Learning neural trans-dimensional random field language models with noise-contrastive estimation

Trans-dimensional random field language models (TRF LMs) where sentences are modeled as a collection of random fields, have shown close performance with LSTM LMs in speech recognition and are computationally more efficient in inference. However, the training efficiency of neural TRF LMs is not satisfactory, which limits the scalability of TRF LMs on large training corpus. In this paper, several techniques on both model formulation and parameter estimation are proposed to improve the training efficiency and the performance of neural TRF LMs. First, TRFs are reformulated in the form of exponential tilting of a reference distribution. Second, noise-contrastive estimation (NCE) is introduced to jointly estimate the model parameters and normalization constants. Third, we extend the neural TRF LMs by marrying the deep convolutional neural network (CNN) and the bidirectional LSTM into the potential function to extract the deep hierarchical features and bidirectionally sequential features. Utilizing all the above techniques enables the successful and efficient training of neural TRF LMs on a 40x larger training set with only 1/3 training time and further reduces the WER with relative reduction of 4.7% on top of a strong LSTM LM baseline.Comment: 5 pages and 2 figure

An Optical Model for Translucent Volume Rendering and Its Implementation Using the Preintegrated Shear-Warp Algorithm

In order to efficiently and effectively reconstruct 3D medical images and clearly display the detailed information of inner structures and the inner hidden interfaces between different media, an Improved Volume Rendering Optical Model (IVROM) for medical translucent volume rendering and its implementation using the preintegrated Shear-Warp Volume Rendering algorithm are proposed in this paper, which can be readily applied on a commodity PC. Based on the classical absorption and emission model, effects of volumetric shadows and direct and indirect scattering are also considered in the proposed model IVROM. Moreover, the implementation of the Improved Translucent Volume Rendering Method (ITVRM) integrating the IVROM model, Shear-Warp and preintegrated volume rendering algorithm is described, in which the aliasing and staircase effects resulting from under-sampling in Shear-Warp, are avoided by the preintegrated volume rendering technique. This study demonstrates the superiority of the proposed method

Institutional Investors, Earnings Management And Mispricing Of Accruals: Evidence From China

This study examines the role of institutional investors in the pricing of normal accruals and discretionary accruals using the firms listed in the Chinese A-share Market. The results show that significant overpricing of discretionary accruals exists for individual investors and institutional investors, suggesting that they are both misled by the earnings management, while institutional investors are associated with significantly less overpricing. With respect to normal accruals, we find there is no evidence that institutional investors misprice normal accruals, while the individual investors overprice normal accruals. Our results suggest that institutional investors’ superiority in mitigating the mispricing of total accruals is mainly due to their accurate pricing of normal accruals, and the reason why institutional investors cannot fully eliminate mispricing of accruals is that they are partly misled by earnings management

Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts

Single Point Incremental Forming (SPIF) is a relatively new process that has been recently used to manufacture medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. In this study, a set of basic geometric shapes were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case. The predicted deviations show a reasonable match with the actual formed shape and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants

LITHIUM ISOTOPIC CONSTRAINTS ON THE ORIGIN OF I- AND A-TYPE GRANITES FROM EAST JUNGGAR (NW CHINA) OF THE CENTRAL ASIAN OROGENIC BELT: IMPLICATIONS FOR LI ISOTOPIC FRACTIONATION DURING CRUSTAL ANATEXIS

Though Li isotope fractionation during mantle melting and differentiation of basaltic melts have been proved insignificant, Li isotopic systems during crustal processes remain unclear. To study this, we report combined petrological, Nd-Sr and Li isotopic data for the late Paleozoic coexisting I- and A-type granites in the East Junggar orogen of the Central Asian Orogenic Belt. The granites were formed responding to underplating of mafic magmas in the lower crust in a postcollisional, extensional regime, and intruded into the Paleozoic foldbelts that formed due to extensive oceanic subduction-accretion processes.Though Li isotope fractionation during mantle melting and differentiation of basaltic melts have been proved insignificant, Li isotopic systems during crustal processes remain unclear. To study this, we report combined petrological, Nd-Sr and Li isotopic data for the late Paleozoic coexisting I- and A-type granites in the East Junggar orogen of the Central Asian Orogenic Belt. The granites were formed responding to underplating of mafic magmas in the lower crust in a postcollisional, extensional regime, and intruded into the Paleozoic foldbelts that formed due to extensive oceanic subduction-accretion processes

Effects of Danqidihuang Granules on glucolipid metabolism in insulin-resistant rats

AbstractObjectiveTo explore whether the insulin resistance (IR) model could be established through feeding Sprague-Dawley (SD) rats high-sugar and high-fat diets and to further observe the preventive and treatment effects of different doses of Danqidihuang Granules in rats.MethodsThirty-two SD rats were divided randomly into control group A (given regular feed), model group B (food high in sugar and fat), intervention group C (food high in sugar and fat as well as regular doses of Danqidihuang Granules), and intervention group D (food high in sugar and fat as well as double doses of Danqidihuang Granules). The interventions were for 8 weeks. Motion, change in color, body weight, and food intake, as well as plasma lipids (including low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), total cholesterol (TC) and triglyceride (TG), fasting blood glucose (FBG), fasting insulin (FINs) levels, insulin sensitivity index (ISI), and insulin resistance index (HOMO-IR) were observed.ResultsAt the end of the second week of the experiment, the appetite and activities of rats in groups B, C and D decreased significantly compared with group A. The fur of the rats in those three groups was curly. After the fourth week, the activities, food intake and color of rats in group B were worse than those in groups C and D, but there were no significant differences in weight (P>0.05). Compared with group A, LDL-C, TC, FBG and HOMO-IR in model group B were increased significantly (P<0.05), whereas the FINs and ISI increased obviously (P<0.05). The levels of LDL-C and TC in group D was decreased obviously compared with those in group C, and HOMO-IR in group D was less than that in group B (P<0.05).ConclusionsDanqidihuang Granules helped to prevent and improved the insulin resistance of rats