibition of Hh pathway of CML-CP patients.</p

Pore structure characteristics of middle and low rank coals and their influence on gas desorption characteristics

The pore structure of coal is an important factor affecting gas storage and migration. In order to further study the gas desorption characteristics of low and medium metamorphic coals, 6 sets of coal samples from the Fukang mining area were selected for mercury intrusion and gas desorption experiment. Mercury intrusion and extrusion curves of coal samples were drawed, the pore structure characteristics of each pore segment were counted, the gas desorption curve was drawed, and the pore morphology, pore volume, pore specific surface area and volume fractal dimension of coal and their influence on the gas desorption capacity and desorption rate were analyzed. The results show that there are different proportions of open pores in coal samples. Macropores are mainly composed of open pores, the middle and small pores are mainly composed of semi-closed pores, and the micropores are mainly composed of closed pores. In addiction, the total pore volume are mainly contributed by micropores and macropores, and micropores contributes the most to the total specific surface area. By drawing the gas desorption curve and the desorption rate scatter diagram, it is found that the gas desorption amount increases rapidly with the desorption time and then tends to a stable value, and then the fitting finds that the gas desorption curve of middle and low rank coal can be expressed by 1/Q=m/t0.75+n, the degree of fitting is above 0.995, where m is a parameter related to the gas desorption rate, n is a parameter related to the desorption volume constant,and the coefficient of 0.75 may be related to the degree of coal metamorphism, and the desorption curves with different degrees of metamorphism can be analyzed in the later stage. And the desorption rate decreases exponentially with the desorption time. Fitting the pore structure characteristics of different pore sizes with the desorption characteristic parameters, it is found that the gas in the macropores is preferentially desorbed in the initial stage of desorption. As the pore size decreases, the priority rate gradually decreases. The fractal dimension of mesopores and macropores is between 2.879 1−2.991 5, which has obvious fractal characteristics. It is proposed that the initial desorption velocity and fractal dimension show a significant positive correlation. The relationship between n value and fractal dimension is not obvious

Nonparametric conditional autoregressive expectile model via neural network with applications to estimating financial risk

The parametric conditional autoregressive expectiles (CARE) models have been developed by [1] to estimate expectiles that can be used to assess value at risk (VaR) and expected shortfall (ES). The challenge lies in parametric CARE modelling is speci cation of a parametric form. To avoid any model misspeci cation, we propose a nonparametric CARE model via neural network. The nonparametric CARE model can be estimated by a classical gradient based nonlinear optimization algorithm. We then apply the nonparametric CARE model to estimating VaR and ES of six stock indices. Empirical results for the new model is competitive with those classical models and parametric CARE models.This work was supported by the National Natural Science Foundation of PR China (71490725, 71071087, 71101134), the National Social Science Foundation of PR China (15BJY008) and the Humanity and Social Science Foundation of Ministry of Education of PR China (No. 14YJA790015)

Two novel hierarchical homogeneous nanoarchitectures of TiO2 nanorods branched and P25-coated TiO2 nanotube arrays and their photocurrent performances

We report here for the first time the synthesis of two novel hierarchical homogeneous nanoarchitectures of TiO2 nanorods branched TiO2 nanotube arrays (BTs) and P25-coated TiO2 nanotube arrays (PCTs) using two-step method including electrochemical anodization and hydrothermal modification process. Then the photocurrent densities versus applied potentials of BTs, PCTs, and pure TiO2 nanotube arrays (TNTAs) were investigated as well. Interestingly, at -0.11 V and under the same illumination condition, the photocurrent densities of BTs and PCTs show more than 1.5 and 1 times higher than that of pure TNTAs, respectively, which can be mainly attributed to significant improvement of the light-absorbing and charge-harvesting efficiency resulting from both larger and rougher surface areas of BTs and PCTs. Furthermore, these dramatic improvements suggest that BTs and PCTs will achieve better photoelectric conversion efficiency and become the promising candidates for applications in DSSCs, sensors, and photocatalysis

Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response

Publicly available data can potentially examine the relationship between environmental exposure and public health, however, it has not yet been widely applied. Arsenic is of environmental concern, and previous studies mathematically parameterized exposure duration to create a link between duration of exposure and increase in risk. However, since the dose metric emerging from exposure duration is not a linear or explicit variable, it is difficult to address the effects of exposure duration simply by using mathematical functions. To relate cumulative dose metric to public health requires a lifetime physiologically-based pharmacokinetic (PBPK) model, yet this model is not available at a population level. In this study, the data from the U.S. total diet study (TDS, 2006–2011) was employed to assess exposure: daily dietary intakes for total arsenic (tAs) and inorganic arsenic (iAs) were estimated to be 0.15 and 0.028 μg/kg/day, respectively. Meanwhile, using National Health and Nutrition Examination Survey (NHANES, 2011–2012) data, the fraction of urinary As(III) levels (geometric mean: 0.31 μg/L) in tAs (geometric mean: 7.75 μg/L) was firstly reported to be approximately 4%. Together with Bayesian technique, the assessed exposure and urinary As(III) concentration were input to successfully optimize a lifetime population PBPK model. Finally, this optimized PBPK model was used to derive an oral reference dose (Rfd) of 0.8 μg/kg/day for iAs exposure. Our study also suggests the previous approach (by using mathematical functions to account for exposure duration) may result in a conservative Rfd estimation

SpeechMirror: A Multimodal Visual Analytics System for Personalized Reflection of Online Public Speaking Effectiveness

As communications are increasingly taking place virtually, the ability to present well online is becoming an indispensable skill. Online speakers are facing unique challenges in engaging with remote audiences. However, there has been a lack of evidence-based analytical systems for people to comprehensively evaluate online speeches and further discover possibilities for improvement. This paper introduces SpeechMirror, a visual analytics system facilitating reflection on a speech based on insights from a collection of online speeches. The system estimates the impact of different speech techniques on effectiveness and applies them to a speech to give users awareness of the performance of speech techniques. A similarity recommendation approach based on speech factors or script content supports guided exploration to expand knowledge of presentation evidence and accelerate the discovery of speech delivery possibilities. SpeechMirror provides intuitive visualizations and interactions for users to understand speech factors. Among them, SpeechTwin, a novel multimodal visual summary of speech, supports rapid understanding of critical speech factors and comparison of different speech samples, and SpeechPlayer augments the speech video by integrating visualization of the speaker's body language with interaction, for focused analysis. The system utilizes visualizations suited to the distinct nature of different speech factors for user comprehension. The proposed system and visualization techniques were evaluated with domain experts and amateurs, demonstrating usability for users with low visualization literacy and its efficacy in assisting users to develop insights for potential improvement.Comment: Main paper (11 pages, 6 figures) and Supplemental document (11 pages, 11 figures). Accepted by VIS 202

SketchGAN: Joint sketch completion and recognition with generative adversarial network

Hand-drawn sketch recognition is a fundamental problem in computer vision, widely used in sketch-based image and video retrieval, editing, and reorganization. Previous methods often assume that a complete sketch is used as input; however, hand-drawn sketches in common application scenarios are often incomplete, which makes sketch recognition a challenging problem. In this paper, we propose SketchGAN, a new generative adversarial network (GAN) based approach that jointly completes and recognizes a sketch, boosting the performance of both tasks. Specifically, we use a cascade Encode-Decoder network to complete the input sketch in an iterative manner, and employ an auxiliary sketch recognition task to recognize the completed sketch. Experiments on the Sketchy database benchmark demonstrate that our joint learning approach achieves competitive sketch completion and recognition performance compared with the state-of-the-art methods. Further experiments using several sketch-based applications also validate the performance of our method