Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections

In this paper, we propose a very deep fully convolutional encoding-decoding framework for image restoration such as denoising and super-resolution. The network is composed of multiple layers of convolution and de-convolution operators, learning end-to-end mappings from corrupted images to the original ones. The convolutional layers act as the feature extractor, which capture the abstraction of image contents while eliminating noises/corruptions. De-convolutional layers are then used to recover the image details. We propose to symmetrically link convolutional and de-convolutional layers with skip-layer connections, with which the training converges much faster and attains a higher-quality local optimum. First, The skip connections allow the signal to be back-propagated to bottom layers directly, and thus tackles the problem of gradient vanishing, making training deep networks easier and achieving restoration performance gains consequently. Second, these skip connections pass image details from convolutional layers to de-convolutional layers, which is beneficial in recovering the original image. Significantly, with the large capacity, we can handle different levels of noises using a single model. Experimental results show that our network achieves better performance than all previously reported state-of-the-art methods.Comment: Accepted to Proc. Advances in Neural Information Processing Systems (NIPS'16). Content of the final version may be slightly different. Extended version is available at http://arxiv.org/abs/1606.0892

A transformative route to nanoporous manganese oxides of controlled oxidation states with identical textural properties

Nanoporous nanocrystalline metal oxides with tunable oxidation states are crucial for controlling their catalytic, electronic, and optical properties. However, previous approaches to modulate oxidation states in nanoporous metal oxides commonly lead to the breakdown of the nanoporous structure as well as involve concomitant changes in their morphology, pore size, surface area, and nanocrystalline size. Herein, we present a transformative route to nanoporous metal oxides with various oxidation states using manganese oxides as model systems. Thermal conversion of Mn-based metal-organic frameworks (Mn-MOFs) at controlled temperature and atmosphere yielded a series of nanoporous manganese oxides with continuously tuned oxidation states: MnO, Mn3O 4, Mn5O8, and Mn2O3. This transformation enabled the preparation of low-oxidation phase MnO and metastable intermediate phase Mn5O8 with nanoporous architectures, which were previously rarely accessible. Significantly, nanoporous MnO, Mn3O4, and Mn5O8 had a very similar morphology, surface area, and crystalline size. We investigated the electrocatalytic activity of nanoporous manganese oxides for oxygen reduction reaction (ORR) to identify the role of oxidation states, and observed oxidation state-dependent activity and kinetics for the ORR.close5

Air and water flows in a vertical sand column

The unsteady state drainage of water from a vertical sand column with and without a finer layer on the top was studied theoretically and experimentally to investigate the airflow generated by the finer layer. The sand column, saturated at its lower portion and initially in the condition of hydrostatic equilibrium, is drained at its bottom at constant head. The results show that significant vacuum can be generated in the vadose zone of the column with a finer layer on the top. The vacuum increases quickly in the earlier stage of the drainage, reaches a maximum, and gradually becomes zero. Because of the effect of the vacuum in the vadose zone, water is held in and the cumulative outflow from the column with the finer layer is much smaller than without the layer during most of the drainage process. Ordinary differential equations (ODE), which require only saturated hydraulic properties of the porous media, are derived to predict the location of the surface of saturation and vacuum in the vadose zone in air-water two-phase flow. The solutions of ODE match very satisfactorily with the experimental data and give better results than TOUGH2. Copyright 2011 by the American Geophysical Union.published_or_final_versio

Study of a micro chamber quadrupole mass spectrometer

Copyright @ 2008 American Vacuum Society / American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Journal of Vacuum Science and Technology Part A: International Journal Devoted to Vacuum, Surfaces, and Films, 26(2), Article number 239 and may be found at http://scitation.aip.org/content/avs/journal/jvsta/26/2/10.1116/1.2827512.The design of a micro chamberquadrupolemass spectrometer (MCQMS) having a small total volume of only 20 cm3, including Faraday cup ion detector and ion source, is described. This MCQMS can resist a vacuum baking temperature of 400–500 °C. The quadrupole elements with a hyperbolic surface are made of a ceramic material and coated with a thin metal layer. The quadrupole mass filter has a field radius of 3 mm and a length of 100 mm. Prototypes of this new MCQMS can detect a minimum partial pressure of 10−8 Pa, have a peak width of ΔM=1 at 10% peak height from mass number 1 to 60, and show an excellent long-term stability. The new MCQMS is intended to be used in residual gas analyses of electron devices during a mutual pumping and baking process.National Key Basic Research Program, the Chinese 111 Project Grant and Program for New Century Excellent Talents in University

Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation

In this paper, we present an algorithmic study on how to surpass competitors in popularity by strategic promotions in social networks. We first propose a novel model, in which we integrate the Preferential Attachment (PA) model for popularity growth with the Independent Cascade (IC) model for influence propagation in social networks called PA-IC model. In PA-IC, a popular item and a novice item grab shares of popularity from the natural popularity growth via the PA model, while the novice item tries to gain extra popularity via influence cascade in a social network. The {\em popularity ratio} is defined as the ratio of the popularity measure between the novice item and the popular item. We formulate {\em Popularity Ratio Maximization (PRM)} as the problem of selecting seeds in multiple rounds to maximize the popularity ratio in the end. We analyze the popularity ratio and show that it is monotone but not submodular. To provide an effective solution, we devise a surrogate objective function and show that empirically it is very close to the original objective function while theoretically, it is monotone and submodular. We design two efficient algorithms, one for the overlapping influence and non-overlapping seeds (across rounds) setting and the other for the non-overlapping influence and overlapping seed setting, and further discuss how to deal with other models and problem variants. Our empirical evaluation further demonstrates that the proposed PRM-IMM method consistently achieves the best popularity promotion compared to other methods. Our theoretical and empirical analyses shed light on the interplay between influence maximization and preferential attachment in social networks.Comment: 22 pages, 8 figures, to be appear SIGMOD 202

Evaluation of lacustrine groundwater discharge, hydrologic partitioning, and nutrient budgets in a proglacial lake in the Qinghai–Tibet Plateau: using ²²²Rn and stable isotopes

Proglacial lakes are good natural laboratories to investigate groundwater and glacier dynamics under current climate conditions and to explore biogeochemical cycling under pristine lake status. This study conducted a series of investigations of 222Rn, stable isotopes, nutrients, and other hydrogeochemical parameters in Ximen Co Lake, a remote proglacial lake in the east of the Qinghai–Tibet Plateau (QTP). A radon mass balance model was used to quantify the lacustrine groundwater discharge (LGD) of the lake, leading to an LGD estimate of 10.3±8.2&thinsp;mm&thinsp;d−1. Based on the three-endmember models of stable 18O and Cl−, the hydrologic partitioning of the lake is obtained, which shows that groundwater discharge only accounts for 7.0&thinsp;% of the total water input. The groundwater-derived DIN and DIP loadings constitute 42.9&thinsp;% and 5.5&thinsp;% of the total nutrient loading to the lakes, indicating the significance of LGD in delivering disproportionate DIN into the lake. This study presents the first attempt to evaluate the LGD and hydrologic partitioning in the glacial lake by coupling radioactive and stable isotopic approaches and the findings advance the understanding of nutrient budgets in the proglacial lakes of the QTP. The study is also instructional in revealing the hydrogeochemical processes in proglacial lakes elsewhere.</p