Jointly Modeling Embedding and Translation to Bridge Video and Language

Automatically describing video content with natural language is a fundamental challenge of multimedia. Recurrent Neural Networks (RNN), which models sequence dynamics, has attracted increasing attention on visual interpretation. However, most existing approaches generate a word locally with given previous words and the visual content, while the relationship between sentence semantics and visual content is not holistically exploited. As a result, the generated sentences may be contextually correct but the semantics (e.g., subjects, verbs or objects) are not true. This paper presents a novel unified framework, named Long Short-Term Memory with visual-semantic Embedding (LSTM-E), which can simultaneously explore the learning of LSTM and visual-semantic embedding. The former aims to locally maximize the probability of generating the next word given previous words and visual content, while the latter is to create a visual-semantic embedding space for enforcing the relationship between the semantics of the entire sentence and visual content. Our proposed LSTM-E consists of three components: a 2-D and/or 3-D deep convolutional neural networks for learning powerful video representation, a deep RNN for generating sentences, and a joint embedding model for exploring the relationships between visual content and sentence semantics. The experiments on YouTube2Text dataset show that our proposed LSTM-E achieves to-date the best reported performance in generating natural sentences: 45.3% and 31.0% in terms of BLEU@4 and METEOR, respectively. We also demonstrate that LSTM-E is superior in predicting Subject-Verb-Object (SVO) triplets to several state-of-the-art techniques

Identification of protein-RNA interaction sites using the information of spatial adjacent residues

<p>Abstract</p> <p>Background</p> <p>Protein-RNA interactions play an important role in numbers of fundamental cellular processes such as RNA splicing, transport and translation, protein synthesis and certain RNA-mediated enzymatic processes. The more knowledge of Protein-RNA recognition can not only help to understand the regulatory mechanism, the site-directed mutagenesis and regulation of RNA–protein complexes in biological systems, but also have a vitally effecting for rational drug design.</p> <p>Results</p> <p>Based on the information of spatial adjacent residues, novel feature extraction methods were proposed to predict protein-RNA interaction sites with SVM-KNN classifier. The total accuracies of spatial adjacent residue profile feature and spatial adjacent residues weighted accessibility solvent area feature are 78%, 67.07% respectively in 5-fold cross-validation test, which are 1.4%, 3.79% higher than that of sequence neighbour residue profile feature and sequence neighbour residue accessibility solvent area feature.</p> <p>Conclusions</p> <p>The results indicate that the performance of feature extraction method using the spatial adjacent information is superior to the sequence neighbour information approach. The performance of SVM-KNN classifier is little better than that of SVM. The feature extraction method of spatial adjacent information with SVM-KNN is very effective for identifying protein-RNA interaction sites and may at least play a complimentary role to the existing methods.</p

Novel Wideband Metallic Patch Antennas with Low Profile

Two planar metallic patch (MP) antennas with low profiles are investigated and compared in this paper. The MP of each antenna consists of metallic patch cells and it is centrally fed by a rectangular slot. Two modes with close resonance frequencies are excited, providing a quite wide bandwidth. The antenna principle is explained clearly through a parametric study. Simulated and measured results show that the MP antennas with profile of 0.06λ0 can obtain a 10 dB impedance bandwidth of ~32% and an average gain of ~10 dBi

Hydrogen Generation from Al-NiCl2/NaBH4 Mixture Affected by Lanthanum Metal

The effect of La on Al/NaBH4 hydrolysis was elaborated in the present paper. Hydrogen generation amount increases but hydrogen generation rate decreases with La content increasing. There is an optimized composition that Al-15 wt% La-5 wt% NiCl2/NaBH4 mixture (Al-15 wt% La-5 wt% NiCl2/NaBH4 weight ratio, 1 : 3) has 126 mL g−1 min−1 maximum hydrogen generation rate and 1764 mL g−1 hydrogen generation amount within 60 min. The efficiency is 88%. Combined with NiCl2, La has great effect on NaBH4 hydrolysis but has little effect on Al hydrolysis. Increasing La content is helpful to decrease the particle size of Al-La-NiCl2 in the milling process, which induces that the hydrolysis byproduct Ni2B is highly distributed into Al(OH)3 and the catalytic reactivity of Ni2B/Al(OH)3 is increased therefore. But hydrolysis byproduct La(OH)3 deposits on Al surface and leads to some side effect. The Al-La-NiCl2/NaBH4 mixture has good stability in low temperature and its hydrolytic performance can be improved with increasing global temperature. Therefore, the mixture has good safety and can be applied as on board hydrogen generation material

Dimension Increase via Hierarchical Hydrogen Bonding from Simple Pincer-like Mononuclear complexes

A tetradentate symmetric ligand bearing both coordination and hydrogen bonding sites, N1,N3-bis(1-(1H-benzimidazol-2-yl)-ethylidene)propane-1,3-diamine (H2bbepd) was utilized to synthesize a series of transition metal complexes, namely [Co(H2bbepd)(H2O)2]·2ClO4 (1), [Cu(H2bbepd)(OTs-)]·OTs- (2),[Cu(bbepd)(CH3OH)] (3), [Cd(H2bbepd)(NO3)2]·CH3OH (4), [Cd(H2bbepd)(CH3OH)Cl]·Cl (5), and [Cd(bbepd)(CH3OH)2] (6). These complexes show similar discrete pincer-like coordination units, possessing different arrangements of hydrogen bonding donor and acceptor sites. With or without the aid of uncoordinated anions and solvent molecules, such mononuclear units have been effectively involved in the construction of hierarchical hydrogen bonding assemblies (successively via level I and level II), leading to discrete binuclear ring (complex 2), one-dimensional chain or ribbon (complexes 3, 4 and 6) and two-dimensional layer (complexes 1 and 5) aggregates

Effects of Erxian decoction, a Chinese medicinal formulation, on serum lipid profile in a rat model of menopause

<p>Abstract</p> <p>Background</p> <p>The prevalence and risk of cardiovascular disease increase after menopause in correlation with the progression of abnormality in the serum lipid profile and the deprivation of estrogen. <it>Erxian </it>decoction (EXD), a Chinese medicinal formulation for treating menopausal syndrome, stimulates ovarian estrogen biosynthesis. This study investigates whether EXD improves the serum lipid profile in a menopausal rat model.</p> <p>Methods</p> <p>Twenty-month-old female Sprague Dawley rats were treated with EXD and its constituent fractions. Premarin was administered for comparison. After eight weeks of treatment, rats were sacrificed and the serum levels of total cholesterol, triglyceride, high-density-lipoprotein cholesterol and low-density-lipoprotein cholesterol were determined. The hepatic protein levels of 3-hydroxy-3-methyl-glutaryl-CoA reductase and low-density-lipoprotein receptor were assessed with Western blot.</p> <p>Results</p> <p>The serum levels of total cholesterol and low-density-lipoprotein cholesterol were significantly lower in the EXD-treated group than in the constituent fractions of EXD or premarin groups. However, the serum levels of triglyceride and high-density-lipoprotein cholesterol were not significantly different from the control groups. Results from Western blot suggest that EXD significantly down-regulated the protein level of 3-hydroxy-3-methyl-glutaryl-CoA reductase and up-regulated low-density-lipoprotein receptor. <b>Conclusion </b>EXD improves serum lipid profile in a menopausal rat model through the suppression of the serum levels of total cholesterol and low-density-lipoprotein cholesterol, possibly through the down-regulation of the 3-hydroxy-3-methyl-glutaryl-CoA and up-regulation of the low-density-lipoprotein receptor.</p

A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III

We established a method on measuring the \dzdzb mixing parameter $y$ for BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to CP-eigenstates and the other $D$ decays semileptonically, are used to reconstruct the signals. Since this analysis requires good $e/\pi$ separation, a likelihood approach, which combines the $dE/dx$, time of flight and the electromagnetic shower detectors information, is used for particle identification. We estimate the sensitivity of the measurement of $y$ to be 0.007 based on a $20fb^{-1}$ fully simulated MC sample.Comment: 6 pages, 7 figure