Constructing Hierarchical Image-tags Bimodal Representations for Word Tags Alternative Choice

This paper describes our solution to the multi-modal learning challenge of ICML. This solution comprises constructing three-level representations in three consecutive stages and choosing correct tag words with a data-specific strategy. Firstly, we use typical methods to obtain level-1 representations. Each image is represented using MPEG-7 and gist descriptors with additional features released by the contest organizers. And the corresponding word tags are represented by bag-of-words model with a dictionary of 4000 words. Secondly, we learn the level-2 representations using two stacked RBMs for each modality. Thirdly, we propose a bimodal auto-encoder to learn the similarities/dissimilarities between the pairwise image-tags as level-3 representations. Finally, during the test phase, based on one observation of the dataset, we come up with a data-specific strategy to choose the correct tag words leading to a leap of an improved overall performance. Our final average accuracy on the private test set is 100%, which ranks the first place in this challenge.Comment: 6 pages, 1 figure, Presented at the Workshop on Representation Learning, ICML 201

Challenges in Representation Learning: A report on three machine learning contests

The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions.Comment: 8 pages, 2 figure

Obtaining Cross Modal Similarity Metric with Deep Neural Architecture

Analyzing complex system with multimodal data, such as image and text, has recently received tremendous attention. Modeling the relationship between different modalities is the key to address this problem. Motivated by recent successful applications of deep neural learning in unimodal data, in this paper, we propose a computational deep neural architecture, bimodal deep architecture (BDA) for measuring the similarity between different modalities. Our proposed BDA architecture has three closely related consecutive components. For image and text modalities, the first component can be constructed using some popular feature extraction methods in their individual modalities. The second component has two types of stacked restricted Boltzmann machines (RBMs). Specifically, for image modality a binary-binary RBM is stacked over a Gaussian-binary RBM; for text modality a binary-binary RBM is stacked over a replicated softmax RBM. In the third component, we come up with a variant autoencoder with a predefined loss function for discriminatively learning the regularity between different modalities. We show experimentally the effectiveness of our approach to the task of classifying image tags on public available datasets

Recent Advances in Ionic Liquids—MOF Hybrid Electrolytes for Solid-State Electrolyte of Lithium Battery

Li-ion batteries are currently considered promising energy storage devices for the future. However, the use of liquid electrolytes poses certain challenges, including lithium dendrite penetration and flammable liquid leakage. Encouragingly, solid electrolytes endowed with high stability and safety appear to be a potential solution to these problems. Among them, ionic liquids (ILs) packed in metal organic frameworks (MOFs), known as ILs@MOFs, have emerged as a hybrid solid-state material that possesses high conductivity, low flammability, and strong mechanical stability. ILs@MOFs plays a crucial role in forming a continuous interfacial conduction network, as well as providing internal ion conduction pathways through the ionic liquid. Hence, ILs@MOFs can not only act as a suitable ionic conduct main body, but also be used as an active filler in composite polymer electrolytes (CPEs) to meet the demand for higher conductivity and lower cost. This review focuses on the characteristic properties and the ion transport mechanism behind ILs@MOFs, highlighting the main problems of its applications. Moreover, this review presents an introduction of the advantages and applications of Ils@MOFs as fillers and the improvement directions are also discussed. In the conclusion, the challenges and suggestions for the future improvement of ILs@MOFs hybrid electrolytes are also prospected. Overall, this review demonstrates the application potential of ILs@MOFs as a hybrid electrolyte material in energy storage systems

Protective effect of resveratrol against light-induced retinal degeneration in aged SAMP8 mice

Purpose The purpose of this study was to determine the protective effects of Resveratrol (RESV) on acute bright light-induced retinal degeneration in aged senescence accelerated mouse strain. Methods: Ten three-month-old male SAMP8 mice (prone to aging) were randomly assigned to two experimental dietary groups: one untreated group and one RESV treatment group (n=20 eyes for each group). After 30 days of treatment, mice were exposed to intense bright light. Ten male SAMR1 mice (resistant to aging) served as control (n=20 eyes). The protective effects of RESV administration on light-induced retinal degeneration in SAMP8 strain as well as the effect of bright light damage in the retinas of SAMP8 mice were analyzed by electroretinography (ERG), retinal histology, mRNA, protein and lipid profile. Results: 68%-85% of a-wave amplitude and 72%-92% of b-wave amplitude were persevered by RESV in SAMP8 mice that were exposed to light damage. Also, RESV preserved their photoreceptor nuclei. mRNA expression of neuroprotective factors leukemia inhibitory factor (LIF), brain derived neurotrophic factor (BDNF), oncostatin M (OSM), cardiotrophin 1(CT-1) and cardiotrophin-like cytokine (CLC) were up-regulated 28, 8, 7, 5 and 9-fold in SAMP8 mice after RESV treatment. In addition, RESV could suppress the NF-κB pathway by down-regulating the expression of pIκB. Light damage led to increase of saturated FA, monoenoic FA, n6 PUFA and n6/n3 ratio and decrease of Docosahexaenoic acid (DHA). There was no significant difference on DHA and the ratio of n6/n3-FA between the untreated and RESV treated SAMP8 mice. Conclusions: Collectively, our study provides evidence that RESV prevents light-induced retinal damage associated with aging

Structural, Surface, and Optical Properties of AlN Thin Films Grown on Different Substrates by PEALD

Plasma-enhanced atomic layer deposition was employed to grow aluminum nitride (AlN) thin films on Si (100), Si (111), and c-plane sapphire substrates at 250 °C. Trimethylaluminum and Ar/N2/H2 plasma were utilized as Al and N precursors, respectively. The properties of AlN thin films grown on various substrates were comparatively analyzed. The investigation revealed that the as-grown AlN thin films exhibit a hexagonal wurtzite structure with preferred c-axis orientation and were polycrystalline, regardless of the substrates. The sharp AlN/substrate interfaces of the as-grown AlN are indicated by the clearly resolved Kiessig fringes measured through X-ray reflectivity. The surface morphology analysis indicated that the AlN grown on sapphire displays the largest crystal grain size and surface roughness value. Additionally, AlN/Si (100) shows the highest refractive index at a wavelength of 532 nm. Compared to AlN/sapphire, AlN/Si has a lower wavelength with an extinction coefficient of zero, indicating that AlN/Si has higher transmittance in the visible range. Overall, the study offers valuable insights into the properties of AlN thin films and their potential applications in optoelectronic devices, and provides a new technical idea for realizing high-quality AlN thin films with sharp AlN/substrate interfaces and smooth surfaces

Research on the Spatial-Temporal Differentiation and Path Analysis of China’s Provincial Regions’ High-Quality Economic Development

High-quality economic development is an important approach for achieving sustainable economic development, and it is an essential condition for coordinated development between economic systems and ecosystems. This paper starts from five key points, namely, “innovation, coordination, opening-up, sharing and greenness”, to construct an evaluation system for the index of high-quality economic development, using the AHP and EVM methods to measure the level of high-quality economic development of 30 regions in China from 2004 to 2019. It uses the kernel density estimation model (hereinafter referred to briefly as KDE) and clustering method to analyze time evolution trends and spatial variation characteristics. Moreover, the LSE model is adopted to explore and analyze the factors influencing high-quality economic development in different regions. Additionally, the driving forces of China’s high-quality economic development are analyzed by means of path analysis combined with the average value of each index. The results show the following: (1) The high-quality economic development of 30 regions in China (excluding Hong Kong, Macao, Taiwan and Tibet) is spatially clustered, with obviously different development levels, characterized by the eastern region being better developed than the central and western regions. (2) With the passage of time, the polarization of China’s 30 regions has been alleviated, but they are still facing challenging development situations; (3) The factors affecting the high-quality economic development of these 30 regions in China can be divided into four types: three-factors, four-factors-I, four-factors-II and five-factors. Contributing regional factors show different distribution characteristics. The above conclusion provides a reference and scientific basis for the government to formulate policies of high-quality economic development and to solve problems facing coordinated sustainable development among regional societies, their economies and the environment

Micro-Nanoarchitectonics of Ga₂O₃/GaN Core-Shell Rod Arrays for High-Performance Broadband Ultraviolet Photodetection

This study presents broadband ultraviolet photodetectors (BUV PDs) based on Ga2O3/GaN core-shell micro-nanorod arrays with excellent performance. Micro-Nanoarchitectonics of Ga2O3/GaN core-shell rod arrays were fabricated with high-temperature oxidization of GaN micro-nanorod arrays. The PD based on the microrod arrays exhibited an ultrahigh responsivity of 2300 A/W for 280 nm at 7 V, the peak responsivity was approximately 400 times larger than those of the PD based on the planar Ga2O3/GaN film. The responsivity was over 1500 A/W for the 270–360 nm band at 7 V. The external quantum efficiency was up to 1.02 × 106% for 280 nm. Moreover, the responsivity was further increased to 2.65 × 104 A/W for 365 nm and over 1.5 × 104 A/W for 270–360 nm using the nanorod arrays. The physical mechanism may have been attributed to the large surface area of the micro-nanorods coupled with the Ga2O3/GaN heterostructure, which excited more photogenerated holes to be blocked at the Ga2O3 surface and Ga2O3/GaN interface, resulting in a larger internal gain. The overall high performance coupled with large-scale production makes it a promising candidate for practical BUV PD

ATG7 upregulation contributes to malignant transformation of human bronchial epithelial cells by B[a]PDE via DNMT3B protein degradation and miR-494 promoter methylation

Lung cancer primarily arises from exposure to various environmental factors, particularly airborne pollutants. Among the various lung carcinogens, benzo(a)pyrene and its metabolite B[a]PDE are the strongest ones that actively contribute to lung cancer development. ATG7 is an E1-like activating enzyme and contributes to activating autophagic responses in mammal cells. However, the potential alterations of ATG7 and its role in B[a]PDE-caused lung carcinogenesis remain unknown. Here, we found that B[a]PDE exposure promoted ATG7 expression in mouse lung tissues, while B[a]PDE exposure resulted in ATG7 induction in human normal bronchial epithelial cells. Our studies also demonstrated a significant correlation between high ATG7 expression levels and poor overall survival in lung cancer patients. ATG7 knockdown significantly repressed Beas-2B cell transformation upon B[a]PDE exposure, and such promotive effect of ATG7 on cell transformation mediated the p27 translation inhibition. Further studies revealed that miR-373 inhibition was required to stabilize ATG7 mRNA, therefore increasing ATG7 expression following B[a]PDE exposure, while ATG7 induction led to the autophagic degradation of the DNA methyltransferase 3 Beta (DNMT3B) protein, in turn promoted miR-494 transcription via its promoter region methylation status suppression. We also found that the miR-494 upregulation inhibited p27 protein translation and promoted bronchial epithelial cell transformation via its directly targeting p27 mRNA 3′-UTR region. Current studies, to the best of our knowledge, are for the first time to identify that ATG7 induction and its mediated autophagy is critical for B[a]PDE-induced transformation of human normal epithelial cells