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State of the art

Katelyn G Bennett, Theodore A Kung, James A Hayman, David L Brown
BACKGROUND: Management of keloids has remained a conundrum, because an optimum treatment regimen has yet to be elucidated. Currently, treatment varies widely between more conservative measures, such as steroid injections, topical medications, and silicone sheeting, to more aggressive options, such as surgery and postoperative radiation. The latter combination has been touted to have superior results, with the lowest rates of pathologic scar recurrence. METHODS: We performed a retrospective review to critically evaluate the effectiveness of surgical excision and radiation treatment in patients with keloids...
October 19, 2016: Annals of Plastic Surgery
Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng
Hashing compresses high-dimensional features into compact binary codes. It is one of the promising techniques to support efficient mobile image retrieval, due to its low data transmission cost and fast retrieval response. However, most of existing hashing strategies simply rely on low-level features. Thus, they may generate hashing codes with limited discriminative capability. Moreover, many of them fail to exploit complex and high-order semantic correlations that inherently exist among images. Motivated by these observations, we propose a novel unsupervised hashing scheme, called topic hypergraph hashing (THH), to address the limitations...
October 21, 2016: IEEE Transactions on Cybernetics
Saad Mohamad, Abdelhamid Bouchachia, Moamar Sayed-Mouchaweh
Active learning (AL) is a promising way to efficiently build up training sets with minimal supervision. A learner deliberately queries specific instances to tune the classifier's model using as few labels as possible. The challenge for streaming is that the data distribution may evolve over time, and therefore the model must adapt. Another challenge is the sampling bias where the sampled training set does not reflect the underlying data distribution. In the presence of concept drift, sampling bias is more likely to occur as the training set needs to represent the whole evolving data...
October 21, 2016: IEEE Transactions on Neural Networks and Learning Systems
Cinzia Pizzi, Mattia Ornamenti, Simone Spangaro, Simona E Rombo, Laxmi Parida
Entropy, being closely related to repetitiveness and compressibility, is a widely used information-related measure to assess the degree of predictability of a sequence. Entropic profiles are based on information theory principles, and can be used to study the under-/over-representation of subwords, by also providing information about the scale of conserved DNA regions. Here we focus on the algorithmic aspects related to entropic profiles. In particular, we propose linear time algorithms for their computation that rely on suffix-based data structures, more specifically on the truncated suffix tree (TST) and on the enhanced suffix array (ESA)...
October 21, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Oleksandr O Kurakevych, Vladimir L Solozhenko
The aim of the present review is to highlight the state of the art in high-pressure design of new advanced materials based on boron nitride. Recent experimental achievements on the governing phase transformation, nanostructuring and chemical synthesis in the systems containing boron nitride at high pressures and high temperatures are presented. All these developments allowed discovering new materials, e.g., ultrahard nanocrystalline cubic boron nitride (nano-cBN) with hardness comparable to diamond, and superhard boron subnitride B13N₂...
October 20, 2016: Molecules: a Journal of Synthetic Chemistry and Natural Product Chemistry
Wenzhangzhi Guo, Parham Aarabi
We present a method for binary classification using neural networks (NNs) that performs training and classification on the same data using the help of a pretraining heuristic classifier. The heuristic classifier is initially used to segment data into three clusters of high-confidence positives, high-confidence negatives, and low-confidence sets. The high-confidence sets are used to train an NN, which is then used to classify the low-confidence set. Applying this method to the binary classification of hair versus nonhair patches, we obtain a 2...
October 18, 2016: IEEE Transactions on Neural Networks and Learning Systems
Jiaxiang Huang, Maoguo Gong, Lijia Ma
Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations...
October 19, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Jian Zhang, Haiting Chai, Bo Gao, Guifu Yang, Zhiqiang Ma
Heme is an essential biomolecule that widely exists in numerous extant organisms. Accurately identifying heme binding residues (HEMEs) is of great importance in disease progression and drug development. In this study, a novel predictor named HEMEsPred was proposed for predicting HEMEs. First, several sequence- and structure-based features, including amino acid composition, motifs, surface preferences and secondary structure, were collected to construct feature matrices. Second, a novel fast-adaptive ensemble learning scheme was designed to overcome the serious class-imbalance problem as well as to enhance the prediction performance...
October 4, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Yongwei Nie, Zhensong Zhang, Hanqiu Sun, Tan Su, Guiqing Li
Wide-baseline street image interpolation is useful but very challenging. Existing approaches either rely on heavyweight 3D reconstruction or computationally intensive deep networks. We present a lightweight and efficient method which uses simple homography computing and refining operators to estimate piecewise smooth homographies between input views. To achieve the goal, we show how to combine homography fitting and homography propagation together based on reliable and unreliable superpixel discrimination. Such a combination, other than using homography fitting only, dramatically increases the accuracy and robustness of the estimated homographies...
October 19, 2016: IEEE Transactions on Visualization and Computer Graphics
Chao Ren, Xiaohai He, Truong Nguyen
Single image super-resolution (SR) is very important in many computer vision systems. However, as a highly ill-posed problem, its performance mainly relies on the prior knowledge. Among these priors, the non-local total variation (NLTV) prior is very popular and has been thoroughly studied in recent years. Nevertheless, technical challenges remain. Because NLTV only exploits a fixed non-shifted target patch in the patch search process, a lack of similar patches is inevitable in some cases. Thus, the non-local similarity cannot be fully characterized, and the effectiveness of NLTV cannot be ensured...
October 19, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Pierre Buyssens, Olivier le Meur, Maxime Daisy, David Tschumperle, Olivier Lezoray
We propose to tackle the problem of RGB-D image disocclusion inpainting when synthesizing new views of a scene by changing its viewpoint. Indeed, such a process creates holes both in depth and color images. First, we propose a novel algorithm to perform depth-map disocclusion inpainting. Our intuitive approach works particularly well for recovering the lost structures of the objects and to inpaint the depth-map in a geometrically plausible manner. Then, we propose a depth-guided patch based inpainting method to fill-in the color image...
October 19, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Yang Cong, Ji Liu, Gan Sun, Quanzeng You, Yuncheng Li, Jiebo Luo
Initializing an effective dictionary is an indispensable step for sparse representation. In this paper, we focus on the dictionary selection problem with the objective to select a compact subset of basis from original training data instead of learning a new dictionary matrix as dictionary learning models do. We first design a new dictionary selection model via `2;0 norm. For model optimization, we propose two methods: one is the standard forward-backward greedy algorithm, which is not suitable for large-scale problems; the other is based on the gradient cues at each forward iteration and speeds up the process dramatically...
October 19, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Yuan Zhou, Anand Rangarajan, Paul D Gader
The normal compositional model (NCM) has been extensively used in hyperspectral unmixing. However, previous research has mostly focused on estimation of endmembers and/or their variability, based on the assumption that the pixels are independent random variables. In this paper, we show that this assumption does not hold if all the pixels are generated by a fixed endmember set. This introduces another concept, endmember uncertainty, which is related to whether the pixels fit into the endmember simplex. To further develop this idea, we derive the NCM from the ground up without the pixel independence assumption, along with (i) using different noise levels at different wavelengths and (ii) using a spatial and sparsity promoting prior for the abundances...
October 18, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Md Akter Hussain, Alauddin Bhuiyan, Andrew Turpin, Chi D Luu, R Theodore Smith, Robyn H Guymer, Ramamohanarao Kotagiri
OBJECTIVE: We propose an effective, automatic method for identification of four retinal layer boundaries from the Spectral Domain Optical Coherence Tomography (SD-OCT) images in the presence and absence of pathologies and morphological changes due to disease. METHODS: The approach first finds an approximate location of three reference layers, and then uses these to bound the search space for the actual layers, which is achieved by modeling the problem as a graph and applying Dijkstra's shortest path algorithm...
October 19, 2016: IEEE Transactions on Bio-medical Engineering
Lina G AbdulHalim, Zahra Hooshmand, Manas R Parida, Shawkat M Aly, Duy Le, Xin Zhang, Talat S Rahman, Matthew Pelton, Yaroslav Losovyj, Peter A Dowben, Osman M Bakr, Omar F Mohammed, Khabiboulakh Katsiev
Noble metal nanoclusters (NCs) play a pivotal role in bridging the gap between molecules and quantum dots. Fundamental understanding of the evolution of the structural, optical, and electronic properties of these materials in various environments is of paramount importance for many applications. Using state-of-the-art spectroscopy, we provide the first decisive experimental evidence that the structural, electronic, and optical properties of Ag44(MNBA)30 NCs can now be tailored by controlling the chemical environment...
October 24, 2016: Inorganic Chemistry
Hongming Lyu, Qi Lu, Jinbiao Liu, Xiaoming Wu, Jinyu Zhang, Junfeng Li, Jiebin Niu, Zhiping Yu, Huaqiang Wu, He Qian
In order to conquer the short-channel effects that limit conventional ultra-scale semiconductor devices, two-dimensional materials, as an option of ultimate thin channels, receive wide attention. Graphene, in particular, bears great expectations because of its supreme carrier mobility and saturation velocity. However, its main disadvantage, the lack of bandgap, has not been satisfactorily solved. As a result, maximum oscillation frequency (fmax) which indicates transistors' power amplification ability has been disappointing...
October 24, 2016: Scientific Reports
Jinnan Xuan, Zhiqiang Wang, Yuyan Chen, Dujuan Liang, Liang Cheng, Xiaojing Yang, Zhuang Liu, Renzhi Ma, Takayoshi Sasaki, Fengxia Geng
The delamination of titanium carbide sheets, an intriguing class of two-dimensional materials, has been critically dependent on the extraction of interlayer Al in acidic media, such as concentrated hydrofluoric acid (HF) or a mixture of hydrochloric acid (HCl) and a fluoride salt. Herein, we report an organic-base-driven intercalation and delamination of titanium carbide that takes advantage of the amphoteric nature of interlayer Al. The resulting aluminum-oxoanion-functionalized titanium carbide sheets manifested unusually strong optical absorption in the near-infrared (NIR) region with a mass extinction coefficient as high as 29...
October 24, 2016: Angewandte Chemie
Zhe Guo, Yi Wang, Tao Lei, Yangyu Fan, Xiuwei Zhang
Diffusion Tensor Imaging (DTI) image registration is an essential step for diffusion tensor image analysis. Most of the fiber bundle based registration algorithms use deterministic fiber tracking technique to get the white matter fiber bundles, which will be affected by the noise and volume. In order to overcome the above problem, we proposed a Diffusion Tensor Imaging image registration method under probabilistic fiber bundles tractography learning. Probabilistic tractography technique can more reasonably trace to the structure of the nerve fibers...
2016: BioMed Research International
Matteo Di Nardo, Graeme MacLaren, Marco Marano, Corrado Cecchetti, Paola Bernaschi, Antonio Amodeo
Extracorporeal life support (ECLS) is an important device in the management of children with severe refractory cardiac and or pulmonary failure. Actually, two forms of ECLS are available for neonates and children: extracorporeal membrane oxygenation (ECMO) and use of a ventricular assist device (VAD). Both these techniques have their own advantages and disadvantages. The intra-aortic balloon pump is another ECLS device that has been successfully used in larger children, adolescents, and adults, but has found limited applicability in smaller children...
2016: Frontiers in Pediatrics
Qidong Li, Qiulong Wei, Jinzhi Sheng, Mengyu Yan, Liang Zhou, Wen Luo, Ruimin Sun, Liqiang Mai
Despite the enormous efforts devoted to high-performance lithium-ion batteries (LIBs), the present state-of-the-art LIBs cannot meet the ever-increasing demands. With high theoretical capacity, fast ionic conductivity, and suitable charge/discharge plateaus, Li3VO4 shows great potential as the anode material for LIBs. However, it suffers from poor electronic conductivity. In this work, we present a novel composite material with mesoporous Li3VO4/C submicron-ellipsoids supported on rGO (LVO/C/rGO). The synthesized LVO/C/rGO exhibits a high reversible capacity (410 mAh g(-1) at 0...
December 2015: Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
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