Enhanced Deep Residual Networks for Single Image Super-Resolution

Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN). In particular, residual learning techniques exhibit improved performance. In this paper, we develop an enhanced deep super-resolution network (EDSR) with performance exceeding those of current state-of-the-art SR methods. The significant performance improvement of our model is due to optimization by removing unnecessary modules in conventional residual networks. The performance is further improved by expanding the model size while we stabilize the training procedure. We also propose a new multi-scale deep super-resolution system (MDSR) and training method, which can reconstruct high-resolution images of different upscaling factors in a single model. The proposed methods show superior performance over the state-of-the-art methods on benchmark datasets and prove its excellence by winning the NTIRE2017 Super-Resolution Challenge.Comment: To appear in CVPR 2017 workshop. Best paper award of the NTIRE2017 workshop, and the winners of the NTIRE2017 Challenge on Single Image Super-Resolutio

Sorghum gene expression modulated by water deficit and cold stress

Global gene expression in Sorghum bicolor, an important crop showing drought tolerance in arid and semi-arid cultivated areas, was monitored to exposure of 8-days seedlings to water deficit (20% polyethylene glycol) or cold stress (4 úC). A sorghum cDNA microarray, including ~13,000 (milestone version 1) or ~28,000 (milestone version 2) unigenes, was used to examine gene expression in shoots and roots at 3 and 27hours after stress treatment. ~1,300 and ~2,300 genes were modulated by water deficit and cold stress, respectively. Up-regulated genes included previously identified stressinduced genes such as early drought-induced gene, dehydrin, late embryogenesis abundant gene, glycin and proline-rich gene, and water stress-inducible genes as well as unknown genes. Genes involved in signal transduction, lipid metabolism, transporter, and carbohydrate metabolism are induced. Quantitative real-time PCR was used to quantify changes in relative mRNA abundance for 333 and 108 genes in response to water deficit and cold stress, respectively. Stress-induced genes were classified by kinetics. Eighteen of 108 cold-induced genes were modulated by cold but not by ABA and PEG treatment. This research provides the starting point for detailed analysis and comparison of water deficit and cold modulated gene networks in sorghum

Investigation of thermal resistance and power consumption in Ga-doped indium oxide (In2O3) nanowire phase change random access memory

The resistance stability and thermal resistance of phase change memory devices using similar to 40 nm diameter Ga-doped In2O3 nanowires (Ga:In2O3 NW) with different Ga-doping concentrations have been investigated. The estimated resistance stability (R(t)/R-0 ratio) improves with higher Ga concentration and is dependent on annealing temperature. The extracted thermal resistance (R-th) increases with higher Ga-concentration and thus the power consumption can be reduced by similar to 90% for the 11.5% Ga: In2O3 NW, compared to the 2.1% Ga: In2O3 NW. The excellent characteristics of Ga-doped In2O3 nanowire devices offer an avenue to develop low power and reliable phase change random access memory applications. (C) 2014 AIP Publishing LLC.X113sciescopu

Time Series Forecasting with Hypernetworks Generating Parameters in Advance

Forecasting future outcomes from recent time series data is not easy, especially when the future data are different from the past (i.e. time series are under temporal drifts). Existing approaches show limited performances under data drifts, and we identify the main reason: It takes time for a model to collect sufficient training data and adjust its parameters for complicated temporal patterns whenever the underlying dynamics change. To address this issue, we study a new approach; instead of adjusting model parameters (by continuously re-training a model on new data), we build a hypernetwork that generates other target models' parameters expected to perform well on the future data. Therefore, we can adjust the model parameters beforehand (if the hypernetwork is correct). We conduct extensive experiments with 6 target models, 6 baselines, and 4 datasets, and show that our HyperGPA outperforms other baselines.Comment: 7 pages, preprint (we open our code after being accepted

Telomere maintenance through recruitment of internal genomic regions

Cells surviving crisis are often tumorigenic and their telomeres are commonly maintained through the reactivation of telomerase. However, surviving cells occasionally activate a recombination-based mechanism called alternative lengthening of telomeres (ALT). Here we establish stably maintained survivors in telomerase-deleted Caenorhabditis elegans that escape from sterility by activating ALT. ALT survivors trans-duplicate an internal genomic region, which is already cis-duplicated to chromosome ends, across the telomeres of all chromosomes. These 'Template for ALT' (TALT) regions consist of a block of genomic DNA flanked by telomere-like sequences, and are different between two genetic background. We establish a model that an ancestral duplication of a donor TALT region to a proximal telomere region forms a genomic reservoir ready to be incorporated into telomeres on ALT activation.

Lightweight Image Super-Resolution with Information Multi-distillation Network

In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results. Thanks to the powerful representation capabilities of the deep networks, numerous previous ways can learn the complex non-linear mapping between low-resolution (LR) image patches and their high-resolution (HR) versions. However, excessive convolutions will limit the application of super-resolution technology in low computing power devices. Besides, super-resolution of any arbitrary scale factor is a critical issue in practical applications, which has not been well solved in the previous approaches. To address these issues, we propose a lightweight information multi-distillation network (IMDN) by constructing the cascaded information multi-distillation blocks (IMDB), which contains distillation and selective fusion parts. Specifically, the distillation module extracts hierarchical features step-by-step, and fusion module aggregates them according to the importance of candidate features, which is evaluated by the proposed contrast-aware channel attention mechanism. To process real images with any sizes, we develop an adaptive cropping strategy (ACS) to super-resolve block-wise image patches using the same well-trained model. Extensive experiments suggest that the proposed method performs favorably against the state-of-the-art SR algorithms in term of visual quality, memory footprint, and inference time. Code is available at \url{https://github.com/Zheng222/IMDN}.Comment: To be appear in ACM Multimedia 2019, https://github.com/Zheng222/IMD

REEP5 depletion causes sarco-endoplasmic reticulum vacuolization and cardiac functional defects

The sarco-endoplasmic reticulum (SR/ER) plays an important role in the development and progression of many heart diseases. However, many aspects of its structural organization remain largely unknown, particularly in cells with a highly differentiated SR/ER network. Here, we report a cardiac enriched, SR/ER membrane protein, REEP5 that is centrally involved in regulating SR/ER organization and cellular stress responses in cardiac myocytes. In vitro REEP5 depletion in mouse cardiac myocytes results in SR/ER membrane destabilization and luminal vacuolization along with decreased myocyte contractility and disrupted Ca2+ cycling. Further, in vivo CRISPR/Cas9-mediated REEP5 loss-of-function zebrafish mutants show sensitized cardiac dysfunction upon short-term verapamil treatment. Additionally, in vivo adeno-associated viral (AAV9)-induced REEP5 depletion in the mouse demonstrates cardiac dysfunction. These results demonstrate the critical role of REEP5 in SR/ER organization and function as well as normal heart function and development

A secretome profile indicative of oleate-induced proliferation of HepG2 hepatocellular carcinoma cells

Increased fatty acid (FA) is often observed in highly proliferative tumors. FAs have been shown to modulate the secretion of proteins from tumor cells, contributing to tumor survival. However, the secreted factors affected by FA have not been systematically explored. Here, we found that treatment of oleate, a monounsaturated omega-9 FA, promoted the proliferation of HepG2 cells. To examine the secreted factors associated with oleate-induced cell proliferation, we performed a comprehensive secretome profiling of oleate-treated and untreated HepG2 cells. A comparison of the secretomes identified 349 differentially secreted proteins (DSPs; 145 upregulated and 192 downregulated) in oleate-treated samples, compared to untreated samples. The functional enrichment and network analyses of the DSPs revealed that the 145 upregulated secreted proteins by oleate treatment were mainly associated with cell proliferation-related processes, such as lipid metabolism, inflammatory response, and ER stress. Based on the network models of the DSPs, we selected six DSPs (MIF, THBS1, PDIA3, APOA1, FASN, and EEF2) that can represent such processes related to cell proliferation. Thus, our results provided a secretome profile indicative of an oleate-induced proliferation of HepG2 cell

Rapid Turnover of Cortical NCAM1 Regulates Synaptic Reorganization after Peripheral Nerve Injury

Peripheral nerve injury can induce pathological conditions that lead to persistent sensitized nociception. Although there is evidence that plastic changes in the cortex contribute to this process, the underlying molecular mechanisms are unclear. Here, we find that activation of the anterior cingulate cortex (ACC) induced by peripheral nerve injury increases the turnover of specific synaptic proteins in a persistent manner. We demonstrate that neural cell adhesion molecule 1 (NCAM1) is one of the molecules involved and show that it mediates spine reorganization and contributes to the behavioral sensitization. We show striking parallels in the underlying mechanism with the maintenance of NMDA-receptor- and protein-synthesis-dependent long-term potentiation (LTP) in the ACC. Our results, therefore, demonstrate a synaptic mechanism for cortical reorganization and suggest potential avenues for neuropathic pain treatment

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe